Compositions and methods for identifying transplant rejection or risk thereof - Patents.com

Abstract

Provided herein are microfluidic arrays and miR panels useful for identifying human subjects experiencing or at risk of experiencing acute cardiac transplant rejection. Also provided are methods for identifying human subjects experiencing or at risk of experiencing acute cardiac transplant rejection, including acute cellular rejection (ACR) or antibody-mediated rejection (AMR). Also provided are aspects of systems, devices, apparatus, methods, and / or computer program products, and / or combinations and subcombinations thereof, for detecting transplant rejection.

Description

[Technical field]

[0001] government support This invention was made with government support under 1K23HL143179 awarded by the National Institutes of Health (NIH). The government has certain rights in the invention.

[0002] Disclosure Fields Aspects of the present disclosure relate to devices and methods of using same for identifying subjects experiencing or at risk of experiencing acute heart graft rejection following heart transplantation. Some aspects of the present disclosure relate to methods of identifying biomarkers that correlate with transplant rejection or risk thereof. [Background technology]

[0003] background Heart transplantation remains the definitive treatment for patients with severe heart failure (HF) and medically refractory symptoms. Median survival after heart transplant is 12.5 years, with only modest improvements in survival over the past two decades.

[0004] Acute and chronic graft rejection are the major causes of morbidity after heart transplantation, leading to graft dysfunction and death. The incidence of rejection is 10–20% in the first year after transplantation, but it is often initially asymptomatic and requires regular surveillance with endomyocardial biopsies (EMB). The standard of care to screen for graft rejection remains EMB in many centers, with the average heart transplant recipient undergoing ~10–17 biopsies in the first year after transplantation. Furthermore, ~4,000 heart transplants are performed annually in the United States (~6,000 worldwide). When other organ transplants are included, this number increases dramatically.

[0005] However, only 5% of EMBs show evidence of graft rejection. Furthermore, there is a variability of ~30% between pathologists in the grading of rejection in tissue sections obtained from EMBs. Furthermore, differentiation between the two major subtypes of rejection (acute cellular rejection (ACR) and antibody-mediated rejection (AMR)) can be difficult in some cases. Also, compared with ACR, AMR is associated with a higher recurrence rate, poorer long-term prognosis, and different management implications. Therefore, accurate diagnosis of AMR is crucial.

[0006] Furthermore, biopsy results can take 48 to 72 hours to become available, which can lead to delays in the initiation of treatment and result in patients being initiated on nonspecific treatment while waiting for the biopsy results.

[0007] Other traditional methods to detect ACR and AMR also have deficiencies. For example, current biomarkers include gene expression profiling (GEP), soluble protein biomarkers, donor-derived cell-free DNA (dd-cfDNA), and T-cell immune function assays. Commercially available gene expression profiling (GEP) measures 11 mRNA transcripts involved in immune system function. However, patients managed with GEP still require endomyocardial biopsy surveillance. In addition, GEP testing has low positive predictive value (PPV) (~10%) and cannot detect AMR, limiting its widespread implementation and reliability. Recently, sequencing of single nucleotide polymorphism (SNP) panels of circulating cell-free DNA has enabled the quantification of the donor-derived portion of cell-free DNA (dd-cfDNA) by utilizing SNP mismatches between donor and recipient DNA. However, currently used dd-cfDNA has a crucial limitation in that it cannot accurately discriminate between ACR and AMR, and EMB is still required. Summary of the Invention [Means for solving the problem]

[0008] Some embodiments of the present disclosure relate to a microfluidic array comprising one or more RNA hybridization probes, where at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3 p, miR-10b-5p, miR-582-3p, let-7b-3p, miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5 p, miR-17-5p, miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, miR -125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, and let-7d-3p.

[0009] Some embodiments of the present disclosure relate to microfluidic arrays comprising one or more RNA hybridization probes, at least one of which hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof.

[0010] In some embodiments, the microfluidic array comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, or an RNA hybridization probe that hybridizes to miR-3615. hybridization probe, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0011] Some embodiments of the present disclosure relate to microfluidic arrays comprising one or more RNA hybridization probes, at least one of which hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof.

[0012] In some embodiments, the microfluidic array comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, an RNA hybridization probe that hybridizes to miR-185-3 an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0013] Some embodiments of the present disclosure relate to a fluidic chip comprising one or more RNA hybridization probes, at least one of which hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof.

[0014] In some embodiments, the fluidic chip comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe that hybridizes to miR-3615. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0015] Some embodiments of the present disclosure relate to a fluidic chip comprising one or more RNA hybridization probes, at least one of which hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof.

[0016] In some embodiments, the fluidic chip comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, miR-185-3p an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0017] In some embodiments, the fluidic chip is a microfluidic chip.

[0018] Some aspects of the present disclosure relate to the use of miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, miR-10b-5p, miR-582-3p, let-7b-3p, miR- 142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR-17-5p, miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, mi The present invention relates to a panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, let-7d-3p, and any combination thereof, for use in identifying a human subject suffering from or at risk of developing acute cardiac allograft rejection following cardiac transplantation.

[0019] In some embodiments, the acute heart transplant rejection comprises ACR, AMR, or any combination thereof.

[0020] Some aspects of the present disclosure relate to a panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof, for use in identifying human subjects having or at risk of developing ACR after heart transplantation.

[0021] In some embodiments, the RNA hybridization probe panel comprises at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven RNA hybridization probes selected from the group consisting of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, miR-374a, an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, an RNA hybridization probe that hybridizes to miR-326, and any combination thereof.

[0022] In some embodiments, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0023] In some embodiments, the RNA hybridization probe panel consists of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe that hybridizes to miR-374a-5p. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0024] Some aspects of the present disclosure relate to a panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof, for use in identifying human subjects suffering from or at risk of developing AMR following heart transplantation.

[0025] In some embodiments, the RNA hybridization probe panel comprises at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven mRNAs selected from the group consisting of an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, or an RNA hybridization probe that hybridizes to miR-374a-5p. probe, an RNA hybridization probe that hybridizes to miR-1307, an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, an RNA hybridization probe that hybridizes to miR-589-5p, and any combination thereof.

[0026] In some embodiments, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, RNA hybridization probe that hybridizes to miR-185-3p, RNA hybridization probe that hybridizes to miR-4433b-3p, RNA hybridization probe that hybridizes to miR-130b-3p, RNA hybridization probe that hybridizes to miR-331-5p, RNA hybridization probe that hybridizes to miR-140-5p, RNA hybridization probe that hybridizes to miR-223-5p, RNA hybridization probe that hybridizes to miR-582-3p, RNA hybridization probe that hybridizes to miR-122-3p, RNA hybridization probe that hybridizes to miR-589-5p.

[0027] In some embodiments, the RNA hybridization probe panel consists of an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, An RNA hybridization probe that hybridizes to iR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0028] Some aspects of the present disclosure relate to a method of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection, including acute cellular rejection (ACR), following cardiac transplantation, comprising obtaining a biological sample from the human subject, where the biological sample comprises RNA, contacting the RNA-containing biological sample with a microfluidic array disclosed herein, a chip disclosed herein, or a panel disclosed herein; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p]. + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln (k)=any number from 4 and 11; and (l)=any number from 6 and 14; wherein "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; wherein a human subject is identified as having or at risk for acute cardiac transplant rejection, including ACR, if the ACR signature score is about 65 or greater.

[0029] Some aspects of the present disclosure relate to a method of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection, including acute cellular rejection (ACR), following a cardiac transplant, comprising: obtaining a biological sample from the human subject, where the biological sample comprises RNA; measuring levels of a miR panel in the biological sample, where the miR panel comprises miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln (k)=any number from 4 and 11; and (l)=any number from 6 and 14; wherein "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; wherein a human subject is identified as having or at risk for acute cardiac transplant rejection, including ACR, if the ACR signature score is about 65 or greater.

[0030] Some embodiments of the present disclosure relate to a method of diagnosing acute cardiac graft rejection, including ACR, following cardiac transplantation in a human subject, comprising obtaining a biological sample from the human subject, where the biological sample comprises RNA; measuring levels of a miR panel in the biological sample, where the miR panel comprises miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln[miR-30e-5p] - (b) * ln[let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln (k)=any number from 4 and 11; and (l)=any number from 6 and 14; wherein "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; wherein a human subject is identified as having or at risk for acute cardiac transplant rejection, including ACR, if the ACR signature score is about 65 or greater.

[0031] In some embodiments, the method further comprises isolating RNA from the biological sample. In some embodiments, the RNA comprises one or more miRs.

[0032] Some aspects of the present disclosure relate to a method of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection including ACR following cardiac transplantation, comprising measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln[miR-30e-5p] - (b) * ln[let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln (k)=any number from 4 and 11; and (l)=any number from 6 and 14; wherein "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; wherein a human subject is identified as having or at risk for acute cardiac transplant rejection, including ACR, if the ACR signature score is about 65 or greater.

[0033] Some aspects of the present disclosure relate to a method of diagnosing acute cardiac graft rejection, including ACR, following cardiac transplantation in a human subject, comprising measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln [miR-326] (c)=any number from 2.5 and 7.5; (d)=any number from 2 and 6; (e)=any number from 4 and 9; (f)=any number from 2 and 6; (g)=any number from 0.5 and 5; (h)=any number from 22 and 32; (i)=any number from 1 and 5; (j)=any number from 3 and 10; (k)=any number from 4 and 11; and (l)=any number from 6 and 14; where "[X]" refers to the amount of "X" in the biological sample, and "ln" stands for natural logarithm; where if the ACR signature score is higher than about 65, acute heart transplant rejection including ACR is diagnosed.

[0034] Some embodiments of the present disclosure include a method of treating acute cardiac transplant rejection, including ACR, in a human subject in need thereof, comprising measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326; and determining an ACR signature score according to the following formula: ACR signature score=251.89 - (a) * ln[miR-30e-5p] - (b) * ln[let-7g-5p] - (c) * ln[miR-223-3p]. + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln [miR-326] (c) = any number between 2.5 and 7.5; (d) = any number between 2 and 6; (e) = any number between 4 and 9; (f) = any number between 2 and 6; (g) = any number between 0.5 and 5; (h) = any number between 22 and 32; (i) = any number between 1 and 5; (j) = any number between 3 and 10; (k) = any number between 4 and 11; and (l) = any number between 6 and 14; and administering an immunosuppressive therapy to a human subject identified as having an ACR signature score of about 65 or greater, wherein "[X]" refers to the amount of "X" in the biological sample and "ln" represents the natural logarithm.

[0035] In some embodiments, (a) = any number from 26 to 31; (b) = any number from 0.16 to 0.21; (c) = any number from 4 to 6; (d) = any number from 3 to 5; (e) = any number from 6 to 7.5; (f) = any number from 3 to 5; (g) = any number from 1 to 3; (h) = any number from 25 to 28; (i) = any number from 2 to 4; (j) = any number from 5 to 7; (k) = any number from 7 to 9; and (l) = any number from 10 to 12.

[0036] In some embodiments, (a) = about 28.90; (b) = about 0.19; (c) = about 5.46; (d) = about 4.77; (e) = about 6.41; (f) = about 4.41; (g) = about 2.20; (h) = about 27.69; (i) = about 3.05; (j) = about 6.17; (k) = about 7.71; and (l) = about 10.63.

[0037] In some embodiments, the miR panel further comprises one or more additional miRs.

[0038] In some embodiments, the method further comprises administering to the human subject an immunosuppressive therapy, hi some embodiments, the immunosuppressive therapy comprises administering a therapy selected from the group consisting of corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof.

[0039] Some embodiments of the present disclosure relate to methods of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection, including antibody-mediated rejection (AMR), following cardiac transplantation, comprising: obtaining a biological sample from the human subject, where the biological sample comprises RNA; contacting the biological sample comprising RNA with a microfluidic array disclosed herein, a chip disclosed herein, or a panel disclosed herein; and determining an AMR signature score according to the following formula: AMR signature score=222.41 - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p]. + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p]; where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = any number from 0.1 to 2; (m) = any number from 1 to 4; (n) = any number from 1 to 5; (o) = any number from 0.5 to 4; (p) = any number from 0.1 to 3; and (q) = 0.where "[X]" refers to the amount of "X" in a biological sample, and ln represents the natural logarithm; and where a human subject is identified as having or at risk for having acute cardiac transplant rejection, including AMR, if the AMR signature score is about 65 or greater.

[0040] Some aspects of the present disclosure include a method of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection, including AMR, following cardiac transplantation, comprising: obtaining a biological sample from the human subject, wherein the biological sample comprises RNA; measuring levels of a miR panel in the biological sample, wherein the miR panel comprises miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-220-5p, miR-215-5p, miR-215-5p, miR-221-5p, miR-2 ... and determining an AMR signature score according to the following formula: AMR signature score=222.41. - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p]; where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h = 0.(i)=any number from 5 to 4; (i)=any number from 5 to 11; (j)=any number from 6 to 13; (k)=any number from 3 to 8; (l)=any number from 0.1 to 2; (m)=any number from 1 to 4; (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; where "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; where a human subject is identified as having or at risk for having acute cardiac transplant rejection, including AMR, if the AMR signature score is about 65 or greater.

[0041] Some embodiments of the present disclosure include a method of diagnosing acute heart transplant rejection, including AMR, following heart transplantation in a human subject, comprising: obtaining a biological sample from the human subject, where the biological sample comprises RNA; measuring levels of a miR panel in the biological sample, where the miR panel comprises miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-220-5p, miR-215 ... and determining an AMR signature score according to the following formula: 222.41. - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p];where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = 0.(m)=any number from 1 to 2; (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; where "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; and where a human subject is identified as having or at risk for having acute cardiac transplant rejection, including AMR, if the AMR signature score is about 65 or greater.

[0042] In some embodiments, the method further comprises isolating RNA from the biological sample. In some embodiments, the RNA comprises one or more miRs.

[0043] Some embodiments of the present disclosure include a method of identifying a human subject experiencing or at risk of experiencing acute cardiac graft rejection, including AMR, following cardiac transplantation, comprising: measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-23b-3p, miR-23c-3p, miR-23d ... and determining an AMR signature score according to the following formula: AMR signature score=222.41. - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p];where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = 0.(m)=any number from 1 to 2; (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; where "[X]" refers to the level of "X" in a biological sample, and "ln" represents the natural logarithm; and where a human subject is identified as having or at risk for having acute cardiac transplant rejection, including AMR, if the AMR signature score is about 65 or greater.

[0044] Some embodiments of the present disclosure include a method of diagnosing acute heart transplant rejection, including AMR, following heart transplantation in a human subject, comprising: measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-220-5p, miR-215 ... , miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, and miR-589-5p); and determining an AMR signature score according to the following formula: AMR signature score=222.41. - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p];where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = 0.(m)=any number from 1 to 2; (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; where "[X]" refers to the level of "X" in the biological sample, and "ln" represents the natural logarithm; where acute cardiac transplant rejection, including AMR, is diagnosed when the AMR signature score is about 65 or greater.

[0045] Some embodiments of the present disclosure include a method of treating acute cardiac transplant rejection in a human subject in need thereof, comprising: measuring levels of a miR panel in a biological sample obtained from the human subject, wherein the miR panel includes miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-443 determining an AMR signature score according to the following formula: AMR signature score=222.41; and administering immunosuppressive therapy to a human subject identified as having an AMR signature score of about 65 or greater: AMR signature score=222.41. - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p]; where (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h = 0.(i)=any number from 5 to 4; (j)=any number from 6 to 13; (k)=any number from 3 to 8; (l)=any number from 0.1 to 2; (m)=any number from 1 to 4; (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; where "[X]" refers to the level of "X" in a biological sample.

[0046] In some embodiments, (a)=any number from 24 to 27; (b)=any number from 8.5 to 10.5; (c)=any number from 2 to 4; (d)=any number from 4.5 to 6.5; (e)=any number from 7.5 to 9.5; (f)=any number from 7 to 9; (g)=any number from 2 to 4; (h)=any number from 1.0 to 1.75; (i)=any number from 7 to 9; (j)=any number from 9 to 11; (k)=any number from 5 to 7; (l)=any number from 1 to 2; (m)=any number from 1.5 to 2.5; (n)=any number from 1.5 to 2.5; (o)=any number from 0.7 to 1.7; (p)=any number from 0.5 to 1.5; and (q)=any number from 1.4 to 2.4.

[0047] In some embodiments, (a)=about 25.44;(b)=about 9.33;(c)=about 3.39;(d)=about 5.82;(e)=about 8.24;(f)=about 8.62;(g)=about 2.75;(h)=about 1.43;(i)=about 7.95;(j)=about 9.69;(k)=about 5.47;(l)=about .60;(m)=about 2.05;(n)=about 2.24;(o)=about 1.40;(p)=about .87; and (q)=about 1.69. In some embodiments, the miR panel further comprises one or more additional miRs.

[0048] In some embodiments, the method further comprises administering to the human subject an immunosuppressive therapy, hi some embodiments, the immunosuppressive therapy comprises administering a therapy selected from the group consisting of intravenous immunoglobulin, plasma exchange, bortezomib, carfilzomib, rituximab, eculizumab, corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof.

[0049] In some embodiments, the biological sample is a blood-derived sample, including whole blood, serum, plasma, or any combination thereof. In some embodiments, the level of the miR panel is measured using small RNA / microRNA / RNA sequencing, array cards, microarray hybridization, probe assays, Northern blots, isothermal nucleic acid amplification (iNAAT), CRISPR, quantitative reverse transcriptase PCR (qRT-PCR), or real-time PCR (RT-PCR), or any combination thereof. In some embodiments, the level of the miR panel is measured using a microfluidic array that includes one or more RNA hybridization probes.

[0050] Some embodiments of the present disclosure relate to kits that include one or more RNA hybridization probes, where at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof; and instructions for measuring the level of a miR panel according to the methods disclosed herein.

[0051] Some embodiments of the present disclosure relate to kits that include one or more RNA hybridization probes, where at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof; and instructions for measuring the level of a miR panel according to the methods disclosed herein.

[0052] Some embodiments of the present disclosure relate to kits that include an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-3 an RNA hybridization probe that hybridizes to miR-45-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326; and instructions for measuring the level of a panel of miRs according to the methods disclosed herein.

[0053] Some embodiments of the disclosure relate to kits that include an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, an RNA hybridization probe that hybridizes to miR-185-3p, or an RNA hybridization probe that hybridizes to miR-23a-3p. an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p; and instructions for measuring the level of a miR panel according to the methods disclosed herein.

[0054] Some aspects of the disclosure relate to a method for generating a microRNA panel for detecting transplant rejection, the method including: obtaining, by a processor, a plurality of microRNA sequence reads for one or more samples obtained from one or more subjects; filtering, by the processor, the plurality of microRNA sequence reads by removing one or more microRNA sequence reads from the plurality of microRNA sequence reads based on predetermined criteria; identifying, by the processor, a target nucleic acid from the filtered plurality of microRNA sequence reads; and filtering, by the processor, a target nucleic acid from the filtered plurality of microRNA sequence reads based on the target nucleic acid. identifying, by a processor, differentially expressed microRNAs from the set of miRs in acute cellular rejection (ACR) or antibody-mediated rejection (AMR); creating, by the processor, a first logistic regression model using the differentially expressed microRNAs; and identifying, by the processor, one or more microRNAs from the differentially expressed microRNAs based on the first logistic regression model, where if the differentially expressed microRNA corresponds to ACR, the one or more microRNAs are used to diagnose ACR, and if the differentially expressed microRNA corresponds to AMR, the one or more microRNAs are used to diagnose AMR.

[0055] In some embodiments, the method further includes: generating, by the processor, a second logistic regression model using the microRNA expression data of each of the one or more samples corresponding to the one or more microRNAs; and identifying, by the processor, a first threshold score indicative of a likelihood of ACR or a second threshold score indicative of a likelihood of AMR based on the second logistic regression model. In some embodiments, the method further includes: receiving, by the processor, a request to determine whether the patient is diagnosed with ACR or AMR using a patient sample (the patient is a heart transplant recipient); obtaining, by the processor, sequence reads of a plurality of microRNAs of the patient as the patient sample; identifying, by the processor, microRNA expression data of the patient from the sequence reads of the plurality of microRNAs of the patient corresponding to one or more microRNAs; and plotting, by the processor, the patient's microRNA expression data on a second logistic regression model; generating, by the processor, an ACR score or an AMR score of the patient based on the patient's microRNA expression data plotted on the second logistic regression model; determining, by the processor, that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score; and identifying, by the processor, heart transplant rejection of the patient based on the patient being diagnosed with ACR or AMR. In some embodiments, the method further includes identifying a treatment for the patient based on the determination by the processor that the patient is diagnosed with ACR or AMR. In some embodiments, the target nucleic acid is involved in ACR or AMR.

[0056] In some embodiments, the plurality of sequence reads are obtained by sequencing one or more samples. In some embodiments, the predetermined criteria includes removing one or more sequence reads from the plurality of sequence reads that are 3' adapter barcode sequences, random barcode sequences, UniVec contaminants, or sequence reads of <15 base pairs. In some embodiments, the method further includes performing, by the processor, a principal component analysis on the plurality of microRNA sequence reads after removing the one or more sequence reads.

[0057] In some embodiments, identifying differentially expressed microRNAs comprises adjusting, by the processor, the differentially expressed microRNAs for clinical covariates. In some embodiments, the clinical covariates comprise age, sex, race, or body mass index.

[0058] In some embodiments, the first logistic regression model is fitted with a LASSO penalty. In some embodiments, the tuning parameters of the LASSO penalty are selected by 10-fold cross-validation to minimize model deviance.

[0059] In some embodiments, the differentially expressed microRNAs used to generate the first logistic regression model have an unadjusted probability value of less than 0.10. In some embodiments, generating the first logistic regression model includes: normalizing, by a processor, the counts of the differentially expressed microRNAs; log-transforming, by a processor, the normalized counts to generate log counts; and standardizing, by a processor, the log counts of each differentially expressed microRNA to have a mean of zero and a variance of one.

[0060] Some aspects of the present disclosure relate to a system for creating a microRNA panel for detecting transplant rejection, the system including: a memory; and a processor, coupled to the memory, configured to: obtain a plurality of microRNA sequence reads for one or more samples obtained from one or more subjects; filter the plurality of microRNA sequence reads by removing one or more microRNA sequence reads from the plurality of microRNA sequence reads based on a predetermined criterion; identify a target nucleic acid from the filtered plurality of microRNA sequence reads; and filter the filtered plurality of microRNA sequence reads based on the target nucleic acid. Identifying a set of microRNAs in the roRNA sequencing reads; identifying differentially expressed microRNAs from the set of miRs in acute cellular rejection (ACR) or antibody-mediated rejection (AMR); creating a first logistic regression model using the differentially expressed microRNAs; and identifying one or more microRNAs from the differentially expressed microRNAs based on the first logistic regression model (wherein if the differentially expressed microRNAs correspond to ACR, the one or more microRNAs are used to diagnose ACR, and if the differentially expressed microRNAs correspond to AMR, the one or more microRNAs are used to diagnose AMR).

[0061] In some embodiments, the processor is further configured to: generate a second logistic regression model using the microRNA expression data of each of the one or more samples corresponding to the one or more microRNAs; and identify a first threshold score indicative of a likelihood of ACR or a second threshold score indicative of a likelihood of AMR based on the second logistic regression model. In some embodiments, the processor is further configured to: receive a request to determine whether a patient is diagnosed with ACR or AMR using a patient sample (the patient is a heart transplant recipient); obtain sequence reads of a plurality of microRNAs of the patient as the patient sample; identify microRNA expression data of the patient from the sequence reads of the plurality of microRNAs of the patient corresponding to one or more microRNAs; and plot the microRNA expression data of the patient on a second logistic regression model; generate an ACR score or an AMR score of the patient based on the microRNA expression data of the patient plotted on the second logistic regression model; determine that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score; and identify a heart transplant rejection of the patient based on the patient being diagnosed with ACR or AMR. In some embodiments, the processor is further configured to identify a treatment for the patient based on the determination that the patient is diagnosed with ACR or AMR. In some embodiments, the target nucleic acid is involved in ACR or AMR.

[0062] In some embodiments, obtaining a plurality of microRNA sequence reads by sequencing one or more samples. In some embodiments, the predetermined criteria includes removing one or more sequence reads from the plurality of sequence reads that are 3' adapter barcode sequences, random barcode sequences, UniVec contaminants, or sequence reads <15 base pairs. In some embodiments, the processor is further configured to perform a principal component analysis on the plurality of microRNA sequence reads after removing the one or more sequence reads.

[0063] In some embodiments, upon identifying the differentially expressed microRNAs, the processor is further configured to adjust the differentially expressed microRNAs for clinical covariates, hi some embodiments, the clinical covariates include age, sex, race, or body mass index.

[0064] In some embodiments, the first logistic regression model is fitted with a LASSO penalty. In some embodiments, the tuning parameters of the LASSO penalty are selected by 10-fold cross-validation to minimize model deviance.

[0065] In some embodiments, the differentially expressed microRNAs used to generate the first logistic regression model have an unadjusted probability value of less than 0.10. In some embodiments, in generating the first logistic regression model, the processor is further configured to: normalize the counts of the differentially expressed microRNAs; log-transform the normalized counts to generate log counts; and standardize the log counts of each differentially expressed microRNA to have a mean of 0 and a variance of 1.

[0066] Some aspects of the present disclosure relate to a non-transitory computer-readable medium having instructions stored thereon, the instructions being executed by one or more processors of a device to cause the one or more processors to perform tasks including: obtaining a plurality of microRNA sequence reads for one or more samples obtained from one or more subjects; filtering the plurality of microRNA sequence reads by removing one or more microRNA sequence reads from the plurality of microRNA sequence reads based on predetermined criteria; identifying a target nucleic acid from the filtered plurality of microRNA sequence reads; filtering the filtered plurality of microRNA sequence reads based on the target nucleic acid; identifying a set of microRNAs in the sequence reads of A; identifying differentially expressed microRNAs from the set of miRs in acute cellular rejection (ACR) or antibody-mediated rejection (AMR); creating a first logistic regression model using the differentially expressed microRNAs; and identifying one or more microRNAs from the differentially expressed microRNAs based on the first logistic regression model (wherein if the differentially expressed microRNAs correspond to ACR, the one or more microRNAs are used to diagnose ACR, or if the differentially expressed microRNAs correspond to AMR, the one or more microRNAs are used to diagnose AMR).

[0067] In some embodiments, the methods further include generating a second logistic regression model using the microRNA expression data of each of the one or more samples corresponding to the one or more microRNAs; and identifying a first threshold score indicative of a likelihood of ACR or a second threshold score indicative of a likelihood of AMR based on the second logistic regression model. In some embodiments, the operations further include: receiving a request to determine whether a patient is diagnosed with ACR or AMR using a patient sample (the patient is a heart transplant recipient); obtaining sequence reads for a plurality of microRNAs as the patient sample; identifying microRNA expression data for the patient from the plurality of sequence reads for the patient corresponding to one or more microRNAs; and plotting the patient's microRNA expression data on a second logistic regression model; generating an ACR score or an AMR score for the patient based on the patient's microRNA expression data plotted on the second logistic regression model; determining that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score; and identifying a heart transplant rejection for the patient based on the patient being diagnosed with ACR or AMR. In some embodiments, the operations further include identifying a treatment for the patient based on the determination that the patient is diagnosed with ACR or AMR. In some embodiments, the target nucleic acid is involved in ACR or AMR.

[0068] In some embodiments, obtaining a plurality of microRNA sequence reads by sequencing one or more samples. In some embodiments, the predetermined criteria includes removing one or more sequence reads from the plurality of sequence reads based on removing 3' adapter barcode sequences, random barcode sequences, UniVec contaminants, or sequence reads <15 base pairs. In some embodiments, the operations further include performing a principal component analysis on the plurality of microRNA sequence reads after removing one or more sequence reads.

[0069] In some embodiments, upon identifying differentially expressed microRNAs, the methods further include adjusting the differentially expressed microRNAs for clinical covariates, in some embodiments, the clinical covariates include age, sex, race, or body mass index.

[0070] In some embodiments, the first logistic regression model is fitted with a LASSO penalty. In some embodiments, the tuning parameters of the LASSO penalty are selected by 10-fold cross-validation to minimize model deviance.

[0071] In some embodiments, the differentially expressed microRNAs used to generate the first logistic regression model have an unadjusted probability value of less than 0.10. In some embodiments, in generating the first logistic regression model, the operations further include: normalizing the counts of the differentially expressed microRNAs; log-transforming the normalized counts to generate log counts; and standardizing the log counts of each differentially expressed microRNA to have a mean of zero and a variance of one.

[0072] Some aspects of the present disclosure relate to a method for identifying transplant rejection in a heart transplant patient, the method including: receiving, by a processor, a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, the patient sample being from a heart transplant patient; obtaining, by the processor, sequence reads of a plurality of microRNAs of the patient as the patient sample; identifying, by the processor, microRNA expression data of the patient from the sequence reads of the plurality of microRNAs of the patient corresponding to one or more microRNAs, the one or more microRNAs being used to detect ACR or AMR; and, by the processor, plotting, by the processor, the microRNA expression data of the patient on a second logistic regression model; generating an ACR score or an AMR score: the processor identifying a coefficient based on the patient's microRNA expression data plotted on the second logistic regression model; the processor creating a weighted ACR score or weighted AMR score by multiplying each natural log transformed microRNA of the one or more microRNAs by the coefficient; and, the processor scaling the weighted ACR score or weighted AMR score based on a numerical range; the processor determining that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score corresponding to the ACR score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score corresponding to AMR; and, the processor identifying graft rejection in the patient based on the patient being diagnosed with ACR or AMR.

[0073] Some aspects of the present disclosure relate to a system for identifying transplant rejection in a patient, the system including: a memory; and a processor coupled to the memory, the processor configured to: receive a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, the patient sample being from a heart transplant patient; obtain sequence reads of a plurality of microRNAs of the patient as the patient sample; identify patient microRNA expression data from the sequence reads of the plurality of microRNAs of the patient corresponding to one or more microRNAs, the one or more microRNAs being used to detect ACR or AMR; and plot the patient microRNA expression data on a second logistic regression model; generate an ACR score or an AMR score for the patient by: identifying a coefficient based on the patient microRNA expression data plotted on the second logistic regression model; and determining one or more microRNAs as a function of the patient's microRNA expression data. creating a weighted ACR score or weighted AMR score by multiplying each natural log transformed microRNA of the roRNA by a coefficient; and scaling the weighted ACR score or weighted AMR score based on a numerical range; creating an ACR score or weighted AMR score for the patient by identifying a coefficient based on the patient's microRNA expression data plotted on a second logistic regression model; creating a weighted ACR score or weighted AMR score by multiplying each natural log transformed microRNA of the one or more microRNAs by a coefficient; and scaling the weighted ACR score or weighted AMR score based on a numerical range; determining that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score corresponding to an ACR score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score corresponding to an AMR; identifying graft rejection in the patient based on the patient being diagnosed with ACR or AMR.

[0074] Some aspects of the present disclosure relate to a non-transitory computer readable medium having instructions stored thereon, the instructions being executed by one or more processors of a device to cause the one or more processors to perform tasks including: receiving a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, where the patient sample is from a heart transplant patient; obtaining sequence reads of a plurality of microRNAs of the patient as the patient sample; identifying patient microRNA expression data from the sequence reads of the plurality of microRNAs corresponding to the one or more microRNAs, where the one or more microRNAs are used to detect ACR and AMR; and performing a second logistic regression on the patient microRNA expression data. generating an ACR score and an AMR score for the patient by: identifying coefficients based on the patient's microRNA expression data plotted on the second logistic regression model; generating a weighted ACR score or a weighted AMR score by multiplying each natural log transformed microRNA of one or more microRNAs by the coefficient; and scaling the weighted ACR score or the weighted AMR score based on a numerical range; determining that the patient is diagnosed with ACR if the ACR score is equal to or greater than a first threshold score corresponding to the ACR score, or that the patient is diagnosed with AMR if the AMR score is equal to or greater than a second threshold score corresponding to AMR; identifying graft rejection for the patient based on the patient being diagnosed with ACR or AMR.

[0075] Some aspects of the present disclosure relate to a method for determining at risk of transplant rejection in a heart transplant patient, the method including: receiving, by a processor, a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, the patient sample being from a heart transplant patient; obtaining, by the processor, sequence reads of a plurality of microRNAs of the patient as the patient sample; identifying, by the processor, microRNA expression data of the patient from the sequence reads of the plurality of microRNAs corresponding to one or more microRNAs, the one or more microRNAs being used to detect ACR or AMR; and plotting, by the processor, the microRNA expression data of the patient onto a second logistic regression model. generating, by the processor, an ACR score or an AMR score for the patient by: identifying, by the processor, a coefficient based on the patient's microRNA expression data plotted on a second logistic regression model; generating, by the processor, a weighted ACR score or a weighted AMR score by multiplying, by the coefficient, each natural log transformed microRNA for one or more microRNAs; and, by the processor scaling, by the processor, the weighted ACR score or the weighted AMR score based on a numerical range; and determining, by the processor, that the patient is at risk of being diagnosed with ACR if the ACR score is equal to or greater than a first threshold score corresponding to the ACR score, or that the patient is at risk of being diagnosed with AMR if the AMR score is equal to or greater than a second threshold score corresponding to AMR.

[0076] Some aspects of the present disclosure relate to a system for identifying transplant rejection in a patient, the system including: a memory; and a processor coupled to the memory, configured to: receive a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, the patient sample being from a heart transplant patient; obtain sequence reads of a plurality of microRNAs of the patient as the patient sample; identify microRNA expression data of the patient from the sequence reads of the plurality of microRNAs of the patient corresponding to one or more microRNAs, the one or more microRNAs being used to detect ACR or AMR; and, generating an ACR score or an AMR score for the patient by: identifying a coefficient based on the patient's microRNA expression data plotted on a second logistic regression model; generating a weighted ACR score or a weighted AMR score by multiplying each natural log transformed microRNA of one or more microRNAs by the coefficient; and scaling the weighted ACR score or the weighted AMR score based on a numerical range; and determining that if the ACR score is equal to or greater than a first threshold score corresponding to the ACR score, the patient is at risk of being diagnosed with ACR, or if the AMR score is equal to or greater than a second threshold score corresponding to AMR, the patient is at risk of being diagnosed with AMR.

[0077] Some aspects of the disclosure relate to a non-transitory computer readable medium having instructions stored thereon, the instructions being executed by one or more processors of a device to cause the one or more processors to perform tasks including: receiving a request to detect acute cellular rejection (ACR) or antibody-mediated rejection (AMR) in a patient sample, where the patient sample is from a heart transplant patient; obtaining sequence reads of a plurality of microRNAs of the patient as the patient sample; identifying patient microRNA expression data from the sequence reads of the plurality of microRNAs of the patient corresponding to the one or more microRNAs, where the one or more microRNAs are used to detect ACR and AMR; and, generating an ACR score and an AMR score for the patient by: identifying a coefficient based on the patient's microRNA expression data plotted on a second logistic regression model; creating a weighted ACR score or a weighted AMR score by multiplying each natural log transformed microRNA of one or more microRNAs by the coefficient; and scaling the weighted ACR score or the weighted AMR score based on a numerical range; and determining, by the processor, that the patient is at risk of being diagnosed with ACR if the ACR score is equal to or greater than a first threshold score corresponding to the ACR score, or that the patient is at risk of being diagnosed with AMR if the AMR score is equal to or greater than a second threshold score corresponding to AMR.

[0078] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate the disclosure and, together with the description, further serve to explain the principles of the disclosure and to enable one skilled in the relevant art to make and use the disclosure. [Brief description of the drawings]

[0079] [Figure 1A]FIG. 1A is a schematic diagram showing an example of a study overview according to certain aspects of the present disclosure. In transplant patients, blood samples were collected immediately before scheduled or clinically indicated endomyocardial biopsy. Biopsy samples were reviewed by an institutional pathologist to grade the presence / severity of ACR and AMR. Plasma was separated from whole blood. Small RNA transcriptomes were then extracted, isolated, and sequenced using shotgun sequencing on a next-generation sequencer. Sequencing data was aligned to the human genome and miRBase to determine the microRNA (miR) transcriptome for each sample. Biostatistical tools were then used to identify miR signatures for ACR and AMR.

[0080] [Figure 1B-1C] Figures 1B-1C are volcano plots showing differential expression of various miRs in ACR (Figure 1B) and AMR (Figure 1C) samples. The X-axis represents log fold + / - 0.5. The Y-axis represents unadjusted p=0.05. miRs with log-fold change ≥ ±0.5 but p-value <0.05 are present in the regions denoted IV and VI. miRs with p-value >0.05 but log-fold change < ±0.5 are present in the regions denoted II; differentially expressed miRs with log-fold change ≥ ±0.5 and p-value <0.05 are present in the regions denoted I and III, respectively (Figures 1B-1C).

[0081] [Fig. 1D-1K] Figures 1D-1K are box plots showing miR levels (log-transformed microRNA reads per million) for four differentially expressed miRs for ACR (Figures 1D-1G) and AMR (Figures 1H-1K) compared between controls and patients at three time points (pre-rejection, during rejection, and post-rejection), which were within 3 months of the rejection episode.

[0082] [Figures 2A-2D] Figures 2A and 2C illustrate the area under the receiver operating characteristic curves (AUC) of the miR panel for diagnosing ACR and AMR, and are further summarized in Figures 2B and 2D, respectively. miRs were selected to maximize diagnostic performance using LASSO regression. Test performance characteristics were reported for blood samples collected from 8 days to 2.6 years post-transplant.

[0083] [Diagram 3] FIG. 3 is a block diagram of a miR-based transplant rejection detection system according to some embodiments.

[0084] [Figure 4] FIG. 4 is a flow chart illustrating a process for generating a miR panel according to some embodiments.

[0085] [Diagram 5] FIG. 5 is a flow chart illustrating a process for identifying heart transplant rejection in a patient, according to some embodiments.

[0086] [Figure 6] FIG. 6 illustrates the clinical application of the miR scores for ACR and AMR.

[0087] [Figure 7] FIG. 7 is a block diagram illustrating example components of an apparatus, according to an embodiment.

[0088] The drawing in which an element first appears is typically indicated by the leftmost digit(s) in the corresponding reference number. In the drawings, like reference numbers may indicate identical or functionally similar elements. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0089] Some aspects of the present disclosure relate to microfluidic arrays, chips (e.g., microfluidic chips), and panels that include one or more RNA hybridization probes, where at least one of the RNA hybridization probes is selected from the group consisting of miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, miR- 10b-5p, miR-582-3p, let-7b-3p, miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR-17-5p, The hybridization is performed with a miR selected from the group consisting of miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, and let-7d-3p. Some embodiments of the present disclosure relate to chips (e.g., microfluidic chips). In some embodiments, the microfluidic arrays, chips (e.g., microfluidic chips), and panels are used in a method for identifying subjects having or at risk of having acute cardiac transplant rejection. In some embodiments, the acute transplant rejection comprises ACR. In some embodiments, the acute transplant rejection comprises AMR.

[0090] Another aspect of the present disclosure relates to a method for identifying a human subject having or at risk of having acute cardiac transplant rejection by measuring the expression of a panel of miRs in a biological sample obtained from the subject.

[0091] Other aspects of the present disclosure relate to methods for identifying differentially expressed miRs in patients experiencing or at risk of experiencing organ rejection. Provided herein are aspects of systems, devices, apparatus, methods, and / or computer program products for detecting graft rejection based on miRs, and / or combinations and subcombinations thereof. According to various aspects, a model is created for developing a miR panel indicative of graft rejection. The model is then applied to patient samples to indicate the status or likelihood of graft rejection in the patient.

[0092] I. Terminology In order that this specification may be more readily understood, certain terms are first defined. Additional definitions are set forth throughout the detailed description.

[0093] It should be noted that the terms "a" or "an" and an entity refer to one or more of that entity; for example, "a nucleotide sequence" is understood to represent one or more nucleotide sequences. Thus, the terms "a" (or "an"), "one or more," and "at least one" may be used interchangeably herein.

[0094] Furthermore, as used herein, "and / or" is taken to mean that each of the two specified features or components is specifically disclosed, either alone or in combination with the other. Thus, the term "and / or" as used herein in phrases such as "A and / or B" is intended to include "A and B," "A or B," "A alone," and "B alone." Similarly, the term "and / or" as used in phrases such as "A, B, and / or C" is intended to include each of the following aspects: A, B, and C; A, B, or C; A or C; A or B; B or C; A and C; A and B; B and C; A alone; B alone; and C alone.

[0095] When an embodiment is described herein with the phrase "comprising", it is understood that other similar embodiments described with the phrase "consisting of" and / or "consisting essentially of" are also provided. As used herein, the terms "comprise" and "include", as well as variations thereof (e.g., "comprises", "comprising", "includes", and "including") are understood to indicate the inclusion of a recited component, feature, element, or step, or group of components, features, elements, or steps, but not the exclusion of any other component, feature, element, or step, or group of components, features, elements, or steps. Any of the terms "comprising", "consisting essentially of" and "consisting of" may be substituted with either of the other two terms while retaining their ordinary meaning.

[0096] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure pertains. For example, the Concise Dictionary of Biomedicine and Molecular Biology, Juo, Pei-Show, 2nd ed., 2002, CRC Press; The Dictionary of Cell and Molecular Biology, 3rd ed., 1999, Academic Press; and the Oxford Dictionary Of Biochemistry And Molecular Biology, Revised, 2000, Oxford University Press provide those skilled in the art with a general dictionary of many of the terms used in this disclosure.

[0097] Units, prefixes, and symbols are written in the format accepted by the Systeme International de Unites (SI). Numeric ranges are inclusive of the numbers defining the range. Nucleotide sequences are written left to right in a 5' to 3' orientation unless otherwise noted. Amino acid sequences are written left to right in an amino to carboxy orientation. The items provided herein are not intended to limit the various aspects of the disclosure, which may be understood by reference to the specification in its entirety. Thus, the terms defined immediately below are more fully defined by reference to the specification in its entirety.

[0098] As used herein, the term "about" is used to mean approximately, roughly, around, or in the regions of. When the term "about" is used in conjunction with a numerical range, it modifies the range up or down (higher or lower) by extending the boundaries above and below the stated numerical values ​​by a variance of 10%.

[0099] As used herein, the term "acute heart allograft rejection" refers to a condition occurring in heart transplant patients in which the transplanted heart is rejected by the patient. As used herein, "acute cellular rejection" or "ACR" refers to a cellular acute heart allograft rejection in which the recipient's immune system, e.g., T cells, target and attack the donor heart. ACR is manifested as a lymphocyte-dominant, mononuclear inflammatory reaction that infiltrates the myocardial tissue. Conventional immunohistological evaluation can confirm the presence of CD-4 and CD-8 positive T lymphocytes with high affinity for the interleukin-2 receptor. An increase in intercellular adhesion molecules with high MHC-II expression on cardiomyocytes is also observed. As used herein, "antibody-mediated rejection" or "acute humoral / antibody rejection" or "AMR" refers to acute humoral cardiac graft rejection in which recipient antibodies react with donor antigens present on the transplanted heart, resulting in deposition of immunoglobulins and complement within the myocardial capillary bed. AMR causes accumulation of intravascular macrophages, accompanied by interstitial edema, hemorrhage, and neutrophil infiltration in and around the capillaries.

[0100] As used herein, when used in conjunction with a particular disease or condition, the term "afflicted with" refers to a subject currently suffering from or currently developing a particular disease or condition. For example, a subject suffering from ACR is one currently experiencing signs or symptoms of ACR, e.g., such a subject is currently developing an immune response to a donor heart. Conversely, the term "at risk of developing" refers to a subject who has not yet begun to develop symptoms and / or effects of a particular disease, but who is predisposed or likely to develop symptoms and / or effects of the disease in the near future (e.g., in the next 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or more weeks). A subject "at risk" of developing a disease may develop signs of the disease, such as increased immunoglobulin accumulation in AMR, but has not yet developed or exhibited any symptoms, e.g., for AMR, interstitial edema, hemorrhage, neutrophil infiltration in and around capillaries.

[0101] In some embodiments, the methods and / or arrays described herein are used for "surveillance" of subjects after organ transplantation (e.g., heart transplantation). "Surveillance," as used herein, refers to the ongoing monitoring of patients after organ transplantation to see if they develop rejection (e.g., AMR or ACR). Patients under surveillance do not need to have signs or symptoms of rejection.

[0102] In some embodiments, the methods and / or arrays described herein are used to "diagnose" organ transplant rejection (e.g., AMR or ACR) in a subject. As used herein, "diagnosis" refers to identifying a patient experiencing organ transplant rejection (e.g., AMR or ACR), where the patient experiences one or more signs or symptoms of rejection prior to or concurrent with diagnosis.

[0103] In some embodiments, the methods and / or arrays described herein are used for the "prediction" of organ transplant rejection (e.g., AMR or ACR). As used herein, "prediction" refers to identifying patients who are at risk of developing rejection (e.g., AMR or ACR) even though the patients do not experience any signs or symptoms of rejection.

[0104] As used herein, an "array" (sometimes called a "microarray") refers to a two- or three-dimensional arrangement of addressable regions, each having a specific chemical moiety or site (called a "probe" or "probe molecule") associated with that region (e.g., an RNA hybridization probe, etc.). An array is "addressable" in that it has multiple regions of different moieties (e.g., RNA hybridization probes), and that a region (an "array feature" or array "spot") at a particular predefined location ("address") on the array detects a specific target or class of targets (although an array feature may incidentally detect something that it is not targeted to). In the case of an array, the "target" is referred to as a component in a mobile phase (usually a fluid) that is detected by probes (sometimes called "target probes") that are bound to a substrate at various regions. The probes can be bound to the substrate by interactions including, for example, covalent bonds and / or electrostatic interactions. In the context of an array, the mobile phase includes or is prepared from a biological sample and includes the targets, i.e., miRs. "Interrogating" an array refers to obtaining information from the array, particularly information about targets that bind to the array. In certain embodiments, the array comprises a fluidic chip. In some embodiments, the array comprises a pneumatic system that includes one or more moveable pins and one or more chambers. In some embodiments, the array comprises a capillary system, where capillary forces move fluid through the array.

[0105] As used herein, the term "biological sample" refers to a sample obtained from a subject. In some embodiments, the sample is a "blood-based sample" and refers to a sample obtained from a subject that includes blood or blood components. A blood-based sample may include whole blood. In some embodiments, the biological sample includes or consists essentially of plasma. In some embodiments, the biological sample includes a tissue biopsy obtained from a subject. In some embodiments, the tissue biopsy is obtained from an organ transplant tissue. The methods disclosed herein for identifying miRs that may be indicative of organ rejection can be applied to any organ transplant. Thus, the biological sample may vary depending on the transplanted organ. In some embodiments, the biological sample includes urine (e.g., in the case of a kidney transplant). In some embodiments, the biological sample includes bronchoalveolar lavage fluid (e.g., in the case of a lung transplant).

[0106] As used herein, the term "microfluidic" refers to a component or system having microfluidic features, e.g., channels and / or chambers, typically fabricated on the micron or submicron scale. In some embodiments, the channels or chambers have at least one cross-sectional dimension in the range of about 0.1 microns to about 1500 microns, more typically in the range of about 0.2 microns to about 1000 microns, and even more typically in the range of about 0.4 microns to about 500 microns. Individual microfluidic features typically hold very small volumes of fluid, e.g., about 10 nanoliters to about 5 milliliters, about 100 nanoliters to about 2 milliliters, about 200 nanoliters to about 500 microliters, or about 500 nanoliters to about 200 microliters. An integrated microfluidic array device includes an array component bonded to a microfluidic component, the microfluidic component and the array component are operable in conjunction with each other, and an array substrate of the array component is in fluid communication with the microfluidic features of the microfluidic component. A microfluidic component is a component that includes microfluidic features and is adapted to operate in concert with an array component. An array component is a component that includes an array substrate and is adapted to operate in concert with a microfluidic component.

[0107] RNA (ribonucleic acid) is a polymeric molecule with multiple biological roles. As used herein, the terms "microRNA", "miRNA", or "miR" are used interchangeably and refer to small, single-stranded, non-coding RNA molecules. In some embodiments, miRs are about 15 to about 30 nucleotides in length (e.g., about 15, about 16, about 17, about 18, about 19, about 20, about 21, about 22, about 23, about 24, about 25, about 26, about 27, about 28, about 29, or about 30 nucleotides in length). miRs can have a variety of natural functions, including RNA silencing and post-transcriptional regulation of gene expression. Structurally, miRs are single-stranded molecules that fold back on themselves to form one or more hairpin loop structures.

[0108] As used herein, "RNA hybridization probe" refers to an RNA molecule for detecting a target RNA molecule, and the RNA hybridization probe has a specific sequence that is complementary to all or part of the target molecule.The RNA hybridization probe further comprises a detectable element, such as a fluorescent label or a radioactive label.In some embodiments, the RNA hybridization probe is further modified to enhance stability.

[0109] The terms "subject" and "patient" are used interchangeably herein and each refer to a human.

[0110] The various aspects described herein are described in further detail in the following subsections.

[0111] II. Arrays of the Present Disclosure Some embodiments of the present disclosure relate to a device comprising one or more RNA hybridization probes, the one or more RNA hybridization probes hybridizing to the miRs disclosed herein. In some embodiments, the device is a microfluidic array. In some embodiments, the device is a chip (e.g., a microfluidic chip). The arrays described in the present disclosure comprise RNA hybridization probes hybridizing to specific miRs identified herein as differentially expressed in subjects experiencing or at risk of experiencing ACR or AMR. Thus, the arrays disclosed herein are novel tools that allow clinicians to easily distinguish between ACR and AMR, as well as identify subjects experiencing or at risk of experiencing acute cardiac transplant rejection.

[0112] Some embodiments of the present disclosure relate to microfluidic arrays comprising one or more RNA hybridization probes, where at least one of the RNA hybridization probes is selected from the group consisting of miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, miR- 10b-5p, miR-582-3p, let-7b-3p, miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR-17-5p, It hybridizes to a miR selected from the group consisting of miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, and let-7d-3p.

[0113] In some embodiments, the microfluidic array comprises one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof.

[0114] In some embodiments, the microfluidic array comprises at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven RNA hybridization probes selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326. In some embodiments, the microfluidic array comprises a plurality of RNA hybridization probes, including an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe that hybridizes to miR-3615. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.In some embodiments, the microfluidic array comprises a plurality of RNA hybridization probes that hybridize to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0115] Some aspects of the present disclosure relate to a microfluidic array for identifying subjects experiencing or at risk of developing ACR, the microfluidic array comprising a plurality of RNA hybridization probes including an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, and an RNA hybridization probe that hybridizes to miR-374a-5p. a hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.In some embodiments, the microfluidic array comprises a plurality of RNA hybridization probes that hybridize to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe that hybridizes to miR-3615. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0116] Some embodiments of the present disclosure relate to microfluidic arrays comprising one or more RNA hybridization probes, where at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof.In some embodiments, the microfluidic array comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16 RNA hybridization probes selected from the group consisting of: an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, or miR-374. an RNA hybridization probe that hybridizes to miR-a-5p, an RNA hybridization probe that hybridizes to miR-1307, an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0117] In some embodiments, the microfluidic array comprises a plurality of RNA hybridization probes, including an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, and an RNA hybridization probe that hybridizes to miR-1307. an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.In some embodiments, the plurality of RNA hybridization probes consists of: an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307 ... an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0118] Some aspects of the disclosure relate to a microfluidic array for identifying subjects experiencing or at risk of developing AMR, the microfluidic array comprising a plurality of RNA hybridization probes, including an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, and an RNA hybridization probe that hybridizes to miR-130. 7, an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.In some embodiments, the plurality of RNA hybridization probes consists of: an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307 ... an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0119] III. RNA Hybridization Probe Panels Some embodiments of the present disclosure relate to RNA hybridization probe panels that can be interrogated to identify subjects experiencing or at risk of experiencing acute cardiac transplant rejection, e.g., ACR or AMR. In some embodiments, the RNA hybridization probe panel hybridizes to one or more miRs selected from the group consisting of: miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, m iR-10b-5p, miR-582-3p, let-7b-3p, miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR- miR-17-5p, miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, let-7d-3p, and any combination thereof, wherein the RNA hybridization probe panel is for use in identifying a human subject having or at risk of developing acute heart graft rejection following heart transplantation.

[0120] In some embodiments, the RNA hybridization probe panel comprises at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, RNA hybridization probes selected from the group consisting of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a- an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, an RNA hybridization probe that hybridizes to miR-326, and any combination thereof, wherein the RNA hybridization probe panel is for use in identifying a human subject experiencing or at risk of developing ACR.

[0121] In some embodiments, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326. In some embodiments, the RNA hybridization probe panel is for use in identifying a human subject experiencing or at risk of developing ACR.

[0122] In some embodiments, the RNA hybridization probe panel consists of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe that hybridizes to miR-374a-5p. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326. In some embodiments, the RNA hybridization probe panel is for use in identifying a human subject experiencing or at risk of developing ACR.

[0123] In some embodiments, the RNA hybridization probe panel comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16 RNA hybridization probes selected from the group consisting of: an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, RNA hybridization probe hybridizing to iR-374a-5p, RNA hybridization probe hybridizing to miR-1307, RNA hybridization probe hybridizing to miR-185-3p, RNA hybridization probe hybridizing to miR-4433b-3p, RNA hybridization probe hybridizing to miR-130b-3p, RNA hybridization probe hybridizing to miR-331-5p An RNA hybridization probe, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0124] In some embodiments, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307 ... an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p. In some embodiments, the RNA hybridization probe panel is for use in identifying a human subject experiencing or at risk of developing AMR.

[0125] In some embodiments, the RNA hybridization probe panel consists of an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307 ... an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p. In some embodiments, the RNA hybridization probe panel is for use in identifying a human subject experiencing or at risk of developing AMR.

[0126] IV. Methods of the Disclosure Described herein are examples of miRs that are differentially expressed in human subjects experiencing or at risk of experiencing ACR or AMR following heart transplantation. Thus, some aspects of the disclosure relate to methods of identifying human subjects experiencing or at risk of experiencing acute heart transplant rejection by measuring expression of one or more miRs disclosed herein.

[0127] Moreover, the methods used to generate the miR panels disclosed herein can be readily adapted to identify differentially expressed miRs associated with other types of organ transplant rejection. Thus, some aspects of the present disclosure relate to methods of identifying differentially expressed miRs in subjects experiencing or at risk for experiencing organ transplant rejection.

[0128] IV.A. Specific Methods Some aspects of the present disclosure relate to methods of identifying or diagnosing a subject as experiencing or at risk of experiencing acute cardiac graft rejection by measuring expression of one or more miRs disclosed herein in a biological sample obtained from the subject. In some embodiments, the acute cardiac graft rejection includes ACR. In some embodiments, the acute cardiac graft rejection includes AMR.

[0129] In some embodiments, the method includes obtaining a biological sample from a subject. In some embodiments, the biological sample is a blood-derived sample. In some embodiments, the blood-derived sample includes whole blood. In some embodiments, the biological sample is a whole blood sample. In some embodiments, the blood-derived sample includes serum. In some embodiments, the biological sample is a serum sample. In some embodiments, the blood-derived sample includes plasma. In some embodiments, the biological sample is a plasma sample. In some embodiments, the biological sample includes a tissue biopsy obtained from an organ transplant tissue. A sample suitable for the method disclosed herein includes miR. In some embodiments, RNA is isolated from the biological sample. In some embodiments, total RNA is isolated from the biological sample. In some embodiments, small RNA, e.g., non-coding RNA, is isolated from the biological sample. In some embodiments, miR is isolated from the biological sample.

[0130] In some embodiments of the present disclosure, the method includes measuring the level of a miR panel in a biological sample by contacting the biological sample with a microfluidic array disclosed herein. In some embodiments, a whole blood sample is applied to the microfluidic array. In some embodiments, a plasma sample is applied to the microfluidic array. In some embodiments, a serum sample is applied to the microfluidic array. In some embodiments, total RNA isolated from a blood-derived biological sample is applied to the microfluidic array. In some embodiments, small RNA isolated from a blood-derived biological sample is applied to the microfluidic array. In some embodiments, miR isolated from a blood-derived biological sample is applied to the microfluidic array.

[0131] In some embodiments, the levels of a particular miR are analyzed to determine the relative amount of the miR in a sample.

[0132] IV.A.1. ACR In some embodiments, the methods include identifying or diagnosing a subject as experiencing or at risk for experiencing ACR, wherein the methods include measuring the level of a panel of miRs in a biological sample obtained from the subject, wherein the miR panel includes miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, and miR-326. Measuring the level of miRs in a biological sample can be performed using any method. In some embodiments, the levels of the miR panel are measured using small RNA / microRNA / RNA sequencing, microarray hybridization, Northern blot, isothermal nucleic acid amplification, quantitative reverse transcriptase PCR (qRT-PCR), or real-time PCR (RT-PCR), or any combination thereof. Thus, in some embodiments, the RNA hybridization probes disclosed herein can be replaced with a pair of PCR primers that can detect the same miR (or cDNA made from the same miR) as the particular RNA hybridization probe.

[0133] In some embodiments, the level of the miR panel is measured by contacting a biological sample (or a sample containing miRs isolated from a biological sample) with one or more RNA hybridization probes. In some embodiments, the level of the miR panel is measured using a microfluidic array (e.g., a microfluidic array disclosed herein) that includes a plurality of RNA hybridization probes. In some embodiments, the level of a particular miR in a sample is determined by measuring the level of a detectable marker on the RNA hybridization probe.

[0134] In some embodiments, the plurality of RNA hybridization probes comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, and an RNA hybridization probe that hybridizes to miR-182-5p. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.In some embodiments, the plurality of RNA hybridization probes consists of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, and an RNA hybridization probe that hybridizes to miR-182-5p. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.In some embodiments, the plurality of RNA hybridization probes consists essentially of an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, and an RNA hybridization probe that hybridizes to miR-182-5p. an RNA hybridization probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

[0135] In some embodiments, the method further comprises determining an ACR signature score. In some embodiments, the ACR signature score is determined according to the following formula: Formula I ACR signature score=251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln [miR-326] To handle non-zero values, we use the number of reads per million data by adding +10 to each count. ln stands for natural logarithm. (c)=any number between 2.5 and 7.5; (d)=any number between 2 and 6; (e)=any number between 4 and 9; (f)=any number between 2 and 6; (g)=any number between 0.5 and 5; (h)=any number between 22 and 32; (i)=any number between 1 and 5; (j)=any number between 3 and 10; (k)=any number between 4 and 11; and (l)=any number between 6 and 14; where "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data) by a sequencer.

[0136] In some embodiments, (a) = any number from 26 to 31; (b) = any number from 0.16 to 0.21; (c) = any number from 4 to 6; (d) = any number from 3 to 5; (e) = any number from 6 to 7.5; (f) = any number from 3 to 5; (g) = any number from 1 to 3; (h) = any number from 25 to 28; (i) = any number from 2 to 4; (j) = any number from 5 to 7; (k) = any number from 7 to 9; and (l) = any number from 10 to 12.

[0137] In some embodiments, (a) = about 28.90; (b) = about 0.19; (c) = about 5.46; (d) = about 4.77; (e) = about 6.41; (f) = about 4.41; (g) = about 2.20; (h) = about 27.69; (i) = about 3.05; (j) = about 6.17; (k) = about 7.71; and (l) = about 10.63.

[0138] In some embodiments, the panel comprises one or more additional ACR miRs. In some embodiments, the miR panel comprises miR-23a-3p, miR-30e-5p, let-7g-5p, miR-24-3p, miR-27a-3p, miR-223-3p, miR-197-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-323b-3p, miR-582-3p, miR-432-5p, miR-329-3p, miR-376c-3p, and miR-326; wherein the ACR score is calculated according to the following formula: Formula II ACR score=326 + (a) * ln [miR-23a-3p] - (b) * ln [miR-30e-5p] + (c) * ln [let-7g-5p] - (d) * [miR-24-3p] + (e) * ln [miR-27a-3p] - (f) * ln [miR-223-3p] + (g) * ln [miR-197-3p] - (h) * ln [miR-3615] + (i) * ln [miR-374a-5p] + (j) * ln [miR-182-5p] - (k) * ln [miR-345-5p] + (l) * ln [miR-361-3p] - (m) * ln [miR-130b-3p] - (n) * ln [miR-1299] + (o) * ln [miR-323b-3p] + (p) * ln [miR-582-3p] + (q) * ln [miR-432-5p] + (r) * ln [miR-329-3p] - (s) * ln [miR-376c-3p] - (t) * ln [miR-326] To handle non-zero values, we use the number of reads per million data by adding +10 to each count. ln stands for natural logarithm. where: (a) = any number from 1 to 7; (b) = any number from 26 to 36; (c) = any number from 1 to 5; (d) = any number from 8 to 18; (e) = any number from 1 to 7; (f) = any number from 4 to 14; (g) = any number from 3 to 13; (h) = any number from 0.1 to 1; (i) = any number from 2 to 12; (j) = any number from 1 to 7; (k) = any number from 1 to 7; (l) = any number from 18 to 28; (m) = any number from 2 to 12 (p)=any number from 2 to 8; (q)=any number from 1 to 7; (r)=any number from 0.5 to 3.5; (s)=any number from 5 to 15; and (t)=any number from 6 to 16; where "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data points) by a sequencer.

[0139] In some embodiments, (a) = any number from 2 to 5; (b) = any number from 30 to 33; (c) = any number from 1.5 to 3; (d) = any number from 11 to 15; (e) = any number from 2 to 5; (f) = any number from 7 to 11; (g) = any number from 6 to 10; (h) = any number from 0.18 to 0.38; (i) = any number from 5 to 9; (j) = any number from 2 to 5. (k) = any number from 2 to 5; (l) = any number from 20 to 25; (m) = any number from 3 to 6; (n) = any number from 4.5 to 6.5; (o) = any number from 0.5 to 1; (p) = any number from 3 to 6; (q) = any number from 2 to 5; (r) = any number from 1 to 3; (s) = any number from 8 to 12; and (t) = any number from 9 to 14.

[0140] In some embodiments, (a) = about 3.64; (b) = about 31.79; (c) = about 2.10; (d) = about 13.49; (e) = about 3.75; (f) = about 9.30; (g) = about 8.18; (h) = about 0.28; (i) = about 7.51; (j) = about 3.88; (k) = about 3.59; (l) = about 23.57; (m) = about 4.58; (n) = about 5.73; (o) = about 0.71; (p) = about 4.69; (q) = about 3.32; (r) = about 1.90; (s) = about 10.12; and (t) = about 11.78.

[0141] In some embodiments, a subject is identified as experiencing ACR if the ACR score is about 65 or greater.

[0142] In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 45 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 50 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 50 to about 60. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 50 to about 55. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 51 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 52 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 53 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 54 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 55 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 56 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 57 or greater. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 58 or greater. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 59 or greater. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 60 or greater.

[0143] In some embodiments, subjects with an ACR score of about 65 or greater are administered immunosuppressive therapy. In some embodiments, immunosuppressive therapy is administered to a subject after the subject is identified as having a score of about 65 or greater. In some embodiments, the immunosuppressive therapy comprises administering a therapy selected from the group consisting of corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. In some embodiments, subjects with an ACR score of about 65 or greater are candidates for endomyocardial biopsy. In some embodiments, endomyocardial biopsy is performed after the subject is identified as having an ACR score of about 65 or greater. In some embodiments, subjects with an ACR score less than 65 are not candidates for endomyocardial biopsy.

[0144] IV.A.2. AMR In some embodiments, the method includes identifying a subject as experiencing or at risk of experiencing AMR, wherein the method includes measuring the level of a panel of miRs in a biological sample obtained from the subject, wherein the miR panel includes miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, and miR-589-5p. Measuring the level of miRs in a biological sample can be performed using any method. In some embodiments, the levels of the miR panel are measured using small RNA / microRNA / RNA sequencing, microarray hybridization, Northern blot, isothermal nucleic acid amplification, quantitative reverse transcriptase PCR (qRT-PCR), or real-time PCR (RT-PCR), or any combination thereof.

[0145] In some embodiments, the level of the miR panel is measured by contacting the biological sample (or a sample containing miRs isolated from the biological sample) with one or more RNA hybridization probes. In some embodiments, the level of the miR panel is measured using a microfluidic array (e.g., a microfluidic array disclosed herein) that includes a plurality of RNA hybridization probes.

[0146] In some embodiments, the plurality of RNA hybridization probes comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307. an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.In some embodiments, the plurality of RNA hybridization probes consists of an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307. an RNA hybridization probe that hybridizes to miR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.In some embodiments, the plurality of RNA hybridization probes consists essentially of an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, An RNA hybridization probe that hybridizes to iR-185-3p, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

[0147] In some embodiments, the method further comprises determining an AMR signature score. In some embodiments, the AMR signature score is determined according to the following formula: Formula III AMR signature score=222.41 - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p] To handle non-zero values, we use the number of reads per million data by adding +10 to each count. ln stands for natural logarithm. where: (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = any number from 0.1 to 2; (m) = any number from 1 to 4; (n (o)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; administering immunosuppressive therapy to a human subject identified as having an AMR signature score of about 65 or greater; wherein "[X]" refers to the level of "X" in a biological sample; and wherein "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data) by a sequencer.

[0148] In some embodiments, (a)=any number from 24 to 27; (b)=any number from 8.5 to 10.5; (c)=any number from 2 to 4; (d)=any number from 4.5 to 6.5; (e)=any number from 7.5 to 9.5; (f)=any number from 7 to 9; (g)=any number from 2 to 4; (h)=any number from 1.0 to 1.75; (i)=any number from 7 to 9; (j)=any number from 9 to 11; (k)=any number from 5 to 7; (l)=any number from 1 to 2; (m)=any number from 1.5 to 2.5; (n)=any number from 1.5 to 2.5; (o)=any number from 0.7 to 1.7; (p)=any number from 0.5 to 1.5; and (q)=any number from 1.4 to 2.4.

[0149] In some embodiments, (a) = about 25.44; (b) = about 9.33; (c) = about 3.39; (d) = about 5.82; (e) = about 8.24; (f) = about 8.62; (g) = about 2.75; (h) = about 1.43; (i) = about 7.95; (j) = about 9.69; (k) = about 5.47; (l) = about 0.60; (m) = about 2.05; (n) = about 2.24; (o) = about 1.40; (p) = about 0.87; and (q) = about 1.69.

[0150] In some embodiments, the panel comprises one or more additional AMR miRs. In some embodiments, the miR panel comprises: miR-143-3p, let-7b-5p, miR-10b-5p, miR-23a-3p, miR-24-3p, miR-10a-5p, miR-27a-3p, miR-125a-5p, miR-93-5p, let-7d-3p, miR-191-5p, miR-484, miR-99b-5p, miR-340-5p, miR-1-3p, miR-193a-5p, miR-145-3p, miR-197-3p, let-7b-3p, miR-454-3p, miR-450b-5p, miR-215- 5p, miR-4433b-5p, miR-1249-3p, miR-142-3p, miR-145-5p, miR-374a-5p, miR-542-3p, miR-1307-3p, miR-17-5p, miR-345-5p, miR-185-3p, miR-338-5p, miR-769-5p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, and miR-589-5p; where the AMR score is calculated according to the following formula: Formula IV AMRスコア=107.1 + (a) ln (miR-143-3p) + (b) ln (let-7b-5p) - (c) ln (miR-10b-5p) - (d) ln (miR-23a-3p) - (e) ln (miR-24-3p) + (f) ln (miR-10a-5p) + (g) ln (miR-27a-3p) + (h) ln (miR-125a-5p) - (i) ln (miR-93-5p) + (j) ln (let-7d-3p) + (k) ln (miR-191-5p) - (l) ln (miR-484) + (m) ln (miR-99b-5p) + (n) ln (miR-340-5p) - (o) ln (miR-1-3p) + (p) ln (miR-193a-5p) + (q) ln (miR-145-3p) - (r) ln (miR-197-3p) - (s) ln (let-7b-3p) - (t) ln (miR-454-3p) + (u) ln (miR-450b-5p) - (v) ln (miR-215-5p) - (w) ln (miR-4433b-5p) + (x) ln (miR-1249-3p) + (y) ln (miR-142-3p) - (z) ln (miR-145-5p) + (aa) ln (miR-374a-5p) - (bb) ln (miR-542-3p) + (cc) ln (miR-1307-3p) + (dd) ln (miR-17-5p) + (ee) ln (miR-345-5p) + (ff) ln (miR-185-3p) + (gg) ln (miR-338-5p) - (hh) ln (miR-769-5p) + (ii) ln (miR-4433b-3p) + (jj) ln (miR-130b-3p) - (kk) ln (miR-331-5p) + (ll) ln (miR-140-5p) - (mm) ln (miR-223-5p) + (nn) ln (miR-582-3p) + (oo) ln (miR-122-3p) - (pp) ln (miR-589-5p) where: (a) = any number from 0.1 to 4; (b) = any number from 1 to 6; (c) = any number from 13 to 25; (d) = any number from 26 to 36; (e) = any number from 3 to 12; (f) = any number from 6 to 16; (g) = any number from 9 to 20; (h) = any number from 1 to 7; (i) = any number from 0.1 to 4; (j) = any number from 25 to 35; (k) = any number from 0.25 to 2.25; (l) = any number between 11 and 22;(m) = any number between 3 and 10;(n) = any number between 0.5 and 5;(o) = any number between 1 and 6;(p) = any number between 1 and 8;(q) = any number between 1 and 8;(r) = any number between 4 and 13;(s) = any number between 1 and 7;(t) = any number between 5 and 15;(u) = any number between 1 and 10;(v) = any number between 1 and 5;(w) = any number between 1 and 6;(x) = 1 or (y) = any number from 8 to 18; (z) = any number from 8 to 18; (aa) = any number from 1 to 6; (bb) = any number from 4 to 13; (cc) = any number from 0.25 to 2.25; (dd) = any number from 1 to 8; (ee) = any number from 1 to 7; (ff) = any number from 3 to 10; (gg) = any number from 3 to 10; (hh) = any number from 1 to 7; (ii) = any number from 5 to 15 (nn) = any number from 0.1 to 3; (oo) = any number from 1 to 6; and (pp) = any number from 1 to 6; where "[X]" refers to the level of "X" in a biological sample, e.g., expressed as the number of reads per sample (per million data) by a sequencer.

[0151] In some embodiments, (a) = any number from 1 to 2; (b) = any number from 3 to 4; (c) = any number from 19 to 22; (d) = any number from 31 to 34; (e) = any number from 6 to 9; (f) = any number from 10 to 13; (g) = any number from 11 to 16; (h) = any number from 3 to 5; (i) = any number from 1 to 2; (j) = any number from 28 to 32; (k) = any number from 0.5 to 0.5; (l) = any number between 15 and 18; (m) = any number between 5 and 7; (n) = any number between 1.5 and 2.5; (o) = any number between 2.5 and 3.5; (p) = any number between 4 and 5; (q) = any number between 4 and 5; (r) = any number between 7 and 10; (s) = any number between 3 and 5; (t) = any number between 7 and 11; (u) = any number between 4.5 and 7; (v) = any number between 2 and (w) = any number from 2.5 to 4.5; (x) = any number from 2 to 5; (y) = any number from 11 to 14; (z) = any number from 11 to 14; (aa) = any number from 2.25 to 4.25; (bb) = any number from 7 to 10; (cc) = any number from 0.75 to 2; (dd) = any number from 3 to 5.5; (ee) = any number from 2 to 5; (ff) = any number from 5 to 9 (gg) = any number from 5 to 9; (hh) = any number from 2 to 5; (ii) = any number from 7 to 12; (jj) = any number from 0.25 to 1.5; (kk) = any number from 2 to 5; (ll) = any number from 2 to 4; (mm) = any number from 3 to 5; (nn) = any number from 0.5 to 1.75; (oo) = any number from 2 to 4; and (pp) = any number from 2 to 4.

[0152] In some embodiments, (a)=about 1.59; (b)=about 3.4; (c)=about 20.35; (d)=about 32.4; (e)=about 7.89; (f)=about 11.93; (g)=about 14.41; (h)=about 3.93; (i)=about 1.39; (j)=about 30.11; (k)=about 1.15; (l)=about 16.25; (m)=about 6.21; (n)=about 2.03; (o)=about 3.07; (p)=about 4.92; (q)=about 4.49; (r)=about 8.65; (s)=about 4.08; (t)=about 9.15; (u)=about 5.62; (v) = about 2.96; (w) = about 3.48; (x) = about 3.21; (y) = about 12.86; (z) = about 13.0; (aa) = about 3.22; (bb) = about 8.56; (cc) = about 1.37; (dd) = about 4.39; (ee) = about 3.18; (ff) = about 6.47; (gg) = about 6.05; (hh) = about 3.74; (ii) = about 9.45; (jj) = about 0.69; (kk) = about 3.61; (ll) = about 2.84; (mm) = about 4.07; (nn) = about 1.11; (oo) = about 2.98; and (pp) = about 3.11.

[0153] In some embodiments, a subject is identified as experiencing AMR if the AMR score is greater than or equal to about 65. In some embodiments, a subject is diagnosed with AMR if the AMR score is greater than or equal to about 65.

[0154] In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 45 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 50 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 50 to about 60. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 55 to about 60. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 51 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 52 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 53 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 54 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 55 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 56 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 57 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 58 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 59 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 60 or greater.

[0155] In some embodiments, subjects with an AMR score of about 65 or greater are administered immunosuppressive therapy. In some embodiments, the immunosuppressive therapy comprises administering a therapy selected from the group consisting of intravenous immunoglobulin, plasma exchange, bortezomib, carfilzomib, rituximab, eculizumab, corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. In some embodiments, subjects with an AMR score of about 65 or greater are candidates for endomyocardial biopsy. In some embodiments, subjects with an AMR score of less than 65 are not candidates for endomyocardial biopsy.

[0156] IV.B. Treatment Methods Some embodiments of the present disclosure relate to a method of treating acute heart transplant rejection in a subject in need of treatment, comprising: (i) identifying a subject experiencing or at risk of experiencing acute heart transplant rejection selected from ACR and AMR, and (ii) administering immunosuppressive therapy to the subject. In some embodiments, the acute heart transplant rejection comprises ACR, and the subject is administered immunosuppressive therapy comprising administering a therapy selected from the group consisting of corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. In some embodiments, the subject is identified as experiencing or at risk of experiencing ACR, and the subject is administered a corticosteroid. In some embodiments, the subject is identified as experiencing or at risk of experiencing ACR, and the subject is administered an antithymocyte globulin. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered tacrolimus. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered cyclosporine. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered sirolimus. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered everolimus. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered mycophenolate mofetil. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered azathioprine. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered tocilizumab. In some embodiments, the subject is identified as having or at risk of having an ACR and the subject is administered belatacept.In some embodiments, the subject is identified as having or at risk of having an ACR, and the subject is treated with a reoperation heart transplant.

[0157] In some embodiments, the acute cardiac transplant rejection comprises AMR, and the subject is administered an immunosuppressive therapy comprising administering a therapy selected from the group consisting of intravenous immunoglobulin, plasma exchange, bortezomib, carfilzomib, rituximab, eculizumab, corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered intravenous immunoglobulin. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered plasma exchange. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered bortezomib. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered carfilzomib. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered rituximab. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered eculizumab. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered a corticosteroid. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered antithymocyte globulin. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered tacrolimus. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered cyclosporine. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered sirolimus. In some embodiments, a subject is identified as undergoing or at risk of undergoing AMR and the subject is administered everolimus.In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered mycophenolate mofetil. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered azathioprine. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered tocilizumab. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is administered belatacept. In some embodiments, the subject is identified as experiencing or at risk of experiencing AMR, and the subject is treated with a heart transplant reoperation.

[0158] IV.C. Graft Rejection Detection Systems Some embodiments of the present disclosure provide methods for identifying subjects experiencing or at risk of developing acute cardiac transplant rejection. However, the techniques used to identify the various miRs used in these methods can be applied to identify miRs that can be indicative of other types of organ rejection. Thus, some embodiments of the present disclosure relate to determining the miR transcriptome of cardiac transplant recipients, identifying miR expression in the context of ACR and AMR, and developing distinct miR panels that can be used to non-invasively diagnose ACR and AMR. Additionally, the embodiments described herein allow for the use of genomic biomarker testing, allowing patients to begin specific therapeutic pathways based on the subtype of rejection. Additionally, the embodiments described herein generate individual ACR and AMR miR gene expression scores, allowing for clinical interpretation and non-invasive diagnosis of acute rejection. This score is specific to ACR or AMR, so that if elevated, targeted therapy can be administered while awaiting the results of other diagnostic tests.

[0159] In this regard, embodiments described herein provide for diagnosing heart transplant rejection using only a blood test ("liquid biopsy").

[0160] 3 is a block diagram of a system for detecting transplant rejection based on miRs, according to some embodiments. The system may include a server 300, a database 310, and a client device 320. The devices of the system may be connected via a network. For example, the devices of the system may be connected via wired connections, wireless connections, or a combination of wired and wireless connections. In an exemplary embodiment, one or more portions of the network may be an ad-hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless wide area network (WWAN), a metropolitan area network (MAN), a portion of the Internet, a portion of the public switched telephone network (PSTN), a cellular network, a wireless network, a WiFi network, a WiMax network, any other type of network, or a combination of two or more of such networks.

[0161] In some embodiments, server 300 and database 310 may reside in a cloud computing environment. In other embodiments, server 300 may reside in a cloud computing environment and database 310 may reside outside of the cloud computing environment. Additionally, in other embodiments, server 300 may reside outside of the cloud computing environment and database 310 may reside in the cloud computing environment.

[0162] The server 300 may be configured to execute one or more applications for identifying likelihood of transplant rejection based on miRs. The database 310 may be configured to store structured and unstructured data. The server 300 may store and retrieve data from the database 310 for identifying likelihood of transplant rejection based on miRs.

[0163] The client device 320 can communicate with the server 300. The client device 320 can be configured to execute an application 325 to communicate with the server 300. The application 325 can be used to send a request to the server 300 to identify miR-based likelihood of graft rejection for one or more patients. The application 325 can include a user interface. The user interface can be used to send the request to the server 300. Further, the user interface can also render responses received from the server 300. The client device 320 can be operated by a user, including, but not limited to, a patient, a medical professional, an insurance company, etc.

[0164] In one embodiment, the client device 320 and the server 300 are integrated into the same device, such that the operations performed by the server described herein are performed directly on the client device, which itself communicates with the database 310.

[0165] IV.C.1. Creation of miR panels FIG. 4 is a flow chart illustrating a process for developing a miR panel according to some embodiments. Although applied herein to a miR panel related to acute cardiac transplant rejection, the methods described herein can be broadly applied to developing miR panels for other organ rejection. Method 400 can be performed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions executed on a processing device), or a combination thereof. It should be understood that not all steps are required to practice the disclosure provided herein. Furthermore, some steps may be performed simultaneously or in a different order than that shown in FIG. 4, as would be understood by one of ordinary skill in the art.

[0166] The method 400 will be described with reference to Figure 3. However, the method 400 is not limited to that exemplary embodiment.

[0167] At 402, sequence data for a plurality of subjects is obtained. In some embodiments, the server 300 can sequence RNA from samples obtained from the subjects to generate sequence reads. The subjects can include subjects that are patients and / or controls. In some embodiments related to the development of miR panels for identifying organ transplant rejection, the samples can be blood, urine, cerebrospinal fluid, semen, saliva, sputum, stool, and tissue. The sequence data is obtained from any suitable internal or external data source (e.g., database 310). As non-limiting examples, sequence data may be obtained from data sources related to Genomic Research Alliance for Transplantation (GRAfT), Cedars-Sinai Medical Center, University of Utah, Stanford University Heart Transplant Biobank, Outcomes AlloMap Registry (OAR) Donor-Derived Cell-Free DNA-Outcomes Allomap Registry (D-OAR), Surveillance HeartCare Outcomes Registry (SHORE), Donor-Derived Cell-free DNA to DETect REjection in Cardiac Transplantation (DETECT), PROTECT Registry, INTERHEART Study, DNA-Based Transplant Rejection Test (DTRT) study, Clinical Trials in Organ Transplantation, etc. Additionally, blood samples may be collected from subjects or patients during surveillance or clinically indicated testing. miRs may be blood-derived. For patients undergoing EMB, blood samples may be collected prior to treatment. Venous blood is collected into containers, such as Streck Cell-Free DNA tubes, and processed to separate the plasma, which can be stored at an appropriate temperature, such as -80°C.RNA can be extracted from the plasma using known extraction techniques, such as MagMAX mirVana isolation kit (Thermo Fisher Scientific, Gaithersburg MD). After elution, library preparation can be performed using a library preparation tool, such as NEXTFLEX Small RNA-Seq Kit v3 (PerkinElmer Inc, Shelton CT). The prepared RNA can then be sequenced using a sequencing machine, such as NEXTSEQ 500 (Illumina Inc., San Diego CA), using, for example, 50 base pair (bp) single end reads. In some embodiments, the server 300 can implement a sequencing machine to sequence the RNA. Sequencing can generate, for example, 11 million sequence reads per sample.

[0168] In some embodiments, other sequencing methods may be used. For example, the server 300 may sequence the RNA in the sample using complementary DNA sequencing, small RNA / non-coding RNA sequencing, Direct RNA sequencing, single molecule real-time RNA sequencing, single cell RNA sequencing (scRNA-Seq), etc. In some embodiments, the sequence may be obtained from a previously imported database, and the server 300 does not perform the actual sequencing, but rather obtains the sequence data from the database.

[0169] In some embodiments, sequence reads can be annotated using PCR, arrays, probe assays, iNAAT, CRISPR, or other molecular testing methods, and based thereon, sequence reads can be identified.

[0170] At 404, the server 300 filters the sequence reads by removing one or more sequence reads from the generated sequence reads. For example, a sequence FASTQ file corresponding to the sequence reads can be processed to remove 3' adapter barcode sequences, random barcode sequences, UniVec contaminants, and reads <15 base pairs (bp). Furthermore, the high quality filtered sequences from the sequence reads can be intrinsically aligned using miRbase v22, GENCODE v24 for reference to the human genome 38, and gtRNAdb v16. Samples with insufficient quality miR reads (<1,000,000 reads per sample) can be excluded from the analysis. Small RNA sequence data in multiple sequence reads can be analyzed using the Extracellular RNA Communication Consortium (ERCC) RNA pipeline (extracellular RNA processing tool, exceRpt).

[0171] To eliminate or mitigate batch effects between small RNA sequencing runs, the server 300 can perform a principal component analysis (PCA) on the sequence reads (excluding one or more removed sequence reads). This PCA can use, for example, spike-in nematode samples and pooled plasma controls from unrelated human donors. Batch effects occur when non-biological factors in an experiment cause variation in the data produced by the experiment. The server 300 can exclude outlier samples from further analysis.

[0172] At 406, the server 300 identifies target genes in the sequence reads of the filtered miR. The target genes are identified as involved in ACR or AMR. For example, the server 300 can use miRTarBase v8.0 to identify target genes of miRs involved in ACR or AMR. The server 300 can include target mRNAs verified, for example, by reporter assays, western blots, or microarray experiments with overexpression or knockdown of miRs in the analysis. The server 300 can perform network analysis and data visualization, for example, using interactive web tools such as MIENTURNET. The server 300 can identify biological pathways that may be regulated by differentially expressed miRs by searching publicly available databases, such as the Reactome database. In some embodiments, the publicly available databases can be part of the database 310.

[0173] At 408, the server 300 identifies miRs in the sample based on the identified target genes. As a non-limiting example, the server 300 can identify ~1,900 expressed miRs in plasma. The server 300 can filter low expressed miRs (e.g., miRs with an average of less than 100 mapped reads across all samples). Additionally, the server 300 removes miRs miR-486-5p and miR-451a, which are miRs derived from red blood cells. The server 300 includes the remaining miRs (e.g., ~350 miRs) in the analysis.

[0174] At 410, the server 300 screens the miRs (e.g., the remaining ∼350 miRs) to identify differentially expressed miRs using a differential gene expression analysis tool such as DESeq2 while adjusting for clinical covariates (e.g., age, sex, race, body mass index). According to an embodiment, the differentially expressed miRs can be screened based on their correspondence with ACR or AMR. By doing so, the server 300 identifies differentially expressed miRs associated with a particular outcome that can be identified from the miR transcriptome. The server 300 may adjust for blood type in a subset of patients with minor changes in miR profiles. Alternatively, the server 300 may adjust the data for age, sex, race, and body mass index to maximize sample size.

[0175] Approximately 50% of all protein-coding genes are under the control of miRs, and one mRNA may be regulated by multiple miRs. In most cases, miRs negatively regulate downstream gene expression. Gene expression signatures in ACR and AMR may result from immune system responses to graft injury or directly from apoptotic cardiomyocytes and endothelial cells in the injured cardiac graft. In this regard, differentially expressed miRs may be dysregulated in certain key pathways involved in ACR and AMR, including mTOR signaling, T cell differentiation, interleukin signaling, DNA damage recognition, transcriptional regulation, TGF-β signaling, tumor necrosis factor (TNF) signaling, toll-like receptor cascade, T cell receptor signaling, lymphocyte proliferation, and cell death / apoptosis.

[0176] According to one embodiment for cardiac transplant detection, after filtering out low-expressed miRs, the server 300 determined that ~350 miRs were consistently expressed across all cardiac transplant patients (12 differentially expressed miRs in ACR and 27 in AMR). Using a rigorous statistical approach while controlling for clinical covariates, the 12 miRs in ACR and 17 miRs in AMR were selected. Furthermore, these miRs showed minimal correlation with each other (data not shown), suggesting that these miRs individually serve as sources of information for rejection.

[0177] At 412, the server 300 creates a first logistic regression model corresponding to a particular outcome (e.g., AMR or ACR) using the identified miRs with unadjusted p-values, e.g., <0.10. In some embodiments, the server 300 fits the first logistic regression model with the identified miRs with a LASSO penalty. Within the LASSO analysis, the server 300 may log-transform the normalized miR counts for normal approximation. The log counts of each miR may be standardized, e.g., to have a mean of 0 and a variance of 1. The tuning parameters of the LASSO penalty may be selected by the server 300, e.g., based on 10-fold cross-validation, to minimize model deviance.

[0178] At 414, the server 300 identifies one or more miRs from the identified miRs using logistic-LASSO regression. The one or more miRs constitute a miR panel used to diagnose AMR or ACR. For example, the server 300 creates a miR panel for diagnosing AMR based on the miRs differentially expressed corresponding to AMR. In another example, the server 300 creates a different miR panel for diagnosing ACR based on the miRs differentially expressed corresponding to ACR. The server 300 can also create a Receiver Operating Characteristic (ROC) curve and calculate the area under the curves (AUC) to evaluate the performance of the identified miR set. The model can also be independently validated for ACR and AMR.

[0179] In view of the above, using one or more identified miRs (corresponding to ACR or AMR) to diagnose AMR or ACR improves computational efficiency and shortens the time required to diagnose transplant rejection. In particular, rather than having to analyze all miRs in a given sample, specific miRs can be targeted in the sample. This significantly reduces the amount of data to be processed. As a result, this improves computational efficiency in diagnosing the possibility of transplant rejection.

[0180] Furthermore, the ability to target specific miRs in a sample can improve the accuracy of transplant rejection diagnosis with less data. For example, attempting to diagnose possible transplant rejection from a given sample without using specific miRs may give a false indication of possible transplant rejection or miss the possibility of transplant rejection entirely. Thus, the use of one or more identified miRs for the diagnosis of AMR or ACR can improve the accuracy of transplant rejection diagnosis.

[0181] IV.C.2. Creating models and scores The server 300 creates a second logistic regression model for ACR and AMR using the read counts per million data (adding 10 for each read count to make it a non-zero value) for one or more miRs selected by the logistic-LASSO regression (e.g., miR panel) and applies it to the subjects identified for the first logistic regression model. The read counts per million data may be based on the miR panel identified for each subject. Regular logistic regression estimates are prone to bias due to small sample sizes and large differences observed in the expression of some miRs in patients and controls (which causes the likelihood function to flatten around the maximum value), especially for AMR. In this scenario, the server 300 can use a reduced bias maximum likelihood estimator for the parameters of the final logistic regression model.

[0182] To evaluate the predictive ability of miRs, for example, 10-fold cross-validation can be used to generate ROC curves and AUC statistics. The Youden index can be used to identify thresholds for maximizing test performance. Test performance characteristics in validation can include sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV).

[0183] The server 300 can identify different rejection score thresholds for ACR and AMR based on the population division indicated by the second logistic regression model. The server 300 can identify score thresholds based on the counts per million data of the miR panel for each subject plotted on the second logistic regression model. These different rejection score thresholds for ACR and AMR are based on the miR expression data of each patient sample. These score thresholds can be used to facilitate interpretation of the miR expression data in blood and can support clinical decision-making regarding the likelihood of ACR or AMR.

[0184] IV.C.3. Development of algorithms to calculate patient ACR or AMR 5 is a flow chart illustrating a process for identifying cardiac transplant rejection in a patient, according to some embodiments. Method 500 can be performed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions executed on a processor), or a combination thereof. It should be understood that not all steps are required to practice the disclosure provided herein. Furthermore, some steps may be performed simultaneously or in a different order than that shown in FIG. 5, as would be understood by one of ordinary skill in the art.

[0185] The method 500 will be described with reference to Figure 1. However, the method 500 is not limited to that exemplary embodiment.

[0186] At 502, the server 300 sequences a sample obtained from a patient and generates sequence reads. The patient is a heart transplant recipient. The sample is sequenced as described above with respect to method 400 (402).

[0187] At 504, the server 300 identifies patient-specific miR expression data from the sequence reads based on the miR panel identified in method 400. The miR panel can be for diagnosing ACR or AMR. In this regard, the server 300 identifies patient counts per million data for each mIR in the miR panel from the patient's sequence reads.

[0188] In 506, the server 300 plots the patient-specific miR expression data against a second logistic regression model (i.e., a logistic regression model based on read counts per million data for one or more miRs in the selected mIR panel).

[0189] At 508, the server 300 creates a patient-specific ACR or AMR score. Specifically, if the server 300 uses a miR panel for diagnosing ACR at 504, the server 300 creates an ACR score. Alternatively, if the server 300 uses a miR panel for diagnosing AMR at 504, the server 300 generates an AMR score. The score can be created based on the miR expression data of each patient sample. This score can facilitate the interpretation of the miR expression data in blood and assist clinical decision-making regarding the likelihood of ACR or AMR, and can also facilitate the selection of treatment pathways to be considered based on the rejection subtype. By creating the score, the server 300 can non-invasively diagnose ACR or AMR using the miR panel and a logistic regression model.

[0190] To calculate the different rejection scores of ACR or AMR, a coefficient is identified based on the patient-specific miR expression data plotted against the second logistic regression model. This coefficient is multiplied by each natural log-transformed miR. A nominal value, such as a value of 10, is added to the sequence reads per million data to reduce calculation errors and biases in the presence of zero values. This creates a weighted score based on the relative importance of each microRNA in predicting ACR or AMR. The ACR or AMR score can be scaled between 0-100. For each blood-derived sample, individual miR ACR and AMR scores can be calculated.

[0191] A threshold can be identified such that patients with a score equal to or greater than the threshold are considered to have or be at risk for developing an ACR or AMR rejection, while patients with a score below the threshold are considered to have a low likelihood of having or being at risk for developing an ACR or AMR rejection. To identify a specific score threshold, a ROC curve can be constructed and the Youden index can be used to identify a score threshold that maximizes the AUC and test performance characteristics. In an example according to certain aspects of the present disclosure, the AMR and ACR threshold scores that maximize sensitivity and specificity were calculated to be 65.

[0192] In the examples, when the ACR score threshold was set at 65, the AUC was 0.85 (95% CI: 0.78-0.92), and the associated test characteristics were sensitivity 86%, specificity 76%, NPV 98%, and PPV 30%. For AMR, the AUC was 0.83 (95% CI: 0.77-0.89). When the AMR score threshold was set at 65, the sensitivity was 89%, specificity 63%, NPV 97%, and PPV 29%. In some embodiments, the score threshold can be increased or decreased to maximize the test sensitivity and specificity.

[0193] As a non-limiting example, the ACR score is calculated as follows: ACR score=251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln [miR-326]

[0194] (a)=any number between 23 and 33; (b)=any number between 0.14 and 0.24; (c)=any number between 2.5 and 7.5; (d)=any number between 2 and 6; (e)=any number between 4 and 9; (f)=any number between 2 and 6; (g)=any number between 0.5 and 5; (h)=any number between 22 and 32; (i)=any number between 1 and 5; (j)=any number between 3 and 10; (k)=any number between 4 and 11; and (l)=any number between 6 and 14, where "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data) by a sequencer.

[0195] In some embodiments, (a) = any number from 26 to 31; (b) = any number from 0.16 to 0.21; (c) = any number from 4 to 6; (d) = any number from 3 to 5; (e) = any number from 6 to 7.5; (f) = any number from 3 to 5; (g) = any number from 1 to 3; (h) = any number from 25 to 28; (i) = any number from 2 to 4; (j) = any number from 5 to 7; (k) = any number from 7 to 9; and (l) = any number from 10 to 12.

[0196] In some embodiments, (a) = about 28.90; (b) = about 0.19; (c) = about 5.46; (d) = about 4.77; (e) = about 6.41; (f) = about 4.41; (g) = about 2.20; (h) = about 27.69; (i) = about 3.05; (j) = about 6.17; (k) = about 7.71; and (l) = about 10.63.

[0197] As another non-limiting example, the ACR score can be calculated as follows: ACR score=326 + (a) * ln [miR-23a-3p] - (b) * ln [miR-30e-5p] + (c) * ln [let-7g-5p] - (d) * [miR-24-3p] + (e) * ln [miR-27a-3p] - (f) * ln [miR-223-3p] + (g) * ln [miR-197-3p] - (h) * ln [miR-3615] + (i) * ln [miR-374a-5p] + (j) * ln [miR-182-5p] - (k) * ln [miR-345-5p] + (l) * ln [miR-361-3p] - (m) * ln [miR-130b-3p] - (n) * ln [miR-1299] + (o) * ln [miR-323b-3p] + (p) * ln [miR-582-3p] + (q) * ln [miR-432-5p] + (r) * ln [miR-329-3p] - (s) * ln [miR-376c-3p] - (t) * ln [miR-326]

[0198] where (a) = any number from 1 to 7; (b) = any number from 26 to 36; (c) = any number from 1 to 5; (d) = any number from 8 to 18; (e) = any number from 1 to 7; (f) = any number from 4 to 14; (g) = any number from 3 to 13; (h) = any number from 0.1 to 1; (i) = any number from 2 to 12; (j) = any number from 1 to 7; (k) = any number from 1 to 7; (l) = any number from 18 to 28. (m) = any number from 2 to 8; (n) = any number from 3 to 9; (o) = any number from 0.1 to 1; (p) = any number from 2 to 8; (q) = any number from 1 to 7; (r) = any number from 0.5 to 3.5; (s) = any number from 5 to 15; and (t) = any number from 6 to 16; where "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data).

[0199] In some embodiments, (a) = any number from 2 to 5; (b) = any number from 30 to 33; (c) = any number from 1.5 to 3; (d) = any number from 11 to 15; (e) = any number from 2 to 5; (f) = any number from 7 to 11; (g) = any number from 6 to 10; (h) = any number from 0.18 to 0.38; (i) = any number from 5 to 9; (j) = any number from 2 to 5. (k) = any number from 2 to 5; (l) = any number from 20 to 25; (m) = any number from 3 to 6; (n) = any number from 4.5 to 6.5; (o) = any number from 0.5 to 1; (p) = any number from 3 to 6; (q) = any number from 2 to 5; (r) = any number from 1 to 3; (s) = any number from 8 to 12; and (t) = any number from 9 to 14.

[0200] In some embodiments, (a) = about 3.64; (b) = about 31.79; (c) = about 2.10; (d) = about 13.49; (e) = about 3.75; (f) = about 9.30; (g) = about 8.18; (h) = about 0.28; (i) = about 7.51; (j) = about 3.88; (k) = about 3.59; (l) = about 23.57; (m) = about 4.58; (n) = about 5.73; (o) = about 0.71; (p) = about 4.69; (q) = about 3.32; (r) = about 1.90; (s) = about 10.12; and (t) = about 11.78.

[0201] As another non-limiting example, the AMR score can be calculated as follows: AMR score=222.41 - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p]

[0202] where: (a) = any number from 23 to 28; (b) = any number from 7 to 11; (c) = any number from 1 to 6; (d) = any number from 3 to 8; (e) = any number from 6 to 11; (f) = any number from 5 to 11; (g) = any number from 1 to 5; (h) = any number from 0.5 to 4; (i) = any number from 5 to 11; (j) = any number from 6 to 13; (k) = any number from 3 to 8; (l) = any number from 0.1 to 2; (m) = any number from 1 to 4 (n)=any number from 1 to 5; (o)=any number from 0.5 to 4; (p)=any number from 0.1 to 3; and (q)=any number from 0.1 to 4; administering immunosuppressive therapy to a human subject identified as having an AMR signature score of about 65 or greater; wherein "[X]" refers to the level of "X" in a biological sample; and wherein "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data) by a sequencer.

[0203] In some embodiments, (a)=any number from 24 to 27; (b)=any number from 8.5 to 10.5; (c)=any number from 2 to 4; (d)=any number from 4.5 to 6.5; (e)=any number from 7.5 to 9.5; (f)=any number from 7 to 9; (g)=any number from 2 to 4; (h)=any number from 1.0 to 1.75; (i)=any number from 7 to 9; (j)=any number from 9 to 11; (k)=any number from 5 to 7; (l)=any number from 1 to 2; (m)=any number from 1.5 to 2.5; (n)=any number from 1.5 to 2.5; (o)=any number from 0.7 to 1.7; (p)=any number from 0.5 to 1.5; and (q)=any number from 1.4 to 2.4.

[0204] In some embodiments, (a) = about 25.44; (b) = about 9.33; (c) = about 3.39; (d) = about 5.82; (e) = about 8.24; (f) = about 8.62; (g) = about 2.75; (h) = about 1.43; (i) = about 7.95; (j) = about 9.69; (k) = about 5.47; (l) = about .60; (m) = about 2.05; (n) = about 2.24; (o) = about 1.40; (p) = about .87; and (q) = about 1.69.

[0205] As another non-limiting example, the AMR score can be calculated as follows: Formula IV AMRスコア=107.1 + (a) ln (miR-143-3p) + (b) ln (let-7b-5p) - (c) ln (miR-10b-5p) - (d) ln (miR-23a-3p) - (e) ln (miR-24-3p) + (f) ln (miR-10a-5p) + (g) ln (miR-27a-3p) + (h) ln (miR-125a-5p) - (i) ln (miR-93-5p) + (j) ln (let-7d-3p) + (k) ln (miR-191-5p) - (l) ln (miR-484) + (m) ln (miR-99b-5p) + (n) ln (miR-340-5p) - (o) ln (miR-1-3p) + (p) ln (miR-193a-5p) + (q) ln (miR-145-3p) - (r) ln (miR-197-3p) - (s) ln (let-7b-3p) - (t) ln (miR-454-3p) + (u) ln (miR-450b-5p) - (v) ln (miR-215-5p) - (w) ln (miR-4433b-5p) + (x) ln (miR-1249-3p) + (y) ln (miR-142-3p) - (z) ln (miR-145-5p) + (aa) ln (miR-374a-5p) - (bb) ln (miR-542-3p) + (cc) ln (miR-1307-3p) + (dd) ln (miR-17-5p) + (ee) ln (miR-345-5p) + (ff) ln (miR-185-3p) + (gg) ln (miR-338-5p) - (hh) ln (miR-769-5p) + (ii) ln (miR-4433b-3p) + (jj) ln (miR-130b-3p) - (kk) ln (miR-331-5p) + (ll) ln (miR-140-5p) - (mm) ln (miR-223-5p) + (nn) ln (miR-582-3p) + (oo) ln (miR-122-3p) - (pp) ln (miR-589-5p) where: (a) = any number from 0.1 to 4; (b) = any number from 1 to 6; (c) = any number from 13 to 25; (d) = any number from 26 to 36; (e) = any number from 3 to 12; (f) = any number from 6 to 16; (g) = any number from 9 to 20; (h) = any number from 1 to 7; (i) = any number from 0.1 to 4; (j) = any number from 25 to 35; (k) = any number from 0.25 to 2.25; (l) = any number between 11 and 22;(m)=any number between 3 and 10;(n)=any number between 0.5 and 5;(o)=any number between 1 and 6;(p)=any number between 1 and 8;(q)=any number between 1 and 8;(r)=any number between 4 and 13;(s)=any number between 1 and 7;(t)=any number between 5 and 15;(u)=any number between 1 and 10;(v)=any number between 1 and 5;(w)=any number between 1 and 6;(x=1 and 6 (y) = any number from 8 to 18; (z) = any number from 8 to 18; (aa) = any number from 1 to 6; (bb) = any number from 4 to 13; (cc) = any number from 0.25 to 2.25; (dd) = any number from 1 to 8; (ee) = any number from 1 to 7; (ff) = any number from 3 to 10; (gg) = any number from 3 to 10; (hh) = any number from 1 to 7; (ii) = any number from 5 to 15 (jj) = any number from 0.25 to 2; (kk) = any number from 1 to 7; (ll) = any number from 1 to 5; (mm) = any number from 1 to 7; (nn) = any number from 0.1 to 3; (oo) = any number from 1 to 6; and (pp) = any number from 1 to 6; and, where "[X]" refers to the level of "X" in a biological sample, e.g., represented by the number of reads per sample (per million data) by a sequencer.

[0206] In some embodiments, (a) = any number from 1 to 2; (b) = any number from 3 to 4; (c) = any number from 19 to 22; (d) = any number from 31 to 34; (e) = any number from 6 to 9; (f) = any number from 10 to 13; (g) = any number from 11 to 16; (h) = any number from 3 to 5; (i) = any number from 1 to 2; (j) = any number from 28 to 32; (k) = any number from 0.5 to 0.5; (l) = any number between 15 and 18; (m) = any number between 5 and 7; (n) = any number between 1.5 and 2.5; (o) = any number between 2.5 and 3.5; (p) = any number between 4 and 5; (q) = any number between 4 and 5; (r) = any number between 7 and 10; (s) = any number between 3 and 5; (t) = any number between 7 and 11; (u) = any number between 4.5 and 7; (v) = any number between 2 and (w) = any number from 2.5 to 4.5; (x) = any number from 2 to 5; (y) = any number from 11 to 14; (z) = any number from 11 to 14; (aa) = any number from 2.25 to 4.25; (bb) = any number from 7 to 10; (cc) = any number from 0.75 to 2; (dd) = any number from 3 to 5.5; (ee) = any number from 2 to 5; (ff) = any number from 5 to 9 (gg) = any number from 5 to 9; (hh) = any number from 2 to 5; (ii) = any number from 7 to 12; (jj) = any number from 0.25 to 1.5; (kk) = any number from 2 to 5; (ll) = any number from 2 to 4; (mm) = any number from 3 to 5; (nn) = any number from 0.5 to 1.75; (oo) = any number from 2 to 4; and (pp) = any number from 2 to 4.

[0207] In some embodiments, (a)=about 1.59; (b)=about 3.4; (c)=about 20.35; (d)=about 32.4; (e)=about 7.89; (f)=about 11.93; (g)=about 14.41; (h)=about 3.93; (i)=about 1.39; (j)=about 30.11; (k)=about 1.15; (l)=about 16.25; (m)=about 6.21; (n)=about 2.03; (o)=about 3.07; (p)=about 4.92; (q)=about 4.49; (r)=about 8.65; (s)=about 4.08; (t)=about 9.15; (u)=about 5.62; (v) = about 2.96; (w) = about 3.48; (x) = about 3.21; (y) = about 12.86; (z) = about 13.0; (aa) = about 3.22; (bb) = about 8.56; (cc) = about 1.37; (dd) = about 4.39; (ee) = about 3.18; (ff) = about 6.47; (gg) = about 6.05; (hh) = about 3.74; (ii) = about 9.45; (jj) = about 0.69; (kk) = about 3.61; (ll) = about 2.84; (mm) = about 4.07; (nn) = about 1.11; (oo) = about 2.98; and (pp) = about 3.11.

[0208] The formula for calculating AMR and ACR scores uses sequence reads per million data with +10 added to each count to handle non-zero values. ln stands for natural logarithm.

[0209] At 510, the server 300 determines attributes associated with the patient based on the ACR or AMR score. For example, the attributes may be information related to surveillance of the patient after an organ transplant (e.g., a heart transplant) and may be a prediction of whether the patient will be diagnosed with ACR or AMR or whether the patient is at risk of being diagnosed with ACR or AMR.

[0210] For diagnosis, the server 300 can compare the patient-specific score with the different ACR or AMR rejection score thresholds identified by the second regression model. The different ACR or AMR rejection score thresholds can be thresholds for determining whether the patient is diagnosed with ACR or AMR. In some embodiments, for example, if the ACR or AMR score is equal to or greater than the corresponding ACR or AMR different rejection score thresholds, the patient can be diagnosed with ACR or AMR.

[0211] In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 50 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 51 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 52 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 53 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 54 or higher. In some embodiments, a subject is identified as at risk of developing ACR if the ACR score is about 55 or higher.

[0212] In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 55 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 56 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 57 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 58 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 59 or greater. In some embodiments, a subject is identified as at risk of developing AMR if the AMR score is about 60 or greater.

[0213] In some embodiments, the server 300 can determine that the ACR score or AMR score is normal and ongoing surveillance is required. Alternatively, the server 300 can determine that the ACR score is elevated, which indicates that the patient should begin appropriate treatment based on clinical severity, such as corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. Alternatively, the server 300 can determine that the AMR score is elevated. This may indicate that the patient should be initiated on appropriate treatment for AMR, such as intravenous immunoglobulin, plasma exchange, bortezomib, carfilzomib, rituximab, eculizumab, corticosteroids, antithymocyte globulin, tacrolimus, cyclosporine, sirolimus, everolimus, mycophenolate mofetil, azathioprine, tocilizumab, belatacept, and any combination thereof. The creation of ACR and AMR scores provides an alternative to invasive procedures (e.g., biopsy) for diagnosing rejection and identifying rejection subtypes, allowing precise therapy based on test results.

[0214] At 512, the server 300 identifies heart transplant rejection of the patient based on the diagnosis of ACR or AMR. In other words, the server 300 determines that the patient is rejecting a heart transplant based on the diagnosis of ACR or AMR.

[0215] The above-described systems and methods (e.g., as shown in Figures 3-5) can diagnose a patient with ACR or AMR based on a blood sample obtained from the patient. For example, Figure 6 shows the clinical application of the miR scores for ACR and AMR.

[0216] As shown in FIG. 6 and using the process described in method 500 of FIG. 5, blood-derived samples (e.g., whole blood, serum, and plasma) are collected in transplant patients during routine surveillance or when graft damage is clinically suspected. Plasma is separated from the whole blood and small RNA is extracted. Small RNA sequencing is performed to identify small RNA molecules. The sequence data is aligned to the human genome and microRNAs are annotated using miRBase. Expression data of individual microRNAs for ACR and AMR in each patient sample is determined, allowing calculation of ACR and AMR scores, determination of rejection subtype, and initiation of specific treatment.

[0217] IV.C.4. Computing Systems Various aspects may be implemented using one or more computer systems, such as, for example, computer system 700 shown in Figure 7. Computer system 700 may be used to implement, for example, method 400 of Figure 4 and method 500 of Figure 5. Additionally, computer system 700 may be at least a portion of server 300, client device 320, database 310 shown in Figure 3. For example, computer system 700 routes communications to various applications. Computer system 700 may be any computer capable of performing the functions described herein.

[0218] Computer system 700 can be any known computer capable of performing the functions described herein.

[0219] Computer system 700 includes one or more processors (also referred to as central processing units, or CPUs), such as processor 704. Processor 704 is connected to a communications infrastructure or bus 706.

[0220] One or more of the processors 704 may each be a graphics processing unit (GPU). In one aspect, a GPU is a processor that is a specialized electronic circuit designed to handle mathematically intensive applications. GPUs can have a parallel structure that is efficient for parallel processing of large blocks of data, such as the mathematically intensive data common in computer graphics applications, images, videos, etc.

[0221] The computer system 700 also includes user input / output devices 703 , such as a monitor, keyboard, pointing device, etc., that communicate with a communications infrastructure 706 via a user input / output interface 702 .

[0222] Computer system 700 also includes a main or primary memory 708, such as a random access memory (RAM). Main memory 708 may include one or more levels of cache. Main memory 708 stores control logic (i.e., computer software) and / or data.

[0223] Computer system 700 may also include one or more secondary storage devices or memories 710. The secondary memory 710 may include, for example, a hard disk drive 712 and / or a removable storage device or drive 714. The removable storage drive 714 may be a floppy disk drive, a magnetic tape drive, a compact disk drive, an optical storage device, a tape backup drive, and / or any other storage device / drive.

[0224] The removable storage drive 714 can interface with a removable storage unit 718. The removable storage unit 718 includes a computer usable or readable storage device having computer software (control logic) and / or data stored thereon. The removable storage unit 718 can be a floppy disk, magnetic tape, compact disk, DVD, optical storage disk, and / or any other computer data storage device. The removable storage drive 714 reads from and / or writes to the removable storage unit 718 in well-known fashion.

[0225] According to an exemplary embodiment, secondary memory 710 may include other means, intermediaries, or other approaches for making computer programs and / or other instructions and / or data accessible by computer system 700. Such means, intermediaries, or other approaches may include, for example, a removable storage unit 722 and an interface 720. Examples of removable storage units 722 and interfaces 720 may include a program cartridge and cartridge interface (such as those found in video game devices), a removable memory chip (such as an EPROM or PROM) and associated socket, a memory stick and USB port, a memory card and associated memory card slot, and / or any other removable storage device and associated interface.

[0226] Computer system 700 may further include a communications interface or network interface 724. Communications interface 724 enables computer system 700 to communicate and interact with any combination of remote devices, remote networks, remote entities, etc. (individually and collectively indicated by reference numeral 728). For example, communications interface 724 may enable computer system 700 to communicate with remote devices 728 over communications path 726, which may be wired and / or wireless and may include any combination of a LAN, a WAN, the Internet, etc. Control logic and / or data may be transferred to and from computer system 700 over communications path 726.

[0227] In an aspect, a tangible, non-transitory device or article of manufacture including a tangible, non-transitory computer usable or readable medium having control logic (software) stored thereon is also referred to herein as a computer program product or program storage device. This includes, but is not limited to, computer system 700, main memory 708, secondary memory 710, and removable storage units 718 and 722, as well as tangible articles of manufacture embodying any combination of the foregoing. Such control logic, when executed by one or more data processing devices (such as computer system 700), causes such data processing devices to operate as described herein. EXAMPLES

[0228] Example 1: Creation of miR panels for ACR and AMR The following examples report the results of a multicenter cohort study called GRAfT. Using a rigorously conducted multicenter prospective cohort study, small RNA sequencing of circulating plasma from heart transplant patients was performed and analyzed with paired clinical data. To validate the miR signature, distinct patient cohorts from GRAfT and external collaborators were included. The objectives of this analysis were to: 1) determine the miR transcriptome of heart transplant recipients; 2) identify miR expression under ACR and AMR conditions; 3) develop distinct miR panels that can be used for noninvasive screening and diagnosis of ACR and AMR; and 4) generate individualized ACR and AMR miR gene expression scores that allow clinical interpretation and noninvasive diagnosis of acute rejection.

[0229] method

[0230] Study design and multicenter discovery cohort

[0231] The GRAfT trial (NCT#02423070) is a prospective, multicenter clinical trial that enrolls heart transplant recipients before transplantation and follows them serially after transplantation. Subjects aged 18 years or older were recruited, consented while waiting for heart transplantation, and serially monitored after transplantation. Patients with a history of heart transplantation or current pregnancy were excluded. GRAfT patients were enrolled from 2015 to 2020.

[0232] Routine clinical care after transplantation included surveillance and clinically indicated monitoring. Surveillance monitoring at prespecified posttransplant time points included EMB for histopathology, right heart catheterization (RHC) hemodynamics, laboratory data to assess end-organ function, donor specific antibodies (DSA), cytomegalovirus (CMV) testing, and monitoring of immunosuppressant levels. Clinically supported monitoring included EMB (for biopsy), RHC, DSA, echocardiography, and other tests performed if patients presented with signs or symptoms of unexplained graft dysfunction. The study followed clinical data longitudinally and blood samples were collected concurrently with both surveillance and clinically indicated monitoring.

[0233] All GRAfT patients who showed ACR, AMR, or mixed rejection were identified during the study period. In patients with a history of both ACR and AMR, ACR and AMR samples were analyzed separately. Patients with mixed rejection were considered together with the AMR cohort, in accordance with previous literature suggesting that the signature of mixed rejection is most similar to AMR. Controls were selected based on the absence of clinical or histopathological rejection throughout the clinical follow-up period. Institutional protocols for the treatment of ACR and AMR are shown.

[0234] Histopathological definition of rejection

[0235] For the purposes of this study, histopathological rejection was characterized by ACR grade ≥ 2R, AMR grade ≥ 1 (histological or immunological), or mixed rejection. Rejection was defined based on biopsy interpretation by pathologists at each institution and consistent with standard clinical practice.

[0236] Pathology Core Laboratory

[0237] Given that rejection grading has previously been reported to be frequently discordant between pathologists, a blinded core lab with two cardiac pathology experts (GB and CM) reviewed a subset of all histopathology slides within GRAfT. Analyses were repeated comparing core lab interpretations with institutional interpretations to evaluate the performance of miRs against the blinded core lab interpretations.

[0238] Independent validation cohort

[0239] Independent validation of the ACR and AMR miR signatures was performed using samples from different patients from GRAfT. In addition to allowing external validation, a similar prospective single-center study (NCT# 01985412) conducted at Stanford University from 2011 to 2018 was also used. Stanford patients were recruited immediately after heart transplantation with similar exclusion criteria, and blood was banked in a similar manner as GRAfT. The method used herein allowed for identification of ACR cases and controls with no history of rejection after transplantation. The ACR miR signature was performance-validated in the Stanford cohort. The prevalence of AMR in the Stanford cohort was low. Therefore, this validation focused only on ACR.

[0240] Sample collection, microRNA extraction, and sequencing

[0241] Blood samples were collected during surveillance or clinically indicated testing. For patients undergoing EMB, blood samples were collected prior to treatment. Venous blood was collected into Streck Cell-Free DNA tubes, processed to separate plasma, and stored at -80°C. Total RNA was extracted using the MagMAX mirVana isolation kit (Thermo Fisher Scientific, Gaithersburg MD), and after elution, library preparation was performed using the NEXTFLEX Small RNA-Seq Kit v3 (PerkinElmer Inc, Shelton CT). Sequencing was performed on a NextSeq 500 (Illumina Inc., San Diego CA) using 50 bp single-end reads, generating ~11 million reads per sample.

[0242] Bioinformatics analysis of sequencing data

[0243] Small RNA sequencing data were analyzed using the Extracellular RNA Communication Consortium (ERCC) RNA pipeline (extracellular RNA processing tool, excerpt). Briefly, sequencing FASTQ files were processed to remove 3' adapter barcode sequences, random barcode sequences, UniVec contaminants, and reads <15 bp. High-quality filtered sequences were then aligned endogenously using miRbase v22, GENCODE v24 for the human genome38 reference, and gtRNAdb v16. Samples with insufficient good-quality miR reads (<1,000,000 reads per sample) were excluded from the analysis. To ensure there were no batch effects between small RNA sequencing runs, principal component analysis was performed using spike-ins of nematode samples and pooled plasma controls from unrelated human donors (data not shown). Outlier samples were excluded from subsequent bioinformatics / biostatistical analyses. Laboratory technicians and the bioinformatics team were blinded to biopsy results.

[0244] Target genes of miRs involved in ACR and AMR were identified using miRTarBase v8.0. Only target mRNAs experimentally validated by reporter assays, western blot, or microarray experiments along with miR overexpression or knockdown were included in the analysis. Network analysis and data visualization were performed using MIENTURNET. The Reactome database was searched to identify biological pathways that may be regulated by differentially expressed miRs.

[0245] Biostatistical analysis

[0246] Small RNA sequencing identified ~1,900 expressed miRs in plasma. The mean expression level across all samples was 475 ± 124 miRs. Low-expressing miRs with an average of <100 mapped reads across all samples were excluded. Additionally, miR-486-5p and miR-451a, which are erythrocyte-derived miRs, were excluded from the analysis. The remaining 286 miRs were included in the analysis. A two-stage analysis was performed to identify miRs that were significant in discriminating cases (ACR or AMR) from controls. In the first stage analysis, 286 miRs were screened while adjusting for clinical covariates (age, sex, race, body mass index) using DESeq2 to identify miRs that were differentially expressed in ACR and AMR. Blood type was adjusted in a subset of patients with only minor changes in miR profiles, but data were missing in other cases, so to maximize sample size, the data presented are adjusted for age, sex, race, and body mass index.

[0247] In the second stage of analysis, a logistic regression model was fitted with a LASSO penalty using miRs identified from the differential gene expression analysis with unadjusted p-values ​​<0.10. For the LASSO analysis, normalized miR counts were log-transformed for normal approximation, and the log counts of each miR were standardized to have a mean of 0 and a variance of 1. Tuning parameters for the LASSO penalty were selected by 10-fold cross-validation to minimize model deviance.

[0248] Receiver operating characteristic (ROC) curves were constructed and the area under the curves (AUC) was calculated to evaluate the performance of LASSO-selected miRs in independent validation cohorts for ACR and AMR from GRAfT and for ACR from Stanford University. AUC statistics were generated with 10-fold cross-validation to evaluate the predictive ability of miRs.

[0249] Finally, logistic regression models were fitted for ACR and AMR using the counts per million data of miRs selected by logistic-LASSO regression. Regular logistic regression estimates are prone to bias, especially for AMR, due to the small sample size and the large differences observed in the expression of several miRs between cases and controls (which causes the likelihood function to flatten around the maximum value). The parameters of the final logistic regression model were determined using maximum likelihood estimators, which reduces bias. ROC curves were generated using sequenced samples from the GRAfT cohort. Youden's index was used to identify thresholds for maximizing test performance. Test performance characteristics, including sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV), were presented. These distinct rejection scores for ACR and AMR were based on the miR expression data of each patient's sample.

[0250] result

[0251] Patient characteristics During the study period, a total of 116 GRAfT heart transplant patients completed 1 year of clinical follow-up and had plasma samples available for inclusion in the study. The median patient age was 52 years (IQR: 42-59), 35% of patients were female, and 45% were black. The most common cause of HF was nonischemic cardiomyopathy (63%), and 67% of patients progressed to permanent left ventricular assist device (LVAD; Table 1) implantation. The median follow-up time after transplant was 3.73 patient-years (IQR: 3.23-4.15).

[0252] [Table 1]

[0253] An incidence of AR of 15.8% has been previously reported within GRAfT (Agbor-Enoh & Shah et al., Circulation 143:1184(2021)). In this analysis, only EMBs with miR sequencing were included. Patients were divided into discovery and validation cohorts (Figure 1A). In the discovery miR analysis, 20 episodes of ACR (all grade 2R, no 3R episodes), 14 episodes of AMR (AMR ≥ 2, n = 6; AMR 1, n = 8), and 2 episodes of mixed ACR / AMR were included. There were 3 patients with ACR and AMR occurring separately in different EMBs, and each episode of rejection was analyzed separately. The median time to ACR was 146 days (range 50-496) and AMR was 55 days (range 21-171).

[0254] The median age of patients with ACR or AMR was 49.5 years, younger than the non-rejection control group of 53.0 years (Table 1). Black patients had a higher incidence of AMR (85.7%) compared with white patients (14.3%, p=0.05), and conversion to LVAD implantation was associated with a higher incidence of AMR compared with patients who did not convert (91.7% vs. 8.3%, p=0.06).

[0255] MicroRNA sequencing A total of 405 plasma samples were subjected to small RNA sequencing between GRAfT and Stanford University. A total of 10.9 ± 3.1 million small RNA reads were generated per sample, including miRs, piwi RNAs, small nucleolar RNAs, transfer RNAs, and unmapped RNA species. After filtering non-miR reads, each sample generated approximately 5.6 ± 2.7 million miR reads (Table 2). An average of 475 ± 124 miRs were expressed per sample, and 286 ± 45 miRs per sample were detected at a depth of 100 reads or more. The top 20 miRs accounted for 75% of the total miR transcriptome in heart transplant patients. miR-451a and miR-486-5p were the most abundant but were excluded from the analysis due to their high abundance in red blood cells.

[0256] [Table 2]

[0257] Differential miR analysis and dysregulated miR target pathways in rejection Differential gene expression analysis was performed using the GRAfT discovery cohort to compare the miR profiles of control patients (without rejection) and ACR patients. When comparing these patient populations, 12 miRs were identified with a p-value <0.05 (Figure 1B; Table 3). Target prediction analysis was performed on the differentially expressed ACR miRs using miRTarBase. A high level of biological relevance was ensured by including only previously published and experimentally validated miR-mRNA target interactions. A total of 294 genes were targeted by ACR miRs, and many of these genes are involved in mTOR signaling, T cell differentiation, transforming growth factor beta (TGF-β) signaling, and T cell receptor (TCR) signaling.

[0258] [Table 3]

[0259] Similarly, when comparing AMR patients with GRAfT with non-rejection control patients, 27 differentially expressed miRs were identified with p-values ​​less than 0.05 ( Figure 1 C, Table 3 ). A total of 478 genes were targeted by AMR miRs, and many of these genes are involved in pathways affecting interleukin signaling, downstream T cell receptor signaling, tumor necrosis factor (TNF) signaling, and toll-like receptor (TLR) cascades.

[0260] Using LASSO regression and internal cross-validation, a panel of 11 miRs was identified that accurately discriminated ACR from controls. Similarly, 15 miRs were identified that accurately discriminated AMR from controls. The internal correlations between these ACR and AMR miRs were low (data not shown). Only two miRs were common to both the ACR and AMR panels (miR-130b-3p and miR-374a-5p).

[0261] miR expression in ACR and AMR before and after rejection

[0262] To understand whether miRs could serve as biomarkers of future rejection and / or predict response to treatment, we investigated miR expression patterns before, during, and after a rejection episode. Using the miR panel identified by LASSO regression, the majority of miRs differentially expressed in ACR were upregulated during graft rejection and returned to control levels once the rejection episode was treated (miR374a-5p, Figure 1D; miR-345-5p, Figure 1F). However, some miRs were altered in expression before ACR onset compared to controls (miR-182-5p, Figure 1E; miR-130b-3p, Figure 1G).

[0263] In AMR, many miRs are dysregulated prior to the clinical diagnosis of rejection (miR-23a-3p, Figure 1H; miR-340-5p, Figure 1J). After treatment of AMR rejection, certain miRs return to normal levels (miR-142-3p, Figure 1I; miR-185-3p, Figure 1K), whereas others remain dysregulated (miR-23a-3p, Figure 1H; miR-340-5p, Figure 1J).

[0264] Performance of miRs for diagnosis of rejection in the validation cohort

[0265] To discern the performance of the selected miR panel to noninvasively diagnose ACR and AMR, validation was performed in an independent cohort of GRAfT patient samples and AUC statistics were calculated. Performance characteristics for ACR and AMR were AUC for ACR 0.92 (95% CI: 0.86-0.98) and AMR 0.82 (95% CI: 0.74-0.90; Figures 2A-2B). This results in sensitivity of 92-100% and specificity of 63-79%.

[0266] To provide further external validation, we sequenced the miR transcriptome of the Stanford transplant cohort (n=41). Stanford patients were older (51.5 vs. 57.5 years), less likely to be female (35.3% vs. 19.5%), black (44.8% vs. 12.2%), and less likely to have LVAD transitions (67.3% vs. 43.9%) than GRAfT patients. Pre-transplant renal dysfunction was more prevalent in the Stanford cohort. Other patient characteristics were similar between both cohorts. The AUC of the ACR miR panel in the Stanford cohort was 0.91 (95% CI: 0.82-0.99; Figures 2A-2B), with a negative predictive value of 81% and a positive predictive value of 100%.

[0267] Pathology Core Lab Analysis Two blinded cardiac pathologists (GP and CM) reviewed a subset of EMB histopathology slides from GRAfT patients to confirm the presence of ACR and AMR. Of the 263 biopsies included in the analysis, 95 (36%) were reviewed by a blinded core laboratory. The concordance rate for EMB histopathology interpretation between pathologists was 63% overall, whereas the concordance rate for non-rejection biopsies with institutional interpretation was 79% and for rejection specimens was only 28%. The lowest concordance rate overall was for AMR (Table 4).

[0268] [Table 4]

[0269] The ACR and AMR miR panels were used to evaluate the performance of the selected ACR miR panel for the detection of acute rejection based on blinded core laboratory interpretation. The AUC for the selected ACR miR panel was 0.85 (95% CI: 0.75-0.95), and the AMR miR panel was 0.96 (95% CI: 0.87-1.00).

[0270] Development of a circulating microRNA clinical rejection score for ACR and AMR

[0271] Using logistic regression, distinct clinical rejection scores for ACR and AMR were developed, ranging from 0 to 100. In the entire GRAfT patient cohort, individual miR ACR and AMR scores were calculated for each biopsy time point:

[0272] Formula I ACR score=251.89 - 28.9 *ln (miR-30e-5p) - 0.19 *ln (let-7g-5p) - 5.46 *ln (miR-223-3p) + 4.77 *ln (miR-3615) + 6.41 *ln (miR-374a-5p) + 4.41 *ln (miR-182-5p) - 2.2 *ln (miR-345-5p) + 27.69 *ln (miR-361-3p) - 3.05 *ln (miR-130b-3p) - 6.17 *ln (miR-1299) - 7.71 *ln (miR-376c-3p) - 10.63 *ln (miR-326)

[0273] Formula III AMR score=222.41 - 25.44 * ln (miR-23a-3p) - 9.33 * ln (miR-484) - 3.39 * ln (miR-340-5p) + 5.82 * ln (miR-193a-5p) - 8.24 * ln (miR-215-5p) + 8.62 * ln (miR-142-3p) -2.75 * ln (miR-374a-5p) + 1.43 * ln (miR-1307) + 7.95 * ln (miR-185-3p) + 9.69 * ln (miR-4433b-3p) + 5.47 * ln (miR-130b-3p) + 0.60*ln (miR-331-5p) + 2.05 * ln (miR-140-5p) +2.24 * ln (miR-223-5p) + 1.40 * ln (miR-582-3p) + 0.87 * ln (miR-122-3p) + 1.69 * ln(miR-589-5p)

[0274] To handle non-zero values, we use the number of reads per million data by adding +10 to each count. ln stands for natural logarithm.

[0275] ROC curves were constructed and the Youden index was used to identify the score threshold that maximized the AUC and test performance characteristics (Figures 2C-2D). The point that maximized sensitivity and specificity was 65. An ACR score threshold of 65 resulted in an AUC of 0.85 (95% CI: 0.78-0.92) and associated test characteristics of sensitivity 86%, specificity 76%, NPV 98%, and PPV 30%. The AMR AUC was 0.83 (95% CI: 0.77-0.89). An AMR score threshold of 65 resulted in a sensitivity of 89%, specificity 63%, NPV 97%, and PPV 29%. The score threshold can be increased or decreased to maximize test sensitivity and specificity, as shown in Figures 2C-2D.

[0276] conclusion

[0277] By analyzing according to the embodiments described herein, distinct combinations of miRs with excellent test performance characteristics were identified that can be used to non-invasively diagnose ACR and AMR from peripheral blood samples. These miR panels were validated in additional patient samples from GRAfT and external validation cohorts. Since ACR and AMR each have different scores, a non-invasive blood test can diagnose rejection subtypes as well as screen for rejection. This type of test, which distinguishes between ACR and AMR and no rejection, allows targeted therapy to be initiated while waiting for additional diagnostic tests.

[0278] The transplant community has been searching for reliable non-invasive biomarkers to detect acute graft rejection for the better part of the past 30 years. Current biomarkers include gene expression profiling (GEP), soluble protein biomarkers, donor-derived cell-free DNA (dd-cfDNA), and T-cell immune function assays. Commercially available gene expression profiling (GEP) involves the measurement of 11 mRNA transcripts involved in immune system function. However, GEP tests have a low PPV (~10%) and an inability to detect AMR, limiting their widespread implementation and reliance. More recently, sequencing of informative panels of single nucleotide polymorphisms (SNPs) in circulating cell-free DNA has allowed the quantification of the donor-derived portion of cell-free DNA (dd-cfDNA) by exploiting SNP mismatches between donor and recipient DNA. The percentage of dd-cfDNA in plasma has been shown to correlate with the presence and severity of graft rejection and is a biomarker of graft injury. Previous studies have demonstrated that dd-cfDNA is a highly sensitive, non-invasive biomarker for ACR and AMR. However, the currently used dd-cfDNA has a critical limitation in that it cannot accurately distinguish between ACR and AMR, and EMB is still required.

[0279] In the aforementioned tests according to the embodiments described herein, a unique miR subset was identified that distinguishes the presence of ACR and AMR from non-rejection patients with excellent NPV (~98%). These ACR and AMR miR scores can be used as part of a non-invasive surveillance strategy after transplantation. Since the miR scores are specific for ACR or AMR, if elevated, clinicians can initiate targeted therapy (e.g., steroids and / or thymoglobulin for ACR, plasma exchange and intravenous immunoglobulin for AMR) while waiting for the results of other diagnostic tests (DSA, echocardiogram, EMB, and / or dd-cfDNA).

[0280] Based on the teachings contained herein, it will be apparent to one skilled in the relevant art how to make and use aspects of the present disclosure while using data processing devices, computer systems, and / or computer architectures other than those shown in Figure 11. In particular, aspects may operate with software, hardware, and / or operating system implementations other than those described herein.

[0281] It should be understood that the Detailed Description section is intended to be used to interpret the claims, and not the other sections, which may describe one or more, but not all, example embodiments contemplated by the inventors, and are not intended to limit the scope of the disclosure or the appended claims in any way.

[0282] This disclosure describes exemplary embodiments for exemplary fields and applications, but it should be understood that the disclosure is not limited thereto. Other embodiments and modifications thereto are possible and are within the scope and spirit of the disclosure. For example, without limiting the generality of this section, the embodiments are not limited to the software, hardware, firmware, and / or entities illustrated in the figures and / or described herein. Moreover, the embodiments (whether or not explicitly described herein) have significant utility for fields and applications beyond the examples described herein.

[0283] Aspects have been described herein with the aid of functional building blocks that illustrate the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for convenience of description. Alternative boundaries may be defined so long as the specified functions and relationships (or equivalents) are appropriately performed. Also, alternative aspects may perform the functional blocks, steps, operations, methods, etc. using an order different from that described herein.

[0284] Reference herein to "one embodiment," "an embodiment," "an example embodiment," or similar phrases indicates that the described embodiment may include a particular feature, structure, or characteristic, but not all embodiments may necessarily include the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. Moreover, if a particular feature, structure, or characteristic is described with respect to one embodiment, it would be within the knowledge of one of ordinary skill in the relevant art to incorporate such feature, structure, or characteristic in other embodiments, whether or not explicitly mentioned or described herein. Moreover, some embodiments may be described using the terms "coupled" and "connected," along with their derivatives. These terms are not necessarily intended as synonyms for each other. For example, some embodiments may be described using the terms "connected" and / or "coupled" to indicate that two or more elements are in direct physical or electrical contact with each other. However, the term "coupled" can also mean that two or more elements are not in direct contact with each other, but still cooperate or interact with each other.

[0285] The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.

Claims

1. A microfluidic array comprising one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes is selected from the group consisting of miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, miR-10b -5p, miR-582-3p, let-7b-3p, miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR-17-5p, miR-1 a microfluidic array hybridized to a miR selected from the group consisting of miR-43-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR-345-5p, miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, and let-7d-3p.

2. 1. A microfluidic array comprising one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof.

3. RNA hybridization probes that hybridize to miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, and miR-345-5p 3. The microfluidic array of claim 2, comprising an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

4. 1. A microfluidic array comprising one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof.

5. RNA hybridization probe hybridizing to miR-23a-3p, RNA hybridization probe hybridizing to miR-484, RNA hybridization probe hybridizing to miR-340-5p, RNA hybridization probe hybridizing to miR-193a-5p, RNA hybridization probe hybridizing to miR-215-5p, RNA hybridization probe hybridizing to miR-142-3p, RNA hybridization probe hybridizing to miR-374a-5p, RNA hybridization probe hybridizing to miR-1307, RNA hybridization probe hybridizing to miR-185-3p 5. The microfluidic array of claim 4, comprising probes, an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

6. 1. A fluidic chip comprising one or more RNA hybridization probes, at least one of which hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof; and optionally, the fluidic chip is a microfluidic chip.

7. RNA hybridization probes hybridizing to miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345- The fluidic chip of claim 6, comprising an RNA hybridization probe that hybridizes to miR-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

8. 1. A fluidic chip comprising one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof; and optionally, wherein the fluidic chip is a microfluidic chip.

9. RNA hybridization probe hybridizing to miR-23a-3p, RNA hybridization probe hybridizing to miR-484, RNA hybridization probe hybridizing to miR-340-5p, RNA hybridization probe hybridizing to miR-193a-5p, RNA hybridization probe hybridizing to miR-215-5p, RNA hybridization probe hybridizing to miR-142-3p, RNA hybridization probe hybridizing to miR-374a-5p, RNA hybridization probe hybridizing to miR-1307, RNA hybridization probe hybridizing to miR-185-3p 9. The fluidic chip of claim 8, comprising an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

10. miR-223-3p, miR-361-3p, miR-3615, miR-24-3p, miR-182-5p, miR-374a-5p, miR-23a-3p, miR-30e-5p, miR-582-3p, miR-130b-3p, miR-326 for use in identifying a human subject suffering from or at risk of developing acute cardiac graft rejection after cardiac transplantation. 92, miR-1299, miR-23a-3p, miR-145-5p, miR-1249-3p, miR-27a-3p, miR-215-5p, miR-145-3p, miR-10b-5p, miR-582-3p, let-7b-3p , miR-142-3p, miR-450b-5p, miR-140-5p, miR-374a-5p, miR-17-5p, miR-143-3p, miR-130b-3p, miR-1-3p, miR-542-3p, miR-484, miR 1. A panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-345-5p, miR-125a-5p, miR-338-5p, miR-769-5p, miR-193a-5p, miR-454-3p, miR-223-5p, let-7d-3p, and any combination thereof, wherein optionally the acute cardiac transplant rejection comprises ACR, AMR, or a combination thereof.

11. 1. A panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof, for use in identifying a human subject having or at risk of developing ACR after heart transplantation, comprising: Optionally, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-30e-5p, an RNA hybridization probe that hybridizes to let-7g-5p, an RNA hybridization probe that hybridizes to miR-223-3p, an RNA hybridization probe that hybridizes to miR-3615, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-182-5p, and an RNA hybridization probe panel including a probe that hybridizes to miR-345-5p, an RNA hybridization probe that hybridizes to miR-361-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-1299, an RNA hybridization probe that hybridizes to miR-376c-3p, and an RNA hybridization probe that hybridizes to miR-326.

12. 1. A panel of RNA hybridization probes that hybridize to one or more miRs selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof, for use in identifying a human subject having or at risk of developing AMR following heart transplantation; Optionally, the RNA hybridization probe panel comprises an RNA hybridization probe that hybridizes to miR-23a-3p, an RNA hybridization probe that hybridizes to miR-484, an RNA hybridization probe that hybridizes to miR-340-5p, an RNA hybridization probe that hybridizes to miR-193a-5p, an RNA hybridization probe that hybridizes to miR-215-5p, an RNA hybridization probe that hybridizes to miR-142-3p, an RNA hybridization probe that hybridizes to miR-374a-5p, an RNA hybridization probe that hybridizes to miR-1307, an RNA hybridization probe that hybridizes to miR-185-3p, and an RNA hybridization probe that hybridizes to miR-193a-5p. an RNA hybridization probe panel including an RNA hybridization probe that hybridizes to miR-4433b-3p, an RNA hybridization probe that hybridizes to miR-130b-3p, an RNA hybridization probe that hybridizes to miR-331-5p, an RNA hybridization probe that hybridizes to miR-140-5p, an RNA hybridization probe that hybridizes to miR-223-5p, an RNA hybridization probe that hybridizes to miR-582-3p, an RNA hybridization probe that hybridizes to miR-122-3p, and an RNA hybridization probe that hybridizes to miR-589-5p.

13. 1. An in vitro or ex vivo method for identifying a human subject experiencing or at risk of experiencing acute heart graft rejection, including acute cellular rejection (ACR), following heart transplantation, comprising: (i) contacting a biological sample containing RNA obtained from the human subject with the microfluidic array of claim 2 or 3, the chip of claim 6 or 7, or the panel of claim 11; and (ii) Determine the ACR signature score according to the following formula: ACR signature score = 251.89 - (a) * ln [miR-30e-5p] - (b) * ln [let-7g-5p] - (c) * ln [miR-223-3p] + (d) * ln [miR-3615] + (e) * ln [miR-374a-5p] + (f) * ln [miR-182-5p] - (g) * ln [miR-345-5p] + (h) * ln [miR-361-3p] - (i) * ln [miR-130b-3p] - (j) * ln [miR-1299] - (k) * ln [miR-376c-3p] - (l) * ln [miR-326]; Where: (a) = any number between 23 and 33; (b) = any number between 0.14 and 0.24; (c) = any number between 2.5 and 7.5; (d) = any number between 2 and 6; (e) = any number between 4 and 9; (f) = any number between 2 and 6; (g) = any number between 0.5 and 5; (h) = any number between 22 and 32; (i) = any number between 1 and 5; (j) = any number between 3 and 10; (k) = any number between 4 and 11; and (l) = any number between 6 and 14; where "[X]" refers to the amount of "X" in a biological sample, and "ln" represents the natural logarithm; Here, a human subject is identified as having or at risk of having acute heart transplant rejection involving ACR if the ACR signature score is about 65 or greater.

14. 1. An in vitro or ex vivo method for identifying a human subject experiencing or at risk of experiencing acute heart transplant rejection, including antibody-mediated rejection (AMR), following heart transplantation, comprising: (i) contacting a biological sample containing RNA obtained from the human subject with the microfluidic array of claim 4 or 5, the chip of claim 8 or 9, or the panel of claim 12; and (ii) determining an AMR signature score according to the following formula: AMR signature score = 222.41 - (a) * ln [miR-23a-3p] - (b) * ln [miR-484] - (c) * ln [miR-340-5p] + (d) * ln [miR-193a-5p] - (e) * ln [miR-215-5p] + (f) * ln [miR-142-3p] - (g) * ln [miR-374a-5p] + (h) * ln [miR-1307] + (i) * ln [miR-185-3p] + (j) * ln [miR-4433b-3p] + (k) * ln [miR-130b-3p] + (l) * ln [miR-331-5p] + (m) * ln [miR-140-5p] + (n) * ln [miR-223-5p] + (o) * ln [miR-582-3p] + (p) * ln [miR-122-3p] + (q) * ln [miR-589-5p]; Where: (a) = any number between 23 and 28; (b) = any number between 7 and 11; (c) = any number from 1 to 6; (d) = any number between 3 and 8; (e) = any number between 6 and 11; (f) = any number between 5 and 11; (g) = any number from 1 to 5; (h) = any number between 0.5 and 4; (i) = any number between 5 and 11; (j) = any number between 6 and 13; (k) = any number between 3 and 8; (l) = any number between 0.1 and 2; (m) = any number from 1 to 4; (n) = any number from 1 to 5; (o) = any number between 0.5 and 4; (p) = any number from 0.1 to 3; and (q) = any number between 0.1 and 4; where "[X]" refers to the amount of "X" in the biological sample, and ln represents the natural logarithm; Here, a human subject is identified as having or at risk of having acute heart transplant rejection including AMR if the AMR signature score is about 65 or greater.

15. An immunosuppressive therapy for use in treating acute cardiac allograft rejection, including acute cellular rejection (ACR) after cardiac transplantation, in a human subject identified according to the method of claim 13.

16. An immunosuppressive therapy for use in treating acute cardiac allograft rejection, including antibody-mediated rejection (AMR), following cardiac transplantation in a human subject identified according to the method of claim 14.

17. (i) one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-30e-5p, let-7g-5p, miR-223-3p, miR-3615, miR-374a-5p, miR-182-5p, miR-345-5p, miR-361-3p, miR-130b-3p, miR-1299, miR-376c-3p, miR-326, and any combination thereof; and (ii) instructions for measuring the level of the miR panel according to the method of claim 13; Kit including:

18. (i) one or more RNA hybridization probes, wherein at least one of the RNA hybridization probes hybridizes to a miR selected from the group consisting of miR-23a-3p, miR-484, miR-340-5p, miR-193a-5p, miR-215-5p, miR-142-3p, miR-374a-5p, miR-1307, miR-185-3p, miR-4433b-3p, miR-130b-3p, miR-331-5p, miR-140-5p, miR-223-5p, miR-582-3p, miR-122-3p, miR-589-5p, and any combination thereof; and (ii) instructions for measuring the level of the miR panel according to the method of claim 14; Kit including:

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