Methods for kidney transplant testing

Abstract

Methods for assessing the likelihood of delayed graft function (DGF) of a donor kidney in a kidney transplant recipient are provided. Additionally, methods for determining the likelihood of requiring dialysis in a kidney transplant recipient are provided. Such methods include measuring expression of at least one gene in a sample from the kidney for transplant or from the transplanted kidney.

Description

[0001] Attorney Docket No.9151.282.WO METHODS FOR KIDNEY TRANSPLANT TESTING RELATED APPLICATIONS The present application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 706,145, filed on October 11, 2024, U.S. Provisional Patent Application Serial No. 63 / 710,658, filed on October 23, 2024, and U.S. Provisional Patent Application Serial No. 63 / 825,029, filed on June 17, 2025, the disclosures of which are hereby incorporated by reference herein. BACKGROUND Acute kidney injury (AKI) is a complex phenomenon whose development involves a multitude of interacting factors, including inflammation, vascular changes, cell damage, and immune dysregulation, often arising from multiple potential causes like ischemia, nephrotoxins, or obstruction, making it difficult to pinpoint a single mechanism and requiring a multifaceted approach to treatment. The injury to the kidney may occur through various pathways depending on the underlying cause, the clinical landscape and patients’ interindividual variability. In the native kidney, it is thought that inflammation drives interstitial fibrosis after an acute insult (Chawla et al. (2015), New England J. Medicine, 371:1) and recent single cell studies have identified a subset of failed repair proximal tubular cells that persist post-acute kidney injury that may be associated with transition to chronic kidney disease (CKD) (Ledru et al. (2024), Nat. Comm., 15:1; Gerhardt et al. (2023), J. Am. Soc. Nephrology, 34:4). In the renal allograft, AKI manifests itself in the form of delayed graft function (DGF), which is a form of injury unique to the transplant setting. Histologically, DGF is characterised by acute tubular injury, but the mechanisms underlying the adaptive or maladaptive repair of the renal allograft remain unknown (Chawla et al. (2015), New England J. Medicine, 371:1; Ledru et al. (2024), Nat. Comm., 15:1; Gerhardt et al. (2023), J. Am. Soc. Nephrology, 34:4; Basile et al. (2016), J. Am. Soc. Nephrology, 27:3; Ferenbach et al. (2024), Nat. Reviews Nephrology, 11:5). One fifth of the kidneys procured for transplantation in the United States are discarded. Identification of kidneys with sufficient functional reserve at the time of procurement may increase Attorney Docket No.9151.282.WO the number of kidneys transplanted. As DGF increases the chances of graft failure, acute rejection, and mortality rates, understanding which kidneys may suffer from DGF will facilitate the administration of therapies that can attenuate the consequences of DGF and thus improve long term outcomes. Moreover, identifying a signature of renal allografts at risk of DGF or primary- non-function (PNF) may enable transplant operators to triage good (transplantable) from bad (non- transplantable) organs, thus maximizing organ utilization while minimizing the discard rate. Recognizing DGF risk of allografts prior to transplant also facilitates appropriate organ allocation as some patients may not tolerate DGF. SUMMARY Provided according to some embodiments is a method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; and measuring expression of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) listed in Table 1 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) listed in Table 1 as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject. Also provided is a method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; and measuring expression of at least one gene selected from the group consisting of: APOE, PER3, STRIT1, FOS, ALDOB, PAH, CUBN, LRP2 and SLC5A12 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of the at least one gene (e.g., at least 2, 3, 4, 5, 6, 7, 8, or all 9 genes) as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject. Also provided is a method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; and Attorney Docket No.9151.282.WO measuring expression of a plurality of the genes (e.g., at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, or at least 60 genes) listed in Table 6, Table 7, Table 8, or Table 9 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of the plurality of genes as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject. In some aspects, the measuring comprises single cell RNA sequencing of the renal proximal tubule cells. In some aspects, the donor kidney is a donation after cardiac death (DCD) donor kidney. In some aspects, the differential expression comprises upregulation of fructose metabolism genes. In some aspects, the method further comprises measuring downregulation of expression of metabolic reprogramming and biosynthesis genes (e.g., PHGDH, MYC, and SERPINA1), inflammation and immune signalling genes (e.g., HAVCR1, CCL2, SERPINA1, and VCAM1), cell stress-related genes (e.g., TACSTD2, TMSB4X, HAVCR1, and MYC), aerobic metabolism-related genes (e.g. PHGDH, and MYC) and oxidative phosphorylation pathway genes (e.g. PHGDH, and MYC). In some aspects, the donor kidney is from a male donor and measuring further comprises measuring a proportion of loss of Y chromosome (LoY) cells in the biopsy, and wherein a higher proportion of LoY cells in the biopsy as compared to a control (e.g., biopsy from a living male donor kidney) indicates a decreased likelihood of donor kidney DGF after implantation in a subject. In some aspects, the donor kidney is from a male donor and measuring further comprises measuring a proportion of LoY cells in the biopsy, and wherein a median proportion of LoY of about 10, 15 or 20%, to about 30, 40 or 50% (e.g., about 25%) indicates a decreased likelihood of donor kidney DGF after implantation in a subject. In some aspects, the at least one gene comprises at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 3. In some aspects, the at least one gene comprises at least one of the genes (e.g., at least 2, 3, 5, 8, 10,15 or 16 genes) listed in Table 4. Attorney Docket No.9151.282.WO In some aspects, the method further comprises implanting the donor kidney into a subject in need thereof. In some aspects, the subject is an allogeneic subject with respect to the donor kidney. In another aspect, a method is provided of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, the method comprises the step of: measuring expression of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) in a sample (e.g., biopsy) from the kidney transplant, wherein the at least one gene comprises at least one gene listed in Table 1, and wherein decreased gene expression of the at least one gene as compared to a control (e.g., gene expression from cells in a living donor kidney) indicates an increased liklihood of requiring dialysis after transplantation in the subject. In another aspect, a method is provided of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, comprising: measuring expression of at least one gene selected from the group consisting of: APOE, PER3, STRIT1, FOS, ALDOB, PAH, CUBN, LRP2 and SLC5A12 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., decreased expression) of the at least one gene (e.g., at least 2, 3, 4, 5, 6, 7, 8, or all 9 genes) as compared to a control (e.g., biopsy from a living donor kidney) indicates an increased liklihood of requiring dialysis after transplantation in the subject. In another aspect, a method is provided of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, comprising: measuring expression of a plurality of the genes (e.g., at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, or at least 60 genes) listed in Table 6, Table 7, Table 8, or Table 9 in a sample (e.g., biopsy) from the kidney transplant, and wherein decreased gene expression of the plurality of genes as compared to a control (e.g., gene expression from cells in a living donor kidney) indicates an increased liklihood of requiring dialysis after transplantation in the subject. In some aspects, the method further comprises measuring a proportion of cells devoid of a Y chromosome, wherein a lower proportion of cells devoid of a Y chromosome as compared to a control indicates an increased likelihood of requiring dialysis after transplantation in the subject. In some aspects, measuring comprises measuring expression at one, two, or three points in time (e.g., 0 months, 1 month, and / or 12 months) prior to and / or after transplantation. In some aspects, the genes comprise PER3, STRIT1, and / or APOE and optionally SLC5A12, LRP2, and / or CUBN. Attorney Docket No.9151.282.WO In some aspects, the higher proportion of cells devoid of a Y chromosome is from about 0.1, 0.15, or 0.2 to about 0.3, 0.4, or 0.5 (e.g. measured as cells devoid of a Y chromosome to cells with a Y chromosome) as compared to a control. In some aspects, the genes comprise at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 3. In some aspects, the genes comprise at least one of the genes (e.g., at least 2, 3, 5, 8, 10,15 or 16 genes) listed in Table 4. In some aspects, the at least one gene is: SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, PER3, QDPR, COTL1, PCK2, FBP1, ACOT7, ADI1, DPEP1, SLC43A2, RBP5, NPL, XPNPEP2, ECHS1, and / or PARM1; SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, and / or PER3; or ALDOB, ANK2, APOE, ATP5IF1, AZGP1, FABP1, FGL2, HPD, HSD11B2, PER3, PRAP1, and / or STRIT1. In some aspects, the method further comprises implanting the donor kidney into a subject in need thereof. Also provided is the use of a donor kidney for implanting into a subject in need thereof, wherein the donor kidney is determined to have a decreased likelihood of donor kidney DGF as determined by a method taught herein, or determined to have an increased or decreased likelihood of requiring kidney dialysis treatment as determined by a method taught herein. BRIEF DESCRIPTION OF THE DRAWINGS FIG.1A, FIG.1B: Monocle2 pseudotime analysis of proximal tubule cells defines 9 cell states. Cell state 5 is minimal at time 0 in biopsies that progress to DGF (FIG.1B). FIG.1C: Analysis of median proportion of LoY in male kidney proximal tubular cells indicates that cell state 5 has a higher proportion of chromosome Y loss. FIG.2A: is an integrated dataset of 5 donation after cardiac death (DCD) kidney transplant biopsies depicted as a UMAP plot of 16,889 cells. All kidney cell types are represented: LoH, loop of Henle; PC, principal cell; PT, proximal tubule; IC, intercalated cell; EC, endothelial cell; DCT, distal convoluted cell; PEC, parietal epithelial cell; Macrophages and T cells are also represented. FIG. 2B: illustrates a combined integrated dataset of 5 DCD kidney transplant biopsies shown as a violin plot highlighting lineage specific markers for each cell type found in FIG.2A. Attorney Docket No.9151.282.WO LoH, loop of Henle; PC, principal cell; PT, proximal tubule; IC, intercalated cell; EC, endothelial cell; DCT, distal convoluted cell; PEC, parietal epithelial cell. FIG. 3A: illustrates a trajectory analysis of proximal tubular (PT) cells in DCD kidney transplants shaded by pseudotime. The bottom arrow highlights a trajectory to a pro-inflammatory cell state, and the top left arrow highlights a trajectory to a healthy cell state. FIG.3B: illustrates a trajectory analysis defining three proximal tubule cell states in DCD kidney transplants. FIG. 4A, 4B: illustrates the proportion of proximal tubule cell states over real time demonstrating the dominance of state 1 cells and the presence of few state 2 cells at time 0 in DCD kidneys that progress to DGF compared to those that do not. FIG. 5: shows a dotplot of relative scaled expression of marker genes for PT States 1, 2 and 3. The x-axis is labelled for each of PT state 1, 2 and 3. * adjusted P value < 1×10-5; ** adjusted P value < 1×10-50versus other PT cells states. FIG.6: illustrates an exemplary loss of Y chromosome analysis of male proximal tubule cells in DCD biopsies. Data show PT cell state 2 has the highest LoY of all PT cells and is a defining feature of PT cell state 2. Black boxed numbers are the proportions of LoY for each PT cell state. DETAILED DESCRIPTION The present invention is explained in greater detail below. This description is not intended to be a detailed catalog of all the different ways in which the invention may be implemented, or all the features that may be added to the instant invention. For example, features illustrated with respect to one embodiment may be incorporated into other embodiments, and features illustrated with respect to a particular embodiment may be deleted from that embodiment. In addition, numerous variations and additions to the various embodiments suggested herein will be apparent to those skilled in the art in light of the instant disclosure which do not depart from the instant invention. Hence, the following description is intended to illustrate some particular embodiments of the invention, and not to exhaustively specify all permutations, combinations and variations thereof. Unless the context indicates otherwise, it is specifically intended that the various features of the invention described herein can be used in any combination. Moreover, the present invention Attorney Docket No.9151.282.WO also contemplates that in some embodiments of the invention, any feature or combination of features set forth herein can be excluded or omitted. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, "a," "an" and "the" can mean one or more than one, depending on the context in which it is used. Also, as used herein, "and / or" refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative ("or"). The term "about," as used herein when referring to a measurable value such as an amount of a compound or agent of this invention, dose, time, temperature, and the like, is meant to encompass variations of ± 10%, ± 5%, ± 1%, ± 0.5%, or even ± 0.1% of the specified amount. Also, as used herein, "one or more" or "at least one" means one, two, three, four, five, six, seven, eight, nine, ten, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, etc. As used herein, the term "subject" can refer to any animal, including, but not limited to, humans and non-human animals (e.g., rodents, non-human primates, ovines, bovines, ruminants, lagomorphs, porcines, caprines, equines, canines, felines, etc.). The terms "patient" and "subject" may be used interchangeably herein in reference to a human subject. Measuring expression of genes may be performed using methods known in the art. In some embodiments, the measuring comprises RNA sequencing. In some embodiments, the measuring comprises cDNA sequencing of reverse transcribed RNA. In some embodiments, the measuring comprises single-cell RNA sequencing, or single-cell cDNA sequencing. As known in the art, "differential expression" of a gene includes an increase in expression of the gene ("upregulation"), or a decrease in expression of the gene ("downregulation"), as compared to a control cell or cell state. In some embodiments of the present invention, differential expression includes upregulation of fructose metabolism genes in kidney cells such as proximal tubule cells. In some embodiments of the present invention, differential expression includes upregulation and / or downregulation of genes in kidney cells such as proximal tubule cells. The control may be, for example, expression of the genes in cells of a biopsy taken from a living donor Attorney Docket No.9151.282.WO kidney, or a baseline expression level typical of gene expression from a biopsy taken from a living donor kidney. "Kidney transplantation," as used herein, is a surgery in which a donor kidney (from a living or deceased donor) is implanted into a recipient subject or patient. A kidney transplant can be used to treat, for example, chronic kidney disease or end-stage renal disease. Because only one kidney is needed, the kidney may be received from a living donor. The donor may be allogeneic or syngeneic (e.g., from an identical twin) with respect to the subject receiving the kidney transplant. "Allotransplantation," as used herein, refers to the transplantation or transfer of biological material, such as cells, tissues, or organs, from one genetically distinct individual to another individual within the same species. In particular, an allotransplantation includes transplantation where the donor and recipient are not genetically identical and thus may differ immunologically, typically necessitating immunosuppressive treatment to prevent rejection of the transplanted material. "Donation after cardiac death" or "DCD" refers to the situation when organs (such as kidney) are harvested after the donor's heart stops beating, such as after withdrawal from life support in the instance of devastating and irreversible brain injury or terminal illness. Typically, such organs have some degree of oxygen deprivation after the heart stops beating. DCD is a risk factor for DGF. "Delayed graft function," "delayed allograft function," or "DGF" with regard to a transplanted kidney refers to an acute kidney injury (AKI) occuring in the first week of kidney transplantation, which may require dialytic treatment. DGF is associated with shorter graft survival. "Loss of Y chromosome," "mosaic loss of Y chromosome," or "LoY" refers to the loss of the Y chromosome in a proportion of somatic cells, typically associated with aging in male subjects. In some embodiments, the donor kidney is from a male donor, and a higher proportion of LoY cells in the biopsy as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF after implantation in a subject. In some embodiments, the proximal tubular cells of the donor kidney have a median proportion of LoY of about 10, 15 or 20%, to 30, 40 or 50% (e.g., about 25%). LoY is associated with increased risk of cardiovascular disease, cancers and other age-related disorders in men (Forseberg (2017), Human Genetics, 136:5; Attorney Docket No.9151.282.WO Sano et al. (2022), Science, 377:6603; Loftfield et al. (2018), Sci. Rep’s, 8:1; Thompson et al. (2019), Nature, 575:6603). In white blood cells, LoY occurs in about 40% of 70-year-olds and 57% of 93-year-olds (Thompson et al. (2019), Nature, 575:6603). In some older men, more than 80% of cells have loss of the Y chromosome. The exact mechanisms driving these LoY associated age related disorders are unknown. However, LoY tumors have been shown to have immunosuppressive effects leading to CD8 T cell exhaustion in the tumor microenvironment (Abdel-Hafiz et al. (2023), Nature, 619:7970). The effect of sex on immunity is well-established and includes the possible modulatory role of the X chromosome (Oertelt-Prigione (2012), Autoimmune Reviews, 11). It is known that sex influences DGF and graft outcomes in kidney transplantation (Aufhauser et al. (2016), J. of Clinical Investigation, 126:5; Melk et al. (2024), Nephrology, Dialysis, Transplantation, 39:4). However, whether donor sex alone modifies this risk is unclear, with some data suggesting DGF risk is only modified in donors older than 60 years (Melk et al. (2024), Nephrology, Dialysis, Transplantation, 39:4). Disclosed herein is a method for determining the likelihood of donor kidney delayed graft function (DGF). In some embodiments, the method may include the steps of: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy including renal cells; and measuring expression of at least one gene in cells of the biopsy, wherein differential expression of at least one gene (e.g., at least one gene listed in Table 1, Table 5, and / or Table 6, Table 7, Table 8, or Table 9) as compared to a control indicates a decrease likelihood of donor kidney DGF after implantation in a subject / allograft recipient. For example, the at least one gene can include at least 2, 3, 5, 8, 10, 15 or 20 genes. In some embodiments, the at least one gene may include at least one gene as listed in Table 1, Table 5, and / or Table 6, Table 7, Table 8, or Table 9 in cells of the biopsy. For example, the cells of the biopsy can be proximal tubule cells from the donor kidney. Also disclosed herein is a method of determining the likelihood of a need for dialysis treatment and / or donor kidney delayed graft function (DGF) recovery in a subject, including measuring expression of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) in a sample (e.g., biopsy), wherein the at least one gene comprises at least one gene listed in Table 1, Table 5, and / or Table 6, Table 7, Table 8, or Table 9, and wherein increased gene expression of the at least one gene as compared to a control (e.g., gene expression from cells of a living donor kidney) indicates an increased liklihood of a need for dialysis treatment after transplantation in the subject. Attorney Docket No.9151.282.WO It will be appreciated by one having skill in the relevant art that a control may include a standard or baseline sample or a standard or baseline level of gene expression that may be used for comparison against that of a collected sample. For example, a control may include measurements from a biopsy of a living donor kidney. In some embodiments, a control may include one or more (e.g., a group or population) of healthy kidney cells, such as, but not limited to, proximal tubule cells, for collection or determination of a standard or baseline level of the measured value such as gene expression. In some embodiments, the method may include single cell RNA sequencing of renal cells. In some embodiments, the donor kidney is a donation after cardiac death (DCD) donor kidney. In some embodiments, differential expression may include increased or decreased expression of at least one gene relative to a control. In some embodiments, differential expression may include upregulation of fructose metabolism genes. In some embodiments, the at least one gene may include STRIT1, CYP3A5, MT-ND6, HPD, NPL, PRODH2, PAH, SULT1C2, DPEP1, MME, SLC22A8, SLC36A2, MIOX, SLC7A9, EBNA1BP2, FBP1, SLC17A3, RAB11FIP3, HDAC6, UPB1, SLC39A5, ACSF2, RSAD1, ACSM2A, ALDOB, MAF, RBP5, MT-CO3, SNRNP70, FABP1, SLC13A3, AZGP1, SLC16A9, AFM, ACAA1, and / or SLC6A19. For example, increased expression of STRIT1 in a biopsy of proximal tubular cells from a live donor kidney can indicate an increased likelihood of recovery from DGF and / or a decreased likelihood of requiring dialysis. In some embodiments, increased gene expression of the at least one gene may include increased expression of PER3, STRIT1, and / or APOE and optionally SLC5A12, LRP2, and / or CUBN. In some embodiments, the at least one gene may include SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, PER3, QDPR, COTL1, PCK2, FBP1, ACOT7, ADI1, DPEP1, SLC43A2, RBP5, NPL, XPNPEP2, ECHS1, and / or PARM1. In some embodiments, the at least one gene may include SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, and / or PER3. In some embodiments, the at least one gene may include ALDOB, ANK2, APOE, ATP5IF1, AZGP1, FABP1, FGL2, HPD, HSD11B2, PER3, PRAP1, and / or STRIT1. In some embodiments, the donor kidney may be from a male donor, and the measuring may further include measuring a proportion of loss of Y chromosome (LoY) cells in a biopsy, wherein a higher proportion of LoY cells in the biopsy as compared to a control (e.g., biopsy from a living male donor kidney), indicates a decreased likelihood of donor kidney DGF after Attorney Docket No.9151.282.WO implantation in a subject. In some embodiments, measuring may include measuring a proportion or percentage of LoY cells in a biopsy and include a median proportion of LoY of about 10%, 15% or 20% to about 30, 40 or 50% (e.g., about 25%), indicating a decreased likelihood of donor kidney DGF after implantation in a subject. In some embodiments, the method may include measuring a proportion of cells devoid of a Y chromosome, wherein a higher proportion of cells devoid of a Y chromosome as compared to a control or baseline indicates an increased likelihood of recovery from DGF after transplantation in the subject. In some embodiments, the higher proportion of cells devoid of a Y chromosome is from about 0.1, 0.15, or 0.2 to about 0.3, 0.4, or 0.5 as compared to a control, e.g. calculated as cells devoid of a Y chromosome to cells with a Y chromosome. In some embodiments, at least one gene may include at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 1, Table 5, and / or Table 6, Table 7, Table 8, or Table 9. In some embodiments, at least one gene may include at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 3. In some embodiments, the at least one gene may include at least one of the genes (e.g., at least 2, 3, 5, 8, 10, 15 or 16 genes) listed in Table 4. In some embodiments, the at least one gene is at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 1, Table 3, Table 4, Table 5, and / or Table 6, Table 7, Table 8, or Table 9. In some embodiments, the method may further include implanting the donor kidney into a subject in need thereof. In some embodiments, the subject may be an allogeneic subject with respect to the donor kidney. In some embodiments, a method of performing a kidney transplant may include implanting a donor kidney into a subject in need thereof, wherein said donor kidney may be determined to have a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation and / or decreased likelihood of needing dialysis by a method of an embodiment disclosed herein. In some embodiments, the method may include measuring expression of the at least one gene at one or more time points before and / or after transplantation. In some embodiments, the time points include one or more of time 0 prior to transplantation, one, two or three weeks after transplantation, 1 month, 2 months, 3 months, 4 months, 5 months, or 6 months after transplantation, etc. As used herein: T0, T1 and T12 refers to the collection and / or assessment of a sample, biopsy, population of cells, and the like, at time 0 months, 1 month and 12 months, respectively. Attorney Docket No.9151.282.WO The present invention is explained below in further detail in the following non-limiting examples. EXAMPLES Example 1: A time course analysis of serial biopsies post kidney transplant reveals a time zero cell state negatively associated with delayed graft function Single-cell RNA-seq analysis of allograft biopsies obtained at time 0, 1 and 12 months identified a signature of functional reserve predictive of successful graft function in marginal organs. Use of this signature to predict successful graft function may aid in minimizing discard rates. Methods As part of the Double R study (IRB00027118) we analysed time 0, 1 and 12 month biopsies of DCD kidney allografts from 5 patients with either DGF (n=3) or no DGF (n=3). We performed single nucleus RNA-seq on snap frozen biopsies using the 10X FLEX™ kit. We used SEURAT™ and MONOCLE2™ to generate data objects and perform analyses. We also estimated the proportion of male cells with LoY per cell type over time. Results We integrated 16889 post-QC cells from 5 patients with and without DGF across three time points (0, 1, 12 months) post DCD kidney transplant. These included 5371 proximal tubule cells. Using MONOCLE™ we identified a cell state present in time 0 biopsies that did not develop DGF. This cell state was minimal in biopsies that progressed to DGF but recovered by 1 month. This cell state was defined by upregulation of fructose metabolism genes and had a high median LoY per cell (0.2459) (FIG.1C). Conclusions We identified a time zero cell state that is negatively associated with DGF in the setting of DCD kidney transplantation. These renal proximal tubule cells differentially express fructose metabolism genes and have a high proportion of LoY cells. Attorney Docket No.9151.282.WO TABLE 1: Genes that are significant markers of proximal tubular cell "State 5", which is a marker of future health in Time 0 DCD kidneys (i.e., kidneys with these cell state markers are associated with immediate function without need for dialysis after transplantation) avg_log2FC pct.1 pct.2 p_val_adj deltaSTRIT1 2.900738817 0.176 0.051 4.01200358408907e-08 0.125 CYP3A5 2.123434545 0.282 0.159 0.000226333 0.123 MT-ND6 2.01520995 0.966 0.9 3.58636050576256e-33 0.066 HPD 2.00634277 0.377 0.22 9.78651152121607e-09 0.157 NPL 1.788362477 0.31 0.167 4.6448927550332e-06 0.143 PRODH2 1.671761409 0.514 0.296 2.50708377742071e-15 0.218 PAH 1.608050034 0.603 0.359 5.1370102426876e-20 0.244 SULT1C2 1.570675933 0.698 0.515 1.40253242767302e-23 0.183 DPEP1 1.563848248 0.517 0.367 1.99656135387036e-09 0.15 MME 1.55047584 0.559 0.413 3.80975908959496e-12 0.146 SLC22A8 1.496836946 0.383 0.218 5.53771304004066e-08 0.165 SLC36A2 1.488932731 0.486 0.307 6.26673080383095e-10 0.179 MIOX 1.488318961 0.765 0.482 2.97600871960609e-31 0.283 SLC7A9 1.480699714 0.433 0.307 2.4583769744532e-06 0.126 EBNA1BP2 1.439247178 0.492 0.378 4.79105302140375e-07 0.114 FBP1 1.427773012 0.603 0.462 7.36247364616659e-14 0.141 SLC17A3 1.393464879 0.654 0.463 4.12375910770208e-18 0.191 RAB11FIP3 1.366522995 0.855 0.668 3.22567436931436e-35 0.187 HDAC6 1.364313527 0.494 0.378 2.05225019079159e-06 0.116 UPB1 1.298070501 0.483 0.338 1.0946988701094e-06 0.145 SLC39A5 1.292956163 0.707 0.529 2.40600334165797e-19 0.178 ACSF2 1.291396876 0.768 0.549 2.41008468020823e-25 0.219 RSAD1 1.290106731 0.461 0.352 8.61980379640396e-05 0.109 ACSM2A 1.289471331 0.922 0.788 1.3132680159742e-35 0.134 ALDOB 1.283073595 0.754 0.555 1.38774835988948e-18 0.199 MAF 1.253108348 0.64 0.565 1.37612780765365e-09 0.075 RBP5 1.208480176 0.726 0.594 1.22426077875113e-20 0.132 MT-CO3 1.207519163 0.64 0.606 5.77840532127879e-05 0.034 SNRNP70 1.19149226 0.782 0.661 1.1423339819282e-21 0.121 FABP1 1.184474806 0.366 0.226 0.000133911 0.14 SLC13A3 1.176917639 0.536 0.399 3.80551081463071e-07 0.137 AZGP1 1.154283087 0.559 0.473 2.10254507176238e-05 0.086 SLC16A9 1.096854049 0.654 0.53 7.85788024097763e-11 0.124 AFM 1.076113197 0.455 0.288 2.74269106354545e-07 0.167 ACAA1 1.026013871 0.777 0.704 2.70191348786226e-13 0.073 SLC6A19 1.003644665 0.534 0.389 8.91603816329164e-07 0.145

[0002] Attorney Docket No.9151.282.WO TABLE 2: Gene Pathways ID Name Source pValu FDR FDR Bonferro Gene Genes in e B&H B&Y ni s Annotati from on 57 02 9 47 84 32 33 TABLE 3: WP Proximal Tubule Transport Pathway Genes NCBI Gene Gene Gene Name Original Attorney Docket No.9151.282.WO TABLE 4: Reactome Metabolism Pathway Genes NCBI Gene Gene Name Original Gene ID Symbol Symbol Example 2: Phenotypic characteristics and clinical outcomes for DGF and non-DGF kidney transplants We conducted a Double R pilot clinical trial aimed at identifying the molecular pathways orchestrating kidney repair and regeneration, as well as developing a viability-and-function fingerprint to recognize grafts with preserved functional reserve at the time of procurement, thereby reducing the discard rate. Thirty-six patients were initially enrolled in the study, twelve of whom were eventually excluded for either their refusal to undergo a renal allograft biopsy or the onset of clinical conditions that precluded them from safely undergoing the biopsy. Of the remaining twenty-six, twenty received a DCD renal allograft, while five received a living donor kidney. Five DCD renal allograft recipients were considered. All kidneys were pumped within a LIFEPORT® KIDNEY TRANSPORTER™ machine before implantation. All recipients received depleting antibody induction with alemtuzumab (30 mg IV), administered for 3 hours during surgery. All patients received a maintenance immunosuppressive Attorney Docket No.9151.282.WO regimen based on tacrolimus (targeting 12-h trough levels of 8–10 ng / mL during the first 3 months), mycophenolic acid (360 mg BID for patients older than 60 years of age, 720 mg BID for younger patients), and prednisone with early taper. DGF was defined as the need for dialysis for any reason in the first week after the transplant. After discharge, patients were seen twice a week during the first month, weekly during the second month, every other week during the third month, and monthly thereafter through month twelve. Data gathered included demographic information and a complete medical record. At one year, patients were referred to their nephrologist and the follow up period ended. We collected data relative to the natural history of the transplant, medication usage, pre- and post-transplant clinical laboratory results, and results from outcomes monitoring. Patients were followed according to the standard follow up regimen enforced at the Abdominal Organ Transplant Program at Atrium Wake Forest Baptist Medical Center, in Winston Salem, North Carolina, US. Biopsy samples: Three biopsy samples were taken and studied. The first biopsy was taken at the back table, before implantation and is therefore referred to as baseline or time 0 biopsy. A 16G, 22 mm disposable core biopsy needle was used. The second and third biopsies were taken at one month and one year, respectively. These were performed percutaneously, using either a 18G marquee or 18G max core 25mm disposable biopsy needle under local anesthesia. Samples were placed in empty vials, frozen at -20°C and shipped thereafter. Results Within the biopsy cohort of 5 recipients of DCD kidney transplants, 3 kidneys progressed to DGF and 2 kidneys did not require dialysis. Donor kidney quality was similar for the biopsy cohort with kidney donor profile index (KDPI) ranging from 50% to 86%, warm ischaemia time 22 to 80 minutes and cold ischaemia time 17.5 to 22 hours. There was no significant difference in eGFR or dd-cfDNA at any time in the first year or six months post-transplant, respectively. No patient required dialysis after discharge post-transplant. All patients received induction therapy with thymoglobulin and were discharged on triple immunosuppression consisting of Tacrolimus, mycophenolate and prednisone. Attorney Docket No.9151.282.WO Example 3: Single cell RNA-seq analysis of serial kidney transplant biopsies Single cell RNA-seq analysis of serial kidney transplant biopsies identified all major kidney and immune cell types. Kidney allograft tissue was taken from 5 patients at the time of procurement, at 1 month and 12 months post-transplantation. A total of 16,889 cells passed quality control filters with a mean of 1,867 genes and 3,137 transcripts per cell. All major kidney and immune cell clusters were identified by recognized lineage marker gene expression, as shown in FIG.2A-B. Tubular cells clustered into 5 categories representing the 5 broad categories of tubular segments, proximal tubule, loop of Henle, distal convoluted tubule, principle cell and intercalated cell (FIG. 2A). Consistent with previous publications, proximal tubular cells (n=5371) and loop of Henle cells (n=6171) represented the most common cell types. Immune cells clustered into two clusters we called T cells and macrophages. The T cell cluster includes a small number of B cell lineage cells and NKT / NK cells. The macrophage cluster includes a CD14+cluster, a CD14+CD16+cluster and a kidney resident macrophage cluster defined by CD81 expression. Macrophage subcluster 1 differentially expressed the Lipocalin 2 gene (LCN2), a marker of macrophage deactivation or anti- inflammatory modulation.18,19We use a machine learning approach (e.g., Discriminative Dimensionality Reduction via learning a Tree (DDRTree), and the like) to cluster cells into X number of groups based on cell to cell gene expression pattern variation. A user can cluster data into any number of predefined groups, e.g., by changing variables. The more groups into which data are clustered, the less biologically meaningful each of the clusters may become. Therefore, subsequent analyses focused on clustering data into 3 groups, as described in Examples 4-7 and Table 6. Example 4: Combined pseudo and real time analysis of proximal tubular cell states associated with DGF post DCD kidney transplants As noted above, the data analysis was modified to cluster into 3 groups. Three proximal tubular (PT) cell states were identified by pseudotime analysis using MONOCLE2™. Proximal tubule cell state 3 represented pseudotime zero and states 1 and 2 represented divergent cell states later in pseudotime (FIG. 3A-B). Pseudotime broadly correlated with real time as most state 3 cells were from T0 biopsies and state 1 and 2 cells were more frequent in T1 and T12 biopsies. However, in DGF, at T0 the dominant cell state was PT state 1 compared with state 3 in non-DGF Attorney Docket No.9151.282.WO kidneys (FIG.4A-B). By month 1 (T1 biopsies) PT state 2 starts to become the dominant cell state in all kidneys (recovered DGF and non-DGF). Of note, PT state 2 was almost absent in DGF biopsies at T0. Normal metabolic and transport pathways, such as solute carrier mediated membrane transport, defined PT state 3. PT cell State 1 was associated with DGF and differentially expressed complement and platelet activation and aggregation pathways. PT cell state 2 was associated with aerobic metabolism and oxidative phosphorylation pathways. Genes that defined PT state 2 included PER3, STRIT1, and APOE (FIG.5). PT state 2 cells also expressed markers of healthy proximal tubule, SLC5A12, LRP2, and CUBN, as did PT state 3, the dominant PT cell state in the pre-transplant kidney. Interestingly, FOS expression is high was PT state 3 and persisted in PT state 1, but was suppressed in PT state 2 (FIG. 5). Thus, FOS expression was positively associated with progression to DGF and negatively associated with healthier, non-DGF tubules. PT state 1 was defined by PT injury markers, VCAM1 and HAVCR1, as well as CCL2, MYC and others (FIG.5). MYC expression increased in PT state 1 but was suppressed in PT state 2. PT cell state 2 was a marker of graft function and PT cell state 1 a marker DGF and poor function in the transplanted kidney. Example 5: Proximal tubular cell loss of Y chromosome associated with recovery from DGF in DCD kidneys The proportion of male proximal tubule cells with loss of Y chromosome was increased in cell state 2 compared to state 1 and the pre-transplant (T0) dominant cell state 3 (FIG. 6). The proportion of loss of Y cells across all male cells in the dataset is 21%. Thus, the proportion of LoY in male proximal tubule cells was below average pre-transplant (17%) and increased to above average in the post-transplant dominant cell state 2 (29%). All donor kidneys that did not progress to DGF were female so an analysis of LoY was not possible. A significant loss of MYC target gene pathways was identified in LoY proximal tubule cells compared to XY proximal tubule cells. MYC gene expression was increased in PT cell states 1 relative to states 2 and 3. As MYC target gene pathways are associated with positive regulation of the cell cycle we calculated mean G2M-phase scores. G2M-phase scores for state 2 were lower compared to state 1. In male kidneys that progress to DGF, increased LoY in proximal tubules is associated with recovery of kidney function. Attorney Docket No.9151.282.WO Example 6: Dicussion of Results Patients that progressed to DGF post DCD transplant (n=3) recovered dialysis independent kidney function by the end of the first week post-transplantation. Estimated glomerular filtration rate (eGFR) and donor-derived cell-free DNA (dd-cfDNA) fraction was comparable for both biopsy groups for the first 12- or 6-months post transplantation, respectively. Most studies reporting outcomes post DGF in kidney transplants are single center or registry studies so results are varied. Furthermore, studies are heterogeneous due to the varied definition and timing of dialysis post transplant. In the current study, DGF was defined as dialysis within the first 7 days post-transplant. We integrated a total of 16,889 post quality control cells from 15 human kidney transplant biopsies from 5 patients (FIG.2A-B). Of these, 5371 were proximal tubule cells, defined by the expression of CUBN and other lineage defining genes (FIG. 2B). Proximal tubule cells were among the most abundant cell type consistent with previous single cell studies in the native and transplanted kidney.20,21We subclustered proximal tubule cells using MONOCLE2™ and performed a pseudotime analysis. We found proximal tubule cells subclustered into 3 cell states along a pseudotime trajectory with one branch point (FIG.3A-B). PT cell state 3 was predominantly found in T0 samples and defined by expression of genes associated with tubule health such as SLC5A12, LRP2, CUBN, and PAH, and pathways such as solute carrier (SLC) mediated transmembrane transport. In post- transplant samples (T1 and T12) proximal tubule cell state 2 becomes the dominant cell state. This state also expresses genes associated with proximal tubule health, SLC5A12, LRP2, CUBN, and PAH (FIG.5). PT cell state 2 is further characterised by expression of STRIT1, PER3, and APOE. Interestingly, expression of all three of these genes is lost in PT cell state 1 but maintained or increased over pseudotime in state 2 when compared to state 3 (FIG.5). There is also a real time non-significant trend to increasing expression of these 3 genes. APOE expression is significantly increased over real time amongst all PT with the most significant increase from T0 to T1. Allelic variation in APOE has been both negatively and positively associated with progression to CKD.22,23In one study of the ARIC CKD cohort the epsilon4 (ε4) APOE allele was associated with a decreased risk of progression to ESKD, consistent with other studies showing that the ε4 allele is an independent predictor of chronic allograft nephropathy. The e4 allele is defined by 2 SNPs, rs7412-C and rs429358-C. These SNPs are over 500 bases proximal to the 3- Attorney Docket No.9151.282.WO prime end of the APOE coding region. Therefore, we were not able to genotype the biopsy patients in this study. However, these findings offer a potential role for APOE in the development and or resolution of renal function in the setting of DGF. Based on the findings in this study PT cell state 2 is a cell state present in recovering kidneys post DCD transplantation. This cell state differs from the predominantly pre-transplant cell state 3 by increasing expression of oxidative pathways and genes such as APOE (FIG. 5). Both PT cell states 3 and 2 are healthy states based on their expression of normal metabolic genes and pathways. We also measured the proportion of LoY cells in male proximal tubular cells states in the DGF kidney transplants. As mentioned above, mosaic LoY is associated with many age related diseases in males such as Alzheimer’s disease, heart disease and cancers. We found that PT cell state 2 had substantially increased proportion of LoY (29%) compared to PT cell state 3 (17%) (FIG.6). PT cell state 1, associated with DGF, had 20% LoY. The mean LoY proportion across all cell types in the DGF kidney was 21%. Thus, PT cell state 2 had the highest proportion LoY of all cell types in the DGF kidney (FIG.6). We explored the transcriptional differences between LoY cells and XY cells. Due to the low number of LoY cells, we compared all male tubular cell types in the DGF kidney. Pathway analysis found a relative loss of genes associated with MYC target pathways and chromatin modifying enzyme pathways. We identified no significantly increased pathways in this analysis due to low LoY cell numbers. As the MYC oncogene promotes the cell cycle by activating cyclins and CDKs,24,25we therefore performed a cell cycle phase analysis and found that mean G2M phase score in PT cell state 2 was lower than state 1. In our study the finding of increased LoY in PT cell state 2 suggests LoY in this setting is associated with repair and regeneration of graft function post DGF. The mechanisms driving this may be related to the induction of cellular senescence and protection from apoptosis as suggested in previous LoY studies.26We also identified a dominant PT cell state in time zero kidneys (>50% of PT cells) that did progress to DGF, PT cell state 1 (FIG. 3A-B). The number of cells in this state dropped by month 1, by which time all DGF kidneys had achieved dialysis independent function (FIG.4A). This cell state was associated with progression to DGF and defined by previously described PT injury genes, VCAM1 and HAVCR1. The chemokine gene CCL2 as also differentially expressed in state1 cells (FIG.5). Tubular cell CCL2 is known to drive kidney inflammation and injury during sepsis.27Loss of Ccl2 in mice mitigated kidney cortical atrophy and mononuclear cell infiltration.28 Attorney Docket No.9151.282.WO We also identified platelet and complement pathway activation state 1 cells compared to state 3 cells. Based on these findings PT cell state 1 was associated with DGF and a pro-inflammatory environment. TABLE 5: relative scaled expression of marker genes for PT States 1-3 State Gene Adj. p-val “1” % “2” % “3” % Expression Expression Expression Attorney Docket No.9151.282.WO Table 6: Upregulated genes of PT cells in state 2. PCT 1 and PCT2 represent the proportion of PT cells state 2, and all other cells expressing a given gene, respectively. Delta Cell Percent (Δ Cell %) represents the proportion of PT state 2 cells expressing the gene, calculated as the difference between PCT 1 and PCT 2 (PCT 1 – PCT 2). Significance determined as p < 0.01. Gene p-value Ave. log2Fold Change PCT 1 PCT 2 Adj. p-value Δ Cell % PAH 2.87E-62 0.85511487 0.626 0.395 5.19E-58 0.231 Attorney Docket No.9151.282.WO MME 6.43E-31 0.87527402 0.562 0.453 1.16E-26 0.109 MT-ND4 2.97E-25 0.85492381 0.469 0.36 5.36E-21 0.109 Attorney Docket No.9151.282.WO PGRMC1 2.68E-17 0.83813098 0.477 0.413 4.85E-13 0.064 ETFB 5.11E-19 0.88152332 0.506 0.443 9.23E-15 0.063 Attorney Docket No.9151.282.WO STK32A 2.27E-11 2.07946469 0.077 0.035 4.10E-07 0.042 FAM151A 2.28E-09 0.9995509 0.089 0.047 4.12E-05 0.042 Attorney Docket No.9151.282.WO ACAA1 1.09E-19 0.45970073 0.736 0.723 1.97E-15 0.013 CLNK 3.78E-07 3.72832358 0.016 0.003 0.00683557 0.013 Table 7: Selection of 28 upregulated genes of PT cells in state 2. Gene p-value Ave. log2Fold Change PCT 1 PCT 2 Adj. p-value Δ Cell % SLC22A8 2.64E-58 1.53303015 0.417 0.23 4.76E-54 0.187 Attorney Docket No.9151.282.WO NPL 5.47E-13 1.02109584 0.268 0.189 9.89E-09 0.079 XPNPEP2 4.74E-13 1.01995454 0.272 0.192 8.56E-09 0.08 Table 8: Selection of 15 upregulated genes of PT cells in state 2. Gene p-value Ave. log2Fold Change PCT 1 PCT 2 Adj. p-value Δ Cell % SLC22A8 2.64E-58 1.53303015 0.417 0.23 4.76E-54 0.187 Table 9: Selection of 12 upregulated genes of PT cells in state 2. Gene p-value Ave. log2 Fold Change PCT 1 PCT 2 Adj. p-value Δ Cell % Attorney Docket No.9151.282.WO HSD11B2 1.21E-20 1.32439604 0.36 0.26 2.18E-16 0.1 PER3 6.15E-10 1.21038222 0.205 0.145 1.11E-05 0.06 References 1. Chawla LS, Eggers PW, Star RA, Kimmel PL. Acute kidney injury and chronic kidney disease as interconnected syndromes. The New England journal of medicine. Jul 3 2014;371(1):58-66. doi:10.1056 / NEJMra1214243 2. Ledru N, Wilson PC, Muto Y, et al. Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing. Nat Commun. Feb 122024;15(1):1291. doi:10.1038 / s41467-024-45706-0 3. Gerhardt LMS, Koppitch K, van Gestel J, et al. Lineage Tracing and Single-Nucleus Multiomics Reveal Novel Features of Adaptive and Maladaptive Repair after Acute Kidney Injury. Journal of the American Society of Nephrology : JASN. Apr 12023;34(4):554-571. doi:10.1681 / asn.0000000000000057 4. Basile DP, Bonventre JV, Mehta R, et al. Progression after AKI: Understanding Maladaptive Repair Processes to Predict and Identify Therapeutic Treatments. Journal of the American Society of Nephrology : JASN. Mar 2016;27(3):687-97. doi:10.1681 / asn.2015030309 5. Ferenbach DA, Bonventre JV. Mechanisms of maladaptive repair after AKI leading to accelerated kidney ageing and CKD. Nature reviews Nephrology. May 2015;11(5):264-76. doi:10.1038 / nrneph.2015.3 6. Lentine KL, Smith JM, Lyden GR, et al. OPTN / SRTR 2022 Annual Data Report: Kidney. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. Feb 2024;24(2s1):S19-s118. doi:10.1016 / j.ajt.2024.01.012 7. Bahl D, Haddad Z, Datoo A, Qazi YA. Delayed graft function in kidney transplantation. Curr Opin Organ Transplant. Feb 2019;24(1):82-86. doi:10.1097 / mot.0000000000000604 8. Rijkse E, Ceuppens S, Qi H, Ijzermans JNM, Hesselink DA, Minnee RC. Implementation of donation after circulatory death kidney transplantation can safely enlarge the donor pool: A Attorney Docket No.9151.282.WO systematic review and meta-analysis. International Journal of Surgery.2021 / 08 / 01 / 2021;92:106021. doi:https: / / doi.org / 10.1016 / j.ijsu.2021.106021 9. Li MT, Ramakrishnan A, Yu M, et al. Effects of Delayed Graft Function on Transplant Outcomes: A Meta-analysis. Transplant Direct. Feb 2023;9(2):e1433. doi:10.1097 / txd.0000000000001433 10. Forsberg LA. Loss of chromosome Y (LOY) in blood cells is associated with increased risk for disease and mortality in aging men. Hum Genet. May 2017;136(5):657-663. doi:10.1007 / s00439-017-1799-2 11. Sano S, Horitani K, Ogawa H, et al. Hematopoietic loss of Y chromosome leads to cardiac fibrosis and heart failure mortality. Science. Jul 152022;377(6603):292-297. doi:10.1126 / science.abn3100 12. Loftfield E, Zhou W, Graubard BI, et al. Predictors of mosaic chromosome Y loss and associations with mortality in the UK Biobank. Sci Rep. Aug 172018;8(1):12316. doi:10.1038 / s41598-018-30759-1 13. Thompson DJ, Genovese G, Halvardson J, et al. Genetic predisposition to mosaic Y chromosome loss in blood. Nature. Nov 2019;575(7784):652-657. doi:10.1038 / s41586-019- 1765-3 14. Abdel-Hafiz HA, Schafer JM, Chen X, et al. Y chromosome loss in cancer drives growth by evasion of adaptive immunity. Nature.2023 / 07 / 012023;619(7970):624-631. doi:10.1038 / s41586-023-06234-x 15. Oertelt-Prigione S. The influence of sex and gender on the immune response. Autoimmun Rev. May 2012;11(6-7):A479-85. doi:10.1016 / j.autrev.2011.11.022 16. Aufhauser DD, Jr., Wang Z, Murken DR, et al. Improved renal ischemia tolerance in females influences kidney transplantation outcomes. The Journal of clinical investigation. May 2 2016;126(5):1968-77. doi:10.1172 / jci84712 17. Melk A, Sugianto RI, Zhang X, et al. Influence of donor sex and age on graft outcome in kidney transplantation. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association. Mar 27 2024;39(4):607-617. doi:10.1093 / ndt / gfad181 Attorney Docket No.9151.282.WO 18. Guo H, Jin D, Chen X. Lipocalin 2 is a regulator of macrophage polarization and NF- κB / STAT3 pathway activation. Mol Endocrinol. Oct 2014;28(10):1616-28. doi:10.1210 / me.2014-1092 19. Warszawska JM, Gawish R, Sharif O, et al. Lipocalin 2 deactivates macrophages and worsens pneumococcal pneumonia outcomes. The Journal of clinical investigation. Aug 2013;123(8):3363-72. doi:10.1172 / jci67911 20. Wilson PC, Muto Y, Wu H, Karihaloo A, Waikar SS, Humphreys BD. Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression. Nature Communications.2022 / 09 / 062022;13(1):5253. doi:10.1038 / s41467- 022-32972-z 21. Malone AF, Wu H, Fronick C, Fulton R, Gaut JP, Humphreys BD. Harnessing Expressed Single Nucleotide Variation and Single Cell RNA Sequencing To Define Immune Cell Chimerism in the Rejecting Kidney Transplant. J Am Soc Nephrol. Sep 2020;31(9):1977-1986. doi:10.1681 / ASN.2020030326 22. Hsu CC, Kao WHL, Coresh J, et al. Apolipoprotein E and Progression of Chronic Kidney Disease. Jama.2005;293(23):2892-2899. doi:10.1001 / jama.293.23.2892 23. Hernández D, Salido E, Linares J, et al. Role of apolipoprotein E epsilon 4 allele on chronic allograft nephropathy after renal transplantation. Transplantation proceedings. Dec 2004;36(10):2982-4. doi:10.1016 / j.transproceed.2004.10.038 24. García-Gutiérrez L, Delgado MD, León J. MYC Oncogene Contributions to Release of Cell Cycle Brakes. Genes (Basel). Mar 222019;10(3)doi:10.3390 / genes10030244 25. García-Gutiérrez L, Bretones G, Molina E, et al. Myc stimulates cell cycle progression through the activation of Cdk1 and phosphorylation of p27. Scientific Reports.2019 / 12 / 10 2019;9(1):18693. doi:10.1038 / s41598-019-54917-1 26. Wilson PC, Verma A, Yoshimura Y, et al. Mosaic loss of Y chromosome is associated with aging and epithelial injury in chronic kidney disease. Genome biology.2024 / 01 / 29 2024;25(1):36. doi:10.1186 / s13059-024-03173-2 27. Jia P, Xu S, Wang X, et al. Chemokine CCL2 from proximal tubular epithelial cells contributes to sepsis-induced acute kidney injury. American journal of physiology Renal physiology. Aug 12022;323(2):F107-f119. doi:10.1152 / ajprenal.00037.2022 Attorney Docket No.9151.282.WO 28. Kashyap S, Osman M, Ferguson CM, et al. Ccl2 deficiency protects against chronic renal injury in murine renovascular hypertension. Scientific Reports.2018 / 06 / 052018;8(1):8598. doi:10.1038 / s41598-018-26870-y The foregoing is illustrative of the present invention and is not to be construed as limiting thereof. The invention is defined by the following claims, with equivalents of the claims to be included therein.

Claims

Attorney Docket No.9151.282.WO What is claimed is:

1. A method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; and measuring expression of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) listed in Table 1 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) listed in Table 1 as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject.

2. A method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; and measuring expression of at least one gene selected from the group consisting of: APOE, PER3, STRIT1, FOS, ALDOB, PAH, CUBN, LRP2 and SLC5A12 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of the at least one gene (e.g., at least 2, 3, 4, 5, 6, 7, 8, or all 9 genes) as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject.

3. A method for determining the likelihood of donor kidney delayed graft function (DGF), comprising: providing a biopsy of the donor kidney, said biopsy collected before implantation of the donor kidney, and said biopsy comprising renal proximal tubule cells; andAttorney Docket No.9151.282.WO measuring expression of a plurality of the genes (e.g., at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, or at least 60 genes) listed in Table 6, Table 7, Table 8, or Table 9 in cells of the biopsy (e.g., the proximal tubule cells), wherein differential expression (e.g., an increased expression) of the plurality of genes as compared to a control (e.g., biopsy from a living donor kidney) indicates a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject.

4. The method of any one of the preceding claims, wherein the measuring comprises single cell RNA sequencing of the renal proximal tubule cells.

5. The method of any one of the preceding claims, wherein the donor kidney is a donation after cardiac death (DCD) donor kidney.

6. The method of any one of the preceding claims, wherein the differential expression comprises upregulation of fructose metabolism genes.

7. The method of any one of the preceding claims, wherein the method further comprises measuring downregulation of expression of metabolic reprogramming and biosynthesis genes (e.g., PHGDH, MYC, and SERPINA1), inflammation and immune signalling genes (e.g., HAVCR1, CCL2, SERPINA1, and VCAM1), cell stress-related genes (e.g., TACSTD2, TMSB4X, HAVCR1, and MYC), aerobic metabolism-related genes (e.g. PHGDH, and MYC) and oxidative phosphorylation pathway genes (e.g., PHGDH, and MYC).

8. The method of any one of the preceding claims, wherein said donor kidney is from a male donor and said measuring further comprises measuring a proportion of loss of Y chromosome (LoY) cells in the biopsy, and wherein a higher proportion of LoY cells in the biopsy as compared to a control (e.g., biopsy from a living male donor kidney) indicates a decreased likelihood of donor kidney DGF after implantation in a subject.

9. The method of any one of the preceding claims, wherein said donor kidney is from a male donor and said measuring further comprises measuring a proportion of LoY cells in the biopsy,Attorney Docket No.9151.282.WO and wherein a median proportion of LoY of about 10, 15 or 20%, to about 30, 40 or 50% (e.g., about 25%) indicates a decreased likelihood of donor kidney DGF after implantation in a subject.

10. The method of any one of the preceding claims, wherein said at least one gene comprises at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 3.

11. The method of any one of the preceding claims, wherein said at least one gene comprises at least one of the genes (e.g., at least 2, 3, 5, 8, 10, 15 or 16 genes) listed in Table 4.

12. The method of any one of the preceding claims, wherein said method further comprises implanting the donor kidney into a subject in need thereof.

13. The method of claim 12, wherein the subject is an allogeneic subject with respect to the donor kidney.

14. A method of performing a kidney transplant, comprising implanting a donor kidney into a subject in need thereof, wherein said donor kidney is determined to have a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject by a method of any one of claims 1-11.

15. The method of claim 14, wherien the subject is an allogeneic subject with respect to the donor kidney.

16. The use of a donor kidney for a kidney transplant, said donor kidney determined to have a decreased likelihood of donor kidney DGF (i.e., negative association) after implantation in a subject by a method of any one of claims 1-11.

17. The use of claim 16, wherien the subject is an allogeneic subject with respect to the donor kidney.Attorney Docket No.9151.282.WO 18. A method of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, comprising: measuring expression of at least one gene (e.g., at least 2, 3, 5, 8, 10, 15 or 20 genes) in a sample (e.g., biopsy) from the kidney transplant, wherein the at least one gene comprises at least one gene listed in Table 1, and wherein decreased gene expression of the at least one gene as compared to a control (e.g., gene expression from cells in a living donor kidney) indicates an increased likelihood of requiring dialysis after transplantation in the subject.

19. A method of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, comprising: measuring expression of at least one gene selected from the group consisting of: APOE, PER3, STRIT1, FOS, ALDOB, PAH, CUBN, LRP2 and SLC5A12 in a sample (e.g., biopsy) from the kidney transplant, wherein differential expression (e.g., decreased expression) of the at least one gene (e.g., at least 2, 3, 4, 5, 6, 7, 8, or all 9 genes) as compared to a control (e.g., biopsy from a living donor kidney) indicates an increased liklihood of requiring dialysis after transplantation in the subject.

20. A method of determining the likelihood of requiring dialysis treatment in a kidney transplant recipient subject, comprising: measuring expression of a plurality of the genes (e.g., at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, or at least 60 genes) listed in Table 6, Table 7, Table 8, or Table 9 in a sample (e.g., biopsy) from the kidney transplant, and wherein decreased gene expression of the plurality of genes as compared to a control (e.g., gene expression from cells in a living donor kidney) indicates an increased liklihood of requiring dialysis after transplantation in the subject.

21. The method of any one of claims 18-20, further comprising measuring a proportion of cells devoid of a Y chromosome, wherein a higher proportion of cells devoid of a Y chromosome as compared to a control indicates an increased likelihood of recovery from DGF after transplantation in the subject.Attorney Docket No.9151.282.WO 22. The method of any one of claims 18-21, wherein measuring comprises measuring expression at one, two, or three points in time (e.g., 0 months, 1 month, and / or 12 months) prior to, and / or after transplantation.

23. The method of any one of claims 18-22, wherein the genes comprise PER3, STRIT1, and / or APOE and optionally SLC5A12, LRP2, and / or CUBN.

24. The method of any one of claims 18-23, wherein the genes comprise at least one of the genes (e.g., at least 2, 3, 4, or 5 genes) listed in Table 3.

25. The method of any one of claims 18-24, wherein the genes comprise at least one of the genes (e.g., at least 2, 3, 5, 8, 10,15 or 16 genes) listed in Table 4.

26. The method of any one of the preceding claims, wherein the genes comprise: (a) SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, PER3, QDPR, COTL1, PCK2, FBP1, ACOT7, ADI1, DPEP1, SLC43A2, RBP5, NPL, XPNPEP2, ECHS1, and / or PARM1; (b) SLC22A8, APOE, ALDOB, STRIT1, SLC7A8, HPD, ANK2, PRAP1, AZGP1, SLC7A9, HSD11B2, FABP1, ATP5IF1, FGL2, and / or PER3; or (c) ALDOB, ANK2, APOE, ATP5IF1, AZGP1, FABP1, FGL2, HPD, HSD11B2, PER3, PRAP1, and / or STRIT1.

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