Single nucleotide polymorphism-mediated risk identification for liver disease

Abstract

The invention relates to methods of assessing liver disease in a subject by detecting one or more single-nucleotide polymorphisms (SNPs) of the subject and correlating the detected SNPs to the liver disease. The methods may also include a step of implementing a treatment decision, such as monitoring the subject for signs of liver disease, administering a therapeutic agent to the subject, liver transplant, or combinations thereof. The invention also relates to computing devices for assessing liver disease in a subject.

Description

PCT Application Attorney Docket No. AF44111.P044WOBLG Ref. No. 25-021TITLESINGLE NUCLEOTIDE POLYMORPHISM-MEDIATED RISK IDENTIFICATION FOR LIVER DISEASESEQUENCE DISCLOSURE STATEMENT

[0001] Pursuant to 37 C.F.R. § 1.834, Applicant has submitted a sequence listing in XML format (“Sequence Listing”). The name of the file containing the Sequence Listing is “AF4411 l.P044WO.xml”. The date of the creation of the Sequence Listing is October 15. 2025. The size of the Sequence Listing is 12,000 bytes. Applicant hereby incorporates by reference the material in the Sequence Listing.CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Patent Application No. 63 / 707,657, filed on October 15, 2024. The entirety of the aforementioned application is incorporated herein by reference.BACKGROUND

[0003] A need exists for more effective methods of detecting liver disease in a subject. Numerous embodiments of the present disclosure aim to address the aforementioned needSUMMARY

[0004] In some embodiments, the present disclosure pertains to methods of assessing liver disease in a subject. In some embodiments, the methods of the present disclosure include: detecting one or more single-nucleotide polymorphisms (SNPs) of the subject; and correlating the detected SNPs to the liver disease. In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision. In some embodiments, the treatment decision includes, without limitation, monitoring the subject for signs of liver disease, administering a therapeutic agent to the subject, liver transplant, or combinations thereof.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0005] Additional embodiments of the present disclosure pertain to computing devices for assessing liver disease in a subject. In some embodiments, the computing device includes one or more computer readable storage mediums having a program code embodied therewith. In some embodiments, the program code includes programming instructions for receiving one or more detected SNPs of the subject. In some embodiments, the program code also includes programming instructions for feeding the detected SNPs into an algorithm that correlates the detected SNPs to the liver disease. In some embodiments, the computing device also includes the algorithm. In some embodiments, the program code also includes programming instructions for recommending a treatment decision.

[0006] The methods and computing devices of the present disclosure may be utilized to correlate various SNPs to liver disease. For instance, in some embodiments, the SNPs include, without limitation, at least one SERPINA1 -associated SNP, at least one FAA / 73 A-associated SNP, at least one MTMR12-associated SNP, at least one FV7B7-associated SNP, at least one ALKBH1 -associated SNP, or combinations thereof.DESCRIPTION OF THE DRAWINGS

[0007] FIG. 1 illustrates the stages of liver damage that result in end-stage liver disease.

[0008] FIG. 2A illustrates a method of assessing liver disease in a subject.

[0009] FIG. 2B illustrates a computing device for assessing liver disease in a subject.

[0010] FIG. 3 illustrates the identification of single nucleotide polymorphisms (SNPs) in \heALKBHl gene.

[0011] FIG. 4 illustrates the hypothesis that end-stage liver disease (ESLD) is linked to ALKBH1 3’- UTR defects that maintain ALKBH1 expression.

[0012] FIG. 5 summarizes the identification of different SNPs responsible for promoting the progression of liver damage to ESLD.

[0013] FIG. 6 illustrates that the Hepatocyte Proliferation Stress Response (HPSR) functions as a decentralized 3-stage system.

[0014] FIG. 7 shows the manner in which the entire HPSR system (both preemptive and proliferative components) operate.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021DETAILED DESCRIPTION

[0015] It is to be understood that both the foregoing general description and the following detailed description are illustrative and explanatory, and are not restrictive of the subject matter, as claimed. In this application, the use of the singular includes the plural, the word “a” or “an” means “at least one”, and the use of “or” means “and / or”, unless specifically stated otherwise. Furthermore, the use of the term “including”, as well as other forms, such as “includes” and “included”, is not limiting. Also, terms such as “element” or “component” encompass both elements or components comprising one unit and elements or components that include more than one unit unless specifically stated otherwise.

[0016] The section headings used herein are for organizational purposes and are not to be construed as limiting the subject matter described. All documents, or portions of documents, cited in this application, including, but not limited to. patents, patent applications, articles, books, and treatises, are hereby expressly incorporated herein by reference in their entirety for any purpose. In the event that one or more of the incorporated literature and similar materials defines a term in a manner that contradicts the definition of that term in this application, this application controls.

[0017] As illustrated in FIG. 1, liver damage often occurs in steps that involve the formation of fatty liver, fibrosis, cirrhosis, and in some cases cancer. Hepatocytes are the predominant cell type. Hepatocytes are able to proliferate in response to damage. Fibrosis emerges in response to the deposition of collagen throughout the liver when hepatocytes, for various reasons, fail to proliferate.

[0018] The Z variant of alpha 1 -antitrypsin leads to the formation of aggregates and polymers. Homozygous expression of the Z variant (designated as ZZ) have been shown to disrupt the flow of proteins through the secretory pathway, causing stress. A subset of patients progress beyond fibrosis and cirrhosis to develop end-stage liver disease (ESLD), requiring orthotopic transplantation to maintain the life of the patient. The underlying cause for progression to ESLD is unknown, but an inherited genetic abnormality (or abnormalities) has been suggested.

[0019] As such, a need exists for more effective methods of detecting liver disease in a subject. Numerous embodiments of the present disclosure aim to address the aforementioned need.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0020] In some embodiments, the present disclosure pertains to methods of assessing liver disease in a subject. In some embodiments illustrated in FIG. 2A, the methods of the present disclosure include: detecting one or more single-nucleotide polymorphisms (SNPs) of the subject (step 10); and correlating the detected SNPs to the liver disease (step 12). In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision (step 14). In some embodiments, the treatment decision includes, without limitation, monitoring the subject for signs of liver disease (step 16), administering a therapeutic agent to the subject (step 18), liver transplant (step 20), or combinations thereof.

[0021] Additional embodiments of the present disclosure pertain to computing devices for assessing liver disease in a subject. In some embodiments, the computing devices of the present disclosure include one or more computer-readable storage media having a program code embodied therewith. In some embodiments, the program code includes programming instructions for receiving one or more detected SNPs of the subject. In some embodiments, the program code also includes programming instructions for feeding the detected SNPs into an algorithm that correlates the detected SNPs to the liver disease. In some embodiments, the computing device also includes the algorithm. In some embodiments, the program code also includes programming instructions for recommending a treatment decision.

[0022] As set forth in more detail herein, the methods and computing devices of the present disclosure can have numerous embodiments.

[0023] SNPs

[0024] The methods and computing devices of the present disclosure may be utilized to correlate various SNPs to liver disease. For instance, in some embodiments, the SNPs include, without limitation, at least one SERP1NA1 -associated SNP, at least one FAM J34A-associated SNP. at least one ATTjW7?J2-associated SNP, at least one MAiWBJ-associated SNP, at least one ALKBH1 -associated SNP, or combinations thereof.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0025] The SNPs may be in various forms. For instance, in some embodiments, the SNPs include homozygous SNPs. In some embodiments, the SNPs include heterozygous SNPs. In some embodiments, the SNPs are associated with a translated region of a gene. In some embodiments, the SNPs are associated with an untranslated region of a gene. In some embodiments, the SNPs are associated with a promoter of a gene. In some of such embodiments, the SNPs can alter the regulation of how an important gene is regulated, possibly contributing to disease.

[0026] In some embodiments, the SNPs include a SERPINA1 -associated SNP. In some embodiments, the SNP is associated with the promoter of SERPINA1. In some embodiments, the SERPINA1- associated SNP has a chromosome location of 14:94390577. In some embodiments, the SERPINA1- associated SNP represents an SNP of the following underlined sequence: CAGCAGCTAG (SEQ ID NO: 1).

[0027] In some embodiments, the SNPs include a FAM134A-associated SNP. In some embodiments, the SNP is associated with an untranslated region of FAM134A. In some embodiments, the FAM734A-associated SNP has a chromosome location of 2:219182235. In some embodiments, the FAAf / j A-associated SNP represents an SNP of the following underlined sequence: TTCAGTGGGG (SEQ ID NO: 2).

[0028] In some embodiments, the SNPs include a A77'A / A> / 2-associated SNP. In some embodiments, the SNP is associated with an untranslated region of MTMR12. In some embodiments, the MTMR12- associated SNP has a chromosome location of 13:94584489. In some embodiments, the MTMR12- associated SNP represents an SNP of the following underlined sequence: TTTCAAAGAG (SEQ ID NO: 3).

[0029] In some embodiments, the SNPs include a MAN IB 1 -associated SNP. In some embodiments, the SNP is associated with an untranslated region of MAN IB 1. In some embodiments, the MAN IB 1- associated SNP has a chromosome location of 9:137108975. In some embodiments, the MAN1B1- associated SNP represents an SNP of the following underlined sequence: AGGCAGGCAG (SEQ ID NO: 4).PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0030] In some embodiments, the SNPs include a ALKBH1 -associated SNP. In some embodiments, the SNP is associated with an untranslated region of ALKBH1. In some embodiments, the ALKBH1- associated SNP has a chromosome location of 14:77672682. In some embodiments, the ALKBH1- associated SNP represents an SNP of the following underlined sequence: ATCCTTTTAG (SEQ ID NO: 5).

[0031] In some embodiments, the / .k7i / 7 / -associated SNP has a chromosome location of 14:77672949. In some embodiments, the ALKBH1 -associated SNP represents an SNP of the following underlined sequence: CAGCAAGAGG (SEQ ID NO: 6).

[0032] In some embodiments, the ALk ?H7-associated SNP has a chromosome location of 14:77673645. In some embodiments, the ALKBH1 -associated SNP represents an SNP of the following underlined sequence: GTGGATGAGT (SEQ ID NO: 7).

[0033] SNPs may be detected by various technologies. For instance, in some embodiments, SNP detection includes DNA sequencing. In some embodiments, SNPs may be detected by various DNA sequencing technologies (e.g., Sanger sequencing technology, Whole Exome Sequencing, and / or Whole Genome Sequencing) when compared to a reference sequence (e.g., GRCh38 as the reference genome).

[0034] In some embodiments, the SNPs are detected from a biological sample of a subject. For instance, in some embodiments, the SNPs are detected from a tissue of a subject. In some embodiments, a subject’s blood DNA can be used as an alternative.

[0035] Correlating SNPs to liver diseasePCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0036] The methods and computing devices of the present disclosure may correlate detected SNPs to liver disease in various manners. For instance, in some embodiments, the correlation includes, without limitation, correlating the detected SNPs to the subject’s susceptibility to a liver disease; correlating the detected SNPs to the subject’s onset of a liver disease; correlating the detected SNPs to a diagnosis of a liver disease in the subject; correlating the detected SNPs to a severity of a liver disease in the subject; correlating the detected SNPs to a clinical stage of a liver disease in the subject; correlating the detected SNPs to a prediction of when the subject may need a liver transplant; correlating the detected SNPs to an age when the subject may need a liver transplant; correlating the detected SNPs to a prediction of a liver disease based on the subject’ s alcohol consumption; correlating the detected SNPs to a differentiation between different liver diseases in the subject; correlating the detected SNPs to a differentiation between liver fibrosis, liver cirrhosis, and end-stage liver disease (ESLD) in the subject; correlating the detected SNPs to end-stage liver disease (ESLD) in the subject; correlating the detected SNPs to a progression of liver damage to end-stage liver disease (ESLD) in the subject; or combinations thereof.

[0037] In some embodiments, the correlation includes correlating the detected SNPs to the subject’s susceptibility to a liver disease. In some embodiments, the correlation includes correlating the detected SNPs to end-stage liver disease (ESLD) in the subject. In some embodiments, the correlation includes correlating the detected SNPs to a progression of liver damage to end-stage liver disease (ESLD) in the subject. In some embodiments, the rate of progression to ESLD is accelerated when specific SNPs in SERPINA1 and ALKBH1 also contain the SNP in MAN1B1.

[0038] In some embodiments, the correlation includes correlating the detected SNPs to an age when the subject may need a liver transplant. In some embodiments, the age is less than 1 year of age. In some embodiments, the age is less than 10 years of age. In some embodiments, the age is between 20-40 years of age. In some embodiments, the age is more than 30 years of age. In some embodiments, the age is between 40-60 years of age. In some embodiments, the age is more than 40 years of age.

[0039] Liver diseasesPCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0040] The detected SNPs may be correlated to various types of liver diseases. For instance, in some embodiments, the liver disease includes, without limitation, liver fibrosis, liver cirrhosis, end-stage liver disease (ESLD), or combinations thereof. In some embodiments, the liver disease includes endstage liver disease (ESLD). In some embodiments, SNPs in SERPINA1 and ALKBH1 are sufficient to be correlated to end-stage liver disease (ESLD).

[0041] Subjects

[0042] The methods and computing devices of the present disclosure may be utilized to assess liver disease in various subjects. For instance, in some embodiments, the subject is a human being. In some embodiments, the subject is a non-human mammal. In some embodiments, the non-human mammal includes, without limitation, a horse, a rabbit, a mouse, a rat, a pig, a sheep, a cow, a dog, or a cat. In some embodiments, the non-human mammal is a domestic animal, such as a dog or a cat. In some embodiments, the subject is an alpha- 1 antitrypsin deficient subject, such as a Z / Z alpha- 1 antitrypsin deficient subject.

[0043] Treatment decision

[0044] In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision. In some embodiments, the computing devices of the present disclosure also include programming instructions for recommending a treatment decision. The methods and computing devices of the present disclosure may be utilized to implement or recommend various treatment decisions. For instance, in some embodiments, the treatment decision includes, without limitation, monitoring the subject for signs of liver disease, administering a therapeutic agent to the subject, liver transplant, or combinations thereof.

[0045] In some embodiments, the treatment decision includes administering a therapeutic agent to the subject. In some embodiments, the therapeutic agent enhances secretion of alpha- 1 antitrypsin.

[0046] Computer-implemented methods

[0047] In some embodiments, the methods of the present disclosure occur in a computer-implemented manner. In some embodiments, the methods of the present disclosure include feeding the detected SNPs of the subject into an algorithm. In some embodiments, the algorithm correlates the detected SNPs to the liver disease. In some embodiments, the algorithm is in the form of a software as a service (SaaS) model.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0048] In some embodiments, the computing devices of the present disclosure include the algorithm. In some embodiments, the algorithm of the computing device recommends a treatment decision based on the correlation.

[0049] Algorithms

[0050] The methods and computing devices of the present disclosure can include various algorithms. For instance, in some embodiments, the algorithm includes: an input layer for receiving the detected SNPs from the subject; one or more hidden layers that include a plurality of neurons; one or more dropout layers to mitigate overfitting; and an output layer for generating a correlation of the detected SNPs to a liver disease.

[0051] in some embodiments, the algorithm includes a machine-learning algorithm trained on the detected SNPs. In some embodiments, the machine-learning algorithm is an LI -regularized logistic regression algorithm. In some embodiments, the machine-learning algorithm includes supervised learning algorithms. In some embodiments, the supervised learning algorithms include nearest neighbor algorithms, naive-Bayes algorithms, decision tree algorithms, linear regression algorithms, support vector machines, neural networks, convolutional neural networks, ensembles (e.g., random forests and gradient boosted decision trees), or combinations thereof.

[0052] Machine-learning algorithms may be trained in various manners. For instance, in some embodiments, the training includes: (1) feeding a first set of detected SNPs into a machine-learning algorithm, where the first set of detected SNPs are from one or more subjects that have one or more liver diseases; (2) feeding a second set of detected SNPs into the machine-learning algorithm, where the second set of detected SNPs are from one or more subjects that do not have liver diseases; and (3) training the machine-learning algorithm to assess liver diseases by comparing the first set of detected SNPs with the second set of measured detected SNPs.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0053] Computing devices

[0054] The computing devices of the present disclosure can include various types of computer- readable storage mediums. For instance, in some embodiments, the computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. In some embodiments, the computer-readable storage medium may include, without limitation, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or combinations thereof.

[0055] A non-exhaustive list of more specific examples of suitable computer-readable storage mediums includes, without limitation, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device, or combinations thereof.

[0056] A computer-readable storage medium, as used herein, is not to be construed as being transitory signals per se. Such transitory signals may be represented by radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0057] In some embodiments, computer-readable program instructions for computing devices can be downloaded to respective computing / processing devices from a computer-readable storage medium or to an external computer or external storage device via a network, such as the Internet, a local area network (LAN), a wide area network (WAN) and / or a wireless network. In some embodiments, the network may include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. In some embodiments, a network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing / processing device.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0058] In some embodiments, computer-readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine- dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object-oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the "C" programming language or similar programming languages.

[0059] In some embodiments, the computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected in some embodiments to the user's computer through any type of network, including a LAN or a WAN, or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field- programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer- readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry in order to perform aspects of the present disclosure.

[0060] Embodiments of the present disclosure for assessing liver disease in a subject as discussed herein may be implemented using a computing device illustrated in FIG. IB. Referring now to FIG. IB, FIG. IB illustrates an embodiment of the present disclosure of the hardware configuration of a computing device 30 which is representative of a hardware environment for practicing various embodiments of the present disclosure.

[0061] Computing device 30 has a processor 31 connected to various other components by computing device bus 32. An operating system 33 runs on processor 31 and provides control and coordinates the functions of the various components of FIG. IB. An application 34 in accordance with the principles of the present disclosure runs in conjunction with operating system 33 and provides calls to operating system 33, where the calls implement the various functions or services to be performed by application 34. Application 34 may include, for example, a program for assessing liver disease in a subject as discussed in the present disclosure.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0062] Referring again to FIG. IB, read-only memory ("ROM") 35 is connected to computing device bus 32 and includes a basic input / output computing device ("BIOS") that controls certain basic functions of computing device 30. Random access memory ("RAM") 36 and disk adapter 37 are also connected to computing device bus 32. It should be noted that software components including operating system 33 and application 34 may be loaded into RAM 36, which may be computing device’s 30 main memory for execution. Disk adapter 37 may be an integrated drive electronics ("IDE") adapter that communicates with a disk unit 38 (e.g., a disk drive). It is noted that the program for assessing liver disease in a subject, as discussed in the present disclosure.

[0063] Computing device 30 may further include a communications adapter 39 connected to computing device bus 32. Communications adapter 39 interconnects computing device bus 32 with an outside network (e.g., wide area network) to communicate with other devices.

[0064] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and systems according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams and combinations of blocks in the flowchart illustrations and / or block diagrams can be implemented by computer-readable program instructions.

[0065] These computer-readable program instructions may be provided to a processor of a computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer- readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer-readable storage medium having instructions stored therein includes an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0066] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer- implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0067] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of computing devices, methods, and computing devices according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which includes one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be accomplished as one step, executed concurrently, substantially concurrently, in a partially or wholly temporally overlapping manner, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based computing devices that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0068] Example 1. Identification of single nucleotide polymorphisms (SNPs) associated with liver disease

[0069] In this Example, Applicant utilized a multiomics approach that includes biochemistry, cell biology, epigenetics, and the identification of Single Nucleotide Polymorphisms to identify and order a decentralized three- stage Hepatocyte Proliferative Stress. The detection of single nucleotide polymorphisms (SNPs) in patient genomic DNA (gDNA) will allow for the risk assessment of individuals who exhibit homozygosity for the alpha- 1 antitrypsin deficiency “Z” allele (i.e., Glu342Lys), and who will progress to end-stage liver disease (ESLD), thereby requiring orthotopic transplantation. Such individuals may include individuals of European descent.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0070] The detected SNPs are summarized in Table 1. An SNP that is located in the promoter of the SERPINA1 gene is dbSNP:8004738(C>T). Different combinations of additional and necessary ESLD modifier single nucleotides (SNPs) include dbSNPs 142234261 in gene FAM134A; dbSNP: 140836761 in gene MTMR12', dbSNP:4567G>A homozygous in the MAN IB 1 gene; and dbSNP:2267755C>T, dbSNP: 11621162T>C, and dbSNP: 10481470 A in the ALKBH1 gene (i.e., all in the last intron or 3’UTR region).Table 1. Detected SNPs.

[0001] Based on the combinations of SNPs, Applicant can generally predict when the transplant will be needed (e.g., early in life as in the first months or few years, mid-life, as a teenager, after 30 years of age, and / or between 40-60 years of age). The aforementioned SNPs can lead to the generation of a genetic signature to serve as a prognostic indicator to identify the patients who will progress to endstage liver disease and require a liver transplant.

[0002] As shown in FIG. 3, an SNP in the MAN1B1 gene was shown to associate with ZZ patients who progressed to end-stage liver disease very early in life (i.e., in the first months after birth). The SNP, rs4567. diminishes the concentration of the encoded Manlbl protein, implying that its role is to somehow protect the liver from damage caused by ZZ. Also, the SNP generates a new binding site for microRNA-362 by comparative genome hybridization in which 60,000 probes were used to scan the entire genome of each patient.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0003] Differences in the hybridization among the patient DNA, of only three probes (Panel A), and at only one gene (TOB2, Panel C), were detected (Panel B). This observation plus the location of the hybridization results implied that the DNA was differentially modified at the TOB2 gene’s transcription start site (TSS). Additional studies indicated that the differential hybridization was caused by the presence or absence of 6-methyladenine (6mA) as an epigenetic modification that suppresses translation of the TOB2 gene. These observations were in line with the fact that transcription of the TOB2 gene functions to prevent the proliferation of cells and therefore plays an anti-proliferative role.

[0004] As illustrated in FIG. 4, considering that hepatocytes must proliferate as a part of a liver damage response, it is reasonable to consider that 6mA must be removed so that hepatocyte proliferation will activate during stress from ZZ, and that this is somehow impaired in the patients who progress to end-stage liver disease. The gene ALKBH1 encodes a protein that removes 6mA from the TSS of many genes, allowing for the activation of the hepatocyte proliferation stress response (HPSR). The hypothesis to be tested was that a genetic defect was responsible for inability of I ALKBHl gene to remove 6mA from the TOB2 TSS, and therefore hinder the activation of the HPSR. This would lead to fibrosis and eventually progression to end-stage liver disease.

[0005] Because of the suspected nature of the proposed defect, the 3-UTR of the ALKBH1 gene in each patient DNA sample was sequenced. FIG. 5 shows the sequenced regions. Although several single nucleotide polymorphisms were detected, only three were present at higher levels in the endstage liver disease (ESLD) patients as compared to the European population. Additionally, an equal number of ZZ individuals never progressed to ESLD.

[0006] Additional SNPs are detected, and their frequencies are shown, that are linked to progression to ESLD in ZZ patients. These include genes for ALKBH1, SERPINA1 (encodes the Z protein), MTMR12, and FAM134A. The addition of the MAN1B1 defects accelerates progression to ESLD.

[0007] The latter two genes are very rare. The numerical designation of the SNP and its relative location in the human genome are indicated. Thick blue horizontal arrows depict SNPs that persistently exist in ZZ individuals who develop ESLD. The thin blue arow depicts an SNP that is linked to the accelerated progression to ESLD.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0008] Based on these findings, the Hepatocyte Proliferation Stress Response (HPSR) functions as a decentralized 3-stage system (FIG. 6). Newly synthesized ZZ first encounters two sequential preemptive stages. ERLAD (ER-Lysosome Associated Degradation) takes advantage of the polymeric / aggregated form of ZZ and causes the molecules to be transported for degradation by lysosomes. Undegraded molecules that remain in response to the saturation of ERLAD next encounter SIEVE (Stress-Induced Extracellular Vesicle Elimination), possibly to prevent the use of lysosomes. SIEVE is activated by the remaining ZZ that causes cellular stress as indicated by the induction of XBPls. MAN1B1 plays a role in the process that escorts ZZ out of the cell. In the event that both ERLAD and SIEVE fail to remove a sufficient amount of ZZ, Additional miRs activate the actual proliferation response (HPSR) by suppressing the capacity of AL KB Hl to prevent the transcription of TOB2. SNPs are shown by (*) that enhance the synthesis of ZZ by generating a Quantitative Trait Locus (QTL), and disrupt the optimal functions of ERLAD, SIEVE, and HPSR.

[0009] The manner in which the entire HPSR system (both preemptive and proliferative components) operate is depicted in FIG. 7. ZZ accumulates, ERLAD functions, SIEVE is activated and the hepatocyte proliferates. The remaining healthy cell is maintained until enough ZZ accumulates to initiate the HPSR system. Cycles continue to protect the liver. However, SNPs in the different components will diminish the effectiveness of the HPSR system, resulting in fibrosis. A sufficient number / combination of SNPs can allow for the progression to end-stage liver disease.

[0010] As specifically illustrated in FIG. 7, repeating cycles of a fully functioning ERLAD / SIEVE / HPRS circuit maintains liver health as previously unknown biological corrective system when ZZ is synthesized in excess. Combinations of two genetic polymorphisms in HPSR are responsible for the emergence of mild / intermediate liver fibrosis even when ZZ is synthesized at normal levels. Combinations of polymorphisms in ZZ and HPSR are responsible for the emergence of end-stage liver disease, requiring liver transplantation.

[0011] Polymorphisms in ERLAD are extremely rare (~2%) and have been identified in only one family. An additional polymorphism in SIEVE (Stress-Induced Extracellular Vesicle Expulsion) can accelerate the onset of ZZ-induced end-stage liver disease by approximately 9 years.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021

[0012] Without further elaboration, it is believed that one skilled in the art can, using the description herein, utilize the present disclosure to its fullest extent. The embodiments described herein are to be construed as illustrative and not as constraining the remainder of the disclosure in any way whatsoever. While the embodiments have been shown and described, many variations and modifications thereof can be made by one skilled in the art without departing from the spirit and teachings of the invention. Accordingly, the scope of protection is not limited by the description set out above, but is only limited by the claims, including all equivalents of the subject matter of the claims. The disclosures of all patents, patent applications and publications cited herein are hereby incorporated herein by reference, to the extent that they provide procedural or other details consistent with and supplementary to those set forth herein.

Claims

PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021CLAIMS1. A method of assessing liver disease in a subject, said method comprising:(a) detecting one or more single-nucleotide polymorphisms (SNPs) of the subject, wherein the SNPs are selected from the group consisting of: at least one SERP1NA 1 -associated SNP, at least one 774A7734A-associated SNP, at least one A77'A7 / ? / 2-associated SNP, at least one MAN IB 1 -associated SNP, at least one ALKBH1- associated SNP, or combinations thereof; and(b) correlating the detected SNPs to the liver disease.

2. The method of claim 1, wherein the SNPs comprise a .S' AAPZ / VA / -associated SNP, wherein the SNP is associated with the promoter of SERPINA1, wherein the SNP has a chromosome location of 14:94390577, and wherein the SNP represents an SNP of the following underlined sequence: CAGCAGCTAG (SEQ ID NO: 1).

3. The method of claim 1, wherein the SNPs comprise a 774M734A-associated SNP, wherein the SNP is associated with an untranslated region of FAM134A, wherein the SNP has a chromosome location of 2:219182235, and wherein the SNP represents an SNP of the following underlined sequence: TTCAGTGGGG (SEQ ID NO: 2).

4. The method of claim 1, wherein the SNPs comprise a A77’A7A 2-associatcd SNP, wherein the SNP is associated with an untranslated region of MTMR12, wherein the SNP has a chromosome location of 13:94584489, and wherein the SNP represents an SNP of the following underlined sequence: TTTCAAAGAG (SEQ ID NO: 3).PCT Application Attorney Docket No. AF44111.P044WOBLG 25-0215. The method of claim 1, wherein the SNPs comprise a MAN1B1 -associated SNP, wherein the SNP is associated with an untranslated region of MAN1B1, wherein the SNP has a chromosome location of 9:137108975, and wherein the SNP represents an SNP of the following underlined sequence: AGGCAGGCAG (SEQ ID NO: 4).

6. The method of claim 1, wherein the SNPs comprise a ALKBH1 -associated SNP, wherein the SNP is associated with an untranslated region otALKBHl, wherein the SNP has a chromosome location of 14:77672682, and wherein the SNP represents an SNP of the following underlined sequence: ATCCTTTTAG (SEQ ID NO: 5).

7. The method of claim 1, wherein the SNPs comprise a ALKBH1 -associated SNP, wherein the SNP is associated with an untranslated region otALKBHl, wherein the SNP has a chromosome location of 14:77672949, and wherein the SNP represents an SNP of the following underlined sequence: CAGCAAGAGG (SEQ ID NO: 6).

8. The method of claim 1, wherein the SNPs comprise a ALKBH1 -associated SNP, wherein the SNP is associated with an untranslated region oiALKBHl, wherein the SNP has a chromosome location of 14:77673645, and wherein the SNP represents an SNP of the following underlined sequence: GTGGATGAGT (SEQ ID NO: 7).

9. The method of claim 1 , wherein the detecting comprises DNA sequencing.

10. The method of claim 1, wherein the correlating is selected from the group consisting of: correlating the detected SNPs to the subject’s susceptibility to the liver disease; correlating the detected SNPs to the subject’s onset of the liver disease; correlating the detected SNPs to a diagnosis of the liver disease in the subject; correlating the detected SNPs to a severity of the liver disease in the subject; correlating the detected SNPs to a clinical stage of the liver disease in the subject; correlating the detected SNPs to a prediction of when the subject may need a liver transplant; correlating the detected SNPs to an age when the subject may need a liver transplant;PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021 correlating the detected SNPs to a prediction of the liver disease based on the subject’s alcohol consumption; correlating the detected SNPs to a differentiation between different liver diseases in the subject; correlating the detected SNPs to a differentiation between liver fibrosis, liver cirrhosis, and endstage liver disease (ESLD) in the subject; correlating the detected SNPs to end-stage liver disease (ESLD) in the subject; correlating the detected SNPs to a progression of liver damage to end-stage liver disease (ESLD) in the subject; or combinations thereof.

11. The method of claim 1, wherein the correlating comprises correlating the detected SNPs to the subject’s susceptibility to the liver disease.

12. The method of claim 1, wherein the correlating comprises correlating the detected SNPs to endstage liver disease (ESLD) in the subject.

13. The method of claim 1, wherein the correlating comprises correlating the detected SNPs to a progression of liver damage to end-stage liver disease (ESLD) in the subject.

14. The method of claim 1, wherein the correlating comprises correlating the detected SNPs to an age when the subject may need a liver transplant.

15. The method of claim 1, wherein the liver disease is selected from the group consisting of liver fibrosis, liver cirrhosis, end-stage liver disease (ESLD), or combinations thereof.

16. The method of claim 1, wherein the liver disease comprises end-stage liver disease (ESLD).

17. The method of claim 1, wherein the subject is a human being.

18. The method of claim 1, wherein the subject is an alpha- 1 antitrypsin deficient subject.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-02119. The method of claim 1. further comprising a step of implementing a treatment decision.

20. The method of claim 19, wherein the treatment decision is selected from the group consisting of monitoring the subject for signs of liver disease, administering a therapeutic agent to the subject, liver transplant, or combinations thereof.

21. The method of claim 19, wherein the treatment decision comprises administering a therapeutic agent to the subject.

22. The method of claim 1, wherein the method occurs in a computer-implemented manner.

23. The method of claim 22, wherein the method comprises feeding the detected SNPs of the subject into an algorithm, wherein the algorithm correlates the detected SNPs to the liver disease.

24. The method of claim 23, wherein the algorithm is in the form of a software as a service (SaaS) model.

25. The method of claim 23, wherein the algorithm comprises a machine-learning algorithm trained on the detected SNPs.

26. The method of claim 23, wherein the algorithm comprises: an input layer for receiving the detected SNPs from the subject; one or more hidden layers comprising a plurality of neurons; one or more dropout layers to mitigate overfitting; and an output layer for generating a correlation of the detected SNPs to the liver disease.

27. The method of claim 23, wherein the algorithm recommends a treatment decision based on the correlation.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-02128. A computing device for assessing liver disease in a subject, wherein the computing device comprises one or more computer readable storage mediums having a program code embodied therewith, wherein the program code comprises:(a) programming instructions for receiving one or more detected single-nucleotide polymorphisms (SNPs) of the subject, wherein the SNPs are selected from the group consisting of: at least one SERPINA 1 -associated SNP, at least one FAM134A- associated SNP, at least one M7'A7 / 72-ass()cialed SNP, at least one 47V7 / i / -associated SNP, at least one ALKBH1 -associated SNP, or combinations thereof: and(b) programming instructions for feeding the detected SNPs into an algorithm, wherein the algorithm correlates the detected SNPs to the liver disease.

29. The computing device of claim 28, wherein the computing device is a component of a software as a service (SaaS) model.

30. The computing device of claim 28, wherein the computing device further comprises the algorithm.

31. The computing device of claim 28, wherein the algorithm comprises: an input layer for receiving the detected SNPs from the subject; one or more hidden layers comprising a plurality of neurons; one or more dropout layers to mitigate overfitting; and an output layer for generating a correlation of the detected SNPs to the liver disease.

32. The computing device of claim 28, further comprising programming instructions for recommending a treatment decision.PCT Application Attorney Docket No. AF44111.P044WOBLG 25-02133. The computing device of claim 32, wherein the treatment decision is selected from the group consisting of monitoring the subject for signs of liver disease, administering a therapeutic agent to the subject, liver transplant, or combinations thereof.

34. The computing device of claim 28, wherein the SNPs comprise: a SERPINA1 -associated SNP, wherein the SNP is associated with the promoter of SERPINA1, wherein the SNP has a chromosome location of 14:94390577, and wherein the SNP represents an SNP of the following underlined sequence: CAGCAGCTAG (SEQ ID NO: 1); a A / W / 3-M-associated SNP, wherein the SNP is associated with an untranslated region of FAM134A, wherein the SNP has a chromosome location of 2:219182235, and wherein the SNP represents an SNP of the following underlined sequence: TTCAGTGGGG (SEQ ID NO: 2); a ATTM 72-associated SNP, wherein the SNP is associated with an untranslated region of MTMR12, wherein the SNP has a chromosome location of 13:94584489, and wherein the SNP represents an SNP of the following underlined sequence: TTTCAAAGAG (SEQ ID NO: 3); a MANI Bl -associated SNP, wherein the SNP is associated with an untranslated region of MAN1B1, wherein the SNP has a chromosome location of 9:137108975, and wherein the SNP represents an SNP of the following underlined sequence: AGGCAGGCAG (SEQ ID NO: 4); a ALKB Hl -associated SNP, wherein the SNP is associated with an untranslated region of ALKBH1, wherein the SNP has a chromosome location of 14:77672682, and wherein the SNP represents an SNP of the following underlined sequence: ATCCTTTTAG (SEQ ID NO: 5); a ARKBH1 -associated SNP, wherein the SNP is associated with an untranslated region of ALKBH1, wherein the SNP has a chromosome location of 14:77672949, and wherein the SNP represents an SNP of the following underlined sequence: CAGCAAGAGG (SEQ ID NO: 6); a ALKB Hl -associated SNP, wherein the SNP is associated with an untranslated region ofALKBHl, wherein the SNP has a chromosome location of 14:77673645, and wherein the SNP represents an SNP of the following underlined sequence: GTGGATGAGT (SEQ ID NO: 7); or combinations thereof.

35. The computing device of claim 28, wherein the correlation of the detected SNPs to the liver disease is selected from the group consisting of:PCT Application Attorney Docket No. AF44111.P044WOBLG 25-021 correlating the detected SNPs to the subject’s susceptibility to the liver disease: correlating the detected SNPs to the subject’s onset of the liver disease; correlating the detected SNPs to a diagnosis of the liver disease in the subject; correlating the detected SNPs to a severity of the liver disease in the subject; correlating the detected SNPs to a clinical stage of the liver disease in the subject; correlating the detected SNPs to a prediction of when the subject may need a liver transplant; correlating the detected SNPs to an age when the subject may need a liver transplant; correlating the detected SNPs to a prediction of the liver disease based on the subject’s alcohol consumption; correlating the detected SNPs to a differentiation between different liver diseases in the subject; correlating the detected SNPs to a differentiation between liver fibrosis, liver cirrhosis, and endstage liver disease (ESLD) in the subject; correlating the detected SNPs to end-stage liver disease (ESLD) in the subject; correlating the detected SNPs to a progression of liver damage to end-stage liver disease (ESLD) in the subject: or combinations thereof.

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