Associations of DNA methylation with biomarkers of liver function among male veterans living with HIV Öffentlichkeit

Lee, Mitchell (Spring 2021)

Permanent URL: https://etd.library.emory.edu/concern/etds/9w032435s?locale=de
Published

Abstract

Background: Chronic liver disease is a prominent cause of morbidity and mortality for people with HIV. The etiology of liver disease and function in people with HIV, however, is not fully understood. This thesis presents epigenome-wide association studies (EWAS) to identify associations between DNA methylation and seven biomarkers of liver function—serum levels of aspartate transaminase, alanine transaminase, and albumin, and total bilirubin, platelet count, FIB-4 score, and APRI score—among a cohort of male US veterans with HIV.

 

Methods: Blood samples and clinical data were obtained for 960 HIV+ male veterans from the Veterans Aging Cohort Study (VACS). Blood DNA methylation was assessed using the HumanMethylation450 (450K) array or the HumanMethylationEPIC (EPIC) array from Illumina, which cover over 450,000 and 870,000 DNA methylation (DNAm) sites, respectively. Associations between DNAm age acceleration (AA) and selected liver biomarkers were assessed by regressing biomarker values on IEAA, EEAA, PhenoAA, and GrimAA in linear models controlling for covariates. Associations between individual DNAm sites and selected liver biomarkers were assessed by separate EWAS of the EPIC and 450K sub-cohorts using mixed effect models controlling for covariates and batch effects. For DNAm sites measured by both platforms, meta-analysis of the separate sub-cohort EWAS results for each liver biomarker was performed.

Results: Significant association was observed between PhenoAA and serum albumin (b = -0.007, P-value = 8.6x10-4) among all AA measurements and liver biomarkers. Nine DNAm sites annotated to the TMEM49, SOCS3, FKBP5, ZEB2, and SAMD14 genes were significantly associated with serum albumin in the meta-analysis of the EPIC and 450K EWAS results. Beta coefficients from the separate EPIC and 450K EWAS results for those DNAm sites were positively correlated, indicating consistency between the EPIC and 450K cohorts. No significant associations were detected for the six other biomarkers after meta-analysis.

 

Conclusion: The EWAS results suggest that the TMEM49, SOCS3, FKBP5, ZEB2, and SAMD14 genes might be linked to liver function through serum albumin. Since this is the first EWAS of liver function among people with HIV, further replication analyses in independent cohorts are warranted to confirm the epigenetic mechanisms underlying liver function.

Table of Contents

Introduction................................................................................................................. 1

Literature Review.......................................................................................................... 4

    Burden of Chronic Liver Disease Among People with HIV.............................................. 4

Physiology and Etiology of Chronic Liver Disease......................................................... 5

DNA Methylation as a Mechanism of Gene Regulation.................................................. 6

DNA Methylation Age Acceleration in People with HIV.................................................. 7

Associations of DNA Methylation with Liver Function................................................... 9

Clinical Biomarkers of Liver Function........................................................................... 12

Methods........................................................................................................................ 16

Blood and Clinical Phenotype Sampling........................................................................ 16

Associations Among Selected Liver Biomarkers............................................................. 16

DNAm Data Generation, Processing, and Quality Control............................................... 17

Associations Between EWAS Covariates and Selected Liver Biomarkers........................... 18

Associations of DNAm Age Acceleration with Selected Liver Biomarkers.......................... 19

Principal Component Analysis...................................................................................... 19

Statistical Methods for DNAm EWAS for Selected Liver Biomarkers................................. 20

Results........................................................................................................................... 21

Participant Characteristics............................................................................................ 21

Correlations Among Selected Liver Biomarkers............................................................... 21

Covariate Associations with Selected Liver Biomarkers.................................................... 22

Associations of DNAm Age Acceleration with Selected Liver Biomarkers........................... 22

DNAm EWAS for Selected Liver Biomarkers.................................................................... 23

Discussion....................................................................................................................... 25

Strengths and Weaknesses............................................................................................. 28

Future Work.................................................................................................................. 31

References....................................................................................................................... 33

Tables.............................................................................................................................. 46

Figures............................................................................................................................. 51

Supplementary Tables & Figures........................................................................................ 56

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