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Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations
BACKGROUND: Liver disease is any condition that causes liver damage and inflammation and may likely affect the function of the liver. Vital biochemical screening tools that can be used to evaluate the health of the liver and help diagnose, prevent, monitor, and control the development of liver disea...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942994/ https://www.ncbi.nlm.nih.gov/pubmed/36809439 http://dx.doi.org/10.1371/journal.pone.0280344 |
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author | Soremekun, Chisom Machipisa, Tafadzwa Soremekun, Opeyemi Pirie, Fraser Oyekanmi, Nashiru Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun |
author_facet | Soremekun, Chisom Machipisa, Tafadzwa Soremekun, Opeyemi Pirie, Fraser Oyekanmi, Nashiru Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun |
author_sort | Soremekun, Chisom |
collection | PubMed |
description | BACKGROUND: Liver disease is any condition that causes liver damage and inflammation and may likely affect the function of the liver. Vital biochemical screening tools that can be used to evaluate the health of the liver and help diagnose, prevent, monitor, and control the development of liver disease are known as liver function tests (LFT). LFTs are performed to estimate the level of liver biomarkers in the blood. Several factors are associated with differences in concentration levels of LFTs in individuals, such as genetic and environmental factors. The aim of our study was to identify genetic loci associated with liver biomarker levels with a shared genetic basis in continental Africans, using a multivariate genome-wide association study (GWAS) approach. METHODS: We used two distinct African populations, the Ugandan Genome Resource (UGR = 6,407) and South African Zulu cohort (SZC = 2,598). The six LFTs used in our analysis were: aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, and albumin. A multivariate GWAS of LFTs was conducted using the exact linear mixed model (mvLMM) approach implemented in GEMMA and the resulting P-values were presented in Manhattan and quantile-quantile (QQ) plots. First, we attempted to replicate the findings of the UGR cohort in SZC. Secondly, given that the genetic architecture of UGR is different from that of SZC, we further undertook similar analysis in the SZC and discussed the results separately. RESULTS: A total of 59 SNPs reached genome-wide significance (P = 5x10(-8)) in the UGR cohort and with 13 SNPs successfully replicated in SZC. These included a novel lead SNP near the RHPN1 locus (lead SNP rs374279268, P-value = 4.79x10(-9), Effect Allele Frequency (EAF) = 0.989) and a lead SNP at the RGS11 locus (lead SNP rs148110594, P-value = 2.34x10(-8), EAF = 0.928). 17 SNPs were significant in the SZC, while all the SNPs fall within a signal on chromosome 2, rs1976391 mapped to UGT1A was identified as the lead SNP within this region. CONCLUSIONS: Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset. |
format | Online Article Text |
id | pubmed-9942994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99429942023-02-22 Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations Soremekun, Chisom Machipisa, Tafadzwa Soremekun, Opeyemi Pirie, Fraser Oyekanmi, Nashiru Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun PLoS One Research Article BACKGROUND: Liver disease is any condition that causes liver damage and inflammation and may likely affect the function of the liver. Vital biochemical screening tools that can be used to evaluate the health of the liver and help diagnose, prevent, monitor, and control the development of liver disease are known as liver function tests (LFT). LFTs are performed to estimate the level of liver biomarkers in the blood. Several factors are associated with differences in concentration levels of LFTs in individuals, such as genetic and environmental factors. The aim of our study was to identify genetic loci associated with liver biomarker levels with a shared genetic basis in continental Africans, using a multivariate genome-wide association study (GWAS) approach. METHODS: We used two distinct African populations, the Ugandan Genome Resource (UGR = 6,407) and South African Zulu cohort (SZC = 2,598). The six LFTs used in our analysis were: aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, and albumin. A multivariate GWAS of LFTs was conducted using the exact linear mixed model (mvLMM) approach implemented in GEMMA and the resulting P-values were presented in Manhattan and quantile-quantile (QQ) plots. First, we attempted to replicate the findings of the UGR cohort in SZC. Secondly, given that the genetic architecture of UGR is different from that of SZC, we further undertook similar analysis in the SZC and discussed the results separately. RESULTS: A total of 59 SNPs reached genome-wide significance (P = 5x10(-8)) in the UGR cohort and with 13 SNPs successfully replicated in SZC. These included a novel lead SNP near the RHPN1 locus (lead SNP rs374279268, P-value = 4.79x10(-9), Effect Allele Frequency (EAF) = 0.989) and a lead SNP at the RGS11 locus (lead SNP rs148110594, P-value = 2.34x10(-8), EAF = 0.928). 17 SNPs were significant in the SZC, while all the SNPs fall within a signal on chromosome 2, rs1976391 mapped to UGT1A was identified as the lead SNP within this region. CONCLUSIONS: Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset. Public Library of Science 2023-02-21 /pmc/articles/PMC9942994/ /pubmed/36809439 http://dx.doi.org/10.1371/journal.pone.0280344 Text en © 2023 Soremekun et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Soremekun, Chisom Machipisa, Tafadzwa Soremekun, Opeyemi Pirie, Fraser Oyekanmi, Nashiru Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title | Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title_full | Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title_fullStr | Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title_full_unstemmed | Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title_short | Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations |
title_sort | multivariate gwas analysis reveals loci associated with liver functions in continental african populations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942994/ https://www.ncbi.nlm.nih.gov/pubmed/36809439 http://dx.doi.org/10.1371/journal.pone.0280344 |
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