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Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population
While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/r...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889551/ https://www.ncbi.nlm.nih.gov/pubmed/32902719 http://dx.doi.org/10.1007/s00439-020-02222-7 |
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author | Hebbar, Prashantha Abubaker, Jehad Ahmed Abu-Farha, Mohamed Alsmadi, Osama Elkum, Naser Alkayal, Fadi John, Sumi Elsa Channanath, Arshad Iqbal, Rasheeba Pitkaniemi, Janne Tuomilehto, Jaakko Sladek, Robert Al-Mulla, Fahd Thanaraj, Thangavel Alphonse |
author_facet | Hebbar, Prashantha Abubaker, Jehad Ahmed Abu-Farha, Mohamed Alsmadi, Osama Elkum, Naser Alkayal, Fadi John, Sumi Elsa Channanath, Arshad Iqbal, Rasheeba Pitkaniemi, Janne Tuomilehto, Jaakko Sladek, Robert Al-Mulla, Fahd Thanaraj, Thangavel Alphonse |
author_sort | Hebbar, Prashantha |
collection | PubMed |
description | While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00439-020-02222-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7889551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-78895512021-03-03 Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population Hebbar, Prashantha Abubaker, Jehad Ahmed Abu-Farha, Mohamed Alsmadi, Osama Elkum, Naser Alkayal, Fadi John, Sumi Elsa Channanath, Arshad Iqbal, Rasheeba Pitkaniemi, Janne Tuomilehto, Jaakko Sladek, Robert Al-Mulla, Fahd Thanaraj, Thangavel Alphonse Hum Genet Original Investigation While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00439-020-02222-7) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2020-09-09 2021 /pmc/articles/PMC7889551/ /pubmed/32902719 http://dx.doi.org/10.1007/s00439-020-02222-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Investigation Hebbar, Prashantha Abubaker, Jehad Ahmed Abu-Farha, Mohamed Alsmadi, Osama Elkum, Naser Alkayal, Fadi John, Sumi Elsa Channanath, Arshad Iqbal, Rasheeba Pitkaniemi, Janne Tuomilehto, Jaakko Sladek, Robert Al-Mulla, Fahd Thanaraj, Thangavel Alphonse Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title | Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title_full | Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title_fullStr | Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title_full_unstemmed | Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title_short | Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population |
title_sort | genome-wide landscape establishes novel association signals for metabolic traits in the arab population |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889551/ https://www.ncbi.nlm.nih.gov/pubmed/32902719 http://dx.doi.org/10.1007/s00439-020-02222-7 |
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