A Perception on Genome-Wide Genetic Analysis of Metabolic Traits in Arab Populations

Despite dedicated nation-wide efforts to raise awareness against the harmful effects of fast-food consumption and sedentary lifestyle, the Arab population continues to struggle with an increased risk for metabolic disorders. Unlike the European population, the Arab population lacks well-established genetic risk determinants for metabolic disorders, and the transferability of established risk loci to this population has not been satisfactorily demonstrated. The most recent findings have identified over 240 genetic risk loci (with similar to 400 independent association signals) for type 2 diabetes, but thus far only 25 risk loci (ADAMTS9, ALX4, BCL11A, CDKAL1, CDKN2A/B, COL8A1, DUSP9, FTO, GCK, GNPDA2, HMG20A, HNF1A, HNF1B, HNF4A, IGF2BP2, JAZF1, KCNJ11 , KCNQ1, MC4R, PPAR gamma, SLC30A8, TCF7L2, TFAP2B, TP53INP1, and WFS1) have been replicated in Arab populations. To our knowledge, large-scale population- or family-based association studies are non-existent in this region. Recently, we conducted genome-wide association studies on Arab individuals from Kuwait to delineate the genetic determinants for quantitative traits associated with anthropometry, lipid profile, insulin resistance, and blood pressure levels. Although these studies led to the identification of novel recessive variants, they failed to reproduce the established loci. However, they provided insights into the genetic architecture of the population, the applicability of genetic models based on recessive mode of inheritance, the presence of genetic signatures of inbreeding due to the practice of consanguinity, and the pleiotropic effects of rare disorders on complex metabolic disorders. This perspective presents analysis strategies and study designs for identifying genetic risk variants associated with diabetes and related traits in Arab populations.Peer reviewe

Kuwaiti population subgroup of nomadic Bedouin ancestry—Whole genome sequence and analysis

AbstractKuwaiti native population comprises three distinct genetic subgroups of Persian, “city-dwelling” Saudi Arabian tribe, and nomadic “tent-dwelling” Bedouin ancestry. Bedouin subgroup is characterized by presence of 17% African ancestry; it owes it origin to nomadic tribes of the deserts of Arabian Peninsula and North Africa. By sequencing whole genome of a Kuwaiti male from this subgroup at 41X coverage, we report 3,752,878 SNPs, 411,839 indels, and 8451 structural variations. Neighbor-joining tree, based on shared variant positions carrying disease-risk alleles between the Bedouin and other continental genomes, places Bedouin genome at the nexus of African, Asian, and European genomes in concordance with geographical location of Kuwait and Peninsula. In congruence with participant's medical history for morbid obesity and bronchial asthma, risk alleles are seen at deleterious SNPs associated with obesity and asthma. Many of the observed deleterious ‘novel’ variants lie in genes associated with autosomal recessive disorders characteristic of the region

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/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.Peer reviewe

Genome-wide association study identifies novel risk variants from RPS6KA1, CADPS, VARS, and DHX58 for fasting plasma glucose in Arab population

Consanguineous populations of the Arabian Peninsula, which has seen an uncontrolled rise in type 2 diabetes incidence, are underrepresented in global studies on diabetes genetics. We performed a genome-wide association study on the quantitative trait of fasting plasma glucose (FPG) in unrelated Arab individuals from Kuwait (discovery-cohort:n = 1,353; replication-cohort:n = 1,196). Genome-wide genotyping in discovery phase was performed for 632,375 markers from Illumina HumanOmniExpress Beadchip; and top-associating markers were replicated using candidate genotyping. Genetic models based on additive and recessive transmission modes were used in statistical tests for associations in discovery phase, replication phase, and meta-analysis that combines data from both the phases. A genome-wide significant association with high FPG was found at rs1002487 (RPS6KA1) (p-discovery = 1.64E-08, p-replication = 3.71E-04, p-combined = 5.72E-11; beta-discovery = 8.315; beta-replication = 3.442; beta-combined = 6.551). Further, three suggestive associations (p-values <8.2E-06) with high FPG were observed at rs487321 (CADPS), rs707927 (VARS and 2Kb upstream of VWA7), and rs12600570 (DHX58); the first two markers reached genome-wide significance in the combined analysis (p-combined = 1.83E-12 and 3.07E-09, respectively). Significant interactions of diabetes traits (serum triglycerides, FPG, and glycated hemoglobin) with homeostatic model assessment of insulin resistance were identified for genotypes heterozygous or homozygous for the risk allele. Literature reports support the involvement of these gene loci in type 2 diabetes etiology.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Aineenvaihduntapiirteiden geneettinen kartoitus arabiväestössä

BACKGROUND: The highly inbred Arab population of the Middle East region has been experiencing complex metabolic health catastrophe ever since adopting a change in lifestyle in the rich post-oil era. Characterization of genetic risk variants by genome-wide (GW) profiling of genetic variations and phenotypes of metabolic health in this population would help understand population specific disease etiology. AIM: This study employs single nucleotide variant association analysis to 1) discover variant association with 13 different quantitative metabolic traits using GW genotype data, 2) characterize runs of homozygous regions and examine the association of variants harbored in such regions with metabolic traits, 3) impute untyped variants and assess their association with quantitative metabolic traits of the Arab population. MATERIALS AND METHODS: The study is focused on two cohorts, namely the Kuwait Obesity Genetics Project (KOGP) and the Kuwait Diabetes Epidemiology Program (KDEP. The cohorts comprised 1965 (genotyped using Illumina HumanCardio-MetaboChip array or by TaqMan Assay) and 1350 Arab inhabitants of Kuwait (genotyped by Illumina HumanOmniExpress array) respectively. The respective GW variant data obtained were subjected to quality control measures and used to analyze variants association with 13 different quantitative traits. RESULTS: Examination of variant association using GW genotyping and/or imputing revealed several variants modulating metabolic traits. Upon using only the genotyped variants, risk variants from the following genes were revealed at GW significant p-values (P ≤ 5E-08): RPS6KA1, LAD1, Or5v1, [CTTNBP2-LSM8], PGAP3, [RP11-191L9.4-CERK], ST6GALNAC5, [SPP2-ARL4C], NPY1R, [LINC00911-FLRT2], [CDK12-NEUROD2], and STARD3 for serum triglycerides (TG); TCN2 for waist circumference; and RPS6KA1, CADPS, and [VARS and VWA7] for fasting plasma glucose (FPG). All these genes, except TCN2, were located in regions of runs of homozygosity. Furthermore, imputing untyped genotypes and combining GWA signals from both the study cohorts revealed 70 unique variants from 9 gene loci at GW significant p-values. Among these variants, 63 were associated with HDL-C, 1 with TG, 1 with LDL-C, 3 with SBP, and 2 with each of FPG and DBP. The gene loci included CETP, [INTS10, LPL], and [LOC105377613, LOC105377614] for HDL-C; CSMD1 for elevated FPG levels; [DYRK1A, LOC105372798] and RTN4 for SBP; RTN4 for DBP, BUD13 for TG, and [INTS10, LPL] for LDL-C. CONCLUSION: Many of the variant associations identified were not previously reported in global GWAS studies. Hence, these studies provide new insights into the Arab specific etiology of the metabolic syndrome and might help in devising more effective therapeutic approaches for Arab population.TAUSTAA: Lähi-idän alueen erittäin sisäsiittoinen arabiväestö on kokenut monimutkaisen aineenvaihduntaterveyskatastrofin siitä lähtien, kun se on omaksunut elämäntapojen muutoksen öljyn jälkeisellä rikkaalla aikakaudella.Geneettisten riskivarianttien luonnehdinta genomin laajuisen (GW) proffiloinnin avulla geneettisistä vaihteluista ja aineenvaihdunnan terveyden fenotyypeistä tässä populaatiossa auttaisi ymmärtämään väestökohtaista sairausetiologiaa. TAVOITTEET:Tutkimuksessa käytettiin yhden nukleotidin variaation assosiaatioanalyysiä, jonka avulla 1) selvitettiin varianttien yhteyttä 13 metaboliseen muuttujaan koko genomin kattavassa genotyyppidatassa, 2) tunnistettiin homotsygoottisia jaksoja sisältäviä alueita ja tarkasteltiin kyseisillä alueilla esiintyvien varianttien yhteyttä metabolisiin muuttujiin, 3) imputoitiin tyypittämättömiä variantteja ja arvioitiin niiden yhteyttä kvantitatiivisiin metabolisiin muuttujiin arabiväestössä. AINEISTO JA MENETELMÄT: Tutkimusaineisto koostui kahdesta kohorttiaineistosta, Kuwait Obesity Genetics Project (KOGP) ja Kuwait Diabetes Epidemiology Program (KDEP). Kohortit koostuivat vuonna 1965 (genotyypillä Illumina HumanCardio-MetaboChip -ryhmän tai TaqMan Assayn avulla) ja 1350 Kuwaitin arabialaisasukkaalla (genotyyppi Illumina HumanOmniExpress -taulukolla). Vastaavat GW -varianttitiedot saatettiin laadunvalvontatoimenpiteisiin ja niitä käytettiin analysoimaan variantteja, jotka liittyivät 13 eri kvantitatiiviseen ominaisuuteen. TULOKSET: Koko genomin genotyypitykseen ja/tai imputointiin perustuvassa varianttien assosiaatiotutkimuksessa löydettiin useita metabolisiin muuttujiin vaikuttavia variantteja. Pelkkiä genotyypitettyjä variantteja käyttämällä tunnistettiin seuraavien geenien riskivariantit, joiden p-arvot olivat tilastollisesti merkitseviä koko genomin kattavassa tutkimuksessa (P ≤ 5E-08): RPS6KA1, LAD1, Or5v1, [CTTNBP2-LSM8], PGAP3, [RP11-191L9.4-CERK], ST6GALNAC5, [SPP2-ARL4C], NPY1R, [LINC00911-FLRT2], [CDK12-NEUROD2] ja STARD3 seerumin triglyseridien (TG); TCN2 vyötärönympäryksen; sekä RPS6KA1, CADPS ja [VARS ja VWA7:n ylävirta-alueen 2 Kb] plasman paastoglukoosin (FPG)osalta. Kaikki kyseiset geenit, lukuun ottamatta geeniä TCN2, paikallistettiin alueille, joilla esiintyi homotsygoottisia jaksoja. Lisäksi imputoimalla tyypittämättömiä genotyyppejä sekä yhdistämällä molemmista tutkimuskohorteista genominlaajuisessa assosiaatiotutkimuksessa (GWA) saatuja signaaleja löydettiin 70 uniikkia varianttia 9 lokuksesta (7 genomialueelta) p-arvojen ollessa tilastollisesti merkitseviä koko genomin kattavassa tutkimuksessa. Näistä varianteista 63 assosioitui HDL-kolesteroliin (HDL-C), 1 TG:iin, 1 LDL-kolesteroliin (LDL-C), 3 systoliseen verenpaineeseen, 2 FPG:iin sekä 2 diastoliseen verenpaineeseen. Geenilokukset olivat CEPT [INTS10, LPL] ja [LOC105377613, LOC105377614] HDL-C:n, CSMD1 kohonneiden FPG-tasojen, [DYRK1A, LOC105372798] ja RTN4 systolisen verenpaineen, RTN4 diastolisen verenpaineen, BUD13 TG:n sekä [INTS10, LPL] LDL-C:n osalta. PÄÄTELMÄ: Monia tunnistettuja varianttiyhdistelmiä ei aiemmin raportoitu maailmanlaajuisissa GWAS -tutkimuksissa. Siksi nämä tutkimukset antavat uutta tietoa metabolisen oireyhtymän arabispesifisestä etiologiasta ja voivat auttaa kehittämään tehokkaampia terapeuttisia lähestymistapoja arabiväestölle