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Pleiotropic genes for metabolic syndrome and inflammation.


ABSTRACT: Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.

SUBMITTER: Kraja AT 

PROVIDER: S-EPMC4122618 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Pleiotropic genes for metabolic syndrome and inflammation.

Kraja Aldi T AT   Chasman Daniel I DI   North Kari E KE   Reiner Alexander P AP   Yanek Lisa R LR   Kilpeläinen Tuomas O TO   Smith Jennifer A JA   Dehghan Abbas A   Dupuis Josée J   Johnson Andrew D AD   Feitosa Mary F MF   Tekola-Ayele Fasil F   Chu Audrey Y AY   Nolte Ilja M IM   Dastani Zari Z   Morris Andrew A   Pendergrass Sarah A SA   Sun Yan V YV   Ritchie Marylyn D MD   Vaez Ahmad A   Lin Honghuang H   Ligthart Symen S   Marullo Letizia L   Rohde Rebecca R   Shao Yaming Y   Ziegler Mark A MA   Im Hae Kyung HK   Schnabel Renate B RB   Jørgensen Torben T   Jørgensen Marit E ME   Hansen Torben T   Pedersen Oluf O   Stolk Ronald P RP   Snieder Harold H   Hofman Albert A   Uitterlinden Andre G AG   Franco Oscar H OH   Ikram M Arfan MA   Richards J Brent JB   Rotimi Charles C   Wilson James G JG   Lange Leslie L   Ganesh Santhi K SK   Nalls Mike M   Rasmussen-Torvik Laura J LJ   Pankow James S JS   Coresh Josef J   Tang Weihong W   Linda Kao W H WH   Boerwinkle Eric E   Morrison Alanna C AC   Ridker Paul M PM   Becker Diane M DM   Rotter Jerome I JI   Kardia Sharon L R SL   Loos Ruth J F RJ   Larson Martin G MG   Hsu Yi-Hsiang YH   Province Michael A MA   Tracy Russell R   Voight Benjamin F BF   Vaidya Dhananjay D   O'Donnell Christopher J CJ   Benjamin Emelia J EJ   Alizadeh Behrooz Z BZ   Prokopenko Inga I   Meigs James B JB   Borecki Ingrid B IB  

Molecular genetics and metabolism 20140509 4


Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic  ...[more]

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