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Pleiotropic genes for metabolic syndrome and inflammation.

Authors :
Kraja, Aldi T
Kraja, Aldi T
Chasman, Daniel I
North, Kari E
Reiner, Alexander P
Yanek, Lisa R
Kilpeläinen, Tuomas O
Smith, Jennifer A
Dehghan, Abbas
Dupuis, Josée
Johnson, Andrew D
Feitosa, Mary F
Tekola-Ayele, Fasil
Chu, Audrey Y
Nolte, Ilja M
Dastani, Zari
Morris, Andrew
Pendergrass, Sarah A
Sun, Yan V
Ritchie, Marylyn D
Vaez, Ahmad
Lin, Honghuang
Ligthart, Symen
Marullo, Letizia
Rohde, Rebecca
Shao, Yaming
Ziegler, Mark A
Im, Hae Kyung
Cross Consortia Pleiotropy Group
Cohorts for Heart and
Aging Research in Genetic Epidemiology
Genetic Investigation of Anthropometric Traits Consortium
Global Lipids Genetics Consortium
Meta-Analyses of Glucose
Insulin-related traits Consortium
Global BPgen Consortium
ADIPOGen Consortium
Women's Genome Health Study
Howard University Family Study
Schnabel, Renate B
Jørgensen, Torben
Jørgensen, Marit E
Hansen, Torben
Pedersen, Oluf
Stolk, Ronald P
Snieder, Harold
Hofman, Albert
Uitterlinden, Andre G
Franco, Oscar H
Ikram, M Arfan
Richards, J Brent
Rotimi, Charles
Wilson, James G
Lange, Leslie
Ganesh, Santhi K
Nalls, Mike
Rasmussen-Torvik, Laura J
Pankow, James S
Coresh, Josef
Tang, Weihong
Linda Kao, WH
Boerwinkle, Eric
Morrison, Alanna C
Ridker, Paul M
Becker, Diane M
Rotter, Jerome I
Kardia, Sharon LR
Loos, Ruth JF
Larson, Martin G
Hsu, Yi-Hsiang
Province, Michael A
Tracy, Russell
Voight, Benjamin F
Vaidya, Dhananjay
O'Donnell, Christopher J
Benjamin, Emelia J
Alizadeh, Behrooz Z
Prokopenko, Inga
Meigs, James B
Borecki, Ingrid B
Kraja, Aldi T
Kraja, Aldi T
Chasman, Daniel I
North, Kari E
Reiner, Alexander P
Yanek, Lisa R
Kilpeläinen, Tuomas O
Smith, Jennifer A
Dehghan, Abbas
Dupuis, Josée
Johnson, Andrew D
Feitosa, Mary F
Tekola-Ayele, Fasil
Chu, Audrey Y
Nolte, Ilja M
Dastani, Zari
Morris, Andrew
Pendergrass, Sarah A
Sun, Yan V
Ritchie, Marylyn D
Vaez, Ahmad
Lin, Honghuang
Ligthart, Symen
Marullo, Letizia
Rohde, Rebecca
Shao, Yaming
Ziegler, Mark A
Im, Hae Kyung
Cross Consortia Pleiotropy Group
Cohorts for Heart and
Aging Research in Genetic Epidemiology
Genetic Investigation of Anthropometric Traits Consortium
Global Lipids Genetics Consortium
Meta-Analyses of Glucose
Insulin-related traits Consortium
Global BPgen Consortium
ADIPOGen Consortium
Women's Genome Health Study
Howard University Family Study
Schnabel, Renate B
Jørgensen, Torben
Jørgensen, Marit E
Hansen, Torben
Pedersen, Oluf
Stolk, Ronald P
Snieder, Harold
Hofman, Albert
Uitterlinden, Andre G
Franco, Oscar H
Ikram, M Arfan
Richards, J Brent
Rotimi, Charles
Wilson, James G
Lange, Leslie
Ganesh, Santhi K
Nalls, Mike
Rasmussen-Torvik, Laura J
Pankow, James S
Coresh, Josef
Tang, Weihong
Linda Kao, WH
Boerwinkle, Eric
Morrison, Alanna C
Ridker, Paul M
Becker, Diane M
Rotter, Jerome I
Kardia, Sharon LR
Loos, Ruth JF
Larson, Martin G
Hsu, Yi-Hsiang
Province, Michael A
Tracy, Russell
Voight, Benjamin F
Vaidya, Dhananjay
O'Donnell, Christopher J
Benjamin, Emelia J
Alizadeh, Behrooz Z
Prokopenko, Inga
Meigs, James B
Borecki, Ingrid B
Source :
Molecular genetics and metabolism; vol 112, iss 4, 317-338; 1096-7192
Publication Year :
2014

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

Details

Database :
OAIster
Journal :
Molecular genetics and metabolism; vol 112, iss 4, 317-338; 1096-7192
Notes :
application/pdf, Molecular genetics and metabolism vol 112, iss 4, 317-338 1096-7192
Publication Type :
Electronic Resource
Accession number :
edsoai.on1391567287
Document Type :
Electronic Resource