Genome-wide association analysis of metabolic traits in a birth cohort from a founder population

By Chiara Sabatti, S. Service, A. Hartikainen, A. Pouta, Samuli Ripatti, J. Brodsky, Chris Jones, Noah A. Zaitlen, T. Varilo, M. Kaakinen and 15 more. Nature Genetics, 2008

824 citations recorded by the source corpus.

Genome-wide association studies (GWAS) of longitudinal birth cohorts enable joint investigation of environmental and genetic influences on complex traits. We report GWAS results for nine quantitative metabolic traits (triglycerides, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, body mass index, and systolic and diastolic blood pressure) in the Northern Finland Birth Cohort 1966 (NFBC1966), drawn from the most genetically isolated Finnish regions. We replicate most previously reported associations for these traits and identify nine new associations, several of which highlight genes with metabolic functions: high-density lipoprotein with NR1H3 (LXRA), low-density lipoprotein with AR and FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1. Two of these new associations emerged after adjustment of results for body mass index. Gene–environment interaction analyses suggested additional associations, which will require validation in larger samples. The currently identified loci, together with quantified environmental exposures, explain little of the trait variation in NFBC1966. The association observed between low-density lipoprotein and an infrequent variant in AR suggests the potential of such a cohort for identifying associations with both common, low-impact and rarer, high-impact quantitative trait loci.

Subfields: Endocrinology, Diabetes and Metabolism, Genetics, Pediatrics, Perinatology and Child Health

View Paper: https://www.semanticscholar.org/paper/9e0d8528dcec37861c86ab08f053245b613a06ef

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Citations in the corpus

Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts (2008, background): “5 kb telomeric of MADD and an associated SNP in this gene was reported in the NFBC cohor”
Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies (2013, methodology): “We analyzed two data sets: the Hybrid Mouse Diversity Panel (HMDP) [48] and the Northern Finland Birth Cohort 1966 (NFBC1966) Study [49].”
Variance component model to account for sample structure in genome-wide association studies (2010, positive): “Currently, association studies typically use a combination of these strategies, first identifying close relatives to remove them from analysis, then correcting for broad sample structure using principal components or spatial information and finally correcting for the residual inflation with genomic ”
Implicit Causal Models for Genome-wide Association Studies (2017, positive): “We also apply our model to a real-world GWAS of Northern Finland Birth Cohorts; our model indeed captures real causal relationships—identifying similar SNP s as previous state of the art.”
A genomewide perspective of genetic variation in human metabolism (2009, background): “Three better-powered GWAS with lipid parameters have only recently confirmed this predictio”
An efficient multi-locus mixed model approach for genome-wide association studies in structured populations (2012, positive): “To illustrate the feasibility as well as the utility of MLMM, we applied it to a previously published dataset of metabolic traits in the Northern Finland Birth Cohort (NFBC1966) 31 .”