DESCRIPTION:

List of positional candidate genes after correcting for multiple testing and controlling the false discovery rate from genome wide association studies (GWAS) retrieved from the NHGRI-EBI Catalog of published genome-wide association studies (http://www.ebi.ac.uk/gwas/). The disease/trait examined in this study, as reported by the authors, was Metabolic traits. The EFO term inflammatory response was annotated to this set after curation by NHGRI-EBI. Intergenic SNPS were mapped to both the upstream and downstream gene. P-value uploaded. This gene set was generated using gwas2gs v. 0.1.8 and the GWAS Catalog v. 1.0.1.

LABEL:

GWAS: inflammatory response

SCORE TYPE:

P-Value

THRESHOLD:

<= 0.05

GENES IN THRESHOLD:

7

DATE ADDED:

2017-05-02

DATE UPDATED:

2024-10-22

SPECIES:

AUTHORS:

C Sabatti, SK Service, AL Hartikainen, A Pouta, S Ripatti, J Brodsky, CG Jones, NA Zaitlen, T Varilo, M Kaakinen, U Sovio, A Ruokonen, J Laitinen, E Jakkula, L Coin, C Hoggart, A Collins, H Turunen, S Gabriel, P Elliot, MI McCarthy, MJ Daly, MR Järvelin, NB Freimer, L Peltonen

TITLE:

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

JOURNAL:

Nature genetics Jan 2009, Vol 41, pp. 35-46

ABSTRACT:

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. PUBMED: 19060910
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