Whole-Genome Pathway Analysis on 132,497 Individuals Identifies Novel Gene-Sets Associated with Body Mass Index

Matthew A Simonson,Matthew B Mcqueen,Matthew C Keller,Peristera Paschou

doi:10.1371/journal.pone.0078546

Matthew A Simonson, Matthew B Mcqueen + Show 2 more

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https://doi.org/10.1371/journal.pone.0078546

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Journal: PloS one	Publication Date: Jan 31, 2014
Citations: 4	License type: CC BY 4.0

Affiliation: University of Colorado Boulder, Mayo Clinic

Abstract

Whole genome pathway analysis is a powerful tool for the exploration of the combined effects of gene-sets within biological pathways. This study applied Interval Based Enrichment Analysis (INRICH) to perform whole-genome pathway analysis of body-mass index (BMI). We used a discovery set composed of summary statistics from a meta-analysis of 123,865 subjects performed by the GIANT Consortium, and an independent sample of 8,632 subjects to assess replication of significant pathways. We examined SNPs within nominally significant pathways using linear mixed models to estimate their contribution to overall BMI heritability. Six pathways replicated as having significant enrichment for association after correcting for multiple testing, including the previously unknown relationships between BMI and the Reactome regulation of ornithine decarboxylase pathway, the KEGG lysosome pathway, and the Reactome stabilization of P53 pathway. Two non-overlapping sets of genes emerged from the six significant pathways. The clustering of shared genes based on previously identified protein-protein interactions listed in PubMed and OMIM supported the relatively independent biological effects of these two gene-sets. We estimate that the SNPs located in examined pathways explain ∼20% of the heritability for BMI that is tagged by common SNPs (3.35% of the 16.93% total).

Highlights

Obesity greatly increases risk for many forms of pathology, including vascular disease, multiple forms of cancer, heart disease, and other serious health problems [1,2]
We performed whole-genome pathway analysis using Interval Based Enrichment Analysis (INRICH) to identify pathways that were significantly enriched for SNP associations in the GIANT discovery set
The clusters were highly concordant with the gene overlap we identified between pathways, as well as the division between novel pathways identified in this analysis and the pathways identified in the candidate pathway analysis performed by the GIANT Consortium (Figure 1)

Summary

Introduction

Obesity greatly increases risk for many forms of pathology, including vascular disease, multiple forms of cancer, heart disease, and other serious health problems [1,2]. A greater understanding of the biology underlying obesity could have widespread effects on public health. This has led to large-scale efforts to understand the genetic architecture of obesity through the application of genome-wide association studies and complementary methods, such as pathway analysis [3,4,5,6,7]. GIANT conducted a metaanalysis using data from 46 studies including 123,865 subjects and identified 42 independent loci associated with BMI at P,561026. In a joint analysis of the first and second stage 32 SNPs were significantly associated with BMI at p,561028, increasing the number of loci robustly associated with BMI from 10 to 32 [3,4,5,6,7,8]. The GIANT study examined biological pathways that contain one or more genes located within 300 kb of the 32 confirmed BMI SNPs in an attempt to discover potentially new pathways associated with BMI, and to test whether the 32 confirmed association’s clustered near genes with biological relevance (Table 1) [8]

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