A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases

Buhm Han, Jennie G. Pouget, Kamil Slowikowski, Eli Stahl, Cue Hyunkyu Lee, Dorothee Diogo, Xinli Hu, Yu Rang Park, Eunji Kim, Peter K. Gregersen, Solbritt Rantapää Dahlqvist, Jane Worthington, Javier Martin, Steve Eyre, Lars Klareskog, Tom Huizinga, Wei Min Chen, Suna Onengut-Gumuscu, Stephen S. Rich, Naomi R. WraySoumya Raychaudhuri

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P < 1 × 10 â '4) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P < 1 × 10 â '3). This sharing was not explained by subgroup heterogeneity (corrected P BUHMBOX > 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P < 1 × 10 â '9) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (P BUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P < 1 × 10 â '4) that was not explained by subgroup heterogeneity (P BUHMBOX = 0.28; 9,238 MDD cases).

Original languageEnglish
Pages (from-to)803-810
Number of pages8
JournalNature Genetics
Volume48
Issue number7
DOIs
StatePublished - 1 Jul 2016
Externally publishedYes

Fingerprint

Dive into the research topics of 'A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases'. Together they form a unique fingerprint.

Cite this