4.3 Article

Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility

Journal

G3-GENES GENOMES GENETICS
Volume 12, Issue 1, Pages -

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/g3journal/jkab394

Keywords

GWAS; CFW; replication; Winner's Curse; power; mega-analysis

Funding

  1. National Institutes of Health [R01MH115979, R01GM097737, P50DA037844]
  2. National Science Foundation Graduate Research Fellowship [DGE-1650604]
  3. [1R01MH115979]

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Combining samples in genetic association studies for complex traits can identify more loci, but replication between studies may be challenging. The Winner's Curse effect, study heterogeneity, and trait differences are factors that affect replication, and integrating various information can assign variants to different confidence levels.
Combining samples for genetic association is standard practice in human genetic analysis of complex traits, but is rarely undertaken in rodent genetics. Here, using 23 phenotypes and genotypes from two independent laboratories, we obtained a sample size of 3076 commercially available outbred mice and identified 70 loci, more than double the number of loci identified in the component studies. Fine-mapping in the combined sample reduced the number of likely causal variants, with a median reduction in set size of 51%, and indicated novel gene associations, including Pnpo, Ttll6, and GM11545 with bone mineral density, and Psmb9 with weight. However, replication at a nominal threshold of 0.05 between the two component studies was low, with less than one-third of loci identified in one study replicated in the second. In addition to overestimates in the effect size in the discovery sample (Winner's Curse), we also found that heterogeneity between studies explained the poor replication, but the contribution of these two factors varied among traits. Leveraging these observations, we integrated information about replication rates, study-specific heterogeneity, and Winner's Curse corrected estimates of power to assign variants to one of four confidence levels. Our approach addresses concerns about reproducibility and demonstrates how to obtain robust results from mapping complex traits in any genome-wide association study.

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