@article{7729, abstract = {Quantifying the effects of inbreeding is critical to characterizing the genetic architecture of complex traits. This study highlights through theory and simulations the strengths and shortcomings of three SNP-based inbreeding measures commonly used to estimate inbreeding depression (ID). We demonstrate that heterogeneity in linkage disequilibrium (LD) between causal variants and SNPs biases ID estimates, and we develop an approach to correct this bias using LD and minor allele frequency stratified inference (LDMS). We quantified ID in 25 traits measured in ∼140,000 participants of the UK Biobank, using LDMS, and confirmed previously published ID for 4 traits. We find unique evidence of ID for handgrip strength, waist/hip ratio, and visual and auditory acuity (ID between −2.3 and −5.2 phenotypic SDs for complete inbreeding; P<0.001). Our results illustrate that a careful choice of the measure of inbreeding combined with LDMS stratification improves both detection and quantification of ID using SNP data.}, author = {Yengo, Loic and Zhu, Zhihong and Wray, Naomi R. and Weir, Bruce S. and Yang, Jian and Robinson, Matthew Richard and Visscher, Peter M.}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences}, number = {32}, pages = {8602--8607}, publisher = {Proceedings of the National Academy of Sciences}, title = {{Detection and quantification of inbreeding depression for complex traits from SNP data}}, doi = {10.1073/pnas.1621096114}, volume = {114}, year = {2017}, }