Narrow-sense heritability estimation of complex traits using identity-by-descent information
Authors: Evans Luke M. , Tahmasbi Rasool , Jones Matthew , Vrieze Scott I. , Abecasis Gonçalo R. , Das Sayantan , Bjelland Doug W. , deCandia Teresa R. ,   - Haplotype Reference Consortium, Abecasis Gonçalo , Altshuler David , Anderson Carl A , Angius Andrea , Barrett Jeffrey C , Berndt Sonja , Boehnke Michael , Boomsma Dorrett , Branham Kari , Breen Gerome , Brummett Chad M , Busonero Fabio , Campbell Harry , Campbell Peter , Chan Andrew , Chen Sai , Chew Emily , Cocca Massimiliano , Collins Francis S , Corbin Laura J , Cucca Francesco , Danecek Petr , Das Sayantan , de Bakker Paul I W , Dedoussis George , Dekker Annelot , Delaneau Olivier , Dorr Marcus , Durbin Richard , Farmaki Aliki-Eleni , Ferrucci Luigi , Forer Lukas , Fraser Ross M , Frayling Timothy , Fuchsberger Christian , Gabriel Stacey , Gandin Ilaria , Gasparini Paolo , Gillies Christopher E , Gilly Arthur , Groop Leif , Harrison Tabitha , Hattersley Andrew , Holmen Oddgeir L , Hveem Kristian , Iacono William , Joshi Amit , Kang Hyun Min , Khalili Hamed , Kooperberg Charles , Koskinen Seppo , Kretzler Matthias , Kretzschmar Warren , Kwong Alan , Lee James C , Levy Shawn , Luo Yang , Mahajan Anubha , Marchini Jonathan , McCarroll Steven , McCarthy Mark I , McCarthy Shane , McGue Matt , McInnis Melvin , Meitinger Thomas , Melzer David , Mezzavilla Massimo , Min Josine L , Mohlke Karen L , Myers Richard M , Nauck Matthias , Nickerson Deborah , Palotie Aarno , Pato Carlos , Pato Michele , Peters Ulrike , Pirastu Nicola , Rheenen Wouter Van , Richards J Brent , Ripatti Samuli , Sala Cinzia , Salomaa Veikko , Sampson Matthew G , Schlessinger David , Schoen Robert E , Schoenherr Sebastian , Scott Laura J , Sharp Kevin , Sidore Carlo , Slagboom P Eline , Small Kerrin , Smith George Davey , Soranzo Nicole , Spector Timothy , Stambolian Dwight , Swaroop Anand , Swertz Morris A , Teumer Alexander , Timpson Nicholas , Toniolo Daniela , Traglia Michela , Tuke Marcus , Tuomilehto Jaakko , den Berg Leonard H Van , van Duijn Cornelia M , Veldink Jan , Vincent John B , Volker Uwe , Vrieze Scott , Walter Klaudia , Wijmenga Cisca , Willer Cristen , Wilson James F , Wood Andrew R , Zeggini Eleftheria , Zhang He , Yang Jian , Goddard Michael E. , Visscher Peter M. , Keller Matthew C. 
Published: July 2017

ABSTRACTHeritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly-tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). IBD-based heritability estimates were unbiased when using unrelated individuals, even for traits with extremely rare CVs, but stratification led to strong biases in IBD-based heritability estimates with poor precision. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied successfully to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in this real data that were not predicted from our simulation, suggesting that more work may be required to understand factors that influence IBD-based estimates.