Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,458 bioRxiv papers from 307,648 authors.

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

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

Posted 17 Jul 2017
bioRxiv DOI: 10.1101/164848 (published DOI: 10.1038/s41437-018-0067-0)

Heritability 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.

Download data

  • Downloaded 939 times
  • Download rankings, all-time:
    • Site-wide: 9,167 out of 70,458
    • In genetics: 683 out of 3,906
  • Year to date:
    • Site-wide: 37,413 out of 70,458
  • Since beginning of last month:
    • Site-wide: 26,453 out of 70,458

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide

PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)

News