---
_id: '12142'
abstract:
- lang: eng
  text: Theory for liability-scale models of the underlying genetic basis of complex
    disease provides an important way to interpret, compare, and understand results
    generated from biological studies. In particular, through estimation of the liability-scale
    heritability (LSH), liability models facilitate an understanding and comparison
    of the relative importance of genetic and environmental risk factors that shape
    different clinically important disease outcomes. Increasingly, large-scale biobank
    studies that link genetic information to electronic health records, containing
    hundreds of disease diagnosis indicators that mostly occur infrequently within
    the sample, are becoming available. Here, we propose an extension of the existing
    liability-scale model theory suitable for estimating LSH in biobank studies of
    low-prevalence disease. In a simulation study, we find that our derived expression
    yields lower mean square error (MSE) and is less sensitive to prevalence misspecification
    as compared to previous transformations for diseases with  =< 2% population prevalence
    and LSH of =< 0.45, especially if the biobank sample prevalence is less than that
    of the wider population. Applying our expression to 13 diagnostic outcomes of  =<
    3% prevalence in the UK Biobank study revealed important differences in LSH obtained
    from the different theoretical expressions that impact the conclusions made when
    comparing LSH across disease outcomes. This demonstrates the importance of careful
    consideration for estimation and prediction of low-prevalence disease outcomes
    and facilitates improved inference of the underlying genetic basis of  =< 2% population
    prevalence diseases, especially where biobank sample ascertainment results in
    a healthier sample population.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: This project was funded by an SNSF Eccellenza grant to M.R.R. (PCEGP3-181181),
  core funding from the Institute of Science and Technology Austria, and core funding
  from the Department of Computational Biology of the University of Lausanne. Z.K.
  was funded by the Swiss National Science Foundation (310030-189147). This research
  was supported by the Scientific Service Units (SSUs) of IST Austria through resources
  provided by Scientific Computing (SciComp). We would like to thank the participants
  of the UK Biobank.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Sven E.
  full_name: Ojavee, Sven E.
  last_name: Ojavee
- first_name: Zoltan
  full_name: Kutalik, Zoltan
  last_name: Kutalik
- first_name: Matthew Richard
  full_name: Robinson, Matthew Richard
  id: E5D42276-F5DA-11E9-8E24-6303E6697425
  last_name: Robinson
  orcid: 0000-0001-8982-8813
citation:
  ama: Ojavee SE, Kutalik Z, Robinson MR. Liability-scale heritability estimation
    for biobank studies of low-prevalence disease. <i>The American Journal of Human
    Genetics</i>. 2022;109(11):2009-2017. doi:<a href="https://doi.org/10.1016/j.ajhg.2022.09.011">10.1016/j.ajhg.2022.09.011</a>
  apa: Ojavee, S. E., Kutalik, Z., &#38; Robinson, M. R. (2022). Liability-scale heritability
    estimation for biobank studies of low-prevalence disease. <i>The American Journal
    of Human Genetics</i>. Elsevier. <a href="https://doi.org/10.1016/j.ajhg.2022.09.011">https://doi.org/10.1016/j.ajhg.2022.09.011</a>
  chicago: Ojavee, Sven E., Zoltan Kutalik, and Matthew Richard Robinson. “Liability-Scale
    Heritability Estimation for Biobank Studies of Low-Prevalence Disease.” <i>The
    American Journal of Human Genetics</i>. Elsevier, 2022. <a href="https://doi.org/10.1016/j.ajhg.2022.09.011">https://doi.org/10.1016/j.ajhg.2022.09.011</a>.
  ieee: S. E. Ojavee, Z. Kutalik, and M. R. Robinson, “Liability-scale heritability
    estimation for biobank studies of low-prevalence disease,” <i>The American Journal
    of Human Genetics</i>, vol. 109, no. 11. Elsevier, pp. 2009–2017, 2022.
  ista: Ojavee SE, Kutalik Z, Robinson MR. 2022. Liability-scale heritability estimation
    for biobank studies of low-prevalence disease. The American Journal of Human Genetics.
    109(11), 2009–2017.
  mla: Ojavee, Sven E., et al. “Liability-Scale Heritability Estimation for Biobank
    Studies of Low-Prevalence Disease.” <i>The American Journal of Human Genetics</i>,
    vol. 109, no. 11, Elsevier, 2022, pp. 2009–17, doi:<a href="https://doi.org/10.1016/j.ajhg.2022.09.011">10.1016/j.ajhg.2022.09.011</a>.
  short: S.E. Ojavee, Z. Kutalik, M.R. Robinson, The American Journal of Human Genetics
    109 (2022) 2009–2017.
corr_author: '1'
date_created: 2023-01-12T12:05:28Z
date_published: 2022-11-03T00:00:00Z
date_updated: 2025-06-11T13:55:19Z
day: '03'
ddc:
- '570'
department:
- _id: MaRo
doi: 10.1016/j.ajhg.2022.09.011
external_id:
  isi:
  - '000898683500006'
  pmid:
  - '36265482'
file:
- access_level: open_access
  checksum: 4cd7f12bfe21a8237bb095eedfa26361
  content_type: application/pdf
  creator: dernst
  date_created: 2023-01-24T09:23:01Z
  date_updated: 2023-01-24T09:23:01Z
  file_id: '12353'
  file_name: 2022_AJHG_Ojavee.pdf
  file_size: 705195
  relation: main_file
  success: 1
file_date_updated: 2023-01-24T09:23:01Z
has_accepted_license: '1'
intvolume: '       109'
isi: 1
issue: '11'
keyword:
- Genetics (clinical)
- Genetics
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 2009-2017
pmid: 1
project:
- _id: 9B8D11D6-BA93-11EA-9121-9846C619BF3A
  grant_number: PCEGP3_181181
  name: Improving estimation and prediction of common complex disease risk
publication: The American Journal of Human Genetics
publication_identifier:
  issn:
  - 0002-9297
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Liability-scale heritability estimation for biobank studies of low-prevalence
  disease
tmp:
  image: /images/cc_by_nc_nd.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
    (CC BY-NC-ND 4.0)
  short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 109
year: '2022'
...