Evidence map›Paper›PMID 35973856›Full record

SynthesisBiological psychiatry2023

Pervasive Downward Bias in Estimates of Liability-Scale Heritability in Genome-wide Association Study Meta-analysis: A Simple Solution.

Andrew D Grotzinger, Javier de la Fuente, Florian Privé, Michel G Nivard, Elliot M Tucker-Drob

Abstract readMeta-Analysis
In one paragraph

Synthesis in Biological psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

71 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Article
  8. Genetic architectures of brain-related traits are shaped by strong selective constraints.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Sex-biased Genetic Risk Loci and Causal Brain Proteins in Parkinson's Disease.medRxiv : the preprint server for health sciences · 2026
    Article
  18. Article
  19. APOE*4 risk-modifying genes and drug targets in Alzheimer's disease through cell-type-specific genomic analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  20. Review

11 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andrew D GrotzingerInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Psychology and NeuroscienceUniversity of Colorado Boulder, Boulder, Colorado. Electronic address: Andrew.Grotzinger@colorado.edu.
Javier de la FuenteDepartment of Psychology, University of Texas at Austin, Austin, Texas; Population Research Center, University of Texas at Austin, Austin, Texas.
Florian PrivéDepartment of Economics and Business Economics, National Center for Register-based Research, Aarhus University, Aarhus, Denmark.
Michel G NivardDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Elliot M Tucker-DrobDepartment of Psychology, University of Texas at Austin, Austin, Texas; Population Research Center, University of Texas at Austin, Austin, Texas.

Funding

Population Research CenterR24HD042849 · NICHD · UNIVERSITY OF TEXAS AUSTIN · PI HAYWARD, MARK D. · 2002 to 2016
$8.4M
Program Development and Pilot CoreP30AG066614 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI KAREN L FINGERMAN · 2020 to 2026
$5.2M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
Dissecting the Multivariate Genetic Architecture of Psychiatric DiseasesR01MH120219 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI NIVARD, MICHEL GUILLAUME, TUCKER-DROB, ELLIOT MAX · 2020 to 2024
$3.3M
Large-Scale Genomic Analysis of Aging-Related Cognitive Change Prior to Dementia OnsetRF1AG073593 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2021 to 2021
$2.1M
NIA NIH HHS P30 AG066614NIA NIH HHS RF1 AG073593NICHD NIH HHS P2C HD042849NICHD NIH HHS R24 HD042849NIMH NIH HHS R01 MH120219
6 · The paper itself

Abstract

backgroundSingle nucleotide polymorphism-based heritability is a fundamental quantity in the genetic analysis of complex traits. For case-control phenotypes, for which the continuous distribution of risk in the population is unobserved, observed-scale heritability estimates must be transformed to the more interpretable liability scale. This article describes how the field standard approach incorrectly performs the liability correction in that it does not appropriately account for variation in the proportion of cases across the cohorts comprising the meta-analysis. We propose a simple solution that incorporates cohort-specific ascertainment using the summation of effective sample sizes across cohorts. This solution is applied at the stage of single nucleotide polymorphism-based heritability estimation and does not require generating updated meta-analytic genome-wide association study summary statistics.

methodsWe began by performing a series of simulations to examine the ability of the standard approach and our proposed approach to recapture liability-scale heritability in the population. We went on to examine the differences in estimates obtained from these 2 approaches for real data for 12 major case-control genome-wide association studies of psychiatric and neurologic traits.

resultsWe found that the field standard approach for performing the liability conversion can downwardly bias estimates by as much as approximately 50% in simulation and approximately 30% in real data.

conclusionsPrior estimates of liability-scale heritability for genome-wide association study meta-analysis may be drastically underestimated. To this end, we strongly recommend using our proposed approach of using the sum of effective sample sizes across contributing cohorts to obtain unbiased estimates.

Indexed as

Genome-Wide Association StudyMultifactorial InheritanceCase-Control StudiesPhenotypePolymorphism, Single NucleotideAscertainment correctionBiasCase-control GWASEffective sample sizeLiability-scaleSNP-based heritability

Identifiers

PMID35973856
PMCPMC10066905

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.