Lassen F et al., The American Journal of Human Genetics - Meta-analysis of up to 948,690 exome- or whole-genome-sequenced individuals across six biobanks used statistical phasing to infer compound-heterozygous genotypes, increasing detectable bi-allelic damaging genotypes by 19% and identifying 58 significant gene-trait associations, 17 of which show stronger recessive effects. Key terms: recessive genetics, compound heterozygous, biobank meta-analysis, loss-of-function, statistical phasing.

Study Highlights:
The study combined data from UKB, All of Us, 100kGP, Genes & Health, BioMe, and BBJ totaling 948,690 samples and phased rare variants to detect compound-heterozygous genotypes. Phasing increased the number of bi-allelic damaging genotypes by 19% and identified 5,563 genes with bi-allelic pLoF genotypes. Gene-based recessive testing across 41 traits found 58 significant associations after meta-analysis and Cauchy combination, with 17 instances showing stronger recessive than additive effects, including HBB with heart failure and LECT2 with height. The federated, cross-biobank approach improved power and highlighted the value of diverse ancestries for discovering recessive effects.

Conclusion:
Federated meta-analysis across multiple biobanks combined with statistical phasing substantially increases discovery of rare recessive gene-trait associations and expands the catalog of human gene knockouts, demonstrating the importance of phasing and diverse cohorts for recessive-effect discovery.

Music:
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Article title:
Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases

First author:
Lassen F

Journal:
The American Journal of Human Genetics

DOI:
10.1016/j.ajhg.2026.04.005

Reference:
Lassen F.H. et al., 2026. Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases. The American Journal of Human Genetics 113, 1–17. https://doi.org/10.1016/j.ajhg.2026.04.005

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

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QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-05-03.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited transcript sections describing: the role of statistical phasing to identify compound-heterozygous genotypes, the scale across six biobanks (~950k individuals), the rise in bi-allelic genotypes, and key recessive gene–trait associations (HBB, LECT2, ENSG00000267561, PYGM, ODAD1), plus pleiotropy and conditional
- transcript topics: Introduction to human knockouts and biobank-scale data; Compound heterozygosity and the need for phasing; Statistical phasing across six biobanks and study scale; Gene-based recessive associations across 41 traits; Notable associations: HBB with heart failure and lipids; LECT2 with height; ENSG00000267561 with height; BTNL9 association with HDL-C and triglycerides

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 7
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- PHASED approach increased bi-allelic damaging genotypes by 19% (compound-heterozygous and homozygous) across biobanks
- Identified 5,563 genes harboring bi-allelic genotypes; 1,767 additional genes beyond previous studies; total 8,925 unique genes when accounting for overlaps
- CH variants increased testable genes by 8.9% to 1,253 genes (from 1,151)
- 58 significant gene–trait associations identified; 17 likely recessive (based on comparing recessive vs additive signals)
- Notable recessive associations include HBB with heart failure and lipid traits; LECT2 with height; ENSG00000267561 with height; PYGM with AST; ODAD1 with COPD
- Ancestry-diversity contribution: 1,371 of the new knockouts found in non-European ancestries, concentrated in SAS cohorts

QC result: Pass.