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Rare variant contribution to human disease in 281,104 UK Biobank exomes

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Wang, Quanli, Dhindsa, Ryan S., Carss, Keren, Harper, Andrew R., Nag, Abhishek, Tachmazidou, Ioanna, Vitsios, Dimitrios, Deevi, Sri V. V. +52 more·2021·Nature
DOI 10.1038/s41586-021-03855-yPMC PMC8458098
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Abstract

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits 1,2 . Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene–phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene–phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).

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  • 13 of the 14 cis-CDS pQTLs (93%) in five Olink proteins independently measured via immunoturbidimetric assays replicated in the biomarker ExWAS (P ≤ 1 × 10−8), with effect sizes showing complete directional concordance.

    “In total, 13 of the 14 cis-CDS pQTLs (93%) replicated in the biomarker ExWAS (P ≤ 1 × 10−8), with effect sizes showing complete directional concordance (Supplementary Table 6).”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [11]

    The Variant-level associations section describes an ExWAS that included quantitative phenotypes, and the Methods > ExWAS analyses section explains its significance threshold (page numbers unavailable). These passages support identifying the cited work as an ExWAS, but our copy does not report that 13 of 14 cis-CDS pQTLs replicated, the five Olink proteins, immunoturbidimetric measurements, or complete directional concordance. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • The HBB-SLC16A1 association likely reflects the enrichment of HBB PTVs in individuals of South Asian ancestries.

    “This likely reflects the enrichment of HBB PTVs in individuals of South Asian ancestries, as observed in our UKB PheWAS11.”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [11]

    The Pan-ancestry collapsing analysis reports a significant association between HBB protein-truncating variants and thalassaemia in participants of South Asian ancestry. It does not report that HBB PTVs are enriched in that group relative to other ancestries or connect them to an HBB–SLC16A1 association, so it supports only part of the attributed explanation. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • There were no significant associations between these three NLRC4 variants and clinically relevant phenotypes in the published PheWAS of 470,000 UKB exomes.

    “Interestingly, there were no significant associations between these three variants and clinically relevant phenotypes in our published PheWAS of 470,000 UKB exomes (https://azphewas.com)11, suggesting that pharmacologic inhibition of NLRC4 may be safe.”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [11]

    The Main section describes a UK Biobank exome PheWAS, and the Discussion says its results are available at azphewas.com. But the paper reports 281,104 participants, not 470,000, and our copy does not report whether the three NLRC4 variants had significant associations with clinically relevant phenotypes (searched: NLRC4). (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Using an n-of-one permutation analysis, P ≤ 1 × 10−8 was identified as an appropriate P value threshold.

    “Using an n-of-one permutation analysis as previously described11, we identified P ≤ 1 × 10−8 as an appropriate P value threshold (Methods and Supplementary Table 3).”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [11]

  • Ten QV models introduced in the previous UKB PheWAS were used, including one synonymous variant model as an empirical negative control.

    “Here, we used ten QV models introduced in our previous UKB phenome-wide association study (PheWAS), including one synonymous variant model as an empirical negative control11 (Extended Data Table 1; www.azphewas.com).”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [11]

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Authors
Wang, Q., Dhindsa, R. S., Carss, K., Harper, A. R., Nag, A., Tachmazidou, I., Vitsios, D., Deevi, S. V. V., Mackay, A., Muthas, D., Hühn, M., Monkley, S., Olsson, H., Initiative, A. G., Angermann, B. R., Artzi, R., Barrett, C., Belvisi, M., Bohlooly-Y, M., Burren, O., Buvall, L., Challis, B., Cameron-Christie, S., Cohen, S., Davis, A., Danielson, R. F., Dougherty, B., Georgi, B., Ghazoui, Z., Hansen, P. B. L., Hu, F., Jeznach, M., Jiang, X., Kumar, C., Lai, Z., Lassi, G., Lewis, S. H., Linghu, B., Lythgow, K., Maccallum, P., Martins, C., Matakidou, A., Michaëlsson, E., Moosmang, S., O’Dell, S., Ohne, Y., Okae, J., O’Neill, A., Paul, D. S., Reznichenko, A., Snowden, M. A., Walentinsson, A., Zeron, J., Pangalos, M. N., Wasilewski, S., Smith, K. R., March, R., Platt, A., Haefliger, C., & Petrovski, S.
Affiliations
  • AstraZeneca (United States) (US)
  • AstraZeneca (United Kingdom) (GB)
  • AstraZeneca (Sweden) (SE)
  • The University of Melbourne (AU)
Corresponding author
Petrovski, Slavé
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2021-08-10
Volume
597
Issue
7877
Pages
527-532
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-021-03855-y
PMC
PMC8458098
OpenAlex
W3191451220
Cited by
604
References
3
Citations by year
2026: 138 · 2025: 162 · 2024: 113 · 2023: 99 · 2022: 80 · 2021: 11
FWCI
44.44
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo (cc-by)
Funders
  • Bristol-Myers Squibb
  • Pfizer
  • AstraZeneca
  • Biogen
  • Alnylam Pharmaceuticals
  • Regeneron Pharmaceuticals
  • Medical Research Council (MC_PC_17228)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
rare variants, genotype-phenotype correlation, common diseases, allelic heterogeneity, therapeutic target, UK Biobank, exome sequencing, binary traits, quantitative traits
MeSH terms
Exome Sequencing, Adult, Aged, Disease, Female, United Kingdom, Humans, Male, Middle Aged, Phenotype, Proteins, Genetic Variation, Biological Specimen Banks, Databases, Genetic, Genome-Wide Association Study, Exome

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