Rare copy-number variants as modulators of common disease susceptibility.

16p11.2 16p13.11 CNV Common diseases GWAS Genomic disorders Pleiotropy Structural variation Time-to-event analysis

Journal

Genome medicine
ISSN: 1756-994X
Titre abrégé: Genome Med
Pays: England
ID NLM: 101475844

Informations de publication

Date de publication:
08 Jan 2024
Historique:
received: 17 07 2023
accepted: 27 11 2023
medline: 8 1 2024
pubmed: 8 1 2024
entrez: 7 1 2024
Statut: epublish

Résumé

Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Sections du résumé

BACKGROUND BACKGROUND
Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.
METHODS METHODS
Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.
RESULTS RESULTS
We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.
CONCLUSIONS CONCLUSIONS
Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Identifiants

pubmed: 38185688
doi: 10.1186/s13073-023-01265-5
pii: 10.1186/s13073-023-01265-5
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5

Subventions

Organisme : Swiss National Science Foundation
ID : 31003A_182632
Pays : Switzerland
Organisme : Swiss National Science Foundation
ID : 310030_189147
Pays : Switzerland

Investigateurs

Tõnu Esko (T)
Andres Metspalu (A)
Lili Milani (L)
Mari Nelis (M)

Informations de copyright

© 2023. The Author(s).

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Auteurs

Chiara Auwerx (C)

Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland. chiara.auwerx@unil.ch.
Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland. chiara.auwerx@unil.ch.
Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland. chiara.auwerx@unil.ch.
University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland. chiara.auwerx@unil.ch.

Maarja Jõeloo (M)

Institute of Molecular and Cell Biology, University of Tartu, 51010, Tartu, Estonia.
Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.

Marie C Sadler (MC)

Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.

Nicolò Tesio (N)

Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.

Sven Ojavee (S)

Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.

Charlie J Clark (CJ)

Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.

Reedik Mägi (R)

Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.

Alexandre Reymond (A)

Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland. alexandre.reymond@unil.ch.

Zoltán Kutalik (Z)

Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland. zoltan.kutalik@unil.ch.
Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland. zoltan.kutalik@unil.ch.
University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland. zoltan.kutalik@unil.ch.

Classifications MeSH