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Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder

Trzaskowski, Maciej, Mehta, Divya, Peyrot, Wouter J., Hawkes, David, Davies, Daniel, Howard, David M., Kemper, Kathryn E., Sidorenko, Julia, Maier, Robert, Ripke, Stephan, Mattheisen, Manuel, Baune, Bernhard T., Grabe, Hans J., Heath, Andrew C., Jones, Lisa, Jones, Ian ORCID: https://orcid.org/0000-0001-5821-5889, Madden, Pamela A.F., McIntosh, Andrew M., Breen, Gerome, Lewis, Cathryn M., Børglum, Anders D., Sullivan, Patrick F., Martin, Nicholas G., Kendler, Kenneth S., Levinson, Douglas F. and Wray, Naomi R. 2019. Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 180 (6) , pp. 439-447. 10.1002/ajmg.b.32713

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Abstract

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between‐cohort and between‐sex heterogeneity. First, we used genome‐wide association study (GWAS) summary statistics to investigate between‐cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between‐sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Publisher: Wiley
ISSN: 1552-4841
Date of First Compliant Deposit: 28 February 2019
Date of Acceptance: 4 January 2019
Last Modified: 07 Nov 2023 18:13
URI: https://orca.cardiff.ac.uk/id/eprint/120069

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