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

Maciej Trzaskowski, Divya Mehta, Wouter J. Peyrot, David Hawkes, Daniel Davies, David M. Howard, Kathryn E. Kemper, Julia Sidorenko, Robert Maier, Stephan Ripke, Manuel Mattheisen, Bernhard T. Baune, Hans J. Grabe, Andrew C. Heath, Lisa Jones, Ian Jones, Pamela A. F. Madden, Andrew M. McIntosh, Gerome Breen, Cathryn M. Lewis & 7 others Anders D. Børglum, Patrick F. Sullivan, Nicholas G. Martin, Kenneth S. Kendler, Douglas F. Levinson, Naomi R. Wray, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

Research output: Contribution to journalArticleAcademicpeer-review

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.
Original languageEnglish
JournalAmerican Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
Volume180
DOIs
Publication statusPublished - 1 Jan 2019

Cite this

Trzaskowski, M., Mehta, D., Peyrot, W. J., Hawkes, D., Davies, D., Howard, D. M., ... Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (2019). Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, 180. https://doi.org/10.1002/ajmg.b.32713
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 ; 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. ; Wray, Naomi R. ; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. / Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder. In: American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics. 2019 ; Vol. 180.
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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.",
author = "Maciej Trzaskowski and Divya Mehta and Peyrot, {Wouter J.} and David Hawkes and Daniel Davies and Howard, {David M.} and Kemper, {Kathryn E.} and Julia Sidorenko and Robert Maier and Stephan Ripke and Manuel Mattheisen and Baune, {Bernhard T.} and Grabe, {Hans J.} and Heath, {Andrew C.} and Lisa Jones and Ian Jones and Madden, {Pamela A. F.} and McIntosh, {Andrew M.} and Gerome Breen and Lewis, {Cathryn M.} and B{\o}rglum, {Anders D.} and Sullivan, {Patrick F.} and Martin, {Nicholas G.} and Kendler, {Kenneth S.} and Levinson, {Douglas F.} and Wray, {Naomi R.} and {Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium}",
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Trzaskowski, M, Mehta, D, Peyrot, WJ, Hawkes, D, Davies, D, Howard, DM, Kemper, KE, Sidorenko, J, Maier, R, Ripke, S, Mattheisen, M, Baune, BT, Grabe, HJ, Heath, AC, Jones, L, Jones, I, Madden, PAF, McIntosh, AM, Breen, G, Lewis, CM, Børglum, AD, Sullivan, PF, Martin, NG, Kendler, KS, Levinson, DF, Wray, NR & Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium 2019, 'Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder' American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, vol. 180. https://doi.org/10.1002/ajmg.b.32713

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; 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.; Wray, Naomi R.; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium.

In: American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, Vol. 180, 01.01.2019.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder

AU - Trzaskowski, Maciej

AU - Mehta, Divya

AU - Peyrot, Wouter J.

AU - Hawkes, David

AU - Davies, Daniel

AU - Howard, David M.

AU - Kemper, Kathryn E.

AU - Sidorenko, Julia

AU - Maier, Robert

AU - Ripke, Stephan

AU - Mattheisen, Manuel

AU - Baune, Bernhard T.

AU - Grabe, Hans J.

AU - Heath, Andrew C.

AU - Jones, Lisa

AU - Jones, Ian

AU - Madden, Pamela A. F.

AU - McIntosh, Andrew M.

AU - Breen, Gerome

AU - Lewis, Cathryn M.

AU - Børglum, Anders D.

AU - Sullivan, Patrick F.

AU - Martin, Nicholas G.

AU - Kendler, Kenneth S.

AU - Levinson, Douglas F.

AU - Wray, Naomi R.

AU - Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

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UR - https://www.ncbi.nlm.nih.gov/pubmed/30708398

U2 - 10.1002/ajmg.b.32713

DO - 10.1002/ajmg.b.32713

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JO - American Journal of Medical Genetics Part B: Neuropsychiatric Genetics

JF - American Journal of Medical Genetics Part B: Neuropsychiatric Genetics

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