TY - JOUR
T1 - Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder
AU - Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
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.
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.
KW - LD score regression
KW - MDD
KW - depression
KW - genetic heterogeneity
KW - sex differences
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060925900&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/30708398
U2 - https://doi.org/10.1002/ajmg.b.32713
DO - https://doi.org/10.1002/ajmg.b.32713
M3 - Article
C2 - 30708398
SN - 1552-4841
VL - 180
SP - 439
EP - 447
JO - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
JF - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
IS - 6
ER -