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Applying polygenic risk scores to postpartum depression |
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| Authors: | Enda M. Byrne Tania Carrillo-Roa Brenda W. J. H. Penninx Hannah M. Sallis Alexander Viktorin Brett Chapman Anjali K. Henders Michele L. Pergadia Andrew C. Heath Pamela A. F. Madden Patrick F. Sullivan Lynn Boschloo Gerard van Grootheest George McMahon Debbie A. Lawlor Mikael Landén Paul Lichtenstein Patrik K. E. Magnusson David M. Evans Grant W. Montgomery Dorret I. Boomsma Nicholas G. Martin Samantha Meltzer-Brody Naomi R. Wray Psychiatric Genomic Consortium Major Depressive Disorder Working Group |
| Affiliation: | 1. Queensland Brain Institute, The University of Queensland, Upland Road, St. Lucia, Brisbane, QLD, 4072, Australia 5. Queensland Institute of Medical Research, Brisbane, Australia 2. Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands 10. School of Social and Community Medicine, University of Bristol, Bristol, UK 3. MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK 4. Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden 6. Department of Psychiatry, Washington University, St. Louis, MO, USA 7. Department of Genetics and Psychiatry, University of North Carolina at Chapel Hill, CB# 7264, 5097 Genomic Medicine, Chapel Hill, NC, 27599-27264, USA 11. University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia 8. Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands 9. Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7570, USA |
| Abstract: | The etiology of major depressive disorder (MDD) is likely to be heterogeneous, but postpartum depression (PPD) is hypothesized to represent a more homogenous subset of MDD. We use genome-wide SNP data to explore this hypothesis. We assembled a total cohort of 1,420 self-report cases of PPD and 9,473 controls with genome-wide genotypes from Australia, The Netherlands, Sweden and the UK. We estimated the total variance attributable to genotyped variants. We used association results from the Psychiatric Genomics Consortia (PGC) of bipolar disorder (BPD) and MDD to create polygenic scores in PPD and related MDD data sets to estimate the genetic overlap between the disorders. We estimated that the percentage of variance on the liability scale explained by common genetic variants to be 0.22 with a standard error of 0.12, p?=?0.02. The proportion of variance (R 2) from a logistic regression of PPD case/control status in all four cohorts on a SNP profile score weighted by PGC-BPD association results was small (0.1 %) but significant (p?=?0.004) indicating a genetic overlap between BPD and PPD. The results were highly significant in the Australian and Dutch cohorts (R 2?>?1.1 %, p?R 2?=?0.06 %, p?=?0.08), despite the larger MDD group affording more power. Our results suggest an empirical genetic evidence for a more important shared genetic etiology between BPD and PPD than between BPD and MDD. |
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