Perinatal depression is associated with a higher polygenic risk for major depressive disorder than non-perinatal depression.


Journal

Depression and anxiety
ISSN: 1520-6394
Titre abrégé: Depress Anxiety
Pays: United States
ID NLM: 9708816

Informations de publication

Date de publication:
03 2022
Historique:
revised: 19 11 2021
received: 18 06 2021
accepted: 12 12 2021
pubmed: 6 1 2022
medline: 11 3 2022
entrez: 5 1 2022
Statut: ppublish

Résumé

Distinctions between major depressive disorder (MDD) and perinatal depression (PND) reflect varying views of PND, from a unique etiological subtype of MDD to an MDD episode that happens to coincide with childbirth. This case-control study investigated genetic differences between PND and MDD outside the perinatal period (non-perinatal depression or NPD). We conducted a genome-wide association study using PND cases (Edinburgh Postnatal Depression Scale score ≥ 13) from the Australian Genetics of Depression Study 2018 data (n = 3804) and screened controls (n = 6134). Results of gene-set enrichment analysis were compared with those of women with non-PND. For six psychiatric disorders/traits, genetic correlations with PND were evaluated, and logistic regression analysis reported polygenic score (PGS) association with both PND and NPD. Genes differentially expressed in ovarian tissue were significantly enriched (stdBeta = 0.07, p = 3.3e-04), but were not found to be associated with NPD. The genetic correlation between PND and MDD was 0.93 (SE = 0.07; p = 3.5e-38). Compared with controls, PGS for MDD are higher for PND cases (odds ratio [OR] = 1.8, confidence interval [CI] = [1.7-1.8], p = 9.5e-140) than for NPD cases (OR = 1.6, CI = [1.5-1.7], p = 1.2e-49). Highest risk is for those reporting both antenatal and postnatal depression, irrespective of prior MDD history. PND has a high genetic overlap with MDD, but points of distinction focus on differential expression in ovarian tissue and higher MDD PGS, particularly for women experiencing both antenatal and postpartum PND.

Sections du résumé

BACKGROUND
Distinctions between major depressive disorder (MDD) and perinatal depression (PND) reflect varying views of PND, from a unique etiological subtype of MDD to an MDD episode that happens to coincide with childbirth. This case-control study investigated genetic differences between PND and MDD outside the perinatal period (non-perinatal depression or NPD).
METHODS
We conducted a genome-wide association study using PND cases (Edinburgh Postnatal Depression Scale score ≥ 13) from the Australian Genetics of Depression Study 2018 data (n = 3804) and screened controls (n = 6134). Results of gene-set enrichment analysis were compared with those of women with non-PND. For six psychiatric disorders/traits, genetic correlations with PND were evaluated, and logistic regression analysis reported polygenic score (PGS) association with both PND and NPD.
RESULTS
Genes differentially expressed in ovarian tissue were significantly enriched (stdBeta = 0.07, p = 3.3e-04), but were not found to be associated with NPD. The genetic correlation between PND and MDD was 0.93 (SE = 0.07; p = 3.5e-38). Compared with controls, PGS for MDD are higher for PND cases (odds ratio [OR] = 1.8, confidence interval [CI] = [1.7-1.8], p = 9.5e-140) than for NPD cases (OR = 1.6, CI = [1.5-1.7], p = 1.2e-49). Highest risk is for those reporting both antenatal and postnatal depression, irrespective of prior MDD history.
CONCLUSIONS
PND has a high genetic overlap with MDD, but points of distinction focus on differential expression in ovarian tissue and higher MDD PGS, particularly for women experiencing both antenatal and postpartum PND.

Identifiants

pubmed: 34985809
doi: 10.1002/da.23232
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

182-191

Informations de copyright

© 2022 Wiley Periodicals LLC.

Références

Aguet, F., Barbeira, A. N., Bonazzola, R., Brown, A., Castel, S. E., Jo, B., Lappalainen, T., Barbeira, A. N., Bonazzola, R., Brown, A., Castel, S. E., Jo, B., Kasela, S., Kim-Hellmuth, S., Liang, Y., Oliva, M., & Parsana, P. (2020). The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science, 369(6509), 1318-1330. https://doi.org/10.1126/science.aaz1776
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596
Athira, K. V., Bandopadhyay, S., Samudrala, P. K., Naidu, V. G. M., Lahkar, M., & Chakravarty, S. (2020). An overview of the heterogeneity of major depressive disorder: Current knowledge and future prospective. Current Neuropharmacology, 18(3), 168-187. https://doi.org/10.2174/1570159X17666191001142934
Barbitoff, Y. A., Tsarev, A. A., Vashukova, E. S., Maksiutenko, E. M., Kovalenko, L. V., Belotserkovtseva, L. D., & Glotov, A. S. (2020). A Data-driven review of the genetic factors of pregnancy complications. International Journal of Molecular Sciences, 21(9). https://doi.org/10.3390/ijms21093384
Bauer, A. E., Liu, X., Byrne, E. M., Sullivan, P. F., Wray, N. R., Agerbo, E., & Meltzer-Brody, S. (2019). Genetic risk scores for major psychiatric disorders and the risk of postpartum psychiatric disorders. Translational Psychiatry, 9(1), 288. https://doi.org/10.1038/s41398-019-0629-9
Bernabe, P. B., Maki, P. M., Dowty, S. M., Salas, M., Cralle, L., Shah, Z., & Gilbert, J. A. (2020). Precision medicine in perinatal depression in light of the human microbiome. Psychopharmacology, 237(4), 915-941. https://doi.org/10.1007/s00213-019-05436-4
Bulik-Sullivan, B. K., Loh, P. R., Finucane, H. K., Ripke, S., Yang, J., Schizophrenia Working Group of the Psychiatric Genomics Consortium, & Neale, B. M. (2015). LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47(3), 291-295. https://doi.org/10.1038/ng.3211
Buttner, M. M., Mott, S. L., Pearlstein, T., Stuart, S., Zlotnick, C., & O'Hara, M. W. (2013). Examination of premenstrual symptoms as a risk factor for depression in postpartum women. Archives of Women's Mental Health, 16(3), 219-225. https://doi.org/10.1007/s00737-012-0323-x
Byrne, E. M., Carrillo-Roa, T., Penninx, B. W., Sallis, H. M., Viktorin, A., Chapman, B., & Wray, N. R. (2014). Applying polygenic risk scores to postpartum depression. Archives of Women's Mental Health, 17(6), 519-528. https://doi.org/10.1007/s00737-014-0428-5
Byrne, E. M., Kirk, K. M., Medland, S. E., McGrath, J. J., Colodro-Conde, L., Parker, R., & Martin, N. G. (2020). Cohort profile: The Australian genetics of depression study. BMJ Open, 10(5), e032580. https://doi.org/10.1136/bmjopen-2019-032580
Byrne, E. M., Kirk, K. M., Medland, S. E., McGrath, J. J., Parker, R., Cross, S., & Martin, N. G. (2019). The Australian Genetics of Depression Study: Study description and sample characteristics. bioRxiv. https://doi.org/10.1101/626762. May 2019.
Cheadle, A. C. D., & Dunkel Schetter, C. (2018). Mastery, self-esteem, and optimism mediate the link between religiousness and spirituality and postpartum depression. Journal of Behavioral Medicine, 41(5), 711-721. https://doi.org/10.1007/s10865-018-9941-8
Christofolini, D. M., Mafra, F. A., Catto, M. C., Bianco, B., & Barbosa, C. P. (2019). New candidate genes associated to endometriosis. Gynecological Endocrinology, 35(1), 62-65. https://doi.org/10.1080/09513590.2018.1499090
Cox, J. L., Holden, J. M., & Sagovsky, R. (1987). Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. British Journal of Psychiatry, 150, 782-786.
Dapas, M., Lin, F. T. J., Nadkarni, G. N., Sisk, R., Legro, R. S., Urbanek, M., & Dunaif, A. (2020). Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis. PLoS Medicine, 17(6), e1003132. https://doi.org/10.1371/journal.pmed.1003132
Das, S., Forer, L., Schönherr, S., Sidore, C., Locke, A., Kwong, A., & Fuchsberger, C. (2016). Next-generation genotype imputation service and methods. Nature Genetics, 48, 1284-1287.
Dave, S., Petersen, I., Sherr, L., & Nazareth, I. (2010). Incidence of maternal and paternal depression in primary care: A cohort study using a primary care database. Archives of Pediatrics and Adolescent Medicine, 164(11), 1038-1044. https://doi.org/10.1001/archpediatrics.2010.184
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015). MAGMA: Generalized gene-set analysis of GWAS data. PLoS Computational Biology, 11(4), e1004219. https://doi.org/10.1371/journal.pcbi.1004219
de Punder, K., Entringer, S., Heim, C., Deuter, C. E., Otte, C., Wingenfeld, K., & Kuehl, L. K. (2018). Inflammatory measures in depressed patients with and without a history of adverse childhood experiences. Frontiers in Psychiatry, 9, 610. https://doi.org/10.3389/fpsyt.2018.00610
Deligiannidis, K. M., Sikoglu, E. M., Shaffer, S. A., Frederick, B., Svenson, A. E., Kopoyan, A., & Moore, C. M. (2016). GABAergic neuroactive steroids and resting-state functional connectivity in postpartum depression: A preliminary study. Journal of Psychiatric Research, 47(6), 816-828. https://doi.org/10.1016/j.jpsychires.2013.02.010
Demontis, D., Walters, R. K., Martin, J., Mattheisen, M., Als, T. D., Agerbo, E., & Neale, B. M. (2019). Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nature Genetics, 51(1), 63-75. https://doi.org/10.1038/s41588-018-0269-7
Fisher, S. D., Sit, D. K., Yang, A., Ciolino, J. D., Gollan, J. K., & Wisner, K. L. (2019). Four maternal characteristics determine the 12-month course of chronic severe postpartum depressive symptoms. Depression and Anxiety, 36(4), 375-383. https://doi.org/10.1002/da.22879
Fried, E. I. (2017). Moving forward: How depression heterogeneity hinders progress in treatment and research. Expert Review of Neurotherapeutics, 17(5), 423-425. https://doi.org/10.1080/14737175.2017.1307737
Gjerdingen, D. K., & Yawn, B. P. (2007). Postpartum depression screening: Importance, methods, barriers, and recommendations for practice. Journal of the American Board of Family Medicine, 20(3), 280-288. https://doi.org/10.3122/jabfm.2007.03.060171
Guintivano, J., Manuck, T., & Meltzer-Brody, S. (2018). Predictors of postpartum depression: A comprehensive review of the last decade of evidence. Clinical Obstetrics and Gynecology, 61(3), 591-603.
Guintivano, J., Putnam, K. T., Sullivan, P. F., & Meltzer-Brody, S. (2019). The international postpartum depression: Action towards causes and treatment (PACT) consortium. International Review of Psychiatry, 1-8. https://doi.org/10.1080/09540261.2018.1551191
Haplotype Reference Consortium. (2016). A reference panel of 64,976 haplotypes for genotype imputation. Nature Genetics, 48(10), 1279-1283. https://doi.org/10.1038/ng.3643
Hoekzema, E., Barba-Muller, E., Pozzobon, C., Picado, M., Lucco, F., Garcia-Garcia, D., & Vilarroya, O. (2017). Pregnancy leads to long-lasting changes in human brain structure. Nature Neuroscience, 20(2), 287-296. https://doi.org/10.1038/nn.4458
Howard, D. M., Adams, M. J., Clarke, T. K., Hafferty, J. D., Gibson, J., Shirali, M., & McIntosh, A. M. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, 22(3), 343-352. https://doi.org/10.1038/s41593-018-0326-7
Jermy, B., Hagenaars, S., Coleman, J., Vassos, E., & Lewis, C. (2021). Context Matters! Depression following childbirth or a chronic disease diagnosis shows specific risk factor profiles. European Neuropsychopharmacology, 51, e33-e34. https://doi.org/10.1016/j.euroneuro.2021.07.079
Jiang, L., Zheng, Z., Qi, T., Kemper, K. E., Wray, N. R., Visscher, P. M., & Yang, J. (2019). A resource-efficient tool for mixed model association analysis of large-scale data. Nature Genetics, 51(12), 1749-1755. https://doi.org/10.1038/s41588-019-0530-8
Kessler, R. C., Andrews, G., Mroczek, D., Ustun, B., & Wittchen, H.-U. (1998). The World Health Organization Composite International Diagnostic Interview short-form (CIDI-SF). International Journal of Methods in Psychiatric Research, 7(4), 171-185. https://doi.org/10.1002/mpr.47
Kettunen, P. (2019). Postpartum depression: Time of onset, severity, symptoms, risk factors and treatment (PhD doctoral dissertation). Tampere University. https://trepo.tuni.fi/handle/10024/105055
Leung, B. M., Letourneau, N. L., Giesbrecht, G. F., Ntanda, H., Hart, M., & Team, A. P. (2017). Predictors of postpartum depression in partnered mothers and fathers from a Longitudinal Cohort. Community Mental Health Journal, 53(4), 420-431. https://doi.org/10.1007/s10597-016-0060-0
Mahon, P. B., Payne, J. L., MacKinnon, D. F., Mondimore, F., M., Goes, F. S., Schweizer, B., & Potash, J. B. (2009). Genome-wide linkage and follow-up association study of postpartum mood symptoms. American Journal of Psychiatry, 166(11), 1229-1237.
Mandal, S. K., Hooker, L., Vally, H., & Taft, A. (2018). Partner violence and postnatal mental health: Cross-sectional analysis of factors associated with depression and anxiety in new mothers. Australian Journal of Primary Health, 24(5). https://doi.org/10.1071/py17174
Martens, R. J. H., Kooman, J. P., Stehouwer, C. D. A., Dagnelie, P. C., van der Kallen, C. J. H., Kroon, A. A., & Henry, R. M. A. (2018). Albuminuria is associated with a higher prevalence of depression in a population-based cohort study: The Maastricht Study. Nephrology, Dialysis, Transplantation, 33(1), 128-138. https://doi.org/10.1093/ndt/gfw377
Mehta, D., Rex-Haffner, M., Sondergaard, H. B., Pinborg, A., Binder, E. B., & Frokjaer, V. G. (2019). Evidence for oestrogen sensitivity in perinatal depression: Pharmacological sex hormone manipulation study. British Journal of Psychiatry, 215(3), 519-527. https://doi.org/10.1192/bjp.2018.234
Meltzer-Brody, S., Boschloo, L., Jones, I., Sullivan, P. F., & Penninx, B. W. (2013). The EPDS-Lifetime: Assessment of lifetime prevalence and risk factors for perinatal depression in a large cohort of depressed women. Archives of Women's Mental Health, 16(6), 465-473. https://doi.org/10.1007/s00737-013-0372-9
Meltzer-Brody, S. Postpartum Depression: Action Towards Causes and Treatment (PACT) Consortium. (2015). Heterogeneity of postpartum depression: A latent class analysis. Articles Lancet Psychiatry, 2, 59-67. https://doi.org/10.1016/S2215-0366(14)00055-8
Mullarkey, M. C., Marchetti, I., & Beevers, C. G. (2019). Using network analysis to identify central symptoms of adolescent depression. Journal of Clinical Child and Adolescent Psychology, 48(4), 656-668. https://doi.org/10.1080/15374416.2018.1437735
Nazzari, S., Fearon, P., Rice, F., Ciceri, F., Molteni, M., & Frigerio, A. (2020). The biological underpinnings of perinatal depressive symptoms: A multi-systems approach. Journal of Affective Disorders, 274, 1004-1012. https://doi.org/10.1016/j.jad.2020.05.023
Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C. Y., Choi, K. W., & Koenen, K. C. (2019). International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature Communications, 10(1), 4558. https://doi.org/10.1038/s41467-019-12576-w
Ning, Z., Pawitan, Y., & Shen, X. (2020). High-definition likelihood inference of genetic correlations across human complex traits. Nature Genetics, 52(8), 859-864. https://doi.org/10.1038/s41588-020-0653-y
O'Connor, E., Rossom, R. C., Henninger, M., Groom, H. C., & Burda, B. U. (2016). Primary care screening for and treatment of depression in pregnant and postpartum women: Evidence report and systematic review for the US Preventive Services Task Force. Journal of the American Medical Association, 315(4), 388-406. https://doi.org/10.1001/jama.2015.18948
Olsen, C. M., Green, A. C., Neale, R. E., Webb, P. M., Cicero, R. A., Jackman, L. M., & Study, Q. S. (2012). Cohort profile: The QSkin Sun and Health Study. International Journal of Epidemiology, 41(4), 929-929i. https://doi.org/10.1093/ije/dys107
Pardiñas, A. F. Antonio, F., Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., Legge, S. E., Bishop, S., Cameron, D., Hamshere, M. L., Han, J., Hubbard, L., Lynham, A., Mantripragada, K., Rees, E., MacCabe, J. H., McCarroll, S. A., Baune, B. T., … Walters, J. T. R. (2018). Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature Genetics, 50(3), 381-389. https://doi.org/10.1038/s41588-018-0059-2
Pawluski, J. L., Lonstein, J. S., & Fleming, A. S. (2017). The neurobiology of postpartum anxiety and depression. Trends in Neurosciences, 40(2), 106-120. https://doi.org/10.1016/j.tins.2016.11.009
Payne, J. L., & Maguire, J. (2019). Pathophysiological mechanisms implicated in postpartum depression. Frontiers in Neuroendocrinology, 52, 165-180. https://doi.org/10.1016/j.yfrne.2018.12.001
Pouget, J. G., Taylor, V. H., Dennis, C.-L., Grigoriadis, S., Oberlander, T., Frey, B. N., & Vigod, S. N. (2021). Preliminary insights into the genetic architecture of postpartum depressive symptom severity using polygenic risk scores. Personalized Medicine in Psychiatry, 27-28. https://doi.org/10.1016/j.pmip.2021.100081
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D., & Sham, P. C. (2007). PLINK: A tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics, 81(3), 559-575. https://doi.org/10.1086/519795
Racine, N., Zumwalt, K., McDonald, S., Tough, S., & Madigan, S. (2020). Perinatal depression: The role of maternal adverse childhood experiences and social support. Journal of Affective Disorders, 263, 576-581. https://doi.org/10.1016/j.jad.2019.11.030
Radell, M. L., Abo Hamza, E. G., Daghustani, W. H., Perveen, A., & Moustafa, A. A. (2021). The impact of different types of abuse on depression. Depression Research and Treatment, 2021, 6654503. https://doi.org/10.1155/2021/6654503
Rafferty, J., Mattson, G., Earls, M. F., & Yogman, M. W. (2019). Incorporating recognition and management of perinatal depression into pediatric practice. Pediatrics, 143(1), e20183259.
Rantalainen, V., Binder, E. B., Lahti-Pulkkinen, M., Czamara, D., Laivuori, H., Villa, P. M., & Raikkonen, K. (2020). Polygenic prediction of the risk of perinatal depressive symptoms. Depression and Anxiety, 37(9), 862-875. https://doi.org/10.1002/da.23066
Rolle, L., Giordano, M., Santoniccolo, F., & Trombetta, T. (2020). Prenatal attachment and perinatal depression: A systematic review. International Journal of Environmental Research and Public Health, 17(8). https://doi.org/10.3390/ijerph17082644
Sacher, J., Rekkas, P. V., Wilson, A. A., Houle, S., Romano, L., Hamidi, J., & Meyer, J. H. (2015). Relationship of monoamine oxidase-A distribution volume to postpartum depression and postpartum crying. Neuropsychopharmacology, 40(2), 429-435. https://doi.org/10.1038/npp.2014.190
Schiller, C. E., Meltzer-Brody, S., & Rubinow, D. R. (2015). The role of reproductive hormones in postpartum depression. CNS Spectrums, 20(1), 48-59. https://doi.org/10.1017/S1092852914000480
Sha, Q., Achtyes, E., Nagalla, M., Keaton, S., Smart, L., Leach, R., & Brundin, L. (2021). Associations between estrogen and progesterone, the kynurenine pathway, and inflammation in the post-partum. Journal of Affective Disorders, 281, 9-12. https://doi.org/10.1016/j.jad.2020.10.052
Silverman, M. E., Reichenberg, A., Lichtenstein, P., & Sandin, S. (2019). Is depression more likely following childbirth? A population-based study. Archives of Women's Mental Health, 22(2), 253-258. https://doi.org/10.1007/s00737-018-0891-5
Silverman, M. E., Reichenberg, A., Savitz, D. A., Cnattingius, S., Lichtenstein, P., Hultman, C. M., & Sandin, S. (2017). The risk factors for postpartum depression: A population-based study. Depression and Anxiety, 34(2), 178-187. https://doi.org/10.1002/da.22597
Stahl, E. A., Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., & Trubetskoy, V., Bipolar Disorder Working Group of the Psychiatric Genomics, C. (2019). Genome-wide association study identifies 30 loci associated with bipolar disorder. Nature Genetics, 51(5), 793-803. https://doi.org/10.1038/s41588-019-0397-8
Studd, J., & Nappi, R. E. (2012). Reproductive depression. Gynecological Endocrinology, 28(Suppl. 1), 42-45. https://doi.org/10.3109/09513590.2012.651932
Takahashi, N., Tainaka, H., Nishimura, T., Harada, T., Okumura, A., Choi, D., & Tsuchiya, K. J. (2020). Distinct genetic profiles in postpartum depression with different trajectory of illness. Research Square Preprint. https://doi.org/10.21203/rs.3.rs-29168/v1
The 1000 Genomes Project ConsortiumAuton, A., Brooks, L. D., Durbin, R. M., Garrison, E. P., Kang, H. M., & Abecasis, G. R. (2015). A global reference for human genetic variation. Nature, 526(7571), 68-74. https://doi.org/10.1038/nature15393
Thombs, B. D., Kwakkenbos, L., Levis, A. W., & Benedetti, A. (2018). Addressing overestimation of the prevalence of depression based on self-report screening questionnaires. Canadian Medical Association Journal, 190(2), E44-E49. https://doi.org/10.1503/cmaj.170691
Treloar, S. A., Martin, N. G., Bucholz, K. K., Madden, P. A., & Heath, A. C. (1999). Genetic influences on post-natal depressive symptoms: Findings from an Australian twin sample. Psychological Medicine, 29(3), 645-654. https://doi.org/10.1017/s0033291799008387
Viktorin, A., Meltzer-Brody, S., Kuja-Halkola, R., Sullivan, P. F., Landen, M., Lichtenstein, P., & Magnusson, P. K. (2016). Heritability of perinatal depression and genetic overlap with nonperinatal depression. American Journal of Psychiatry, 173(2), 158-165. https://doi.org/10.1176/appi.ajp.2015.15010085
Vismara, L., Sechi, C., Neri, M., Paoletti, A., & Lucarelli, L. (2020). Maternal perinatal depression, anxiety, fear of birth, and perception of infants' negative affectivity at three months. Journal of Reproductive and Infant Psychology, 1-12. https://doi.org/10.1080/02646838.2020.1843612
Watanabe, K. (2019). Functional mapping and annotation of genome-wide association studies. https://fuma.ctglab.nl/
Watson, H. J., Yilmaz, Z., Thornton, L. M., Hubel, C., Coleman, J. R. I., Gaspar, H. A., & Bulik, C. M. (2019). Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nature Genetics, 51(8), 1207-1214. https://doi.org/10.1038/s41588-019-0439-2
Woody, C. A., Ferrari, A. J., Siskind, D. J., Whiteford, H. A., & Harris, M. G. (2017). A systematic review and meta-regression of the prevalence and incidence of perinatal depression. Journal of Affective Disorders, 219, 86-92. https://doi.org/10.1016/j.jad.2017.05.003
World Health Organization. (2019). International Classification of Diseases ICD-11. https://icd.who.int/icd11refguide/en/index.html
Zhang, Y., Cheng, Y., Jiang, W., Ye, Y., Lu, Q., & Zhao, H. (2020). Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics. bioRxiv. October 2020. https://doi.org/10.1101/2020.10.12.336867
Zhou, W., Nielsen, J. B., Fritsche, L. G., Dey, R., Gabrielsen, M. E., Wolford, B. N., & Lee, S. (2018). Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nature Genetics, 50(9), 1335-1341. https://doi.org/10.1038/s41588-018-0184-y

Auteurs

Jacqueline Kiewa (J)

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia.

Samantha Meltzer-Brody (S)

Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA.

Jeanette Milgrom (J)

Parent-Infant Research Institute, Austin Health, Melbourne, Victoria, Australia.
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia.

Jerry Guintivano (J)

Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA.

Ian B Hickie (IB)

Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia.

David C Whiteman (DC)

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Catherine M Olsen (CM)

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Lucía Colodro-Conde (L)

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Sarah E Medland (SE)

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Nicholas G Martin (NG)

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Naomi R Wray (NR)

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.

Enda M Byrne (EM)

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH