Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders

Piotr Jaholkowski; Alexey A Shadrin; Andreas Jangmo; Evgeniia Frei; Markos Tesfaye; Guy F L Hindley; Marit Haram; Zillur Rahman; Lavinia Athanasiu; Nora Refsum Bakken; Børge Holen; Vera Fominykh; Gleda Kutrolli; Pravesh Parekh; Nadine Parker; Linn Rødevand; Viktoria Birkenæs; Srdjan Djurovic; Oleksandr Frei; Kevin S O’Connell; Olav B Smeland; Martin Tesli; Ole A Andreassen

doi:10.1001/jamapsychiatry.2023.1137

. 2023 May 10;80(7):738–742. doi: 10.1001/jamapsychiatry.2023.1137

Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders

Piotr Jaholkowski ^1,^✉, Alexey A Shadrin ^1,², Andreas Jangmo ³, Evgeniia Frei ¹, Markos Tesfaye ^1,⁴, Guy F L Hindley ^1,⁵, Marit Haram ^3,⁶, Zillur Rahman ¹, Lavinia Athanasiu ¹, Nora Refsum Bakken ¹, Børge Holen ¹, Vera Fominykh ¹, Gleda Kutrolli ¹, Pravesh Parekh ¹, Nadine Parker ¹, Linn Rødevand ¹, Viktoria Birkenæs ¹, Srdjan Djurovic ^7,⁸, Oleksandr Frei ^1,⁹, Kevin S O’Connell ¹, Olav B Smeland ¹, Martin Tesli ^1,³, Ole A Andreassen ^1,^2,^✉

¹Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway

²KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway

³Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway

⁴Department of Psychiatry, St Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia

⁵Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom

⁶Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

⁷Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

⁸NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway

⁹Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway

Accepted for Publication: March 7, 2023.

Published Online: May 10, 2023. doi:10.1001/jamapsychiatry.2023.1137

^✉

Corresponding Authors: Piotr Jaholkowski, MD, PhD (p.p.jaholkowski@medisin.uio.no), and Ole A. Andreassen, MD, PhD (ole.andreassen@medisin.uio.no), Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Ullevål, Kirkeveien 166, 0424 Oslo, Norway.

Author Contributions: Dr Jaholkowski had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Jaholkowski, Fominykh, Birkenæs, Smeland, Tesli, Andreassen.

Acquisition, analysis, or interpretation of data: Jaholkowski, Shadrin, Jangmo, E. Frei, Tesfaye, Hindley, Haram, Rahman, Athanasiu, Bakken, Holen, Kutrolli, Parekh, Parker, Rødevand, Djurovic, O. Frei, O’Connell, Smeland, Tesli, Andreassen.

Drafting of the manuscript: Jaholkowski, E. Frei, Fominykh, Kutrolli, O’Connell, Smeland, Andreassen.

Critical revision of the manuscript for important intellectual content: Jaholkowski, Shadrin, Jangmo, Tesfaye, Hindley, Haram, Rahman, Athanasiu, Bakken, Holen, Fominykh, Parekh, Parker, Rødevand, Birkenæs, Djurovic, O. Frei, O’Connell, Tesli, Andreassen.

Statistical analysis: Jaholkowski, Shadrin, Hindley, Kutrolli, Parekh, O. Frei, Tesli.

Obtained funding: Andreassen.

Administrative, technical, or material support: Jangmo, Rahman, Athanasiu, Bakken, Birkenæs, Djurovic, Smeland, Tesli, Andreassen.

Supervision: O. Frei, O’Connell, Andreassen.

Conflict of Interest Disclosures: Dr Haram reported receiving grants from the Norwegian Institute of Public Health during the conduct of the study. Ms Bakken reported receiving grants from the Research Council of Norway during the conduct of the study. Dr Parker reported receiving a Marie Skłodowska-Curie Actions Grant (Scientia fellowship) and grants from the Research Council of Norway during the conduct of the study. Dr Andreassen reported grants for unrestricted research funding from KG Jebsen Stiftelsen, the South East Norway Health Authority, the Research Council of Norway, the European Union, and the National Institutes of Health during the conduct of the study; personal fees from cortechs.ai and HealthLytix as a consultant outside the submitted work; personal fees from Lundbeck, Sunovion, and Janssen for speaker’s honorarium outside the submitted work; and is working as a consultant at Østfold Hospital and is the local principal investigaator for clinical trials sponsored by BI, COMPASS, MAPS, and Janssen. No other disclosures were reported.

Funding/Support: The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. This research is part of the HARVEST collaboration, supported by the Research Council of Norway (grant 229624). The Norwegian Centre for Mental Disorders Research (NORMENT) provided genotype data, funded by the Research Council of Norway (grant 223273), South East Norway Health Authorities, and Stiftelsen Kristian Gerhard Jebsen. The Center for Diabetes Research, the University of Bergen, provided genotype data funded by the ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, the Trond Mohn Foundation, the Research Council of Norway, the Novo Nordisk Foundation, the University of Bergen, and the Western Norway Health Authorities. This work was supported by the Research Council of Norway (grants 223273, 271555/F21, 273291, 273446, 296030, 300309, 324252, 324499, and 326813), the European Economic Area and Norway Grants (grants EEA-RO-NO-2018-0535, EEA-RO-NO-2018-0573, 2014-2021, and 6/2019), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant (grant 801133), the European Union’s Horizon 2020 research and innovation programme (grant 847776 CoMorMent), the European Commission Grant Committee (grant 964874), the US National Institute of Mental Health (grants R01MH123724 and 1R01 MH124839-01).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We are grateful to all the participating families in Norway who take part in this ongoing cohort study. We thank the Norwegian Institute of Public Health for generating high-quality genomic data.

Additional Information: Dr Holen is supported by the University of Oslo. This work was performed on resources provided by the Tjeneste for Sensitive Data facilities.

^✉

Corresponding author.

PMCID: PMC10173094 PMID: 37163253

Key Points

Question

Are symptoms of premenstrual disorders associated with genetic liability for major psychiatric disorders?

Findings

In this genetic association study of 56 725 women, premenstrual disorder symptoms were associated with polygenic liability for major psychiatric disorders but not for height.

Meaning

The results of this study suggest that symptoms of premenstrual disorders share genetic liability with major psychiatric disorders.

Abstract

Importance

Premenstrual disorders are heritable, clinically heterogenous, with a range of affective spectrum comorbidities. It is unclear whether genetic predispositions to affective spectrum disorders or other major psychiatric disorders are associated with symptoms of premenstrual disorders.

Objective

To assesss whether symptoms of premenstrual disorders are associated with the genetic liability for major psychiatric disorders, as indexed by polygenic risk scores (PRSs).

Design, Setting, and Participants

Women from the Norwegian Mother, Father and Child Cohort Study were included in this genetic association study. PRSs were used to determine whether genetic liability for major depression, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism spectrum disorder were associated with the symptoms of premenstrual disorders, using the PRS for height as a somatic comparator. The sample was recruited across Norway between June 1999 and December 2008, and analyses were performed from July 1 to October 14, 2022.

Main Outcomes and Measures

The symptoms of premenstrual disorders were assessed at recruitment at week 15 of pregnancy with self-reported severity of depression and irritability before menstruation. Logistic regression was applied to test for the association between the presence of premenstrual disorder symptoms and the PRSs for major psychiatric disorders.

Results

The mean (SD) age of 56 725 women included in the study was 29.0 (4.6) years. Premenstrual disorder symptoms were present in 12 316 of 56 725 participants (21.7%). The symptoms of premenstrual disorders were associated with the PRSs for major depression (β = 0.13; 95% CI, 0.11-0.15; P = 1.21 × 10⁻³⁶), bipolar disorder (β = 0.07; 95% CI, 0.05-0.09; P = 1.74 × 10⁻¹¹), attention deficit/hyperactivity disorder (β = 0.07; 95% CI, 0.04-0.09; P = 1.58 × 10⁻⁹), schizophrenia (β = 0.11; 95% CI, 0.09-0.13; P = 7.61 × 10⁻²⁵), and autism spectrum disorder (β = 0.03; 95% CI, 0.01-0.05; P = .02) but not with the PRS for height. The findings were confirmed in a subsample of women without a history of psychiatric diagnosis.

Conclusions

The results of this genetic association study show that genetic liability for both affective spectrum disorder and major psychiatric disorders was associated with symptoms of premenstrual disorders, indicating that premenstrual disorders have overlapping genetic foundations with major psychiatric disorders.

This genetic association study assesses whether symptoms of premenstrual disorders are associated with the genetic liability for major psychiatric disorders, as indexed by polygenic risk scores.

Introduction

The premenstrual disorders (PMDs) encompass premenstrual syndrome (PMS), premenstrual dysphoric disorder (PMDD), and premenstrual exacerbation of another medical condition.¹ The symptoms of these clinically heterogenous disorders occur during the luteal phase of the menstrual cycle and include affective symptoms in addition to somatic symptoms.¹ The severity of premenstrual symptoms varies from mild to disabling.¹ The estimated prevalence is 20% to 30% for PMS and 1% to 6% for PMDD among menstruating women.¹ The mechanisms underlying PMDs remain unclear, but a pathological response to fluctuations in progesterone or allopregnanolone concentrations and the dysfunction of serotonergic pathways are implicated.¹ The heritability of premenstrual symptoms was estimated to be 31% to 56%, with a minimal contribution from familial environment.²

Several lines of evidence suggest that PMDs and major psychiatric disorders share some pathophysiological mechanisms. There is increased prevalence of PMDs among women with affective spectrum disorders such as major depression (MD).³ Prepregnancy PMS is one of the most important risk factors for postpartum depression.⁴ Comorbid PMDD in individuals with bipolar disorder (BIP) is associated with more severe clinical characteristics.⁵ Furthermore, selective serotonin reuptake inhibitors are first-line pharmacotherapeutics for both PMDD and MD.¹ Still, it remains unclear whether these disorders have shared genetic underpinnings. In the present study, we examined whether PMD symptoms are associated with the genetic liability for affective spectrum disorders and nonaffective major psychiatric disorders, as indexed by polygenic risk scores (PRSs).

Methods

Participants

In this genetic association study, a total of 70 863 pregnant women from the Norwegian Mother, Father and Child Cohort Study (MoBa)⁶ were included in the analysis (eAppendix 1 in Supplement 1). Participants provided written informed consent to participate in MoBa. The present study was approved by the Regional Committees for Medical and Health Research Ethics (2016/1226/REK).

Polygenic Risk Scores

The genotyping, quality control, and imputation of the MoBa sample genetic data are described elsewhere.⁷ We applied PRSice, version 2.3.3⁸ to calculate the PRSs from genome wide association studies of MD, BIP, attention deficit/hyperactivity disorder (ADHD), schizophrenia (SCZ), autism spectrum disorder (ASD), as well as 1 somatic comparator, height, following a well-established method (eAppendix 2 in Supplement 1).⁹

Phenotype Measures

Experienced symptoms of PMDs were defined based on the mothers’ responses to the questions “Are you usually depressed or irritable before your period?” and “If yes, does this feeling disappear after you get your period?” at 15th week of gestation. The presence of PMD symptoms was defined based on the response “yes, noticeably” or “yes, very much” to the first question, and “yes” to the second question (n = 12 316). No experience of PMD symptoms was defined based on the response “no” or “yes, but just slightly” to the first question (n = 44 409). We excluded individuals who were noticeably or very much depressed or irritable before their periods and whose symptoms did not resolve after their period (n = 1919; eAppendix 3 and eFigure 1 in Supplement 1).

For subsample analyses, we excluded participants with a history of a psychiatric disorder based on data from the Norwegian Patient Registry (years 2008-2018), as well as individuals with self-reported psychiatric illness or health problems based on responses to MoBa questionnaires at the 15th and 30th week of gestation (eAppendix 3 in Supplement 1).

Statistical Analysis

Analyses were performed from July 1 to October 14, 2022. Logistic regression models were used to test the association between PMD symptoms and each PRS. Covariates included 10 genome-wide principal components and age. The Kruskal-Wallis test was applied to compare PRSs between the groups with different severity of PMD symptoms. All P values were corrected for multiple testing using Bonferroni correction. A 2-sided P < .05 was considered to be statistically significant.

Results

The sample was recruited across Norway between June 1999 and December 2008. A total of 56 725 women were included in the study, and the mean (SD) age was 29.0 (4.6) years. PMD symptoms were present in 12 316 of 56 725 participants (21.7%). Symptoms of PMDs were associated with the PRSs for the following affective spectrum disorders: MD (β = 0.13; 95% CI, 0.11-0.15; P = 1.21 × 10⁻³⁶) and BIP (β = 0.07; 95% CI, 0.05-0.09; P = 1.74 × 10⁻¹¹), in addition to ADHD (β = 0.07; 95% CI, 0.04-0.09; P = 1.58 × 10⁻⁹), SCZ (β = 0.11; 95% CI, 0.09-0.13; P = 7.61 × 10⁻²⁵), and ASD (β = 0.03; 95% CI, 0.01-0.05; P = .02). No association was found between PMD symptoms and the PRS for height (Figure 1; eTable in Supplement 1).

Figure 1. — Association of the symptoms of PMDs with PRSs for affective spectrum disorders (major depression [MD] and bipolar disorder [BIP]), attention deficit/hyperactivity disorder (ADHD), schizophrenia (SCZ), autism spectrum disorder (ASD), and height, derived from the logistic regression models. Error bars indicate the 95% CIs of the estimated values. The vertical lines indicate an effect estimate equal to zero.

When the analyses were restricted to participants without a history of psychiatric disorders (n = 44 620), a similar pattern of associations was found. Symptoms of PMDs remained significantly associated with the PRSs for MD (β = 0.10; 95% CI, 0.08-0.12; P = 1.48 × 10⁻¹⁵), BIP (β = 0.06; 95% CI, 0.04-0.09; P = 1.57 × 10⁻⁶), ADHD (β = 0.05; 95% CI, 0.03-0.07; P = 2.85 × 10⁻⁴), and SCZ (β = 0.10; 95% CI, 0.08-0.13; P = 1.40 × 10⁻¹⁵) but not for ASD or height. The associations remained significant after conditioning on the other PRSs for all disorders except BIP (eFigure 2 and eAppendix 4 in Supplement 1), with similar findings when comparing explained variance (Nagelkerke R²) for each PRS. The largest R² was achieved when combining all PRSs in a single model (eFigure 3 and eAppendix 5 in Supplement 1). Odds ratios for the PMD symptoms by deciles of PRSs are presented in eFigure 4 in Supplement 1.

Further analysis revealed that the severity of PMD symptoms was associated with the PRSs for MD (P = 2.65 × 10⁻²⁴), BIP (P = 1.70 × 10⁻¹⁴), ADHD (P = 1.16 × 10⁻⁴), SCZ (P = 3.06 × 10⁻²⁴), and ASD (P = .02) but not the PRS for height (Figure 2). Significant associations were also observed in all regression models between the symptoms of PMDs and age (eg, the subsample without psychiatric diagnosis; model for height; age [β = 0.04; 95% CI, 0.04-0.05; P = 3.69 × 10⁻⁵⁴]).

Figure 2. — Association of the mean PRSs for affective spectrum disorders (major depression [MD] and bipolar disorder [BIP]), attention deficit/hyperactivity disorder (ADHD), schizophrenia (SCZ), autism spectrum disorder (ASD), and height with groups of different severity of PMD symptoms based on response to the question “Are you usually depressed or irritable before your period?” There were significant associations in a dose-dependent manner between severity of PMD symptoms and higher PRS for SCZ, MD, BIP, ADHD, and ASD but not for height. Statistically significant results after pairwise post hoc multiple comparison correction (following the Kruskal-Wallis rank sum test; P < .05) are indicated.

^aCompared with “no.”

^bCompared with “yes, but just slightly.”

^cCompared with “yes, noticeably.”

Discussion

Our main finding is an association between the symptoms of PMDs and the PRSs for affective disorders (MD and BIP) but also ADHD and SCZ, independent of a history of psychiatric disorders. The largest effect size was observed for MD and SCZ, with only borderline significance for ASD. These findings indicate that PMDs share genetic architecture not only within the spectrum of affective disorders but also with other major psychiatric disorders. The specificity of the findings was supported by a lack of association with the PRS for height. These results demonstrate that polygenic liability for the symptoms of PMDs is associated with a range of major psychiatric disorders, showing shared genetic liability as suggested by twin studies.²

These findings support the hypothesis that PMD symptoms emerge due to the interplay between hormonal changes during menstruation and genetic susceptibility for major psychiatric disorders. The mechanisms of this interplay should be identified in experimental studies, to provide insights into the neurobiology of sex-specific mental traits and disorders. Thus, the current findings of shared genetic architecture between PMDs and major psychiatric disorders may contribute to the development of novel treatments as well as improved nosology.

Strengths and Limitations

A limitation of this study is that the presence of PMD symptoms was based on retrospective self-reports, which have some degree of uncertainty. However, they have been successfully used in other MoBa studies of PMD symptoms,^10,11 and there is a high consistency between retrospective and prospective PMS symptom assessments.¹² The lack of diagnostic tools is another limitation, but the validity and reliability of PMDs’ criteria themselves are debated.^1,13 The analyses were restricted to 2 psychological symptoms of PMDs. However, the current measures are well defined and capture the core features of PMDs, yielding, to our knowledge, the largest sample on PMD symptoms with genotype data to date. One should interpret the relative association between the genetic liability for each psychiatric disorder and the symptoms of PMDs with caution due to the lack of calibration of the different PRSs and the lack of sex-specific PRSs.

Conclusions

The results of this genetic association study show that genetic liability for both affective spectrum disorder and major psychiatric disorders were associated with symptoms of premenstrual disorders, indicating that premenstrual disorders have overlapping genetic foundations with major psychiatric disorders.

Supplement 1.

eAppendix 1. The Norwegian Mother, Father and Child Cohort Study (MoBa) Sample

eAppendix 2. Implementation of MoBaPsychGen Pipeline and Polygenic Risk Scores Calculation

eAppendix 3. Phenotypic Description of Subsample Without History Of Psychiatric Diagnosis

eFigure 1. Study Sample

eAppendix 4. Associations Between the Symptoms of Premenstrual Disorders and PRSs for Major Psychiatric Disorders – a Multiple Regression Model

eFigure 2. Associations of the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders - Multiple Logistic Regression Model Associations

eAppendix 5. Nagelkerke’s Pseudo-R² From Logistic Regression Models for the Association Between the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eFigure 3. Nagelkerke’s Pseudo-R² From Logistic Regression Models for the Association Between the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eFigure 4. Odds Ratios for the Premenstrual Disorder Symptoms, by Deciles of PRSs

eTable. Associations of the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eReferences.

Click here for additional data file.^{(963.9KB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(13.3KB, pdf)}

References

1.Yonkers KA, Simoni MK. Premenstrual disorders. Am J Obstet Gynecol. 2018;218(1):68-74. doi: 10.1016/j.ajog.2017.05.045 [DOI] [PubMed] [Google Scholar]
2.Epperson CN, Steiner M, Hartlage SA, et al. Premenstrual dysphoric disorder: evidence for a new category for DSM-5. Am J Psychiatry. 2012;169(5):465-475. doi: 10.1176/appi.ajp.2012.11081302 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Forrester-Knauss C, Zemp Stutz E, Weiss C, Tschudin S. The interrelation between premenstrual syndrome and major depression: results from a population-based sample. BMC Public Health. 2011;11:795. doi: 10.1186/1471-2458-11-795 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Cao S, Jones M, Tooth L, Mishra GD. History of premenstrual syndrome and development of postpartum depression: a systematic review and meta-analysis. J Psychiatr Res. 2020;121:82-90. doi: 10.1016/j.jpsychires.2019.11.010 [DOI] [PubMed] [Google Scholar]
5.Slyepchenko A, Frey BN, Lafer B, Nierenberg AA, Sachs GS, Dias RS. Increased illness burden in women with comorbid bipolar and premenstrual dysphoric disorder: data from 1 099 women from STEP-BD study. Acta Psychiatr Scand. 2017;136(5):473-482. doi: 10.1111/acps.12797 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Magnus P, Birke C, Vejrup K, et al. Cohort profile update: the Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2016;45(2):382-388. doi: 10.1093/ije/dyw029 [DOI] [PubMed] [Google Scholar]
7.Corfield EC, Frei O, Shadrin AA, et al. The Norwegian Mother, Father, and Child cohort study (MoBa) genotyping data resource: MoBaPsychGen pipeline v.1. bioRxiv. Preprint posted June 26, 2022. Published online January 1, 2022. doi: 10.1101/2022.06.23.496289 [DOI]
8.Choi SW, O’Reilly PF. PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience. 2019;8(7):giz082. doi: 10.1093/gigascience/giz082 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Coombes BJ, Ploner A, Bergen SE, Biernacka JM. A principal component approach to improve association testing with polygenic risk scores. Genet Epidemiol. 2020;44(7):676-686. doi: 10.1002/gepi.22339 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Chortatos A. Nausea and vomiting in pregnancy: effects on maternal diet, health, and birth outcomes. An investigation using the Norwegian Mother and Child Cohort Study. Oslo Centre for Biostatistics and Epidemiiology and Department of Nutrition, University of Oslo. 2016. Accessed March 31, 2022. https://www.duo.uio.no/bitstream/handle/10852/53674/PhD-Chortatos-DUO.pdf?sequence=1
11.Chortatos A, Iversen PO, Haugen M, Eberhard-Gran M, Bjelland EK, Veierød MB. Nausea and vomiting in pregnancy—association with pelvic girdle pain during pregnancy and 4-6 months post-partum. BMC Pregnancy Childbirth. 2018;18(1):137. doi: 10.1186/s12884-018-1764-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Bertone-Johnson ER, Hankinson SE, Johnson SR, Manson JE. A simple method of assessing premenstrual syndrome in large prospective studies. J Reprod Med. 2007;52(9):779-786. [PubMed] [Google Scholar]
13.O’Brien PMS, Bäckström T, Brown C, et al. Towards a consensus on diagnostic criteria, measurement and trial design of the premenstrual disorders: the ISPMD Montreal consensus. Arch Womens Ment Health. 2011;14(1):13-21. doi: 10.1007/s00737-010-0201-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eAppendix 1. The Norwegian Mother, Father and Child Cohort Study (MoBa) Sample

eAppendix 2. Implementation of MoBaPsychGen Pipeline and Polygenic Risk Scores Calculation

eAppendix 3. Phenotypic Description of Subsample Without History Of Psychiatric Diagnosis

eFigure 1. Study Sample

eAppendix 4. Associations Between the Symptoms of Premenstrual Disorders and PRSs for Major Psychiatric Disorders – a Multiple Regression Model

eFigure 2. Associations of the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders - Multiple Logistic Regression Model Associations

eAppendix 5. Nagelkerke’s Pseudo-R² From Logistic Regression Models for the Association Between the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eFigure 3. Nagelkerke’s Pseudo-R² From Logistic Regression Models for the Association Between the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eFigure 4. Odds Ratios for the Premenstrual Disorder Symptoms, by Deciles of PRSs

eTable. Associations of the Symptoms of Premenstrual Disorders (PMDs) and PRSs for Major Psychiatric Disorders

eReferences.

Click here for additional data file.^{(963.9KB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(13.3KB, pdf)}

[ybr230003r1] 1.Yonkers KA, Simoni MK. Premenstrual disorders. Am J Obstet Gynecol. 2018;218(1):68-74. doi: 10.1016/j.ajog.2017.05.045 [DOI] [PubMed] [Google Scholar]

[ybr230003r2] 2.Epperson CN, Steiner M, Hartlage SA, et al. Premenstrual dysphoric disorder: evidence for a new category for DSM-5. Am J Psychiatry. 2012;169(5):465-475. doi: 10.1176/appi.ajp.2012.11081302 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r3] 3.Forrester-Knauss C, Zemp Stutz E, Weiss C, Tschudin S. The interrelation between premenstrual syndrome and major depression: results from a population-based sample. BMC Public Health. 2011;11:795. doi: 10.1186/1471-2458-11-795 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r4] 4.Cao S, Jones M, Tooth L, Mishra GD. History of premenstrual syndrome and development of postpartum depression: a systematic review and meta-analysis. J Psychiatr Res. 2020;121:82-90. doi: 10.1016/j.jpsychires.2019.11.010 [DOI] [PubMed] [Google Scholar]

[ybr230003r5] 5.Slyepchenko A, Frey BN, Lafer B, Nierenberg AA, Sachs GS, Dias RS. Increased illness burden in women with comorbid bipolar and premenstrual dysphoric disorder: data from 1 099 women from STEP-BD study. Acta Psychiatr Scand. 2017;136(5):473-482. doi: 10.1111/acps.12797 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r6] 6.Magnus P, Birke C, Vejrup K, et al. Cohort profile update: the Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2016;45(2):382-388. doi: 10.1093/ije/dyw029 [DOI] [PubMed] [Google Scholar]

[ybr230003r7] 7.Corfield EC, Frei O, Shadrin AA, et al. The Norwegian Mother, Father, and Child cohort study (MoBa) genotyping data resource: MoBaPsychGen pipeline v.1. bioRxiv. Preprint posted June 26, 2022. Published online January 1, 2022. doi: 10.1101/2022.06.23.496289 [DOI]

[ybr230003r8] 8.Choi SW, O’Reilly PF. PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience. 2019;8(7):giz082. doi: 10.1093/gigascience/giz082 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r9] 9.Coombes BJ, Ploner A, Bergen SE, Biernacka JM. A principal component approach to improve association testing with polygenic risk scores. Genet Epidemiol. 2020;44(7):676-686. doi: 10.1002/gepi.22339 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r10] 10.Chortatos A. Nausea and vomiting in pregnancy: effects on maternal diet, health, and birth outcomes. An investigation using the Norwegian Mother and Child Cohort Study. Oslo Centre for Biostatistics and Epidemiiology and Department of Nutrition, University of Oslo. 2016. Accessed March 31, 2022. https://www.duo.uio.no/bitstream/handle/10852/53674/PhD-Chortatos-DUO.pdf?sequence=1

[ybr230003r11] 11.Chortatos A, Iversen PO, Haugen M, Eberhard-Gran M, Bjelland EK, Veierød MB. Nausea and vomiting in pregnancy—association with pelvic girdle pain during pregnancy and 4-6 months post-partum. BMC Pregnancy Childbirth. 2018;18(1):137. doi: 10.1186/s12884-018-1764-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ybr230003r12] 12.Bertone-Johnson ER, Hankinson SE, Johnson SR, Manson JE. A simple method of assessing premenstrual syndrome in large prospective studies. J Reprod Med. 2007;52(9):779-786. [PubMed] [Google Scholar]

[ybr230003r13] 13.O’Brien PMS, Bäckström T, Brown C, et al. Towards a consensus on diagnostic criteria, measurement and trial design of the premenstrual disorders: the ISPMD Montreal consensus. Arch Womens Ment Health. 2011;14(1):13-21. doi: 10.1007/s00737-010-0201-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders

Piotr Jaholkowski, MD, PhD

Alexey A Shadrin, PhD

Andreas Jangmo, PhD

Evgeniia Frei, MD

Markos Tesfaye, MD, PhD

Guy F L Hindley, MD

Marit Haram, MD, PhD

Zillur Rahman, PhD

Lavinia Athanasiu, PhD

Nora Refsum Bakken

Børge Holen, MD

Vera Fominykh, MD, PhD

Gleda Kutrolli, PhD

Pravesh Parekh, PhD

Nadine Parker, PhD

Linn Rødevand, PhD

Viktoria Birkenæs, MSc

Srdjan Djurovic, PhD

Oleksandr Frei, PhD

Kevin S O’Connell, PhD

Olav B Smeland, MD, PhD

Martin Tesli, MD, PhD

Ole A Andreassen, MD, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions

Introduction

Methods

Participants

Polygenic Risk Scores

Phenotype Measures

Statistical Analysis

Results

Figure 1. Associations of the Symptoms of Premenstrual Disorders (PMDs) With the Polygenic Risk Scores (PRSs) for Major Psychiatric Disorders.

Figure 2. Severity of Premenstrual Disorder (PMD) Symptoms and Polygenic Risk Scores (PRSs) for Major Psychiatric Disorders Among 44 620 Women Without a History of Psychiatric Disorders.

Discussion

Strengths and Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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