Abstract
Background:
While genetic factors are important influences on maternal mental health, few studies have used symptom-level analyses to examine how genetic liability is related to the experience of specific mental health problems in mothers. A symptom-level approach can account for disorder heterogeneity and delineate key associations between genetic liabilities and mental health.
Methods:
Three waves of data (30 weeks of gestation, 6 and 18 months postpartum) from the Norwegian Mother, Father and Child Cohort Study (MoBa) were used to assess item-level associations between genetic liabilities to depression, anxiety, neuroticism and positive affect, and maternal mental health phenotypes (i.e., symptoms of anxiety, depression, positive and negative affect) using a network analysis approach. Sample sizes ranged from 46,537 to 59,308 mothers.
Results:
PGSs exhibited both phenotype-specific associations (e.g., depression PGS linked with hopelessness, anxiety PGS linked with worry) and cross-phenotype (e.g., depression PGS linked with nervousness, positive affect PGS inversely related to anxiety and depressive symptoms) relationships, with partial correlations ranging between r = −0.025 and r = 0.024. Some PGS-phenotype associations were consistent (e.g., depression PGS linked with feeling like screaming or banging on something across all waves) and others inconsistent (e.g., anxiety PGS linked with nervousness only at 6 months postpartum) across the perinatal and postpartum periods.
Conclusions:
Our findings highlight symptom-level associations between PGSs and maternal mental health, which may be obscured when global measures of mental health (e.g., overall scores) are used. Identifying symptom-specific PGS associations could advance current understanding of aetiological influences on maternal mental health.
While genetic factors are important influences on maternal mental health, few studies have used symptom-level analyses to examine how genetic liability is related to the experience of specific mental health problems in mothers. A symptom-level approach can account for disorder heterogeneity and delineate key associations between genetic liabilities and mental health.
Methods:
Three waves of data (30 weeks of gestation, 6 and 18 months postpartum) from the Norwegian Mother, Father and Child Cohort Study (MoBa) were used to assess item-level associations between genetic liabilities to depression, anxiety, neuroticism and positive affect, and maternal mental health phenotypes (i.e., symptoms of anxiety, depression, positive and negative affect) using a network analysis approach. Sample sizes ranged from 46,537 to 59,308 mothers.
Results:
PGSs exhibited both phenotype-specific associations (e.g., depression PGS linked with hopelessness, anxiety PGS linked with worry) and cross-phenotype (e.g., depression PGS linked with nervousness, positive affect PGS inversely related to anxiety and depressive symptoms) relationships, with partial correlations ranging between r = −0.025 and r = 0.024. Some PGS-phenotype associations were consistent (e.g., depression PGS linked with feeling like screaming or banging on something across all waves) and others inconsistent (e.g., anxiety PGS linked with nervousness only at 6 months postpartum) across the perinatal and postpartum periods.
Conclusions:
Our findings highlight symptom-level associations between PGSs and maternal mental health, which may be obscured when global measures of mental health (e.g., overall scores) are used. Identifying symptom-specific PGS associations could advance current understanding of aetiological influences on maternal mental health.
| Original language | English |
|---|---|
| Article number | 120228 |
| Number of pages | 10 |
| Journal | Journal of Affective Disorders |
| Volume | 392 |
| Early online date | 3 Sept 2025 |
| DOIs | |
| Publication status | Published - 1 Jan 2026 |
Bibliographical note
Publisher Copyright:© 2025 The Authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Maternal anxiety and depression
- Maternal mental health
- Network analysis
- Polygenic risk
- Polygenic scores
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