Polygenic Risk: Predicting Depression Outcomes in Clinical and Epidemiological Cohorts of Youths

Halldorsdottir, Thorhildur; Piechaczek, Charlotte; Matos, Ana Paula; Czamara, Darina; Pehl, Verena; Wagenbuechler, Petra; Feldmann, Lisa; Quickenstedt-Reinhardt, Peggy; Allgaier, Antje-Kathrin; Freisleder, Franz Joseph; Greimel, Ellen; Kvist, Tuomas; Lahti, Jari; Räikkönen, Katri; Rex‐Haffner, Monika; Arnarson, Eiríkur Örn; Craighead, W. Edward; Schulte‐Körne, Gerd; Binder, Elisabeth B.

doi:10.1176/appi.ajp.2019.18091014

Cited by 83 publications

(69 citation statements)

References 34 publications

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“…This could be due to several factors including small sample size (i.e., power) in the previous study among other differences in sample characteristics, measures, and study design. Our findings are in line with two recent studies, which found no evidence for an interaction between a PRS for major depression and self-reported childhood trauma in adulthood (21) and in childhood/youth (24), respectively. Two studies (37,38), applying similar methods but using self-reported recent SLEs (in adulthood), reported a significant interaction effect in line with the diathesis-stress model.…”

Section: G3e Interactionsupporting

confidence: 93%

“…Our findings are in line with two recent studies using self-reported trauma measures reporting a small but significant association between major depression PRSs and childhood trauma (21) and between the PRSs for major depression and neuroticism with recent SLE exposure, respectively (36). However, the majority of studies exploring main effects of genetic risk and SLE exposure and their interaction on mental health outcomes did not assess potential gene-environment correlations [e.g., (24,37)].…”

Section: Genetic Differencessupporting

confidence: 89%

“…This suggests passive rGE, in which the child's genetic predisposition (for mental health problems) is correlated with the environment that the child is born into (increased adversity owing to the parent's higher likelihood to experience mental health problems). As such, the well-known association between adoption and mental health, which has largely been attributed to stressful environmental factors in childhood (1,24), such as being exposed to trauma, abuse, or neglect, is likely better explained by a more complex model including a combination of genetic and environmental factors. It seems plausible that this finding may extend to general associations between childhood adversity-if experienced in the context of a biological family-and mental health outcomes, even if not resulting in an adoption.…”

Section: Genetic Differencesmentioning

confidence: 99%

“…Polygenic risk scores (PRSs)-a measure of the combined impact of all genotyped single nucleotide polymorphisms (18)-may be preferable to candidate genes to test for G3E effects (19). To our knowledge, only 5 studies have investigated G3E interaction between childhood adversity and genetic risk on mental health using PRSs, showing very mixed results (20)(21)(22)(23)(24). In all but one study, early-life adversity was self-reported and assessed simultaneously with mental health, making the assessment subjective and prone to hindsight and recall bias, resulting in low validity and substantial measurement error (16).…”

mentioning

confidence: 99%

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Childhood Adoption and Mental Health in Adulthood: The Role of Gene-Environment Correlations and Interactions in the UK Biobank

Lehto

Hägg

et al. 2020

Biological Psychiatry

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BACKGROUND: Being adopted early in life, an indicator of exposure to early-life adversity, has been consistently associated with poor mental health outcomes in adulthood. Such associations have largely been attributed to stressful environments, e.g., exposure to trauma, abuse, or neglect. However, mental health is substantially heritable, and genetic influences may contribute to the exposure to childhood adversity, resulting in potential genetic confounding of such associations. METHODS: Here, we explored associations between childhood adoption and mental health-related outcomes in midlife in 243,797 UK Biobank participants (n adopted = 3151). We used linkage disequilibrium score regression and polygenic risk scores for depressive symptoms, schizophrenia, neuroticism, and subjective well-being to address potential genetic confounding (gene-environment correlations) and gene-environment interactions. As outcomes, we explored depressive symptoms, bipolar disorder, neuroticism, loneliness, and mental health-related socioeconomic and psychosocial measures in adoptees compared with nonadopted participants. RESULTS: Adoptees were slightly worse off on almost all mental, socioeconomic, and psychosocial measures. Each standard deviation increase in polygenic risk for depressive symptoms, schizophrenia, and neuroticism was associated with 6%, 5%, and 6% increase in the odds of being adopted, respectively. Significant genetic correlations between adoption status and depressive symptoms, major depression, and schizophrenia were observed. No evidence for gene-environment interaction between genetic risk and adoption on mental health was found. CONCLUSIONS: The association between childhood adoption and mental health cannot fully be attributed to stressful environments but is partly explained by differences in genetic risk between adoptees and those who have not been adopted (i.e., gene-environment correlation).

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Section: G3e Interactionsupporting

confidence: 93%

Section: Genetic Differencessupporting

confidence: 89%

Section: Genetic Differencesmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Childhood Adoption and Mental Health in Adulthood: The Role of Gene-Environment Correlations and Interactions in the UK Biobank

Lehto

Hägg

et al. 2020

Biological Psychiatry

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“…Polygenic risk scores (PRS), which sum the number of "risk" variants that an individual possesses for a trait weighted by their effect size (Martin, Daly, Robinson, Hyman, & Neale, 2018), can be used as an indicator of an individual's genetic liability to depression. Several studies have used depression PRS taken from GWAS of major depressive disorder or depressive symptoms in adult populations to investigate how they influence depressive symptomatology over development in younger populations (Halldorsdottir et al, 2019;Kwong, López-López, et al, 2019;Rice et al, 2018;Riglin et al, 2018). One study found that the influence of an MDD PRS on emotional problems increased with age with weaker effects in childhood which developed in adulthood (Riglin et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Polygenic Risk for Depression is Associated with the Severity and Rate of Change in Depressive Symptoms Across Adolescence

Kwong

Morris

Pearson

et al. 2020

Preprint

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Adolescence marks a period where depression will commonly onset and previous research using twin studies has suggested that genetic influences play a role in how depression develops and changes across adolescence. Recent genome-wide association studies have also shown that common genetic variants − which can be combined into a polygenic risk score (PRS) − are also implicated in depression. However, the role of PRS in adolescent depression and changes in adolescent depression is not yet understood. We aimed to examine the association between a PRS for depressive symptoms and depressive symptoms across adolescence and young adulthood, and how polygenic risk is associated with changes in depressive symptoms using two methods: cross-sectional analysis and multilevel growth curve modelling to examine the rate of change over time. Using data from over 6000 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC) we examined associations between genetic liability to depressive symptoms (PRS for depressive symptoms) and self-reported depressive symptoms (short mood and feelings questionnaire over 9 occasions from 10-24 years). We examined cross-sectional associations at each age and longitudinal trajectories of depressive symptoms in a repeated measures framework using growth curve analysis. The PRS was associated with depressive symptoms throughout adolescence and young adulthood in cross-sectional and growth curve analyses, though associations were stronger in the latter analyses. Growth curve analyses also provided additional insights, demonstrating that individuals with a higher PRS had steeper trajectories of depressive symptoms across adolescence with a greater increasing rate of change. These results show that common genetics variants as indexed by a PRS for depressive symptoms influence both the severity and rate of change in adolescent depressive symptoms. Longitudinal data that make use of repeated measures designs have the potential to provide greater insights into the factors that influence the onset and persistence of adolescent depression.

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Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts

Grimes,

Adams,

Thng

et al. 2024

JAMA Psychiatry

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ImportanceAdolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.ObjectiveTo investigate univariate and multivariate genetic risk for adolescent depression trajectories and assess generalizability across ancestries.Design, Setting, and ParticipantsThis cohort study entailed longitudinal growth modeling followed by polygenic risk score (PRS) association testing for individual and multitrait genetic models. Two longitudinal cohorts from the US and UK were used: the Adolescent Brain and Cognitive Development (ABCD; N = 11 876) study and the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8787) study. Included were adolescents with genetic information and depression measures at up to 8 and 4 occasions, respectively. Study data were analyzed January to July 2023.Main Outcomes and MeasuresTrajectories were derived from growth mixture modeling of longitudinal depression symptoms. PRSs were computed for depression, anxiety, neuroticism, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism in European ancestry. Genomic structural equation modeling was used to build multitrait genetic models of psychopathology followed by multitrait PRS. Depression PRSs were computed in African, East Asian, and Hispanic ancestries in the ABCD cohort only. Association testing was performed between all PRSs and trajectories for both cohorts.ResultsA total sample size of 14 112 adolescents (at baseline: mean [SD] age, 10.5 [0.5] years; 7269 male sex [52%]) from both cohorts were included in this analysis. Distinct depression trajectories (stable low, adolescent persistent, increasing, and decreasing) were replicated in the ALSPAC cohort (6096 participants; 3091 female [51%]) and ABCD cohort (8016 participants; 4274 male [53%]) between ages 10 and 17 years. Most univariate PRSs showed significant uniform associations with persistent trajectories, but fewer were significantly associated with intermediate (increasing and decreasing) trajectories. Multitrait PRSs—derived from a hierarchical factor model—showed the strongest associations for persistent trajectories (ABCD cohort: OR, 1.46; 95% CI, 1.26-1.68; ALSPAC cohort: OR, 1.34; 95% CI, 1.20-1.49), surpassing the effect size of univariate PRS in both cohorts. Multitrait PRSs were associated with intermediate trajectories but to a lesser extent (ABCD cohort: hierarchical increasing, OR, 1.27; 95% CI, 1.13-1.43; decreasing, OR, 1.23; 95% CI, 1.09-1.40; ALSPAC cohort: hierarchical increasing, OR, 1.16; 95% CI, 1.04-1.28; decreasing, OR, 1.32; 95% CI, 1.18-1.47). Transancestral genetic risk for depression showed no evidence for association with trajectories.Conclusions and RelevanceResults of this cohort study revealed a high multitrait genetic loading of persistent symptom trajectories, consistent across traits and cohorts. Variability in univariate genetic association with intermediate trajectories may stem from environmental factors. Multitrait genetics may strengthen depression prediction models, but more diverse data are needed for generalizability.

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Polygenic Risk: Predicting Depression Outcomes in Clinical and Epidemiological Cohorts of Youths

Cited by 83 publications

References 34 publications

Childhood Adoption and Mental Health in Adulthood: The Role of Gene-Environment Correlations and Interactions in the UK Biobank

Childhood Adoption and Mental Health in Adulthood: The Role of Gene-Environment Correlations and Interactions in the UK Biobank

Polygenic Risk for Depression is Associated with the Severity and Rate of Change in Depressive Symptoms Across Adolescence

Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts

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