1
|
Kendler KS, Lönn SL, Sundquist J, Sundquist K. The joint effects of genetic liability and the death of close relatives on risk for major depression and alcohol use disorder in a Swedish national sample. Psychol Med 2024; 54:1709-1716. [PMID: 38173119 DOI: 10.1017/s0033291723003641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
BACKGROUND To determine whether genetic risk factors for major depression (MD) and alcohol use disorder (AUD) interact with a potent stressor - death of spouse, parent, and sibling - in predicting episodes of, respectively, MD and AUD. METHODS MD and AUD registrations were assessed from national Swedish registries. In individuals born in Sweden 1960-1970, we identified 7586, 388 459, and 34 370 with the loss of, respectively, a spouse, parent, and sibling. We started following subjects at age 18 or the year 2002 with end of follow-up in 2018. We examined time to event - a registration for MD within 6 months or AUD within a year - on an additive scale, using the Nelson-Aalen estimator. Genetic risk was assessed by the Family Genetic Risk Score (FGRS). RESULTS In separate models controlling for the main effects of death of spouse, parent, and sibling, FGRS, and sex, significant interactions were seen in all analyses between genetic risk for MD and death of relative in prediction of subsequent MD registration. A similar pattern of results, albeit with weaker interaction effects, was seen for genetic risk for AUD and risk for AUD registration. Genetic risk for bipolar disorder (BD) and anxiety disorders (AD) also interacted with event exposure in predicting MD. CONCLUSIONS Genetic risk for both MD and AUD act in part by increasing the sensitivity of individuals to the pathogenic effects of environmental stressors. For prediction of MD, similar effects are also seen for genetic risk for AD and BD.
Collapse
Affiliation(s)
- Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Sara L Lönn
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health, Lund University, Malmö, Sweden
| | - Kristina Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health, Lund University, Malmö, Sweden
| |
Collapse
|
2
|
Schowe AM, Godara M, Czamara D, Adli M, Singer T, Binder EB. Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01795-y. [PMID: 38587666 DOI: 10.1007/s00406-024-01795-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 03/09/2024] [Indexed: 04/09/2024]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic was accompanied by an increase in mental health challenges including depression, stress, loneliness, and anxiety. Common genetic variants can contribute to the risk for psychiatric disorders and may present a risk factor in times of crises. However, it is unclear to what extent polygenic risk played a role in the mental health response to the COVID-19 pandemic. In this study, we investigate whether polygenic scores (PGSs) for mental health-related traits can distinguish between four resilience-vulnerability trajectories identified during the COVID-19 pandemic and associated lockdowns in 2020/21. We used multinomial regression in a genotyped subsample (n = 1316) of the CovSocial project. The most resilient trajectory characterized by the lowest mental health burden and the highest recovery rates served as the reference group. Compared to this most resilient trajectory, a higher value on the PGS for the well-being spectrum decreased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.3%). Conversely, a higher value on the PGS for neuroticism increased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.2%). Latent change in mental health burden extracted from the resilience-vulnerability trajectories was not associated with any PGS. Although our findings support an influence of PGS on mental health during COVID-19, the small added explained variance suggests limited utility of such genetic markers for the identification of vulnerable individuals in the general population.
Collapse
Affiliation(s)
- Alicia M Schowe
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany.
- Graduate School of Systemic Neuroscience, Ludwig Maximilian University, Munich, Germany.
| | - Malvika Godara
- Social Neuroscience Lab, Max Planck Society, 10557, Berlin, Germany.
| | - Darina Czamara
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Mazda Adli
- Department of Psychiatry and Neurosciences, CCM, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Center for Psychiatry, Psychotherapy and Psychosomatic Medicine, Fliedner Klinik Berlin, Berlin, Germany
| | - Tania Singer
- Social Neuroscience Lab, Max Planck Society, 10557, Berlin, Germany
| | - Elisabeth B Binder
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| |
Collapse
|
3
|
Lu T, Silveira PP, Greenwood CMT. Development of risk prediction models for depression combining genetic and early life risk factors. Front Neurosci 2023; 17:1143496. [PMID: 37534032 PMCID: PMC10390723 DOI: 10.3389/fnins.2023.1143496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Background Both genetic and early life risk factors play important roles in the pathogenesis and progression of adult depression. However, the interplay between these risk factors and their added value to risk prediction models have not been fully elucidated. Methods Leveraging a meta-analysis of major depressive disorder genome-wide association studies (N = 45,591 cases and 97,674 controls), we developed and optimized a polygenic risk score for depression using LDpred in a model selection dataset from the UK Biobank (N = 130,092 European ancestry individuals). In a UK Biobank test dataset (N = 278,730 European ancestry individuals), we tested whether the polygenic risk score and early life risk factors were associated with each other and compared their associations with depression phenotypes. Finally, we conducted joint predictive modeling to combine this polygenic risk score with early life risk factors by stepwise regression, and assessed the model performance in identifying individuals at high risk of depression. Results In the UK Biobank test dataset, the polygenic risk score for depression was moderately associated with multiple early life risk factors. For instance, a one standard deviation increase in the polygenic risk score was associated with 1.16-fold increased odds of frequent domestic violence (95% CI: 1.14-1.19) and 1.09-fold increased odds of not having access to medical care as a child (95% CI: 1.05-1.14). However, the polygenic risk score was more strongly associated with depression phenotypes than most early life risk factors. A joint predictive model integrating the polygenic risk score, early life risk factors, age and sex achieved an AUROC of 0.6766 for predicting strictly defined major depressive disorder, while a model without the polygenic risk score and a model without any early life risk factors had an AUROC of 0.6593 and 0.6318, respectively. Conclusion We have developed a polygenic risk score to partly capture the genetic liability to depression. Although genetic and early life risk factors can be correlated, joint predictive models improved risk stratification despite limited improvement in magnitude, and may be explored as tools to better identify individuals at high risk of depression.
Collapse
Affiliation(s)
- Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
| | - Patrícia Pelufo Silveira
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Center, McGill University, Montreal, QC, Canada
| | - Celia M. T. Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
| |
Collapse
|
4
|
Flint J. The genetic basis of major depressive disorder. Mol Psychiatry 2023; 28:2254-2265. [PMID: 36702864 PMCID: PMC10611584 DOI: 10.1038/s41380-023-01957-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 12/30/2022] [Accepted: 01/11/2023] [Indexed: 01/27/2023]
Abstract
The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.
Collapse
Affiliation(s)
- Jonathan Flint
- Department of Psychiatry and Biobehavioral Sciences, Billy and Audrey Wilder Endowed Chair in Psychiatry and Neuroscience, Center for Neurobehavioral Genetics, 695 Charles E. Young Drive South, 3357B Gonda, Box 951761, Los Angeles, CA, 90095-1761, USA.
| |
Collapse
|
5
|
Thorp JG, Gerring ZF, Colodro-Conde L, Byrne EM, Medland SE, Middeldorp CM, Derks EM. The association between trauma exposure, polygenic risk and individual depression symptoms. Psychiatry Res 2023; 321:115101. [PMID: 36774750 PMCID: PMC9977888 DOI: 10.1016/j.psychres.2023.115101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/11/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Traumatic experiences are associated with increased risk for major depressive disorder (MDD). This study sought to determine the extent that trauma exposure, depression polygenic risk scores (PRS), and their interaction are associated with MDD and individual depression symptoms. METHODS Data from 102,182 individuals from the large-scale UK Biobank population cohort was analysed. A series of regression analyses were conducted to estimate the association between trauma, depression PRS and 1) current depression, 2) lifetime MDD case-control status, 3) nine individual current depressive symptoms, and 4) thirteen individual symptoms experienced during a major depressive episode. Additive and multiplicative PRS-by-trauma interactions were also assessed. RESULTS Trauma and depression PRS were significantly associated with both current depression and lifetime MDD. A positive, additive interaction effect was observed on depression, but multiplicative interactions were not significant. Trauma exposure and depression PRS were associated with specific patterns of depression symptoms; Trauma was associated with low self-esteem, suicidal ideation, and atypical (but not typical) neurovegetative symptoms. Additive interaction effects were observed on six out of nine current depressive symptoms. CONCLUSIONS Trauma exposure and genetic predisposition to depression may lead to particular symptomatology, which may contribute to the extreme clinical heterogeneity observed in individuals with major depression.
Collapse
Affiliation(s)
- Jackson G Thorp
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia.
| | - Zachary F Gerring
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Lucía Colodro-Conde
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Enda M Byrne
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia; Child Health Research Centre, University of Queensland, Brisbane, Australia
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Christel M Middeldorp
- Child Health Research Centre, University of Queensland, Brisbane, Australia; Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Australia
| | - Eske M Derks
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| |
Collapse
|