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| PMID |
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| TITLE |
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| Polygenic Risk Scores Derived From Varying Definitions of Depression and Risk of Depression. |
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| ABSTRACT |
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| Importance |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. |
| Objective |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). |
| Design, Setting, and Participants |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. |
| Main Outcome and Measures |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health. |
| Results |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health. Participants included 12 106 (71% female; mean age, 42.3 years; range, 18-88 years) patients meeting criteria for MDD and 12 621 (55% female; mean age, 60.9 years; range, 43-87 years) control participants with no history of psychiatric disorders. The effect size of the PRS was proportional to the discovery sample size, with the largest study having the largest effect size with the odds ratio for MDD (1.75; 95% CI, 1.73-1.77) per SD of PRS and the PRS derived from ICD-10 codes documented in hospitalization records in a population health cohort having the lowest odds ratio (1.14; 95% CI, 1.12-1.16). When accounting for differences in sample size, the PRS from a genome-wide association study of patients meeting diagnostic criteria for MDD and control participants was the best estimator of MDD, but not in those with self-reported depression, and associations with higher odds ratios with childhood adverse experiences and measures of somatic distress. |
| Conclusions and Relevance |
NlmCategory: UNASSIGNED |
| Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health. Participants included 12 106 (71% female; mean age, 42.3 years; range, 18-88 years) patients meeting criteria for MDD and 12 621 (55% female; mean age, 60.9 years; range, 43-87 years) control participants with no history of psychiatric disorders. The effect size of the PRS was proportional to the discovery sample size, with the largest study having the largest effect size with the odds ratio for MDD (1.75; 95% CI, 1.73-1.77) per SD of PRS and the PRS derived from ICD-10 codes documented in hospitalization records in a population health cohort having the lowest odds ratio (1.14; 95% CI, 1.12-1.16). When accounting for differences in sample size, the PRS from a genome-wide association study of patients meeting diagnostic criteria for MDD and control participants was the best estimator of MDD, but not in those with self-reported depression, and associations with higher odds ratios with childhood adverse experiences and measures of somatic distress. These findings suggest that increasing sample sizes, regardless of the depth of phenotyping, may be most informative for estimating risk of depression. The next generation of genome-wide association studies should, like the Australian Genetics of Depression Study, have both large sample sizes and extensive phenotyping to capture genetic risk factors for MDD not identified by other definitions of depression. |
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| DATE PUBLISHED |
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| HISTORY |
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| PUBSTATUS |
PUBSTATUSDATE |
| pmc-release |
2022/08/11 |
| entrez |
2021/08/11 12:18 |
| pubmed |
2021/08/12 06:00 |
| medline |
2021/08/12 06:00 |
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| AUTHORS |
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| NAME |
COLLECTIVENAME |
LASTNAME |
FORENAME |
INITIALS |
AFFILIATION |
AFFILIATIONINFO |
| Mitchell BL |
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Mitchell |
Brittany L |
BL |
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School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia. |
| Thorp JG |
|
Thorp |
Jackson G |
JG |
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Faculty of Medicine, The University of Queensland, Brisbane, Australia. |
| Wu Y |
|
Wu |
Yeda |
Y |
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Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. |
| Campos AI |
|
Campos |
Adrian I |
AI |
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School of Biomedical Sciences, The University of Queensland, Brisbane, Australia. |
| Nyholt DR |
|
Nyholt |
Dale R |
DR |
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Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Australia. |
| Gordon SD |
|
Gordon |
Scott D |
SD |
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QIMR Berghofer Medical Research Institute, Brisbane, Australia. |
| Whiteman DC |
|
Whiteman |
David C |
DC |
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QIMR Berghofer Medical Research Institute, Brisbane, Australia. |
| Olsen CM |
|
Olsen |
Catherine M |
CM |
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QIMR Berghofer Medical Research Institute, Brisbane, Australia. |
| Hickie IB |
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Hickie |
Ian B |
IB |
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Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia. |
| Martin NG |
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Martin |
Nicholas G |
NG |
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QIMR Berghofer Medical Research Institute, Brisbane, Australia. |
| Medland SE |
|
Medland |
Sarah E |
SE |
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QIMR Berghofer Medical Research Institute, Brisbane, Australia. |
| Wray NR |
|
Wray |
Naomi R |
NR |
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Queensland Brain Institute, The University of Queensland, Brisbane, Australia. |
| Byrne EM |
|
Byrne |
Enda M |
EM |
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Child Health Research Centre, The University of Queensland, Brisbane, Australia. |
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| INVESTIGATORS |
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| JOURNAL |
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| VOLUME: |
| ISSUE: |
| TITLE: JAMA psychiatry |
| ISOABBREVIATION: JAMA Psychiatry |
| YEAR: 2021 |
| MONTH: Aug |
| DAY: 11 |
| MEDLINEDATE: |
| SEASON: |
| CITEDMEDIUM: Internet |
| ISSN: 2168-6238 |
| ISSNTYPE: Electronic |
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| MEDLINE JOURNAL |
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| MEDLINETA: JAMA Psychiatry |
| COUNTRY: United States |
| ISSNLINKING: 2168-622X |
| NLMUNIQUEID: 101589550 |
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| PUBLICATIONTYPE TEXT |
| Journal Article |
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