Minimal phenotyping yields genome-wide association signals of low specificity for major depression

Cai, Na; Revez, Joana A.; Adams, Mark J.; Andlauer, Till F. M.; Breen, Gerome; Byrne, Enda M.; Clarke, Toni‐Kim; Forstner, Andreas J.; Grabe, Hans‐Jörgen; Hamilton, Steven P.; Levinson, Douglas F.; Lewis, Cathryn M.; Lewis, Glyn; Martin, Nicholas G.; Milaneschi, Yuri; Mors, Ole; Müller‐Myhsok, Bertram; Penninx, Brenda W.J.H.; Perlis, Roy H.; Pistis, Giorgio; Potash, James B.; Preisig, Martin; Shi, Jianxin; Smoller, Jordan W.; Streit, F.; Tiemeier, Henning; Uher, Rudolf; Auwera, Sandra Van der; Viktorin, Alexander; Weissman, Myrna M.; Kendler, Kenneth S.; Flint, Jonathan

doi:10.1038/s41588-020-0594-5

Cited by 235 publications

(270 citation statements)

References 89 publications

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“…Assuming lifetime risk of 15%, h 2 SNP for Lifetime Depression (MHQ) ranged between 11-13%, depending on the control group. This range is notably different to the h 2 SNP estimate of 26% reported by Cai, et al10 for the corresponding phenotype named 'LifetimeMDD'. Much of the difference is accounted for by methodology and lifetime risk assumptions.…”

contrasting

confidence: 89%

“…Our results converge on the conclusion that repeated measures of depression may be used to reduce misclassification of depression cases and controls and increase the sample size of credible depression cases in addition to those defined using the MHQ. Cai, et al 10 compared depression phenotypes derived from different sources of information in the UKB and showed that the strength of the genetic contribution was highest in CIDI-defined cases. We propose that our findings build upon this work by considering that the number of endorsed measures of depression can be used to decrease misclassification by identifying those participants who perhaps had a single mild episode of depression but would not meet the CIDI diagnostic criteria.…”

Section: Discussionmentioning

confidence: 99%

“…Another interpretation is that more endorsements represent greater severity, but this is not easily demonstrable in the current study because we have not directly measured severity. However, Cai, et al10 observed higher h 2 SNP…”

mentioning

confidence: 91%

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Multiple measures of depression to enhance validity of Major Depressive Disorder in the UK Biobank

Glanville

Coleman

Howard

et al. 2020

Preprint

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Background: The UK Biobank (UKB) contains data with varying degrees of reliability and completeness for assessing depression. A third of participants completed a Mental Health Questionnaire (MHQ) containing the gold-standard Composite International Diagnostic Interview (CIDI) criteria for assessing mental health disorders. Aims: To investigate whether multiple observations of depression from sources other than the MHQ can enhance the validity of Major Depressive Disorder. Methods: In participants who did not complete the MHQ (n = 325k), we calculated the number of other depression measures endorsed, e.g. from hospital episode statistics and interview data. We compared the strength of the genetic contribution in cases defined this way, to CIDI-defined cases. We compared the variance explained by polygenic risk scores (PRS), area under the curve attributable to PRS, SNP-based heritability, and genetic correlations with summary statistics from the Psychiatric Genomics Consortium Major Depressive Disorder (PGC MDD) GWAS. Results: The strength of the genetic contribution increased with the number of measures endorsed. For example, SNP-based heritability increased from 7% with one measure of depression to 21% with four or five. The strength of the genetic contribution to cases defined by at least two measures approximated that for CIDI-defined cases. Most genetic correlations between UKB and PGC MDD exceeded 0.7, but there was variability between pairwise comparisons. Conclusions: Multiple measures of depression can serve as a reliable approximation for case-status where the CIDI measure is not available, with the implication that sample size can be optimised using the full suite of UKB data.

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confidence: 89%

Section: Discussionmentioning

confidence: 99%

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Multiple measures of depression to enhance validity of Major Depressive Disorder in the UK Biobank

Glanville

Coleman

Howard

et al. 2020

Preprint

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“…As the hierarchical model reflects a constrained version of the bifactor model, the bifactor model is always able to approximate the empirical genetic covariance as well as, or better than, the hierarchical model. 46 Indeed, the bifactor model fit the data very well (c 2 [28] = 120.35, AIC = 196.35, CFI = .982, SRMR = .062). Multivariate GWAS results using the bifactor model are presented here in order to more fully consider the utility of a p-factor, but are treated as exploratory and post-hoc.…”

Section: Post-hoc Multivariate Gwas: Bifactor Specification Of Pmentioning

confidence: 92%

“…51 Moreover, our results may have been influenced by the phenotyping and caseascertainment methods used methods used. For instance, we included data from have been influenced by the inclusion of GWAS cohorts relying primarily on self-report phenotypes, 28 though sensitivity analyses suggested minimal differences when excluding GWAS that used self-report cohorts. Future analyses may benefit from evaluating these findings using a set of traits that is balanced with respect to statistical power.…”

Section: Estimating Causal Effects Of Problematic Alcohol Use On Psycmentioning

confidence: 99%

Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis

Grotzinger

Mallard

Akingbuwa

et al. 2020

Preprint

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We systematically interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis. We identify four broad factors (Neurodevelopmental, Compulsive, Psychotic, and Internalizing) that underlie genetic correlations among the disorders, and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce Stratified Genomic Structural Equation Modelling, which we use to identify gene sets and genomic regions that disproportionately contribute to pleiotropy, including protein-truncating variant intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for pleiotropy between disorders with psychotic features. Multivariate association analyses detect a total of 152 (20 novel) independent loci which act on the four factors, and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate to high genetic correlations across all 11 disorders, we find very little utility of, or evidence for, a single dimension of genetic risk across psychiatric disorders.

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Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder

Miller,

Kuo,

Johnson

et al. 2023

JAMA Netw Open

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ImportanceCurrent Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) diagnoses of substance use disorders rely on criterion count–based approaches, disregarding severity grading indexed by individual criteria.ObjectiveTo examine correlates of alcohol use disorder (AUD) across count-based severity groups (ie, mild, moderate, mild-to-moderate, severe), identify specific diagnostic criteria indicative of greater severity, and evaluate whether specific criteria within mild-to-moderate AUD differentiate across relevant correlates and manifest in greater hazards of severe AUD development.Design, Setting, and ParticipantsThis cohort study involved 2 cohorts from the family-based Collaborative Study on the Genetics of Alcoholism (COGA) with 7 sites across the United States: cross-sectional (assessed 1991-2005) and longitudinal (assessed 2004-2019). Statistical analyses were conducted from December 2022 to June 2023.Main Outcomes and MeasuresSociodemographic, alcohol-related, psychiatric comorbidity, brain electroencephalography (EEG), and AUD polygenic score measures as correlates of DSM-5 AUD levels (ie, mild, moderate, severe) and criterion severity–defined mild-to-moderate AUD diagnostic groups (ie, low-risk vs high-risk mild-to-moderate).ResultsA total of 13 110 individuals from the cross-sectional COGA cohort (mean [SD] age, 37.8 [14.2] years) and 2818 individuals from the longitudinal COGA cohort (mean baseline [SD] age, 16.1 [3.2] years) were included. Associations with alcohol-related, psychiatric, EEG, and AUD polygenic score measures reinforced the role of increasing criterion counts as indexing severity. Yet within mild-to-moderate AUD (2-5 criteria), the presence of specific high-risk criteria (eg, withdrawal) identified a group reporting heavier drinking and greater psychiatric comorbidity even after accounting for criterion count differences. In longitudinal analyses, prior mild-to-moderate AUD characterized by endorsement of at least 1 high-risk criterion was associated with more accelerated progression to severe AUD (adjusted hazard ratio [aHR], 11.62; 95% CI, 7.54-17.92) compared with prior mild-to-moderate AUD without endorsement of high-risk criteria (aHR, 5.64; 95% CI, 3.28-9.70), independent of criterion count.Conclusions and RelevanceIn this cohort study of a combined 15 928 individuals, findings suggested that simple count-based AUD diagnostic approaches to estimating severe AUD vulnerability, which ignore heterogeneity among criteria, may be improved by emphasizing specific high-risk criteria. Such emphasis may allow better focus on individuals at the greatest risk and improve understanding of the development of AUD.

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Minimal phenotyping yields genome-wide association signals of low specificity for major depression

Cited by 235 publications

References 89 publications

Multiple measures of depression to enhance validity of Major Depressive Disorder in the UK Biobank

Multiple measures of depression to enhance validity of Major Depressive Disorder in the UK Biobank

Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis

Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder

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