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Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries.

ABSTRACT: OBJECTIVE:To investigate whether diagnostic data from structured interviews, primary care and specialist care registries on major depressive disorder (MDD), anxiety disorders (AD) and alcohol use disorder (AUD) identify the same individuals, yield comparable comorbidity estimates and reflect the same genetic influences. METHODS:Registry data from primary and specialist care were available for 11 727 twins and diagnostic interview data for 2271 of these. We used logistic regression analyses and biometric modelling to investigate the overlap between the data sources. RESULTS:Most individuals meeting diagnostic criteria at interview were not registered with a corresponding diagnosis. The rates of registration were higher for MDD (36% in primary care and 15% in specialist care) and AD (21% and 18%) than for AUD (3% and 7%). Comorbidity estimated as odds ratios, but not as polychoric correlations, was higher in the registries than in the interviews. Genetic influences on the disorders were highly correlated across data sources (median r = 0.81), bordering unity for MDD and AD. CONCLUSION:Prevalence and comorbidity estimates differ between registries and population-based assessment. Nevertheless, diagnoses from health registries reflect the same genetic influences as common mental disorders assessed in the general population, indicating generalizability of aetiological factors across data sources.

SUBMITTER: Torvik FA

PROVIDER: S-EPMC6322205 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries.

Torvik F A FA Ystrom E E Gustavson K K Rosenström T H TH Bramness J G JG Gillespie N N Aggen S H SH Kendler K S KS Reichborn-Kjennerud T T

Acta psychiatrica Scandinavica 20171026 1

<h4>Objective</h4>To investigate whether diagnostic data from structured interviews, primary care and specialist care registries on major depressive disorder (MDD), anxiety disorders (AD) and alcohol use disorder (AUD) identify the same individuals, yield comparable comorbidity estimates and reflect the same genetic influences.<h4>Methods</h4>Registry data from primary and specialist care were available for 11 727 twins and diagnostic interview data for 2271 of these. We used logistic regression ...[more]

PMID: 29072781

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Project description:BackgroundDifferent diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.MethodData collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.ResultsA total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97).ConclusionsThe MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.

Project description:ObjectiveMental disorders are heritable and polygenic, and genome-wide genetic correlations (rg) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, rg may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions.MethodsThe authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of "causal" variants for a given trait ("polygenicity"), the number of variants shared between traits, and the genetic correlation of shared variants (rgs). Local rg was investigated using LAVA.ResultsAmong mental disorders, ADHD was the least polygenic (5.6K "causal" variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in rg and rgs. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local rg (r=0.88, p<0.001).ConclusionsThere is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction.

Project description:ObjectivesTo investigate the correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Secondary aims were to investigate length of sick leave by diagnoses on sick leave certificates, diagnoses made in structured interviews and symptom severity.DesignObservational study consisting of a secondary analysis of data from a randomised controlled trial and an observational study.SettingThe regions of Stockholm and Västra Götaland, Sweden.Participants480 people on sick leave for common mental disorders.InterventionsParticipants were examined with structured psychiatric interviews and self-rated symptom severity scales.Outcome measures(1) Sick leave certificate diagnoses, (2) diagnoses from the Mini International Neuropsychiatric Interview and the Self-rated Stress-Induced Exhaustion Disorder (SED) Instrument (s-ED), (3) symptom severity (Montgomery-Asberg Depression Rating Scale-self-rating version and the Karolinska Exhaustion Disorder Scale) and (4) number of sick leave days.ResultsThere was little correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Many participants on sick leave for SED, anxiety disorder or depression fulfilled criteria for other mental disorders. Most on sick leave for SED (76%) and anxiety disorder (67%) had depression (p=0.041). Length of sick leave did not differ by certificate diagnoses. Participants with SED (s-ED) had longer sick leave than participants without SED (144 vs 84 days; 1.72 (1.37-2.16); p<0.001). More severe symptoms were associated with longer sick leave.ConclusionDiagnoses on sick leave certificates did not reflect the complex and overlapping nature of the diagnoses found in the structured psychiatric interviews. This finding is relevant to the interpretation of information from health data registers, including studies and guidelines based on these data. A result of clinical interest was that more severe symptoms predicted long-term sick leave better than actual diagnoses.

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Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries.

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Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries.

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