Phenomewide Association Study of Health Outcomes Associated With the Genetic Correlates of 25 Hydroxyvitamin D Concentration and Vitamin D Binding Protein Concentration.

While it is known that vitamin D deficiency is associated with adverse bone outcomes, it remains unclear whether low vitamin D status may increase the risk of a wider range of health outcomes. We had the opportunity to explore the association between common genetic variants associated with both 25 hydroxyvitamin D (25OHD) and the vitamin D binding protein (DBP, encoded by the GC gene) with a comprehensive range of health disorders and laboratory tests in a large academic medical center. We used summary statistics for 25OHD and DBP to generate polygenic scores (PGS) for 66,482 participants with primarily European ancestry and 13,285 participants with primarily African ancestry from the Vanderbilt University Medical Center Biobank (BioVU). We examined the predictive properties of PGS25OHD, and two scores related to DBP concentration with respect to 1322 health-related phenotypes and 315 laboratory-measured phenotypes from electronic health records. In those with European ancestry: (a) the PGS25OHD and PGSDBP scores, and individual SNPs rs4588 and rs7041 were associated with both 25OHD concentration and 1,25 dihydroxyvitamin D concentrations; (b) higher PGS25OHD was associated with decreased concentrations of triglycerides and cholesterol, and reduced risks of vitamin D deficiency, disorders of lipid metabolism, and diabetes. In general, the findings for the African ancestry group were consistent with findings from the European ancestry analyses. Our study confirms the utility of PGS and two key variants within the GC gene (rs4588 and rs7041) to predict the risk of vitamin D deficiency in clinical settings and highlights the shared biology between vitamin D-related genetic pathways a range of health outcomes.

Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians.

Mental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

The Role of Socioeconomic Position in the Association Between Mental Disorders and Mortality: A Systematic Review and Meta-Analysis.

Importance: Studies are lacking summarizing how the association between mental disorders and mortality varies by socioeconomic position (SEP), particularly considering different aspects of SEP, specific types of mental disorders, and causes of death. Objective: To investigate the role of SEP in the association between mental disorders and mortality and the association between SEP and mortality among people with mental disorders. Data Sources: MEDLINE, Embase, PsycINFO, and Web of Science were searched from January 1, 1980, through April 3, 2023, and a snowball search of reference and citation lists was conducted. Study Selection: Inclusion criteria were observational studies estimating the associations between different types of mental disorders and mortality, stratified by SEP and between SEP and mortality in people with mental disorders. Data Extraction and Synthesis: Pairs of reviewers independently extracted data using a predefined data extraction form and assessed the risk of bias using the adapted Newcastle-Ottawa scale. Graphical analyses of the dose-response associations and random-effects meta-analyses were performed. Heterogeneity was explored through meta-regressions and sensitivity analyses. Main Outcomes and Measures: All-cause and cause-specific mortality. Results: Of 28 274 articles screened, 71 including more than 4 million people with mental disorders met the inclusion criteria (most of which were conducted in high-income countries). The relative associations between mental disorders and mortality were similar across SEP levels. Among people with mental disorders, belonging to the highest rather than the lowest SEP group was associated with lower all-cause mortality (pooled relative risk [RR], 0.79; 95% CI, 0.73-0.86) and mortality from natural causes (RR, 0.73; 95% CI, 0.62-0.85) and higher mortality from external causes (RR, 1.18; 95% CI, 0.99-1.41). Heterogeneity was high (I2 = 83% to 99%). Results from subgroup, sensitivity, and meta-regression analyses were consistent with those from the main analyses. Evidence on absolute scales, specific diagnoses, and specific causes of death was scarce. Conclusion and Relevance: This study did not find a sufficient body of evidence that SEP moderated the relative association between mental disorders and mortality, but the underlying mortality rates may differ by SEP group, despite having scarcely been reported. This information gap, together with our findings related to SEP and a possible differential risk between natural and external causes of death in individuals with specific types of mental disorders, warrants further research.

Polygenic Risk of Mental Disorders and Subject-Specific School Grades.

BACKGROUND: Education is essential for socioeconomic security and long-term mental health; however, mental disorders are often detrimental to the educational trajectory. Genetic correlations between mental disorders and educational attainment do not always align with corresponding phenotypic associations, implying heterogeneity in the genetic overlap. METHODS: We unraveled this heterogeneity by investigating associations between polygenic risk scores for 6 mental disorders and fine-grained school outcomes: school grades in language and mathematics in ninth grade and high school, as well as educational attainment by age 25, using nationwide-representative data from established cohorts (N = 79,489). RESULTS: High polygenic liability of attention-deficit/hyperactivity disorder was associated with lower grades in language and mathematics, whereas high polygenic risk of anorexia nervosa or bipolar disorder was associated with higher grades in language and mathematics. Associations between polygenic risk and school grades were mixed for schizophrenia and major depressive disorder and neutral for autism spectrum disorder. CONCLUSIONS: Polygenic risk scores for mental disorders are differentially associated with language and mathematics school grades.

Cat Ownership and Schizophrenia-Related Disorders and Psychotic-Like Experiences: A Systematic Review and Meta-Analysis.

BACKGROUND: It has been proposed that cat ownership may be a risk-modifying factor for schizophrenia-related disorders and psychotic-like experiences (PLE). This study aimed to systematically review and meta-analyze publications that reported the relationship between cat ownership and schizophrenia-related outcomes. METHODOLOGY: We searched Medline, Embase, CINAHL, Web of Science, and gray literature for publications between January 1, 1980, and May 30, 2023, regardless of geographical location and language. Backward citation search methods were used to locate additional articles. We included studies that reported original data on cat ownership and schizophrenia-related outcomes. We meta-analyzed estimates based on broad definitions (cat ownership, cat bites, and cat contact) with estimates with or without covariate adjustments. We pooled comparable estimates using random-effects models and assessed the risk of bias, heterogeneity, and study quality. RESULTS: We identified 1915 studies, of which 106 were chosen for full-text review, ultimately resulting in the inclusion of 17 studies. We found an association between broadly defined cat ownership and increased odds of developing schizophrenia-related disorders. The unadjusted pooled odds ratio (OR) was 2.35 (95% CI: 1.38-4.01), while the adjusted pooled estimate was 2.24 (95% CI: 1.61-3.12). We were unable to aggregate the estimates for the PLE outcomes because of the broad range of measures. CONCLUSIONS: Our findings support an association between cat exposure and an increased risk of broadly defined schizophrenia-related disorders; however, the findings related to PLE as an outcome are mixed. There is a need for more high-quality studies in this field. PROSPERO REGISTRATION: PROSPERO 2023 CRD42023426974. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023426974.

The correlates of neonatal complement component 3 and 4 protein concentrations with a focus on psychiatric and autoimmune disorders.

Complement components have been linked to schizophrenia and autoimmune disorders. We examined the association between neonatal circulating C3 and C4 protein concentrations in 68,768 neonates and the risk of six mental disorders. We completed genome-wide association studies (GWASs) for C3 and C4 and applied the summary statistics in Mendelian randomization and phenome-wide association studies related to mental and autoimmune disorders. The GWASs for C3 and C4 protein concentrations identified 15 and 36 independent loci, respectively. We found no associations between neonatal C3 and C4 concentrations and mental disorders in the total sample (both sexes combined); however, post-hoc analyses found that a higher C3 concentration was associated with a reduced risk of schizophrenia in females. Mendelian randomization based on C4 summary statistics found an altered risk of five types of autoimmune disorders. Our study adds to our understanding of the associations between C3 and C4 concentrations and subsequent mental and autoimmune disorders.

Cross-ancestry analyses identify new genetic loci associated with 25-hydroxyvitamin D.

Vitamin D status-a complex trait influenced by environmental and genetic factors-is tightly associated with skin colour and ancestry. Yet very few studies have investigated the genetic underpinnings of vitamin D levels across diverse ancestries, and the ones that have, relied on small sample sizes, resulting in inconclusive results. Here, we conduct genome-wide association studies (GWAS) of 25 hydroxyvitamin D (25OHD)-the main circulating form of vitamin D-in 442,435 individuals from four broad genetically-determined ancestry groups represented in the UK Biobank: European (N = 421,867), South Asian (N = 9,983), African (N = 8,306) and East Asian (N = 2,279). We identify a new genetic determinant of 25OHD (rs146759773) in individuals of African ancestry, which was not detected in previous analysis of much larger European cohorts due to low minor allele frequency. We show genome-wide significant evidence of dominance effects in 25OHD that protect against vitamin D deficiency. Given that key events in the synthesis of 25OHD occur in the skin and are affected by pigmentation levels, we conduct GWAS of 25OHD stratified by skin colour and identify new associations. Lastly, we test the interaction between skin colour and variants associated with variance in 25OHD levels and identify two loci (rs10832254 and rs1352846) whose association with 25OHD differs in individuals of distinct complexions. Collectively, our results provide new insights into the complex relationship between 25OHD and skin colour and highlight the importance of diversity in genomic studies. Despite the much larger rates of vitamin D deficiency that we and others report for ancestry groups with dark skin (e.g., South Asian), our study highlights the importance of considering ancestral background and/or skin colour when assessing the implications of low vitamin D.

Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management.

Populations with common physical diseases - such as cardiovascular diseases, cancer and neurodegenerative disorders - experience substantially higher rates of major depressive disorder (MDD) than the general population. On the other hand, people living with MDD have a greater risk for many physical diseases. This high level of comorbidity is associated with worse outcomes, reduced adherence to treatment, increased mortality, and greater health care utilization and costs. Comorbidity can also result in a range of clinical challenges, such as a more complicated therapeutic alliance, issues pertaining to adaptive health behaviors, drug-drug interactions and adverse events induced by medications used for physical and mental disorders. Potential explanations for the high prevalence of the above comorbidity involve shared genetic and biological pathways. These latter include inflammation, the gut microbiome, mitochondrial function and energy metabolism, hypothalamic-pituitary-adrenal axis dysregulation, and brain structure and function. Furthermore, MDD and physical diseases have in common several antecedents related to social factors (e.g., socioeconomic status), lifestyle variables (e.g., physical activity, diet, sleep), and stressful live events (e.g., childhood trauma). Pharmacotherapies and psychotherapies are effective treatments for comorbid MDD, and the introduction of lifestyle interventions as well as collaborative care models and digital technologies provide promising strategies for improving management. This paper aims to provide a detailed overview of the epidemiology of the comorbidity of MDD and specific physical diseases, including prevalence and bidirectional risk; of shared biological pathways potentially implicated in the pathogenesis of MDD and common physical diseases; of socio-environmental factors that serve as both shared risk and protective factors; and of management of MDD and physical diseases, including prevention and treatment. We conclude with future directions and emerging research related to optimal care of people with comorbid MDD and physical diseases.

ADuLT: An efficient and robust time-to-event GWAS.

Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.

Multi-PGS enhances polygenic prediction by combining 937 polygenic scores.

The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and takes time, but this sample size can be effectively increased by using genetically correlated phenotypes. We propose a framework to generate multi-PGS from thousands of publicly available genome-wide association studies (GWAS) with no need to individually select the most relevant ones. In this study, the multi-PGS framework increases prediction accuracy over single PGS for all included psychiatric disorders and other available outcomes, with prediction R2 increases of up to 9-fold for attention-deficit/hyperactivity disorder compared to a single PGS. We also generate multi-PGS for phenotypes without an existing GWAS and for case-case predictions. We benchmark the multi-PGS framework against other methods and highlight its potential application to new emerging biobanks.

Age of onset and cumulative risk of mental disorders: a cross-national analysis of population surveys from 29 countries.

BACKGROUND: Information on the frequency and timing of mental disorder onsets across the lifespan is of fundamental importance for public health planning. Broad, cross-national estimates of this information from coordinated general population surveys were last updated in 2007. We aimed to provide updated and improved estimates of age-of-onset distributions, lifetime prevalence, and morbid risk. METHODS: In this cross-national analysis, we analysed data from respondents aged 18 years or older to the World Mental Health surveys, a coordinated series of cross-sectional, face-to-face community epidemiological surveys administered between 2001 and 2022. In the surveys, the WHO Composite International Diagnostic Interview, a fully structured psychiatric diagnostic interview, was used to assess age of onset, lifetime prevalence, and morbid risk of 13 DSM-IV mental disorders until age 75 years across surveys by sex. We did not assess ethnicity. The surveys were geographically clustered and weighted to adjust for selection probability, and standard errors of incidence rates and cumulative incidence curves were calculated using the jackknife repeated replications simulation method, taking weighting and geographical clustering of data into account. FINDINGS: We included 156 331 respondents from 32 surveys in 29 countries, including 12 low-income and middle-income countries and 17 high-income countries, and including 85 308 (54·5%) female respondents and 71 023 (45·4%) male respondents. The lifetime prevalence of any mental disorder was 28·6% (95% CI 27·9-29·2) for male respondents and 29·8% (29·2-30·3) for female respondents. Morbid risk of any mental disorder by age 75 years was 46·4% (44·9-47·8) for male respondents and 53·1% (51·9-54·3) for female respondents. Conditional probabilities of first onset peaked at approximately age 15 years, with a median age of onset of 19 years (IQR 14-32) for male respondents and 20 years (12-36) for female respondents. The two most prevalent disorders were alcohol use disorder and major depressive disorder for male respondents and major depressive disorder and specific phobia for female respondents. INTERPRETATION: By age 75 years, approximately half the population can expect to develop one or more of the 13 mental disorders considered in this Article. These disorders typically first emerge in childhood, adolescence, or young adulthood. Services should have the capacity to detect and treat common mental disorders promptly and to optimise care that suits people at these crucial parts of the life course. FUNDING: None.

Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses.

Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment.

Perspectives on environment and health research in Denmark.

AIMS: We provide an overview of nationwide environmental data available for Denmark and its linkage potentials to individual-level records with the aim of promoting research on the potential impact of the local surrounding environment on human health. BACKGROUND: Researchers in Denmark have unique opportunities for conducting large population-based studies treating the entire Danish population as one big, open and dynamic cohort based on nationally complete population and health registries. So far, most research in this area has utilised individual- and family-level information to study the clustering of disease in families, comorbidities, risk of, and prognosis after, disease onset, and social gradients in disease risk. Linking environmental data in time and space to individuals enables novel possibilities for studying the health effects of the social, built and physical environment. METHODS: We describe the possible linkage between individuals and their local surrounding environment to establish the exposome - that is, the total environmental exposure of an individual over their life course. CONCLUSIONS: The currently available nationwide longitudinal environmental data in Denmark constitutes a valuable and globally rare asset that can help explore the impact of the exposome on human health.

Schizophrenia spectrum disorders in Denmark between 2000 and 2018: Incidence and early diagnostic transition.

BACKGROUND: Schizophrenia spectrum disorders (SSD) comprise a group of related mental disorders, which share clinical features and common genetic disposition, but it is unknown if there is a diagnostic transition between these disorders over time. We aimed to study the incidence at the first SSD diagnosis between 2000 and 2018, defined as schizophrenia, schizotypal or schizoaffective disorder, and the early diagnostic transition between these disorders. METHODS: Using Danish nationwide healthcare registers, we identified all individuals aged 15-64 years during the period from 2000 to 2018 in Denmark and calculated the yearly incidence rates for the specific SSDs. We studied the diagnostic pathways from the first ever diagnosis of an SSD across the subsequent two treatment courses with an SSD diagnosis to evaluate early diagnostic stability, and explore potential changes over time. RESULTS: Among 21,538 patients, yearly incidence rates per 10,000 individuals were similar during the observation period for schizophrenia (2000: 1.8; 2018: 1.6), lower for schizoaffective disorder (2000: 0.3; 2018: 0.1) and increasing for schizotypal disorder (2000: 0.7; 2018: 1.3). Among the subgroup of 13,417 individuals with three separate treatment courses, early diagnostic stability was present among 89.9% which differed between the disorders (schizophrenia: 95.4%; schizotypal disorder: 78.0%; schizoaffective disorder: 80.5%). Among 1352 (10.1%) experiencing an early diagnostic transition, 398 (3.0%) were diagnosed with schizotypal disorder after a schizophrenia or schizoaffective disorder diagnosis. CONCLUSION: This study provides comprehensive incidence rates for SSDs. The majority of patients experienced early diagnostic stability, but sizable proportions of people with initial schizophrenia or schizoaffective disorder are subsequently diagnosed with schizotypal disorder.

Agreement between survey- and register-based measures of depression in Denmark.

BACKGROUND: Register-based studies of major depressive disorder (MDD) do not capture all prevalent cases, as untreated cases and diagnoses made by general practitioners are not recorded in the registers. We examined the prevalence and agreement of survey- and register-based measures of depression, and explored sociodemographic and health-related factors that may have influenced this agreement. METHODS: All 32,407 participants in the 2017 Central Denmark Region How are you? survey were linked to hospital and prescription records. A checklist for depressive symptoms within the last 14 days (Major Depression Inventory; MDI) from the survey was compared with register-based assessment of hospital-diagnosed MDD and/or prescriptions for antidepressants. We estimated agreement between survey-based and register-based measures for depression and used logistic regression models to explore selected associated factors. RESULTS: In total, 5.9% of How are you? survey participants screened positive for current depression on the MDI. Of these, 51.3% (95% confidence interval (CI): 49.0-53.6) filled a prescription for an antidepressant medication during the 10 years prior or 2 years following the administration of the survey, and 14.5% (95% CI: 12.9-16.2) were treated for MDD in a psychiatric hospital-based setting. When using a higher threshold of the MDI indicating more severe current depression, 22.8% (95% CI: 19.6-26.1) of those who screened positive also received an MDD diagnosis and 63.4% (95% CI: 59.7-67.2) were prescribed antidepressants during this 12-year period. Among those with current depression, female sex, older age, chronic diseases, hospital-treated self-harm, and being permanently outside the workforce were associated with having a register-based MDD diagnosis or antidepressant prescription. Among those with a register-based depression record, female sex, younger age, hospital-treated self-harm, stress, and severe loneliness were associated with current depression. CONCLUSION: We found that as few as 15% of individuals with current depression in the general Danish population were captured by the psychiatric hospital register, while 51% of these individuals were identifiable in the prescription register. These findings demonstrate that register-based measures significantly underestimate the true prevalence of depression by identifying only the cases that are most severe.

Antidepressant use in low- middle- and high-income countries: a World Mental Health Surveys report.

BACKGROUND: The most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries. METHODS: Face-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents. RESULTS: 3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2-4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness. CONCLUSION: ADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Genetic correlates of vitamin D-binding protein and 25-hydroxyvitamin D in neonatal dried blood spots.

The vitamin D binding protein (DBP), encoded by the group-specific component (GC) gene, is a component of the vitamin D system. In a genome-wide association study of DBP concentration in 65,589 neonates we identify 26 independent loci, 17 of which are in or close to the GC gene, with fine-mapping identifying 2 missense variants on chromosomes 12 and 17 (within SH2B3 and GSDMA, respectively). When adjusted for GC haplotypes, we find 15 independent loci distributed over 10 chromosomes. Mendelian randomization analyses identify a unidirectional effect of higher DBP concentration and (a) higher 25-hydroxyvitamin D concentration, and (b) a reduced risk of multiple sclerosis and rheumatoid arthritis. A phenome-wide association study confirms that higher DBP concentration is associated with a reduced risk of vitamin D deficiency. Our findings provide valuable insights into the influence of DBP on vitamin D status and a range of health outcomes.

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use.

AIMS: Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD. DESIGN: A prediction model was developed for DSM-IV AD onset by age 25 years using an ensemble machine-learning algorithm known as 'Super Learner'. Shapley additive explanations (SHAP) assessed variable importance. SETTING AND PARTICIPANTS: Respondents reporting early onset of regular alcohol use (i.e. by 17 years of age) who were aged 25 years or older at interview from 14 representative community surveys conducted in 13 countries as part of WHO's World Mental Health Surveys. MEASUREMENTS: The primary outcome to be predicted was onset of life-time DSM-IV AD by age 25 as measured using the Composite International Diagnostic Interview, a fully structured diagnostic interview. FINDINGS: AD prevalence by age 25 was 5.1% among the 10 687 individuals who reported drinking alcohol regularly by age 17. The prediction model achieved an external area under the curve [0.78; 95% confidence interval (CI) = 0.74-0.81] higher than any individual candidate risk model (0.73-0.77) and an area under the precision-recall curve of 0.22. Overall calibration was good [integrated calibration index (ICI) = 1.05%]; however, miscalibration was observed at the extreme ends of the distribution of predicted probabilities. Interventions provided to the 20% of people with highest risk would identify 49% of AD cases and require treating four people without AD to reach one with AD. Important predictors of increased risk included younger onset of alcohol use, males, higher cohort alcohol use and more mental disorders. CONCLUSIONS: A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models.