Adverse effects of antidepressants are most common at the beginning of the treatment, but possible also later. We examined the association between antidepressant use and work-related injuries taking into account the duration of antidepressant use.

Antidepressant use and work-related injuries between 2000 and 2011 were measured among 66 238 employees (mean age 43.8 years, 80% female) using linkage to national records (the Finnish Public Sector study). We analysed data using time-dependent modelling with individuals as their own controls (self-controlled case-series design).

In 2238 individuals who had used antidepressants and had a work-related injury during a mean follow-up of 7.8 years, no increase in the risk of injury was observed in the beginning of antidepressant treatment. However, an increased injury risk was seen after 3 months of treatment (rate ratio, compared with no recent antidepressant use, 1.27, 95% confidence interval 1.10–1.48). This was also the case among those who had used only selective serotonin reuptake inhibitors (n = 714; rate ratio 1.41, 95% confidence interval 1.08–1.83).

Antidepressant use was not associated with an increased risk of work-related injury at the beginning of treatment. Post-hoc analyses of antidepressant trials are needed to determine whether long-term use of antidepressants increases the risk of work-related injury.

Most studies examining predictors of the onset of depression focus on variable centered regression methods that focus on the effects of multiple predictors. In contrast, person-centered approaches develop profiles of factors and these profiles can be examined as predictors of onset. Here, we developed profiles of adolescent psychosocial and clinical functioning among adolescents without a history of major depression.

Data come from a subsample of participants from the Oregon Adolescent Depression Project who completed self-report measures of functioning in adolescence and completed diagnostic and self-report measures at follow-up assessments up to approximately 15 years after baseline.

We identified four profiles of psychosocial and clinical functioning: Thriving; Average Functioning; Externalizing Vulnerability and Family Stress and Internalizing Vulnerability at the baseline assessment of participants without a history of depression at the initial assessment in mid-adolescence. Classes differed in the likelihood of onset and course of depressive disorders, experience of later anxiety and substance use disorders, and psychosocial functioning in adulthood. Moreover, the predictive utility of these classes was maintained when controlling for multiple other established risk factors for depressive disorders.

This work highlights the utility of examining multiple factors simultaneously to understand risk for depression.

Altered white matter brain connectivity has been linked to depression. The aim of this study was to investigate the association of markers of white matter connectivity with prevalence, incidence and course of depressive symptoms.

Markers of white matter connectivity (node degree, clustering coefficient, local efficiency, characteristic path length, and global efficiency) were assessed at baseline by 3 T MRI in the population-based Maastricht Study (n = 4866; mean ± standard deviation age 59.6 ± 8.5 years, 49.0% women; 17 406 person-years of follow-up). Depressive symptoms (9-item Patient Health Questionnaire; PHQ-9) were assessed at baseline and annually over seven years of follow-up. Major depressive disorder (MDD) was assessed with the Mini-International Neuropsychiatric Interview at baseline only. We used negative binominal, logistic and Cox regression analyses, and adjusted for demographic, cardiovascular, and lifestyle risk factors.

A lower global average node degree at baseline was associated with the prevalence and persistence of clinically relevant depressive symptoms [PHQ-9 ⩾ 10; OR (95% confidence interval) per standard deviation = 1.21 (1.05–1.39) and OR = 1.21 (1.02–1.44), respectively], after full adjustment. On the contrary, no associations were found of global average node degree with the MDD at baseline [OR 1.12 (0.94–1.32) nor incidence or remission of clinically relevant depressive symptoms [HR = 1.05 (0.95–1.17) and OR 1.08 (0.83–1.41), respectively]. Other connectivity measures of white matter organization were not associated with depression.

Our findings suggest that fewer white matter connections may contribute to prevalent depressive symptoms and its persistence but not to incident depression. Future studies are needed to replicate our findings.

Converging evidence suggests that a subgroup of bipolar disorder (BD) with an early age at onset (AAO) may develop from aberrant neurodevelopment. However, the definition of early AAO remains unprecise. We thus tested which age cut-off for early AAO best corresponds to distinguishable neurodevelopmental pathways.

We analyzed data from the FondaMental Advanced Center of Expertise-Bipolar Disorder cohort, a naturalistic sample of 4421 patients. First, a supervised learning framework was applied in binary classification experiments using neurodevelopmental history to predict early AAO, defined either with Gaussian mixture models (GMM) clustering or with each of the different cut-offs in the range 14 to 25 years. Second, an unsupervised learning approach was used to find clusters based on neurodevelopmental factors and to examine the overlap between such data-driven groups and definitions of early AAO used for supervised learning.

A young cut-off, i.e. 14 up to 16 years, induced higher separability [mean nested cross-validation test AUROC = 0.7327 (± 0.0169) for ⩽16 years]. Predictive performance deteriorated increasing the cut-off or setting early AAO with GMM. Similarly, defining early AAO below 17 years was associated with a higher degree of overlap with data-driven clusters (Normalized Mutual Information = 0.41 for ⩽17 years) relatively to other definitions.

Early AAO best captures distinctive neurodevelopmental patterns when defined as ⩽17 years. GMM-based definition of early AAO falls short of mapping to highly distinguishable neurodevelopmental pathways. These results should be used to improve patients' stratification in future studies of BD pathophysiology and biomarkers.

A growing volume of research suggests that religion protects against late-life suicide, but it remains unclear whether effects are relevant to clinical samples, which facets of religion are most relevant, and variations over the course of mood disorders (e.g. during periods of euthymia, depression, and/or heightened suicidality).

Eighty adults aged 55–85 years with mood disorders completed assessments of religion (affiliation, service attendance, importance of religion, belief and faith in God), depression, and suicidality over time (M = 7.31 measurements over M = 727 days). We computed metrics to identify mean and maximum levels of depression and suicidality, and the number of episodes of significant depression and suicidality experienced by each participant.

Religious affiliation and importance of religion, but not service attendance, belief, or faith in God, were associated with lower mean and maximum depression. Conversely, all facets of religion predicted significantly lower mean and maximum levels of suicidality (rs ranging from −0.24 to −0.39), and substantially less likelihood of experiencing significant suicidality during the study (ORs ranging from 0.19 to 0.33). Service attendance, belief, and faith in God predicted less suicidality even among individuals who did not affiliate with a religious group.

Religious factors, particularly faith in God, are associated with substantially less suicidality over time among older adults with mood disorders, irrespective of religious affiliation.