We introduce and apply an elegant, contrastive genetic-epidemiological design – Maternal Half-Sibling Families with Discordant Fathers – to clarify cross-generational transmission of genetic risk to alcohol use disorder (AUD), drug abuse (DA) and major depression (MD).

Using Swedish national registries, we identified 73 108 eligible pairs of reared together maternal half-siblings and selected those whose biological fathers were discordant for AUD, DA and MD, and had minimal contact with the affected father. We examined differences in outcome in half-siblings with an affected v. unaffected father.

For AUD, DA and MD, the HR (95% confidence intervals) for the offspring of affected v. unaffected fathers were, respectively, 1.72 (1.61; 1.84), 1.55 (1.41; 1.70) and 1.51 (1.40; 1.64). Paternal DA and AUD, but not MD, predicted risk in offspring for attention deficit hyperactivity disorder, conduct disorder, and poor educational performance and attainment. Offspring of affected v. unaffected fathers had poorer pregnancy outcomes, with the effect strongest for DA and weakest for MD. A range of potential biases and confounders were examined and were not found to alter these findings substantially.

Reared together maternal half-siblings differ in their paternal genetic endowment, sharing the same mother, family, school and community. They can help clarify the nature of paternal genetic effects and produce results consistent with other designs. Paternal genetic risk for DA and AUD have effects on offspring educational achievement, child and adult psychopathology, and possibly prenatal development. The impact of paternal genetic risk for MD is narrower in scope.

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global health crisis that may cause mental health problems and heighten suicide risk. We investigated the impact of the COVID-19 pandemic on trends in suicide attempts and suicide deaths in New Taipei City, Taiwan.

The current study used the official daily data on suicide attempts and deaths in New Taipei City, Taiwan (4 million inhabitants) between 2015 and 2020 from the Taiwan National Suicide Prevention Reporting System. Interrupted time-series (ITS) analyses with parameters corrected by the estimated autocorrelations were applied on weekly aggregated data to examine whether the suicide trends during the early COVID-19 pandemic (late January to July 2020) deviated from previous trends (January 2015 to late January 2020). The impact due to the suicide prevention policy change was also examined (since August 2020).

ITS analyses revealed no significant increases in both mean and trend on weekly suicide deaths during the COVID-19 pandemic and after the policy change. In contrast, there was a significant increasing trend in weekly suicide attempts since the COVID-19 outbreak at the rate of 1.54 attempts per week (95% confidence interval 0.49–2.60; p = 0.004). Sex difference analysis revealed that, however, this increasing trend was observed only in females not in males.

The COVID-19 pandemic has different impacts on suicides attempts and deaths during the early pandemic in New Taipei City, Taiwan. The COVID-19 outbreak drastically increased the trend of suicide attempts. In contrast, the number of suicide deaths had remained constant in the investigated periods.

Neurobehavioral decision profiles have often been neglected in chronic diseases despite their direct impact on major public health issues such as treatment adherence. This remains a major concern in diabetes, despite intensive efforts and public awareness initiatives regarding its complications. We hypothesized that high rates of low adherence are related to risk-taking profiles associated with decision-making phenotypes. If this hypothesis is correct, it should be possible to define these endophenotypes independently based both on dynamic measures of metabolic control (HbA1C) and multidimensional behavioral profiles.

In this study, 91 participants with early-stage type 1 diabetes fulfilled a battery of self-reported real-world risk behaviors and they performed an experimental task, the Balloon Analogue Risk Task (BART).

K-means and two-step cluster analysis suggest a two-cluster solution providing information of distinct decision profiles (concerning multiple domains of risk-taking behavior) which almost perfectly match the biological partition, based on the division between stable or improving metabolic control (MC, N = 49) v. unstably high or deteriorating states (NoMC, N = 42). This surprising dichotomy of behavioral phenotypes predicted by the dynamics of HbA1C was further corroborated by standard statistical testing. Finally, the BART game enabled to identify groups differences in feedback learning and consequent behavioral choices under ambiguity, showing distinct group choice behavioral patterns.

These findings suggest that distinct biobehavioral endophenotypes can be related to the success of metabolic control. These findings also have strong implications for programs to improve patient adherence, directly addressing risk-taking profiles.

Psychotic disorders develop gradually along a continuum of severity. Understanding factors associated with psychosis development, such as sleep, could aid in identification of individuals at elevated risk. This study aimed to assess (1) the dynamic relationship between psychotic experiences (PEs) and sleep quality and quantity, and (2) whether this relationship differed between different clinical stages along the psychosis continuum.

We used daily diary data (90 days) of individuals (N = 96) at early stages (i.e. before a first diagnosis of psychosis) along the psychosis continuum. Multilevel models were constructed with sleep quality and sleep quantity as predictors of PEs and vice versa. Post-hoc, we constructed a multilevel model with both sleep quality and quantity as predictors of PEs. In addition, we tested whether associations differed between clinical stages.

Within persons, poorer sleep predicted next day PEs (B = −0.02, p = 0.01), but not vice versa. Between persons, shorter sleep over the 90-day period predicted more PEs (B = −0.04, p = 0.002). Experiencing more PEs over 90-days predicted poorer (B = −0.02, p = 0.02) and shorter (B = −1.06, p = 0.008) sleep. We did not find any significant moderation effects for clinical stage.

We found a bidirectional relationship between sleep and PEs with daily fluctuations in sleep predicting next day PEs and general patterns of more PEs predicting poorer and shorter sleep. Our results highlight the importance of assessing sleep as a risk marker in the early clinical stages for psychosis.

We tested the degree to which longitudinal observations fit two hypotheses of psychiatric co-morbidity in DSM-IV major depressive disorder (MDD) among adult patients: (1) Axis I co-morbidity is dependent on major depressive episode (MDE) course, and (2) Axis I co-morbidity is independent of MDE course.

In the Vantaa Depression Study (VDS), 269 psychiatric secondary-care patients with a DSM-IV MDD were evaluated with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) at intake and at 6 and 18 months. Three evaluations of co-morbidity were available for 193 out of 259 living patients (75%). A latent curve model (LCM) was used to examine individual-level changes in depressive and anxiety symptoms across time. Outcome of MDD was modeled in terms of categorical DSM-IV diagnosis and Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HAMD) scores, and co-morbidity in terms of categorical DSM-IV anxiety and alcohol use disorder (AUD) diagnoses and Beck Anxiety Inventory (BAI) scores.

Depression and anxiety correlated cross-sectionally at baseline. Longitudinally, changes in depression and anxiety correlated in both the 0–6 and 6–18 months time windows. Higher baseline depression raised the likelihood of an AUD at 6 months, and patients with more depressive symptoms in the 0–6 months time window were more likely to have had an AUD at 6 months, which further linked to less improvement in depression symptoms in the 6–18 months time window.

Longitudinal and individual-level courses of both internalizing and externalizing disorders in adult patients with MDD seem to be dependent, albeit to differing degrees, on the course of depressive symptoms.

Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.

A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.

Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.

Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.

Cognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks.

Cognitive performance of n = 805 healthy and n = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength.

All cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course.

Our study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.

Preschool psychiatric symptoms significantly increase the risk for long-term negative outcomes. Transdiagnostic hierarchical approaches that capture general (‘p’) and specific psychopathology dimensions are promising for understanding risk and predicting outcomes, but their predictive utility in young children is not well established. We delineated a hierarchical structure of preschool psychopathology dimensions and tested their ability to predict psychiatric disorders and functional impairment in preadolescence.

Data for 1253 preschool children (mean age = 4.17, s.d. = 0.81) were drawn from three longitudinal studies using a similar methodology (one community sample, two psychopathology-enriched samples) and followed up into preadolescence, yielding a large and diverse sample. Exploratory factor models derived a hierarchical structure of general and specific factors using symptoms from the Preschool Age Psychiatric Assessment interview. Longitudinal analyses examined the prospective associations of preschool p and specific factors with preadolescent psychiatric disorders and functional impairment.

A hierarchical dimensional structure with a p factor at the top and up to six specific factors (distress, fear, separation anxiety, social anxiety, inattention-hyperactivity, oppositionality) emerged at preschool age. The p factor predicted all preadolescent disorders (ΔR2 = 0.04–0.15) and functional impairment (ΔR2 = 0.01–0.07) to a significantly greater extent than preschool psychiatric diagnoses and functioning. Specific dimensions provided additional predictive power for the majority of preadolescent outcomes (disorders: ΔR2 = 0.06–0.15; functional impairment: ΔR2 = 0.05–0.12).

Both general and specific dimensions of preschool psychopathology are useful for predicting clinical and functional outcomes almost a decade later. These findings highlight the value of transdiagnostic dimensions for predicting prognosis and as potential targets for early intervention and prevention.

To explore the cross-sectional and longitudinal association between vitamin D and depressive symptoms across early adolescence.

This longitudinal study included 1607 early adolescents [mean (s.d.) age, 12.49 years; 972 (60.5%) males] from the Chinese Early Adolescents Cohort, recruited from a middle school in Anhui Province and followed up annually (2019–2021). Serum 25(OH)D levels were measured in both 2019 and 2021. Self-reports on depression were assessed at each of three time points from 2019 to 2021.

In the whole sample, higher baseline serum 25(OH)D levels were linked with a lower risk of cumulative incident depression within two-year follow-ups (adjusted RR = 0.97, 95% CI 0.94–0.99) and the increasing trajectory of depression symptoms across the three waves (adjusted RR = 0.97, 95% CI 0.95–0.99). Baseline vitamin D deficiency (VDD) (adjusted RR = 1.50, 95% CI 1.10–2.05) were associated with an increased risk for the increasing trajectory of depression symptoms across the three waves. Remitted VDD was positively related to one dichotomous depression symptoms across three waves (adjusted OR 2.15, 95% CI 1.15–4.01). The above-mentioned significant association was also found in males. Additionally, baseline VDD (adjusted OR 1.59, 95% CI 1.04–2.44) and persistent VDD (adjusted OR 1.58, 95% CI 1.02–2.60) were linked to an increased risk of having two dichotomous depression symptoms only in males.

Our results highlight a prospective association between baseline vitamin D and depression risk in early adolescents. Additionally, a male-specific association between vitamin D and depression risk was observed. Our findings support a potential beneficial effect of vitamin D supplementation in reducing depression risk in early adolescents.

Chronic pain has been extensively explored as a risk factor for opioid misuse, resulting in increased focus on opioid prescribing practices for individuals with such conditions. Physical disability sometimes co-occurs with chronic pain but may also represent an independent risk factor for opioid misuse. However, previous research has not disentangled whether disability contributes to risk independent of chronic pain.

Here, we estimate the independent and joint adjusted associations between having a physical disability and co-occurring chronic pain condition at time of Medicaid enrollment on subsequent 18-month risk of incident opioid use disorder (OUD) and non-fatal, unintentional opioid overdose among non-elderly, adult Medicaid beneficiaries (2016–2019).

We find robust evidence that having a physical disability approximately doubles the risk of incident OUD or opioid overdose, and physical disability co-occurring with chronic pain increases the risks approximately sixfold as compared to having neither chronic pain nor disability. In absolute numbers, those with neither a physical disability nor chronic pain condition have a 1.8% adjusted risk of incident OUD over 18 months of follow-up, those with physical disability alone have an 2.9% incident risk, those with chronic pain alone have a 3.6% incident risk, and those with co-occurring physical disability and chronic pain have a 11.1% incident risk.

These findings suggest that those with a physical disability should receive increased attention from the medical and healthcare communities to reduce their risk of opioid misuse and attendant negative outcomes.