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Background Separating with close siblings and leaving the parental home at an early age represents a major life event for an adolescent (reflected by age at separation in a twin pair) and may predispose them to poor mental health. This study aims to examine the association of age at separation and residential mobility on depressive symptoms in late adolescence and young adulthood and to explore possible underlying genetic effects. Methods Residential mobility consisted of the number and total distance of moves before age 17. Based on 3071 twins from the FinnTwin12 cohort, we used linear regression to assess the association of age at separation and residential mobility with General Behavior Inventory (GBI) scores at age 17 and in young adulthood. A higher GBI score indicated more depressive symptoms occurred. Then, the mixed model for repeated measures (MMRM) was used to visualize the scores’ trajectory and test the associations, controlling for \"baseline\" state. Twin analyses with a bivariate cross-lagged path model were performed between the difference in GBI scores, between cotwins, and separation status for the potential genetic influence. Results Compared to twins separated before age 17, twins who separated later had significantly lower GBI scores at age 17 and in young adulthood. In MMRM, separation at a later age and a higher number of moves were associated with a higher GBI score in young adulthood. A small genetic effect was detected wherein GBI within-pair differences at age 17 were associated with separation status before age 22 (coefficient: 0.01). Conclusion The study provides valid evidence about the influence of siblings and family on depressive symptoms in later adolescence and young adulthood while finding some evidence for a reverse direction effect. This suggests more caution in the interpretation of results. A strong association between residential mobility and depressive symptoms was affirmed, although further detailed research is needed.

Depression is a heterogeneous mental health problem affecting millions worldwide, but the majority of individuals with depression do not experience relief from initial treatments. Therefore, we need to improve our understanding of the biology of depression, and metabolomic approaches, especially untargeted ones, can suggest new hypotheses for further exploring biological mechanisms. Using the FinnTwin12 cohort, a longitudinal Finnish population-based twin cohort with data collected in adolescence and young adulthood including 725 blood plasma samples, we investigated associations between depression and 11 low-molecular-weight metabolites (amino acids and ketone bodies). In linear regression models with the metabolite (measured at age 22) as the dependent variable and depression ratings (measured at age 12, 14, 17, or 22 from multiple raters) as independent variables (adjusted first for age, sex, body mass index, and additional covariates later), we initially identified a significant negative association of valine with depression. Upon further analyses, valine remained significantly negatively associated with depression cross-sectionally and over time (meta-analysis beta = -13.86, 95% CI (-18.48 to -9.25)). Analyses of the other branched chain amino acids showed a significant negative association of leucine with depression (meta-analysis beta = -9.24, 95% CI (-14.53 to -3.95)), while no association was seen between isoleucine and depression (meta-analysis beta = -0.95, 95% CI (-6.00 to 4.11)). These exploratory epidemiologic findings support further investigations into the role of branched chain amino acids in depression.

Despite increasing mental health problems among young people, few studies have examined associations between plasma proteins and mental health. Interactions between proteins and metabolites in association with mental health problems remain underexplored. In 730 twins, we quantified associations between plasma proteins measured at age 22 with 21 indicators of either depressive symptoms or the p-factor and tested for interactions with metabolites. Symptoms were collected from questionnaires and interviews completed by different raters (e.g., self-report, teachers) through adolescence to young adulthood (12 to 22 years). We found 47 proteins associated with depressive symptoms or the p-factor (FDR < 0.2), 9 being associated with both. Two proteins, contactin-1 and mast/stem cell growth factor receptor kit, positively interacted with valine levels in explaining p-factor variability. Our study demonstrates strong associations between plasma proteins and mental health and provides evidence for proteome–metabolome interactions in explaining higher levels of mental health problems.

Background The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein–BMI trajectory associations in adolescents and adults and how these connect to other omics layers. Methods Our study included two cohorts of longitudinally followed twins: FinnTwin12 ( N  = 651) and the Netherlands Twin Register (NTR) ( N  = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23–27 years old) to 10 years (FinnTwin12: 12–22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks. Results We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. Conclusions Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Global emphasis on enhancing prevention and treatment strategies necessitates an increased understanding of the biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the “general psychopathology factor”, is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here, we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography–tandem mass spectrometry, 13 proteins with a significant connection with the p-factor were identified, 8 of which were linked to epidermal growth factor receptor (EGFR) signaling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.

Aggressive behavior in school is an ongoing concern. The current focus is on specific manifestations such as bullying, but the behavior is broad and heterogenous. Children spend a substantial amount of time in school, but their behaviors in the school setting tend to be less well characterized than at home. Because aggression may index multiple behavioral problems, we used three validated instruments to assess means, correlations and gender differences of teacher-rated aggressive behavior with co-occurring externalizing/internalizing problems and social behavior in 39,936 schoolchildren aged 7–14 from 4 population-based cohorts from Finland, the Netherlands, and the UK. Correlations of aggressive behavior were high with all other externalizing problems ( r : 0.47–0.80) and lower with internalizing problems ( r : 0.02–0.39). A negative association was observed with prosocial behavior ( r : -0.33 to -0.54). Mean levels of aggressive behavior differed significantly by gender. Despite the higher mean levels of aggressive behavior in boys, the correlations were notably similar for boys and girls (e.g., aggressive-hyperactivity correlations: 0.51–0.75 boys, 0.47–0.70 girls) and did not vary greatly with respect to age, instrument or cohort. Thus, teacher-rated aggressive behavior rarely occurs in isolation; boys and girls with problems of aggressive behavior likely require help with other behavioral and emotional problems. Important to note, higher aggressive behavior is not only associated with higher amounts of other externalizing and internalizing problems but also with lower levels of prosocial behavior.

Modestly prevalent in the general population (~ 4%), but highly prevalent in prison populations (> 40%), the diagnosis of antisocial personality disorder (ASPD) involves aggression as one of several possible criteria. Using multiple informants, we aimed to determine if general aggression, as well as direct and indirect subtypes, assessed in early adolescence (ages 12, 14) predict young adulthood ASPD in a population-based sample. Using data from a Finnish population-based longitudinal twin cohort study with psychiatric interviews available at age 22 (N = 1347), we obtained DSM-IV-based ASPD diagnoses. Aggression measures from ages 12 (parental and teacher ratings) and 14 (teacher, self, and co-twin ratings) were used to calculate odds ratios (OR) of ASPD from logistic regression models and the area under the curve (AUC) from receiver operating characteristic curve analysis. Analyses were adjusted for sex, age, and family structure. All informants’ aggression ratings were significant (p < 0.05) predictors of ASPD (OR range 1.3–1.8; AUC range 0.65–0.72). Correlations between informants ranged from 0.13 to 0.33. Models including two or more aggression ratings, particularly age 14 teacher and self ratings, more accurately predicted ASPD (AUC: 0.80; 95% confidence interval 0.73–0.87). Direct aggression rated by all informants significantly predicted ASPD (OR range 1.4–1.9), whereas only self-rated indirect aggression was significantly associated with ASPD (OR = 1.4). Across different informants, general and direct aggression at ages 12 and 14 predicted ASPD in a population-based sample. Psychiatric, social, and parenting interventions for ASPD prevention should focus on children and adolescents with high aggression levels, with an aim to gather information from multiple informants.

BackgroundDepressive symptoms lead to a serious public health burden and are considerably affected by the environment. Land use, describing the urban living environment, influences mental health, but complex relationship assessment is rare.ObjectiveWe aimed to examine the complicated association between urban land use and depressive symptoms among young adults with differential land use environments, by applying multiple models.MethodsWe included 1804 individual twins from the FinnTwin12 cohort, living in urban areas in 2012. There were eight types of land use exposures in three buffer radii. The depressive symptoms were assessed through the General Behavior Inventory (GBI) in young adulthood (mean age: 24.1). First, K-means clustering was performed to distinguish participants with differential land use environments. Then, linear elastic net penalized regression and eXtreme Gradient Boosting (XGBoost) were used to reduce dimensions or prioritize for importance and examine the linear and nonlinear relationships.ResultsTwo clusters were identified: one is more typical of city centers and another of suburban areas. A heterogeneous pattern in results was detected from the linear elastic net penalized regression model among the overall sample and the two separated clusters. Agricultural residential land use in a 100 m buffer contributed to GBI most (coefficient: 0.097) in the “suburban” cluster among 11 selected exposures after adjustment with demographic covariates. In the “city center” cluster, none of the land use exposures was associated with GBI, even after further adjustment with social indicators. From the XGBoost models, we observed that ranks of the importance of land use exposures on GBI and their nonlinear relationships are also heterogeneous in the two clusters.ImpactThis study examined the complex relationship between urban land use and depressive symptoms among young adults in Finland. Based on the FinnTwin12 cohort, two distinct clusters of participants were identified with different urban land use environments at first. We then employed two pluralistic models, elastic net penalized regression and XGBoost, and revealed both linear and nonlinear relationships between urban land use and depressive symptoms, which also varied in the two clusters. The findings suggest that analyses, involving land use and the broader environmental profile, should consider aspects such as population heterogeneity and linearity for comprehensive assessment in the future.

This review offers an update on research conducted with FinnTwin12 (FT12), the youngest of the three Finnish Twin Cohorts. FT12 was designed as a two-stage study. In the first stage, we conducted multiwave questionnaire research enrolling all eligible twins born in Finland during 1983–1987 along with their biological parents. In stage 2, we intensively studied a subset of these twins with in-school assessments at age 12 and semistructured poly-diagnostic interviews at age 14. At baseline, parents of intensively studied twins were administered the adult version of the interview. Laboratory studies with repeat interviews, neuropsychological tests, and collection of DNA were made of intensively studied twins during follow-up in early adulthood. The basic aim of the FT12 study design was to obtain information on individual, familial and school/neighborhood risks for substance use/abuse prior to the onset of regular tobacco and alcohol use and then track trajectories of use and abuse and their consequences into adulthood. But the longitudinal assessments were not narrowly limited to this basic aim, and with multiwave, multirater assessments from ages 11 to 12, the study has created a richly informative data set for analyses of gene–environment interactions of both candidate genes and genomewide measures with measured risk-relevant environments. Because 25 years have elapsed since the start of the study, we are planning a fifth-wave follow-up assessment.

We investigated the association between perceived occupational noise exposure and depressive symptoms in young Finnish adults and whether noise sensitivity moderates this association. This study was based on an ongoing longitudinal twin study. We included those who had been working daily (n = 521) or weekly (n = 245) during the past 12 months (mean age 22.4, SD 0.7, 53% female). We asked about occupational noise exposure at age 22 and assessed depressive symptoms using the General Behavior Inventory (GBI) at age 17 and 22. Noise sensitivity and covariates were used in linear regression models. Perceived daily occupational noise exposure was associated, as a statistically independent main effect with depressive symptoms at age 22 (beta 1.19; 95% CI 0.09, 2.29) among all, and separately for females (beta 2.22; 95% CI 0.34, 4.09) but not males (beta 0.22; 95% CI −1.08, 1.52). Noise sensitivity was independently associated with depressive symptoms among all (beta 1.35; 95% CI 0.54, 2.17), and separately for males (beta 1.96; 95% CI 0.68, 3.24) but not females (beta 1.05; 95 % CI −0.04, 2.13). Noise sensitivity was independent of perceived occupational noise exposure. Pre-existing depressive symptoms at age 17 were predictive of perceived occupational noise exposure, suggesting complex interactions of noise and depression.