Low mood in a sample of 5-12 year-old child psychiatric patients: a cross-sectional study.

BACKGROUND: Not much is known about low mood and its associates in child psychiatric patients. In this study, we examined the prevalence of low mood, how it associates with disruptive behaviour, and affects clinician-rated global functioning in child psychiatric outpatients. METHODS: The study population consisted of 862 5-12 year-old child psychiatric patients. The study sample was a subsample of all 1251 patients attending a child psychiatric outpatient clinic at Helsinki University Hospital in 2013-2015 formed by excluding 4 year-old and 13 year-old patients and those with missing or incomplete data. The parent-rated Strengths and Difficulties Questionnaire, collected as part of the routine clinical baseline measure, was used as a measure of psychiatric symptoms. The diagnoses were set according to ICD-10 by the clinician in charge after an initial evaluation period. The Children's Global Assessment Scale (CGAS) score set by clinicians provided the measure of the patients' global functioning. All information for the study was collected from hospital registers. Associations between emotional symptoms and conduct problems/hyperactivity scores were examined using ordinal regression in univariate and multivariate models, controlling for age and sex. The independent samples T test was used to compare the CGAS values of patient groups with low/normal mood. RESULTS: In our sample, 512 children (59.4%) showed low mood. In multivariate ordinal regression analysis, low mood associated with conduct problems (OR 1.93, 95% CI 1.39-2.67), but no association was found between low mood and hyperactivity. Low mood was prevalent among children with oppositional defiant disorder or conduct disorder (51.8%). The global functioning score CGAS was lower among children with parent-reported low mood (52.21) than among children with normal mood (54.62, p < 0.001). The same was true in the subgroup of patients with no depression diagnosis (54.85 vs. 52.82, p = 0.001). CONCLUSIONS: Low mood is prevalent in child psychiatric outpatients regardless of depression diagnosis and it has a negative effect on global functioning. Low mood and behavioural problems are often associated. It is important to pay attention to low mood in all child psychiatric patients. We recommend prevention measures and low-threshold services for children with low mood.

Temperament clusters in a normal population: implications for health and disease.

BACKGROUND: The object of this study was to identify temperament patterns in the Finnish population, and to determine the relationship between these profiles and life habits, socioeconomic status, and health. METHODS/PRINCIPAL FINDINGS: A cluster analysis of the Temperament and Character Inventory subscales was performed on 3,761 individuals from the Northern Finland Birth Cohort 1966 and replicated on 2,097 individuals from the Cardiovascular Risk in Young Finns study. Clusters were formed using the k-means method and their relationship with 115 variables from the areas of life habits, socioeconomic status and health was examined. RESULTS: Four clusters were identified for both genders. Individuals from Cluster I are characterized by high persistence, low extravagance and disorderliness. They have healthy life habits, and lowest scores in most of the measures for psychiatric disorders. Cluster II individuals are characterized by low harm avoidance and high novelty seeking. They report the best physical capacity and highest level of income, but also high rate of divorce, smoking, and alcohol consumption. Individuals from Cluster III are not characterized by any extreme characteristic. Individuals from Cluster IV are characterized by high levels of harm avoidance, low levels of exploratory excitability and attachment, and score the lowest in most measures of health and well-being. CONCLUSIONS: This study shows that the temperament subscales do not distribute randomly but have an endogenous structure, and that these patterns have strong associations to health, life events, and well-being.

Early environment and neurobehavioral development predict adult temperament clusters.

BACKGROUND: Investigation of the environmental influences on human behavioral phenotypes is important for our understanding of the causation of psychiatric disorders. However, there are complexities associated with the assessment of environmental influences on behavior. METHODS/PRINCIPAL FINDINGS: We conducted a series of analyses using a prospective, longitudinal study of a nationally representative birth cohort from Finland (the Northern Finland 1966 Birth Cohort). Participants included a total of 3,761 male and female cohort members who were living in Finland at the age of 16 years and who had complete temperament scores. Our initial analyses (Wessman et al., in press) provide evidence in support of four stable and robust temperament clusters. Using these temperament clusters, as well as independent temperament dimensions for comparison, we conducted a data-driven analysis to assess the influence of a broad set of life course measures, assessed pre-natally, in infancy, and during adolescence, on adult temperament. RESULTS: Measures of early environment, neurobehavioral development, and adolescent behavior significantly predict adult temperament, classified by both cluster membership and temperament dimensions. Specifically, our results suggest that a relatively consistent set of life course measures are associated with adult temperament profiles, including maternal education, characteristics of the family's location and residence, adolescent academic performance, and adolescent smoking. CONCLUSIONS: Our finding that a consistent set of life course measures predict temperament clusters indicate that these clusters represent distinct developmental temperament trajectories and that information about a subset of life course measures has implications for adult health outcomes.

Mixture model clustering of phenotype features reveals evidence for association of DTNBP1 to a specific subtype of schizophrenia.

BACKGROUND: While DTNBP1, DISC1, and NRG1 have been extensively studied as candidate genes of schizophrenia, results remain inconclusive. Possible explanations for this are that the genes might be relevant only to certain subtypes of the disease and/or only in certain populations. METHODS: We performed unsupervised clustering of individuals from Finnish schizophrenia families, based on extensive clinical and neuropsychological data, including Structured Clinical Interview for DSM-IV (SCID) information. Families with at least one affected member with DSM-IV diagnosis of a schizophrenia spectrum psychosis were included in a register-based ascertainment. Final sample consisted of 904 individuals from 288 families. We then used the cluster phenotypes in a genetic association study of candidate genes. RESULTS: A robust three-class clustering of individuals emerged: 1) psychotic disorder with mood symptoms (n = 172), 2) core schizophrenia (n = 223), and 3) absence of psychotic disorder (n = 509). One third of the individuals diagnosed with schizophrenia were assigned to cluster 1. These individuals had fewer negative and positive psychotic symptoms and cognitive deficits but more depressive symptoms than individuals in cluster 2. There was a significant association of cluster 2 cases with the DTNBP1 gene, while the DISC1 gene indicated a significant association with schizophrenia spectrum disorders based on the DSM-IV criteria. CONCLUSIONS: In the Finnish population, DTNBP1 gene is associated with a schizophrenia phenotype characterized by prominent negative symptoms, generalized cognitive impairment, and few mood symptoms. Identification of genes and pathways related to schizophrenia necessitates novel definitions of disease phenotypes associated more directly with underlying biology.