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Background There is still limited evidence from prospective high-risk research on the evolution of specific disorders that may emerge early in the development of mood disorders. Moreover, few studies have examined the specificity of mood disorder subtypes among offspring of parents with both major subtypes of mood disorders and controls based on prospective tracking across the transition from childhood to adulthood. Our specific objectives were to (a) identify differences in patterns of psychopathological precursors among youth with (hypo)mania compared to MDD and (b) examine whether these patterns differ by subtypes of parental mood disorders. Methods Our data stem from a prospective cohort study of 449 directly interviewed offspring (51% female, mean age 10.1 years at study intake) of 88 patients with BPD, 71 with MDD, 30 with substance use disorders and 60 medical controls. The mean duration of follow-up was 13.2 years with evaluations conducted every three years. Results Within the whole cohort of offspring, MDE (Hazard Ratio = 4.44; 95%CI: 2.19-9.02), CD (HR = 3.31;1.55-7.07) and DUD (HR = 2.54; 1.15-5.59) predicted the onset of (hypo)manic episodes, whereas MDD in offspring was predicted by SAD (HR = 1.53; 1.09-2.15), generalized anxiety (HR = 2.56; 1.05-6.24), and panic disorder (HR = 3.13; 1.06-9.23). The early predictors of (hypo)mania in the whole cohort were also significantly associated with the onset of (hypo)mania among the offspring of parents with BPD. Conclusions The onset of mood disorders is frequently preceded by identifiable depressive episodes and nonmood disorders. These precursors differed by mood subtype in offspring. High-risk offspring with these precursors should be closely monitored to prevent the further development of MDD or conversion to BPD.

OBJECTIVE There is much controversy about the neurobiological mechanisms underlying the effects of sleep-disordered breathing on the brain. The aim of this study was to investigate the association between markers of sleep-related hypoxemia and brain anatomy. METHODS We used data from a large-scale cohort from the general population (n = 775, 50.6% males, age range = 45-86 years, mean age = 60.3 ± 9.9) that underwent full polysomnography and brain magnetic resonance imaging to correlate respiratory variables with regional brain volume estimates. RESULTS After adjusting for age, gender, and cardiovascular risk factors, only mean oxygen saturation during sleep was associated with bilateral volume of hippocampus (right: p = 0.001; left: p

The human brain undergoes dramatic structural change over the life span. In a large imaging cohort of 801 individuals aged 7–84 years, we applied quantitative relaxometry and diffusion microstructure imaging in combination with diffusion tractography to investigate tissue property dynamics across the human life span. Significant nonlinear aging effects were consistently observed across tracts and tissue measures. The age at which white matter (WM) fascicles attain peak maturation varies substantially across tissue measurements and tracts. These observations of heterochronicity and spatial heterogeneity of tract maturation highlight the importance of using multiple tissue measurements to investigate each region of the WM. Our data further provide additional quantitative evidence in support of the last‐in‐first‐out retrogenesis hypothesis of aging, demonstrating a strong correlational relationship between peak maturational timing and the extent of quadratic measurement differences across the life span for the most myelin sensitive measures. These findings present an important baseline from which to assess divergence from normative aging trends in developmental and degenerative disorders, and to further investigate the mechanisms connecting WM microstructure to cognition.

Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging.

INTRODUCTION: It’s imperative to understand the specific and shared aetiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. METHODS: Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic aetiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in eleven data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. RESULTS: All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. CONCLUSIONS: The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic aetiology irrespective of the age depression first presents.

To achieve sample sizes necessary for effectively conducting genome-wide association studies (GWASs), researchers often combine data from samples possessing multiple potential sources of heterogeneity. This is particularly relevant for psychiatric disorders, where symptom self-report, differing assessment instruments, and diagnostic comorbidity complicates the phenotypes and contribute to difficulties with detecting and replicating genetic association signals. We investigated sources of heterogeneity of anxiety disorders (ADs) across five large cohorts used in a GWAS meta-analysis project using a dimensional structural modeling approach including confirmatory factor analyses (CFAs) and measurement invariance (MI) testing. CFA indicated a single-factor model provided the best fit in each sample with the same pattern of factor loadings. MI testing indicated degrees of failure of metric and scalar invariance which depended on the inclusion of the effects of sex and age in the model. This is the first study to examine the phenotypic structure of psychiatric disorder phenotypes simultaneously across multiple, large cohorts used for GWAS. The analyses provide evidence for higher order invariance but possible break-down at more detailed levels that can be subtly influenced by included covariates, suggesting caution when combining such data. These methods have significance for large-scale collaborative studies that draw on multiple, potentially heterogeneous datasets. Copyright © 2016 John Wiley & Sons, Ltd.

OBJECTIVE: Periodic limb movements during sleep (PLMS) are sleep phenomena characterized by periodic episodes of repetitive stereotyped limb movements. The aim of this study was to describe the prevalence and determinants of PLMS in a middle to older aged general population. METHODS: Data from 2,162 subjects (51.2% women, mean age = 58.4 ± 11.1 years) participating in a population-based study (HypnoLaus, Lausanne, Switzerland) were collected. Assessments included laboratory tests, sociodemographic data, personal and treatment history, and full polysomnography at home. PLMS index (PLMSI) was determined, and PLMSI > 15/h was considered as significant. RESULTS: Prevalence of PLMSI > 15/h was 28.6% (31.3% in men, 26% in women). Compared to subjects with PLMSI ≤ 15/h, subjects with PLMSI > 15/h were older (p 15/h also had a higher prevalence of diabetes, hypertension, and beta-blocker or hypnotic treatments. The prevalence of antidepressant use was higher, but not statistically significant (p = 0.07). Single nucleotide polymorphisms (SNPs) within BTBD9 (rs3923809), TOX3 (rs3104788), and MEIS1 (rs2300478) genes were significantly associated with PLSMI > 15/h. Conversely, mean hemoglobin and ferritin levels were similar in both groups. In the multivariate analysis, age, male gender, antidepressant intake, RLS, and rs3923809, rs3104788, and rs2300478 SNPs were independently associated with PLMSI > 15/h. INTERPRETATION: PLMS are highly prevalent in our middle-aged European population. Age, male gender, RLS, antidepressant treatment, and specific BTBD9, TOX3, and MEIS1 SNP distribution are independent predictors of PLMSI > 15/h. ANN NEUROL 2016;79:464-474.

The American Psychiatric Association estimates that 3 to 7 per cent of all school aged children are diagnosed with attention deficit hyperactivity disorder (ADHD). Even after correcting for general cognitive ability, numerous studies report a negative association between ADHD and educational achievement. With polygenic scores we examined whether genetic variants that have a positive influence on educational attainment have a protective effect against ADHD. The effect sizes from a large GWA meta-analysis of educational attainment in adults were used to calculate polygenic scores in an independent sample of 12-year-old children from the Netherlands Twin Register. Linear mixed models showed that the polygenic scores significantly predicted educational achievement, school performance, ADHD symptoms and attention problems in children. These results confirm the genetic overlap between ADHD and educational achievement, indicating that one way to gain insight into genetic variants responsible for variation in ADHD is to include data on educational achievement, which are available at a larger scale. (C) 2014 Wiley Periodicals, Inc.

There is limited information on the specificity of associations between parental bipolar disorder (BPD) and major depressive disorder (MDD) and the risk of psychopathology in offspring. The chief aim of the present study was to investigate the association between mood disorder subtypes in the two parents and mental disorders in the offspring.

Bipolar affective disorder (BPAD) is a complex psychiatric disorder with a major genetic contribution. Abnormalities in serotonergic function have been implicated in its aetiology. The 5HT2A receptor (5HT2AR) gene is a strong candidate gene for involvement in BPAD, but previous association studies have reported conflicting results. These data are difficult to interpret because most negative results were obtained with small samples. The aim of this study was to test the association between the 5HT2AR gene and BPAD in a large West European sample. We studied the -1438G/A and the His452Tyr polymorphisms, for haplotype analysis to increase both informativity and the likelihood of detecting an association between BPAD and the 5HT2AR gene. We analysed the genotype, allele and haplotype distributions of two 5HT2AR gene variants in a population of 356 BPAD patients, which we compared with 208 healthy controls. We also carried out exploratory analysis in clinical subgroups of patients defined according to personal history of mood disorders, suicidal behaviour, comorbid psychiatric disorders and family history of affective disorders. We found no difference between BPAD patients and controls for allele, genotype and haplotype distributions. Exploratory analysis in subgroups of BPAD patients showed only a marginal difference in haplotype distribution between controls and BPAD patients with antidepressant-induced mania (P = 0.018). This difference was not significant after correction for multiple testing. Our study suggests that the 5HT2AR gene is unlikely to be involved in genetic susceptibility to BPAD but should be further investigated in a pharmacogenetic study.

Objective: This report examines: 1) the magnitude of co-occurrence of threshold and subthreshold-level depression and anxiety in the community, and 2) the relationship between comorbidity and the diagnostic level of depression and anxiety and their clinical correlates. Method: A community sample of 591 subjects was interviewed prospectively five times across 15 years from the ages of 20-35, The diagnostic interview allowed the assignment of diagnoses according to DSM-III criteria and operational definitions of subthreshold syndromes. Results: I ) Comorbidity between depression and anxiety was more frequent when one syndrome reached threshold level; 2) comorbidity at both the threshold and subthreshold diagnostic levels was associated with symptom severity, disability and treatment, whereas the diagnostic level was associated with disability and suicidal attempts. Conclusion: The systematic association between comorbidity across diagnostic threshold levels of anxiety and depression with clinical correlates suggests the importance of a more dimensional approach to their classification.

Objective: The aims of the present study were to assess the associations between mood, anxiety and substance use disorders, including their subtypes, and the prevalence of cardiovascular risk factors (CVRFs). Method: Thorough physical investigations, biological measures and standardized interview techniques were used to assess 3716 subjects of an urban area, aged 35–66 years. Results: Atypical depression was associated with increased prevalence of overweight, diabetes and the metabolic syndrome (OR = 1.5, 95% C.I. 1.1–2.0; OR = 2.0, 95% C.I. 1.1–3.5, OR = 1.6, 95% C.I. 1.0–2.4 respectively), whereas decreased prevalence of overweight was found in melancholic (OR = 0.7, 95% C.I. 0.6–0.9) and unspecified depression (OR = 0.8, 95% C.I. 0.7–1.0). Alcohol abuse was associated with diabetes (OR = 1.8, 95% C.I. 1.1–2.9) and dyslipidemia (OR = 1.3, 95% C.I. 1.0–1.8), alcohol dependence with dyslipidemia only (OR = 1.4, 95% C.I. 1.0–2.0). Almost all mental disorders were associated with a lifetime history of regular cigarette smoking, and atypical depression, alcohol misuse and drug dependence were associated with inactivity. Conclusion: To conclude results emphasize the need to subtype depression and to pay particular attention to the atypical subtype. Comorbid alcohol misuse may further increase the cardiovascular risk. Efforts to diminish smoking in subjects with mental disorders could be crucial measures to reduce their high incidence of cardiovascular disease.