Longitudinal associations between alcohol use, smoking, genetic risk scoring and symptoms of depression in the general population: a prospective 6-year cohort study.

BACKGROUND: Alcohol consumption, smoking and mood disorders are leading contributors to the global burden of disease and are highly comorbid. Yet, their interrelationships have remained elusive. The aim of this study was to examine the multi-cross-sectional and longitudinal associations between (change in) smoking and alcohol use and (change in) number of depressive symptoms. METHODS: In this prospective, longitudinal study, 6646 adults from the general population were included with follow-up measurements after 3 and 6 years. Linear mixed-effects models were used to test multi-cross-sectional and longitudinal associations, with smoking behaviour, alcohol use and genetic risk scores for smoking and alcohol use as independent variables and depressive symptoms as dependent variables. RESULTS: In the multi-cross-sectional analysis, smoking status and number of cigarettes per day were positively associated with depressive symptoms (p < 0.001). Moderate drinking was associated with less symptoms of depression compared to non-use (p = 0.011). Longitudinally, decreases in the numbers of cigarettes per day and alcoholic drinks per week as well as alcohol cessation were associated with a reduction of depressive symptoms (p = 0.001-0.028). Results of genetic risk score analyses aligned with these findings. CONCLUSIONS: While cross-sectionally smoking and moderate alcohol use show opposing associations with depressive symptoms, decreases in smoking behaviour as well as alcohol consumption are associated with improvements in depressive symptoms over time. Although we cannot infer causality, these results open avenues to further investigate interventions targeting smoking and alcohol behaviours in people suffering from depressive symptoms.

Polygenic risk scores for genetic counseling in psychiatry: Lessons learned from other fields of medicine.

Polygenic risk scores (PRS) may aid in the identification of individuals at-risk for psychiatric disorders, treatment optimization, and increase in prognostic accuracy. PRS may also add significant value to genetic counseling. Thus far, integration of PRSs in genetic counseling sessions remains problematic because of uncertainties in risk prediction and other concerns. Here, we review the current utility of PRSs in the context of clinical psychiatry. By comprehensively appraising the literature in other fields of medicine including breast cancer, Alzheimer's Disease, and cardiovascular disease, we outline several lessons learned that could be applied to future studies and may thus benefit the incorporation of PRS in psychiatric genetic counseling. These include integrating PRS with environmental factors (e.g. lifestyle), setting up large-scale studies, and applying reproducible methods allowing for cross-validation between cohorts. We conclude that psychiatry may benefit from experiences in these fields. PRS may in future have a role in genetic counseling in clinical psychiatric practice, by advancing prevention strategies and treatment decision-making, thus promoting quality of life for (potentially) affected individuals.

Genome-wide association study of monoamine metabolite levels in human cerebrospinal fluid.

Studying genetic determinants of intermediate phenotypes is a powerful tool to increase our understanding of genotype-phenotype correlations. Metabolic traits pertinent to the central nervous system (CNS) constitute a potentially informative target for genetic studies of intermediate phenotypes as their genetic underpinnings may elucidate etiological mechanisms. We therefore conducted a genome-wide association study (GWAS) of monoamine metabolite (MM) levels in cerebrospinal fluid (CSF) of 414 human subjects from the general population. In a linear model correcting for covariates, we identified one locus associated with MMs at a genome-wide significant level (standardized ß=0.32, P=4.92 × 10(-8)), located 20 kb from SSTR1, a gene involved with brain signal transduction and glutamate receptor signaling. By subsequent whole-genome expression quantitative trait locus (eQTL) analysis, we provide evidence that this variant controls expression of PDE9A (ß=0.21; P unadjusted=5.6 × 10(-7); P corrected=0.014), a gene previously implicated in monoaminergic transmission, major depressive disorder and antidepressant response. A post hoc analysis of loci significantly associated with psychiatric disorders suggested that genetic variation at CSMD1, a schizophrenia susceptibility locus, plays a role in the ratio between dopamine and serotonin metabolites in CSF. The presented DNA and mRNA analyses yielded genome-wide and suggestive associations in biologically plausible genes, two of which encode proteins involved with glutamate receptor functionality. These findings will hopefully contribute to an exploration of the functional impact of the highlighted genes on monoaminergic transmission and neuropsychiatric phenotypes.