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 β=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 (β=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.

Seasonal patterns in behavior and biological parameters are widespread. Here, we examined seasonal changes in whole blood gene expression profiles of 233 healthy subjects. Using weighted gene co-expression network analysis, we identified three co-expression modules showing circannual patterns. Enrichment analysis suggested that this signal stems primarily from red blood cells and blood platelets. Indeed, a large clinical database with 51 142 observations of blood cell counts over 3 years confirmed a corresponding seasonal pattern of counts of red blood cells, reticulocytes and platelets. We found no direct evidence that these changes are linked to genes known to be key players in regulating immune function or circadian rhythm. It is likely, however, that these seasonal changes in cell counts and gene expression profiles in whole blood represent biological and clinical relevant phenomena. Moreover, our findings highlight possible confounding factors relevant to the study of gene expression profiles in subjects collected at geographical locations with disparaging seasonality patterns.

The blood–brain barrier separates circulating blood from the central nervous system (CNS). The scope of this barrier is not fully understood which limits our ability to relate biological measurements from peripheral to central phenotypes. For example, it is unknown to what extent gene expression levels in peripheral blood are reflective of CNS metabolism. In this study, we examine links between central monoamine metabolite levels and whole-blood gene expression to better understand the connection between peripheral systems and the CNS. To that end, we correlated the prime monoamine metabolites in cerebrospinal fluid (CSF) with whole-genome gene expression microarray data from blood (N=240 human subjects). We additionally applied gene-enrichment analysis and weighted gene co-expression network analyses (WGCNA) to identify modules of co-expressed genes in blood that may be involved with monoamine metabolite levels in CSF. Transcript levels of two genes were significantly associated with CSF serotonin metabolite levels after Bonferroni correction for multiple testing: THAP7 (P=2.8 × 10−8, β=0.08) and DDX6 (P=2.9 × 10−7, β=0.07). Differentially expressed genes were significantly enriched for genes expressed in the brain tissue (P=6.0 × 10−52). WGCNA revealed significant correlations between serotonin metabolism and hub genes with known functions in serotonin metabolism, for example, HTR2A and COMT. We conclude that gene expression levels in whole blood are associated with monoamine metabolite levels in the human CSF. Our results, including the strong enrichment of brain-expressed genes, illustrate that gene expression profiles in peripheral blood can be relevant for quantitative metabolic phenotypes in the CNS.