Seasonal variation of serotonin turnover in human cerebrospinal fluid, depressive symptoms and the role of the 5-HTTLPR.

Studying monoaminergic seasonality is likely to improve our understanding of neurobiological mechanisms underlying season-associated physiological and pathophysiological behavior. Studies of monoaminergic seasonality and the influence of the serotonin-transporter-linked polymorphic region (5-HTTLPR) on serotonin seasonality have yielded conflicting results, possibly due to lack of power and absence of multi-year analyses. We aimed to assess the extent of seasonal monoamine turnover and examined the possible involvement of the 5-HTTLPR. To determine the influence of seasonality on monoamine turnover, 5-hydroxyindoleacetic acid (5-HIAA) and homovanillic acid (HVA) were measured in the cerebrospinal fluid of 479 human subjects collected during a 3-year period. Cosine and non-parametric seasonal modeling were applied to both metabolites. We computed serotonin (5-HT) seasonality values and performed an association analysis with the s/l alleles of the 5-HTTLPR. Depressive symptomatology was assessed using the Beck Depression Inventory-II. Circannual variation in 5-HIAA fitted a spring-peak cosine model that was significantly associated with sampling month (P=0.0074). Season of sampling explained 5.4% (P=1.57 × 10(-7)) of the variance in 5-HIAA concentrations. The 5-HTTLPR s-allele was associated with increased 5-HIAA seasonality (standardized regression coefficient=0.12, P=0.020, N=393). 5-HIAA seasonality correlated with depressive symptoms (Spearman's rho=0.13, P=0.018, N=345). In conclusion, we highlight a dose-dependent association of the 5-HTTLPR with 5-HIAA seasonality and a positive correlation between 5-HIAA seasonality and depressive symptomatology. The presented data set the stage for follow-up in clinical populations with a role for seasonality, such as affective disorders

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci.

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies

Fitness Consequences of Advanced Ancestral Age over Three Generations in Humans

A rapid rise in age at parenthood in contemporary societies has increased interest in reports of higher prevalence of de novo mutations and health problems in individuals with older fathers, but the fitness consequences of such age effects over several generations remain untested. Here, we use extensive pedigree data on seven pre-industrial Finnish populations to show how the ages of ancestors for up to three generations are associated with fitness traits. Individuals whose fathers, grandfathers and great-grandfathers fathered their lineage on average under age 30 were ~13% more likely to survive to adulthood than those whose ancestors fathered their lineage at over 40 years. In addition, females had a lower probability of marriage if their male ancestors were older. These findings are consistent with an increase of the number of accumulated de novo mutations with male age, suggesting that deleterious mutations acquired from recent ancestors may be a substantial burden to fitness in humans. However, possible non-mutational explanations for the observed associations are also discussed

The Co-Morbidity Burden of Children and Young Adults with Autism Spectrum Disorders

Objectives: Use electronic health records Autism Spectrum Disorder (ASD) to assess the comorbidity burden of ASD in children and young adults. Study Design: A retrospective prevalence study was performed using a distributed query system across three general hospitals and one pediatric hospital. Over 14,000 individuals under age 35 with ASD were characterized by their co-morbidities and conversely, the prevalence of ASD within these comorbidities was measured. The comorbidity prevalence of the younger (Age<18 years) and older (Age 18–34 years) individuals with ASD was compared. Results: 19.44% of ASD patients had epilepsy as compared to 2.19% in the overall hospital population (95% confidence interval for difference in percentages 13.58–14.69%), 2.43% of ASD with schizophrenia vs. 0.24% in the hospital population (95% CI 1.89–2.39%), inflammatory bowel disease (IBD) 0.83% vs. 0.54% (95% CI 0.13–0.43%), bowel disorders (without IBD) 11.74% vs. 4.5% (95% CI 5.72–6.68%), CNS/cranial anomalies 12.45% vs. 1.19% (95% CI 9.41–10.38%), diabetes mellitus type I (DM1) 0.79% vs. 0.34% (95% CI 0.3–0.6%), muscular dystrophy 0.47% vs 0.05% (95% CI 0.26–0.49%), sleep disorders 1.12% vs. 0.14% (95% CI 0.79–1.14%). Autoimmune disorders (excluding DM1 and IBD) were not significantly different at 0.67% vs. 0.68% (95% CI −0.14-0.13%). Three of the studied comorbidities increased significantly when comparing ages 0–17 vs 18–34 with p<0.001: Schizophrenia (1.43% vs. 8.76%), diabetes mellitus type I (0.67% vs. 2.08%), IBD (0.68% vs. 1.99%) whereas sleeping disorders, bowel disorders (without IBD) and epilepsy did not change significantly. Conclusions: The comorbidities of ASD encompass disease states that are significantly overrepresented in ASD with respect to even the patient populations of tertiary health centers. This burden of comorbidities goes well beyond those routinely managed in developmental medicine centers and requires broad multidisciplinary management that payors and providers will have to plan for

Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD

Seasonal variation of serotonin turnover in human cerebrospinal fluid, depressive symptoms and the role of the 5-HTTLPR.

Studying monoaminergic seasonality is likely to improve our understanding of neurobiological mechanisms underlying season-associated physiological and pathophysiological behavior. Studies of monoaminergic seasonality and the influence of the serotonin-transporter-linked polymorphic region (5-HTTLPR) on serotonin seasonality have yielded conflicting results, possibly due to lack of power and absence of multi-year analyses. We aimed to assess the extent of seasonal monoamine turnover and examined the possible involvement of the 5-HTTLPR. To determine the influence of seasonality on monoamine turnover, 5-hydroxyindoleacetic acid (5-HIAA) and homovanillic acid (HVA) were measured in the cerebrospinal fluid of 479 human subjects collected during a 3-year period. Cosine and non-parametric seasonal modeling were applied to both metabolites. We computed serotonin (5-HT) seasonality values and performed an association analysis with the s/l alleles of the 5-HTTLPR. Depressive symptomatology was assessed using the Beck Depression Inventory-II. Circannual variation in 5-HIAA fitted a spring-peak cosine model that was significantly associated with sampling month (P=0.0074). Season of sampling explained 5.4% (P=1.57 × 10(-7)) of the variance in 5-HIAA concentrations. The 5-HTTLPR s-allele was associated with increased 5-HIAA seasonality (standardized regression coefficient=0.12, P=0.020, N=393). 5-HIAA seasonality correlated with depressive symptoms (Spearman's rho=0.13, P=0.018, N=345). In conclusion, we highlight a dose-dependent association of the 5-HTTLPR with 5-HIAA seasonality and a positive correlation between 5-HIAA seasonality and depressive symptomatology. The presented data set the stage for follow-up in clinical populations with a role for seasonality, such as affective disorders

Increased paternal age and the influence on burden of genomic copy number variation in the general population

Item does not contain fulltextGenomic copy number variations (CNVs) and increased parental age are both associated with the risk to develop a variety of clinical neuropsychiatric disorders such as autism, schizophrenia and bipolar disorder. At the same time, it has been shown that the rate of transmitted de novo single nucleotide mutations is increased with paternal age. To address whether paternal age also affects the burden of structural genomic deletions and duplications, we examined various types of CNV burden in a large population sample from the Netherlands. Healthy participants with parental age information (n = 6,773) were collected at different University Medical Centers. CNVs were called with the PennCNV algorithm using Illumina genome-wide SNP array data. We observed no evidence in support of a paternal age effect on CNV load in the offspring. Our results were negative for global measures as well as several proxies for de novo CNV events in this unique sample. While recent studies suggest de novo single nucleotide mutation rate to be dominated by the age of the father at conception, our results strongly suggest that at the level of global CNV burden there is no influence of increased paternal age. While it remains possible that local genomic effects may exist for specific phenotypes, this study indicates that global CNV burden and increased father's age may be independent disease risk factors

Common alleles contribute to schizophrenia in CNV carriers

The genetic architecture of schizophrenia is complex, involving risk alleles ranging from common alleles of weak effect to rare alleles of large effect, the best exemplar of the latter being large copy number variants (CNVs). It is currently unknown whether pathophysiology in those with defined rare mutations overlaps with that in other individuals with the disorder who do not share the same rare mutation. Under an extreme heterogeneity model, carriers of specific high-penetrance mutations form distinct subgroups. In contrast, under a polygenic threshold model, high-penetrance rare allele carriers possess many risk factors, of which the rare allele is the only one, albeit an important, factor. Under the latter model, cases with rare mutations can be expected to share some common risk alleles, and therefore pathophysiological mechanisms, with cases without the same mutation. Here we show that, compared with controls, individuals with schizophrenia who have known pathogenic CNVs carry an excess burden of common risk alleles (P=2.25 × 10−17) defined from a genome-wide association study largely based on individuals without known CNVs. Our finding is not consistent with an extreme heterogeneity model for CNV carriers, but does offer support for the polygenic threshold model of schizophrenia. That this is so provides support for the notion that studies aiming to model the effects of rare variation may uncover pathophysiological mechanisms of relevance to those with the disorder more widely