Paternal age and psychiatric disorders: A review.

We review the hypotheses concerning the association between the paternal age at childbearing and childhood psychiatric disorders (autism spectrum- and attention deficit/hyperactive disorder) and adult disorders (schizophrenia, bipolar-, obsessive-compulsive-, and major depressive disorder) based on epidemiological studies. Several hypotheses have been proposed to explain the paternal age effect. We discuss the four main-not mutually exclusive-hypotheses. These are the de novo mutation hypothesis, the hypothesis concerning epigenetic alterations, the selection into late fatherhood hypothesis, and the environmental resource hypothesis. Advanced paternal age in relation to autism spectrum disorders and schizophrenia provided the most robust epidemiological evidence for an association, with some studies reporting a monotonic risk increase over age, and others reporting a marked increase at a given age threshold. Although there is evidence for the de novo mutation hypothesis and the selection into late fatherhood hypothesis, the mechanism(s) underlying the association between advanced paternal age and psychiatric illness in offspring remains to be further clarified. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Seasonal changes in gene expression represent cell-type composition in whole blood.

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.

Large recurrent microdeletions associated with schizophrenia.

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

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

Genomic 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.

Familial clustering of schizophrenia, bipolar disorder, and major depressive disorder.

PURPOSE: To investigate familial clustering of schizophrenia, bipolar disorder, and major depressive disorder. METHODS: Combining data from a psychiatric case registry and Statistics Netherlands provided information on 4,673 affected probands and 18,692 matched population controls. RESULTS: Probands with schizophrenia had relative risks (RRs) for having a sibling with schizophrenia of 3.77 (95% confidence interval (CI): 2.60-5.46) and with bipolar disorder of 1.79 (95% CI: 0.64-4.96) as compared with a reference proband. Probands affected with bipolar disorder have an RR of 6.51 (95% CI: 2.60-16.29) for having a sibling with bipolar disorder and of 1.71 (95% CI: 0.71-4.14) for having a sibling with schizophrenia as compared with a reference proband. Probands affected with major depressive disorder also have increased risk for having a sibling with schizophrenia (RR: 2.04, 95% CI: 1.54-2.72) as compared with a reference proband, which was similar to the risk for having a sibling with major depressive disorder (RR: 1.91, 95% CI: 1.63-2.24) or bipolar disorder (RR: 2.06, 95% CI: 1.18-3.60). CONCLUSION: Our findings suggest, as previous studies have, that risk across schizophrenia and bipolar disorder is considerably lower (twofold) than within diagnostic entities, whereas for major depressive disorder risk is similar within and across diagnostic entities.

Disruption of the neurexin 1 gene is associated with schizophrenia.

Deletions within the neurexin 1 gene (NRXN1; 2p16.3) are associated with autism and have also been reported in two families with schizophrenia. We examined NRXN1, and the closely related NRXN2 and NRXN3 genes, for copy number variants (CNVs) in 2977 schizophrenia patients and 33 746 controls from seven European populations (Iceland, Finland, Norway, Germany, The Netherlands, Italy and UK) using microarray data. We found 66 deletions and 5 duplications in NRXN1, including a de novo deletion: 12 deletions and 2 duplications occurred in schizophrenia cases (0.47%) compared to 49 and 3 (0.15%) in controls. There was no common breakpoint and the CNVs varied from 18 to 420 kb. No CNVs were found in NRXN2 or NRXN3. We performed a Cochran-Mantel-Haenszel exact test to estimate association between all CNVs and schizophrenia (P = 0.13; OR = 1.73; 95% CI 0.81-3.50). Because the penetrance of NRXN1 CNVs may vary according to the level of functional impact on the gene, we next restricted the association analysis to CNVs that disrupt exons (0.24% of cases and 0.015% of controls). These were significantly associated with a high odds ratio (P = 0.0027; OR 8.97, 95% CI 1.8-51.9). We conclude that NRXN1 deletions affecting exons confer risk of schizophrenia.

Recurrent CNVs disrupt three candidate genes in schizophrenia patients.

Schizophrenia is a severe psychiatric disease with complex etiology, affecting approximately 1% of the general population. Most genetics studies so far have focused on disease association with common genetic variation, such as single-nucleotide polymorphisms (SNPs), but it has recently become apparent that large-scale genomic copy-number variants (CNVs) are involved in disease development as well. To assess the role of rare CNVs in schizophrenia, we screened 54 patients with deficit schizophrenia using Affymetrix's GeneChip 250K SNP arrays. We identified 90 CNVs in total, 77 of which have been reported previously in unaffected control cohorts. Among the genes disrupted by the remaining rare CNVs are MYT1L, CTNND2, NRXN1, and ASTN2, genes that play an important role in neuronal functioning but--except for NRXN1--have not been associated with schizophrenia before. We studied the occurrence of CNVs at these four loci in an additional cohort of 752 patients and 706 normal controls from The Netherlands. We identified eight additional CNVs, of which the four that affect coding sequences were found only in the patient cohort. Our study supports a role for rare CNVs in schizophrenia susceptibility and identifies at least three candidate genes for this complex disorder.

A co-segregating microduplication of chromosome 15q11.2 pinpoints two risk genes for autism spectrum disorder.

High resolution genomic copy-number analysis has shown that inherited and de novo copy-number variations contribute significantly to autism pathology, and that identification of small chromosomal aberrations related to autism will expedite the discovery of risk genes involved. Here, we report a microduplication of chromosome 15q11.2, spanning only four genes, co-segregating with autism in a Dutch pedigree, identified by SNP microarray analysis, and independently confirmed by FISH and MLPA analysis. Quantitative RT-PCR analysis revealed over 70% increase in peripheral blood mRNA levels for the four genes present in the duplicated region in patients, and RNA in situ hybridization on mouse embryonic and adult brain sections revealed that two of the four genes, CYFIP1 and NIPA1, were highly expressed in the developing mouse brain. These findings point towards a contribution of microduplications at chromosome 15q11.2 to autism, and highlight CYFIP1 and NIPA1 as autism risk genes functioning in axonogenesis and synaptogenesis. Thereby, these findings further implicate defects in dosage-sensitive molecular control of neuronal connectivity in autism. However, the prevalence of this microduplication in patient samples was statistically not significantly different from control samples (0.94% in patients vs. 0.42% controls, P = 0.247), which suggests that our findings should be interpreted with caution and indicates the need for studies that include large numbers of control subjects to ascertain the impact of these changes on a population scale.

FAIR, safe and high-quality data: The data infrastructure and accessibility of the YOUth cohort study.

The YOUth cohort study aims to be a trailblazer for open science. Being a large-scale, longitudinal cohort following children in their development from gestation until early adulthood, YOUth collects a vast amount of data through a variety of research techniques. Data are collected through multiple platforms, including facilities managed by Utrecht University and the University Medical Center Utrecht. In order to facilitate appropriate use of its data by research organizations and researchers, YOUth aims to produce high-quality, FAIR data while safeguarding the privacy of participants. This requires an extensive data infrastructure, set up by collaborative efforts of researchers, data managers, IT departments, and the Utrecht University Library. In the spirit of open science, YOUth will share its experience and expertise in setting up a high-quality research data infrastructure for sensitive cohort data. This paper describes the technical aspects of our data and data infrastructure, and the steps taken throughout the study to produce and safely store FAIR and high-quality data. Finally, we will reflect on the organizational aspects that are conducive to the success of setting up such an enterprise, and we consider the financial challenges posed by individual studies investing in sustainable science.

The YOUth study: Rationale, design, and study procedures.

Behavioral development in children shows large inter-individual variation, and is driven by the interplay between biological, psychological, and environmental processes. However, there is still little insight into how these processes interact. The YOUth cohort specifically focuses on two core characteristics of behavioral development: social competence and self-regulation. Social competence refers to the ability to engage in meaningful interactions with others, whereas self-regulation is the ability to control one's emotions, behavior, and impulses, to balance between reactivity and control of the reaction, and to adjust to the prevailing environment. YOUth is an accelerated population-based longitudinal cohort study with repeated measurements, centering on two groups: YOUth Baby & Child and YOUth Child & Adolescent. YOUth Baby & Child aims to include 3,000 pregnant women, their partners and children, wheras YOUth Child & Adolescent aims to include 2,000 children aged between 8 and 10 years old and their parents. All participants will be followed for at least 6 years, and potentially longer. In this paper we describe in detail the design of this study, the population included, the determinants, intermediate neurocognitive measures and outcomes included in the study. Furthermore, we describe in detail the procedures of inclusion, informed consent, and study participation.

Identification of schizophrenia-associated loci by combining DNA methylation and gene expression data from whole blood.

Emerging evidence suggests that schizophrenia (SZ) susceptibility involves variation at genetic, epigenetic and transcriptome levels. We describe an integrated approach that leverages DNA methylation and gene expression data to prioritize genetic variation involved in disease. DNA methylation levels were obtained from whole blood of 260 SZ patients and 250 unaffected controls of which a subset with gene expression data was available. By assessing DNA methylation and gene expression in cases and controls, we identified 432 CpG sites with differential methylation levels that are associated with differential gene expression. We hypothesized that genetic factors involved in these methylation levels may be associated with the genetic risk of SZ susceptibility. To test this hypothesis, we used results from the Psychiatric Genomics Consortium SZ genome-wide association study (GWAS). We observe an enrichment of SZ-associated SNPs in the mQTLs of which the associated CpG site is also correlated with differential gene expression in SZ. While this enrichment was already apparent when using nominal significant thresholds, enrichment was even more pronounced when applying more stringent significance levels. One locus, previously identified as susceptibility locus in a SZ GWAS, involves SNP rs11191514:C>T, which regulates DNA methylation of calcium homeostasis modulator 1 that is also associated with differential gene expression in patients. Overall, our results suggest that epigenetic variation plays an important role in SZ susceptibility and that the integration of analyses of genetic, epigenetic and gene expression profiles may be a biologically meaningful approach for identifying disease susceptibility loci, even when using whole blood data in studies of brain-related disorders.

Genetic schizophrenia risk variants jointly modulate total brain and white matter volume.

BACKGROUND: Thousands of common single nucleotide polymorphisms (SNPs) are weakly associated with schizophrenia. It is likely that subsets of disease-associated SNPs are associated with distinct heritable disease-associated phenotypes. Therefore, we examined the shared genetic susceptibility modulating schizophrenia and brain volume. METHODS: Odds ratios for genome-wide SNP data were calculated in the sample collected by the Psychiatric Genome-wide Association Study Consortium (8690 schizophrenia patients and 11,831 control subjects, excluding subjects from the present study). These were used to calculate individual polygenic schizophrenia (risk) scores in an independent sample of 152 schizophrenia patients and 142 healthy control subjects with available structural magnetic resonance imaging scans. RESULTS: In the entire group, the polygenic schizophrenia score was significantly associated with total brain volume (R2 = .048, p = 1.6 × 10(-4)) and white matter volume (R2 = .051, p = 8.6 × 10(-5)) equally in patients and control subjects. The number of (independent) SNPs that substantially influenced both disease risk and white matter (n = 2020) was much smaller than the entire set of SNPs that modulated disease status (n = 14,751). From the set of 2020 SNPs, a group of 186 SNPs showed most evidence for association with white matter volume and an explorative functional analysis showed that these SNPs were located in genes with neuronal functions. CONCLUSIONS: These results indicate that a relatively small subset of schizophrenia genetic risk variants is related to the (normal) development of white matter. This, in turn, suggests that disruptions in white matter growth increase the susceptibility to develop schizophrenia.

D-amino acid aberrations in cerebrospinal fluid and plasma of smokers.

The glutamatergic neurotransmission system and the N-methyl-D-aspartate receptor (NMDAR) have been implicated in smoking and alcohol consumption behavior. Preclinical studies have demonstrated that nicotine and ethanol influence NMDAR functionality, which may have a role in tendencies to consume these substances. Nonetheless, little is known about concentrations of NMDAR coagonists in the cerebrospinal fluid (CSF) and plasma of individuals who smoke or consume alcohol. Glycine and L- and D-stereoisomers of alanine, serine, and proline were therefore measured using ultra-high-performance liquid chromatography-tandem mass spectrometry in 403 healthy subjects. Nicotine and alcohol consumption were quantified using questionnaires. Possible differences in NMDAR coagonist concentrations in plasma and CSF were investigated using ANCOVA with age, body mass index, and storage duration as covariates. The significance threshold was Bonferroni corrected (α=0.00625). Compared with non-smokers, smokers displayed lower levels of D-proline in plasma (p=0.0027, Cohen's d=-0.41) and D-proline in CSF (p=0.0026, Cohen's d=-0.43). D-Serine in CSF was higher in smokers than in non-smokers (p=0.0052, Cohen's d=0.41). After subdividing participants based on smoking quantity, dose-dependent decreases were demonstrated in smokers for D-proline in plasma (F=5.65, p=0.0039) and D-proline in CSF (F=5.20, p=0.0060). No differences in NMDAR coagonist levels between alcohol consumption groups were detected. To our knowledge, this is the first report to implicate D-amino acids in smoking behavior of humans. Whether such concentration differences lie at the root of or result from smoking habits may be addressed in prospective studies.

Effects of season of birth and a common MTHFR gene variant on the risk of schizophrenia.

Season of birth - in particular winter birth - has been persistently related to increased schizophrenia risk. Variation in folate intake is among the explanations for this seasonal effect. Methylenetetrahydrofolate reductase (MTHFR) is an essential enzyme in the folate mediated methylation transfer reactions. Interestingly, the MTHFR gene has been related to schizophrenia risk in various studies. We investigated a possible interaction between MTHFR 677C>T polymorphism and winter birth in the development of schizophrenia in a group of 742 schizophrenia patients and 884 control subjects. All subjects were of Dutch ancestry. Winter birth (December up to and including February) was associated with a 20% increase in schizophrenia risk (odds ratio (OR) of 1.20 and 95% confidence interval (CI), 0.96-1.5; P=0.113). The MTHFR 677TT genotype was associated with an overall schizophrenia risk of 1.13 (95% CI, 0.82-1.57; P=0.454) compared with the MTHFR 677CC genotype. In the winter period the MTHFR 677TT genotype associated schizophrenia risk was 0.90 (95% CI, 0.47-1.70; P=0.744). In conclusion, neither winter birth nor MTHFR genotype were significantly associated with increased schizophrenia risk. There was no evidence for interaction between MTHFR 677TT genotype and winter birth in the development of schizophrenia.

Genome-wide analysis shows increased frequency of copy number variation deletions in Dutch schizophrenia patients.

BACKGROUND: Since 2008, multiple studies have reported on copy number variations (CNVs) in schizophrenia. However, many regions are unique events with minimal overlap between studies. This makes it difficult to gain a comprehensive overview of all CNVs involved in the etiology of schizophrenia. We performed a systematic CNV study on the basis of a homogeneous genome-wide dataset aiming at all CNVs ≥ 50 kilobase pair. We complemented this analysis with a review of cytogenetic and chromosomal abnormalities for schizophrenia reported in the literature with the purpose of combining classical genetic findings and our current understanding of genomic variation. METHODS: We investigated 834 Dutch schizophrenia patients and 672 Dutch control subjects. The CNVs were included if they were detected by QuantiSNP (http://www.well.ox.ac.uk/QuantiSNP/) as well as PennCNV (http://www.neurogenome.org/cnv/penncnv/) and contain known protein coding genes. The integrated identification of CNV regions and cytogenetic loci indicates regions of interest (cytogenetic regions of interest [CROIs]). RESULTS: In total, 2437 CNVs were identified with an average number of 2.1 CNVs/subject for both cases and control subjects. We observed significantly more deletions but not duplications in schizophrenia cases versus control subjects. The CNVs identified coincide with loci previously reported in the literature, confirming well-established schizophrenia CROIs 1q42 and 22q11.2 as well as indicating a potentially novel CROI on chromosome 5q35.1. CONCLUSIONS: Chromosomal deletions are more prevalent in schizophrenia patients than in healthy subjects and therefore confer a risk factor for pathogenicity. The combination of our CNV data with previously reported cytogenetic abnormalities in schizophrenia provides an overview of potentially interesting regions for positional candidate genes.

Paternal age and psychiatric disorders: findings from a Dutch population registry.

BACKGROUND: We measured the association between paternal age and schizophrenia (SCZ), autism spectrum disorders (ASD), major depressive disorder (MDD), and bipolar disorder (BPD) in the Dutch population. METHODS: In total, 14231 patients and 56924 matched controls were collected and analyzed for an association with paternal age by logistic regression. RESULTS: ASD is significantly associated with increased paternal age: Older fathers >40 years of age have a 3.3 times increased odds of having a child with ASD compared to young fathers <20 years of age. SCZ has significant associations for fathers aged >35 years (OR=1.27, 95% Confidence Interval: 1.05 and 1.53). For MDD, both younger and older fathers have increased odds. No association was found for BPD. CONCLUSIONS: The effects of paternal age as a risk factor are different for ASD and SCZ on one hand, and the affective disorders on the other hand. Different types of association might indicate different biological or psychosocial mechanisms. Late paternity (associated with predispositions to psychiatric disorders) seems the most probable explanation for the association with paternal age.

Genomics education in practice: Evaluation of a mobile lab design.

Dutch genomics research centers have developed the 'DNA labs on the road' to bridge the gap between modern genomics research practice and secondary-school curriculum in the Netherlands. These mobile DNA labs offer upper-secondary students the opportunity to experience genomics research through experiments with laboratory equipment that is not available in schools and place genomics research in a relevant societal context. The design of the DNA lab 'read the language of the tumor' is evaluated, by clarifying the goals and choices in the design, and the effects of the DNA lab are presented. Based on the analysis of the design of the DNA lab and supported by the results of the evaluating studies, we consider this module to be a good example of relevant and up-to-date genomics education.

Systematic genotype-phenotype analysis of autism susceptibility loci implicates additional symptoms to co-occur with autism.

Many genetic studies in autism have been performed, resulting in the identification of multiple linkage regions and cytogenetic aberrations, but little unequivocal evidence for the involvement of specific genes exists. By identifying novel symptoms in these patients, enhanced phenotyping of autistic individuals not only improves understanding and diagnosis but also helps to define biologically more homogeneous groups of patients, improving the potential to detect causative genes. Supported by recent copy number variation findings in autism, we hypothesized that for some susceptibility loci, autism resembles a contiguous gene syndrome, caused by aberrations within multiple (contiguous) genes, which jointly increases autism susceptibility. This would result in various different clinical manifestations that might be rather atypical, but that also co-occur with autism. To test this hypothesis, 13 susceptibility loci, identified through genetic linkage and cytogenetic analyses, were systematically analyzed. The Online Mendelian Inheritance in Man database was used to identify syndromes caused by mutations in the genes residing in each of these loci. Subsequent analysis of the symptoms expressed within these disorders allowed us to identify 33 symptoms (significantly more than expected, P=0.037) that were over-represented in previous reports mapping to these loci. Some of these symptoms, including seizures and craniofacial abnormalities, support our hypothesis as they are already known to co-occur with autism. These symptoms, together with ones that have not previously been described to co-occur with autism, might be considered for use as inclusion or exclusion criteria toward defining etiologically more homogeneous groups for molecular genetic studies of autism.

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.