Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR.

Epigenetic differences may help to distinguish between PTSD cases and trauma-exposed controls. Here, we describe the results of the largest DNA methylation meta-analysis of PTSD to date. Ten cohorts, military and civilian, contribute blood-derived DNA methylation data from 1,896 PTSD cases and trauma-exposed controls. Four CpG sites within the aryl-hydrocarbon receptor repressor (AHRR) associate with PTSD after adjustment for multiple comparisons, with lower DNA methylation in PTSD cases relative to controls. Although AHRR methylation is known to associate with smoking, the AHRR association with PTSD is most pronounced in non-smokers, suggesting the result was independent of smoking status. Evaluation of metabolomics data reveals that AHRR methylation associated with kynurenine levels, which are lower among subjects with PTSD. This study supports epigenetic differences in those with PTSD and suggests a role for decreased kynurenine as a contributor to immune dysregulation in PTSD.

Epigenetic mechanisms and associated brain circuits in the regulation of positive emotions: A role for transposable elements.

Epigenetic programming and reprogramming are at the heart of cellular differentiation and represent developmental and evolutionary mechanisms in both germline and somatic cell lines. Only about 2% of our genome is composed of protein-coding genes, while the remaining 98%, once considered "junk" DNA, codes for regulatory/epigenetic elements that control how genes are expressed in different tissues and across time from conception to death. While we already know that epigenetic mechanisms are at play in cancer development and in regulating metabolism (cellular and whole body), the role of epigenetics in the developing prenatal and postnatal brain, and in maintaining a proper brain activity throughout the various stages of life, in addition to having played a critical role in human evolution, is a relatively new domain of knowledge. Here we present the current state-of-the-art techniques and results of these studies within the domain of emotions, and then speculate on how genomic and epigenetic mechanisms can modify and potentially alter our emotional (limbic) brain and affect our social interactions. J. Comp. Neurol. 524:2944-2954, 2016. © 2016 Wiley Periodicals, Inc.

Insulin receptor variants and obesity-related cancers in the Framingham Heart Study.

PURPOSE: The insulin-signaling pathway plays a pivotal role in cancer biology; however, evidence of genetic alterations in human studies is limited. This case-control study nested within the Framingham Heart Study (FHS) examined the association between inherited genetic variation in the insulin receptor (INSR) gene and obesity-related cancer risk. METHODS: The study sample consisted of 1,475 controls and 396 cases from the second familial generation of the FHS. Participants who provided consent were genotyped. Nineteen single-nucleotide polymorphisms (SNPs) in the INSR gene were investigated in relation to risk of obesity-related cancers combined and breast, prostate and colorectal cancers. Generalized estimation equation models controlling for familial correlations and include age, sex, smoking and body mass index as covariates, assuming additive models, were used. RESULTS: Three SNPs, rs2059807, s8109559 and rs919275, were significantly associated with obesity-related cancers (p value < 0.02) with the most significantly associated SNP being rs2059807 (p value = 0.008). Carriers of two copies of SNP rs2059807 risk allele T were significantly less prevalent among subjects with obesity-related cancers [f(TT)cases = 14 vs. f(TT)controls = 18 %; OR 1.23]. In exploratory analyses evaluating site-specific cancers, the INSR rs2059807 association with these cancers was consistent with that observed for the main outcome (ORs colorectal cancer = 1.5, breast cancer = 1.29, prostate = 1.06). There was no statistically significant interaction between the INSR-SNP and blood glucose in relation to obesity-related cancer. CONCLUSIONS: The INSR gene is implicated in obesity-related cancer risk, as 3 of 19 SNPs were nominally associated, after false discovery rate (FDR) correction, with the main outcome. Risk allele homozygotes (rs2059807) were less prevalent among subjects with obesity-related cancer. These results should be replicated in other populations to confirm the findings.

Transposable elements and psychiatric disorders.

Transposable Elements (TEs) or transposons are low-complexity elements (e.g., LINEs, SINEs, SVAs, and HERVs) that make up to two-thirds of the human genome. There is mounting evidence that TEs play an essential role in genomic architecture and regulation related to both normal function and disease states. Recently, the identification of active TEs in several different human brain regions suggests that TEs play a role in normal brain development and adult physiology and quite possibly in psychiatric disorders. TEs have been implicated in hemophilia, neurofibromatosis, and cancer. With the advent of next-generation whole-genome sequencing approaches, our understanding of the relationship between TEs and psychiatric disorders will greatly improve. We will review the biology of TEs and early evidence for TE involvement in psychiatric disorders.

A newly identified group of adolescents at "invisible" risk for psychopathology and suicidal behavior: findings from the SEYLE study.

This study explored the prevalence of risk behaviors (excessive alcohol use, illegal drug use, heavy smoking, reduced sleep, overweight, underweight, sedentary behavior, high use of Internet/TV/videogames for reasons not related to school or work, and truancy), and their association with psychopathology and self-destructive behaviors, in a sample of 12,395 adolescents recruited in randomly selected schools across 11 European countries. Latent class analysis identified three groups of adolescents: a low-risk group (57.8%) including pupils with low or very low frequency of risk behaviors; a high-risk group (13.2%) including pupils who scored high on all risk behaviors, and a third group ("invisible" risk, 29%) including pupils who were positive for high use of Internet/TV/videogames for reasons not related to school or work, sedentary behavior and reduced sleep. Pupils in the "invisible" risk group, compared with the high-risk group, had a similar prevalence of suicidal thoughts (42.2% vs. 44%), anxiety (8% vs. 9.2%), subthreshold depression (33.2% vs. 34%) and depression (13.4% vs. 14.7%). The prevalence of suicide attempts was 5.9% in the "invisible" group, 10.1% in the high-risk group and 1.7% in the low-risk group. The prevalence of all risk behaviors increased with age and most of them were significantly more frequent among boys. Girls were significantly more likely to experience internalizing (emotional) psychiatric symptoms. The "invisible" group may represent an important new intervention target group for potentially reducing psychopathology and other untoward outcomes in adolescence, including suicidal behavior.

SNP-based pathway enrichment analysis for genome-wide association studies.

BACKGROUND: Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs. RESULTS: We describe a SNP-based pathway enrichment method for GWAS studies. The method consists of the following two main steps: 1) for a given pathway, using an adaptive truncated product statistic to identify all representative (potentially more than one) SNPs of each gene, calculating the average number of representative SNPs for the genes, then re-selecting the representative SNPs of genes in the pathway based on this number; and 2) ranking all selected SNPs by the significance of their statistical association with a trait of interest, and testing if the set of SNPs from a particular pathway is significantly enriched with high ranks using a weighted Kolmogorov-Smirnov test. We applied our method to two large genetically distinct GWAS data sets of schizophrenia, one from European-American (EA) and the other from African-American (AA). In the EA data set, we found 22 pathways with nominal P-value less than or equal to 0.001 and corresponding false discovery rate (FDR) less than 5%. In the AA data set, we found 11 pathways by controlling the same nominal P-value and FDR threshold. Interestingly, 8 of these pathways overlap with those found in the EA sample. We have implemented our method in a JAVA software package, called SNP Set Enrichment Analysis (SSEA), which contains a user-friendly interface and is freely available at http://cbcl.ics.uci.edu/SSEA. CONCLUSIONS: The SNP-based pathway enrichment method described here offers a new alternative approach for analysing GWAS data. By applying it to schizophrenia GWAS studies, we show that our method is able to identify statistically significant pathways, and importantly, pathways that can be replicated in large genetically distinct samples.

Role of UBE3A and ATP10A genes in autism susceptibility region 15q11-q13 in an Italian population: a positive replication for UBE3A.

The aetiology of autism is still largely unknown despite analyses from family and twin studies demonstrating substantial genetic role in the aetiology of the disorder. Data from linkage studies and analyses of chromosomal abnormalities identified 15q11-q13 as a region of particular aetiopathogenesis interest. We screened a set of markers spanning two known imprinted, maternally expressed genes, UBE3A and ATP10A, harboured in this candidate region. We replicated evidence of linkage disequilibrium (LD) at marker D15S122, located at the 5' end of UBE3A and originally reported by Nurmi et al. (2001). The potential role of UBE3A in our family-based association study is further supported by the association of two haplotypes that include one of the alleles of D15S122 and by the transmission disequilibrium test (TDT) evidence of the same allele in a parent of origin effect analysis. In a secondary analysis, we provided the first evidence of a significant association between first word delay and psychomotor regression with the 15q11-q13 region. Our data support a potential role of UBE3A in the complex pathogenic mechanisms of autism.