Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability.

The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case-control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h2SNP) for European-American females of 29% that is similar to h2SNP for schizophrenia and is substantially higher than h2SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD-for both European- and African-American individuals-and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for ∼10 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.

CRP polymorphisms and DNA methylation of the AIM2 gene influence associations between trauma exposure, PTSD, and C-reactive protein.

BACKGROUND: Recent studies have implicated inflammatory processes in the pathophysiology of posttraumatic stress disorder (PTSD). C-reactive protein (CRP) is a widely-used measure of peripheral inflammation, but little is known about the genetic and epigenetic factors that influence blood levels of C-reactive protein (CRP) in individuals with PTSD. METHODS: Participants were 286 U.S. military veterans of post-9/11 conflicts (57% with current PTSD). Analyses focused on single nucleotide polymorphisms (SNPs) in the CRP gene and DNA methylation at cg10636246 in AIM2-a locus recently linked to CRP levels through results from a large-scale epigenome-wide association study. RESULTS: PTSD was positively correlated with serum CRP levels with PTSD cases more likely to have CRP levels in the clinically-elevated range compared to those without a PTSD diagnosis. Multivariate analyses that controlled for white blood cell proportions, genetic principal components, age and sex, showed this association to be mediated by methylation at the AIM2 locus. rs3091244, a functional SNP in the CRP promoter region, moderated the association between lifetime trauma exposure and current PTSD severity. Analyses also revealed that the top SNPs from the largest genome-wide association study of CRP conducted to date (rs1205 and rs2794520) significantly interacted with PTSD to influence CRP levels. CONCLUSIONS: These findings provide new insights into genetic and epigenetic mechanisms of inflammatory processes in the pathophysiology of PTSD and point to new directions for biomarker identification and treatment development for patients with PTSD.

SKA2 methylation is associated with decreased prefrontal cortical thickness and greater PTSD severity among trauma-exposed veterans.

Methylation of the SKA2 (spindle and kinetochore-associated complex subunit 2) gene has recently been identified as a promising biomarker of suicide risk. Based on this finding, we examined associations between SKA2 methylation, cortical thickness and psychiatric phenotypes linked to suicide in trauma-exposed veterans. About 200 trauma-exposed white non-Hispanic veterans of the recent conflicts in Iraq and Afghanistan (91% male) underwent clinical assessment and had blood drawn for genotyping and methylation analysis. Of all, 145 participants also had neuroimaging data available. Based on previous research, we examined DNA methylation at the cytosine-guanine locus cg13989295 as well as DNA methylation adjusted for genotype at the methylation-associated single nucleotide polymorphism (rs7208505) in relationship to whole-brain cortical thickness, posttraumatic stress disorder symptoms (PTSD) and depression symptoms. Whole-brain vertex-wise analyses identified three clusters in prefrontal cortex that were associated with genotype-adjusted SKA2 DNA methylation (methylation(adj)). Specifically, DNA methylation(adj) was associated with bilateral reductions of cortical thickness in frontal pole and superior frontal gyrus, and similar effects were found in the right orbitofrontal cortex and right inferior frontal gyrus. PTSD symptom severity was positively correlated with SKA2 DNA methylation(adj) and negatively correlated with cortical thickness in these regions. Mediation analyses showed a significant indirect effect of PTSD on cortical thickness via SKA2 methylation status. Results suggest that DNA methylation(adj) of SKA2 in blood indexes stress-related psychiatric phenotypes and neurobiology, pointing to its potential value as a biomarker of stress exposure and susceptibility.

A genome-wide association study of post-traumatic stress disorder identifies the retinoid-related orphan receptor alpha (RORA) gene as a significant risk locus.

We describe the results of the first genome-wide association study (GWAS) of post-traumatic stress disorder (PTSD) performed using trauma-exposed white non-Hispanic participants from a cohort of veterans and their intimate partners (295 cases and 196 controls). Several single-nucleotide polymorphisms (SNPs) yielded evidence of association. One SNP (rs8042149), located in the retinoid-related orphan receptor alpha gene (RORA), reached genome-wide significance. Nominally significant associations were observed for other RORA SNPs in two African-American replication samples-one from the veteran cohort (43 cases and 41 controls) and another independent cohort (100 cases and 421 controls). However, only the associated SNP from the veteran African-American replication sample survived gene-level multiple-testing correction. RORA has been implicated in prior GWAS studies of psychiatric disorders and is known to have an important role in neuroprotection and other behaviorally relevant processes. This study represents an important step toward identifying the genetic underpinnings of PTSD.

Computation of the posterior probability of linkage using 'high effect' genetic model priors.

OBJECTIVES: The posterior probability of linkage, or PPL, directly measures the probability that a disease gene is linked to a marker. By placing a Bayesian prior on the elements of the genetic model, it allows for an unknown genetic model without the inflationary effects of maximization. The standard technique uses essentially uniform priors over the elements of the penetrance vector. However, much of the parameter space corresponds to models that seem unlikely to yield substantial evidence for linkage: for example, models with very high phenocopy rates. METHODS: A new class of priors on the elements of the genetic model is examined both theoretically and in simulations. These priors place 0% probability over models with low sibling relative risk, lambda(s). RESULTS: Focusing the prior probability on high lambda(s) models does tend to increase the mean PPL for linked markers, and to decrease the mean PPL for unlinked markers. However, the power to detect linkage remains virtually unchanged. Moreover, under these priors, the PPL occasionally yields unacceptably high values under no linkage. CONCLUSIONS: It appears important to retain prior probability over apparently 'uninformative' genetic models to accurately characterize the amount of evidence for linkage represented by the data.

BDNF genotype is associated with hippocampal volume in mild traumatic brain injury.

The negative long-term effects of mild traumatic brain injury (mTBI) have been a growing concern in recent years, with accumulating evidence suggesting that mTBI combined with additional vulnerability factors may induce neurodegenerative-type changes in the brain. However, the factors instantiating risk for neurodegenerative disease following mTBI are unknown. This study examined the link between mTBI and brain-derived neurotrophic factor (BDNF) genotype, which has previously been shown to regulate processes involved in neurodegeneration including synaptic plasticity and facilitation of neural survival through its expression. Specifically, we examined nine BDNF single-nucleotide polymorphisms (SNPs; rs908867, rs11030094, rs6265, rs10501087, rs1157659, rs1491850, rs11030107, rs7127507 and rs12273363) previously associated with brain atrophy or memory deficits in mTBI. Participants were 165 white, non-Hispanic Iraq and Afghanistan war veterans between the ages of 19 and 58, 110 of whom had at least one mTBI in their lifetime. Results showed that the BDNF SNP rs1157659 interacted with mTBI to predict hippocampal volume. Furthermore, exploratory analysis of functional resting state data showed that rs1157659 minor allele homozygotes with a history of mTBI had reduced functional connectivity in the default mode network compared to major allele homozygotes and heterozygotes. Apolipoprotein E (APOE) was not a significant predictor of hippocampal volume or functional connectivity. These results suggest that rs1157659 minor allele homozygotes may be at greater risk for neurodegeneration after exposure to mTBI and provide further evidence for a potential role for BDNF in regulating neural processes following mTBI.

Genome-wide association study of Alzheimer's disease.

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ~2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69-180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P = 3.05E-07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples.

A posterior probability of linkage-based re-analysis of schizophrenia data yields evidence of linkage to chromosomes 1 and 17.

OBJECTIVE: Linkage analysis using 22 Canadian pedigrees identified a promising schizophrenia candidate region on 1q23 with a maximum 2-point HLOD under a recessive model of 5.8 [Brzustowicz et al. 2000]. In the current study, we revisited this data set using a Bayesian linkage analysis technique, namely the posterior probability of linkage (PPL). METHODS: The PPL has been developed as an alternative to traditional linkage analysis. It differs from both LOD scores and 'non-parametric' methods in that it directly measures the probability of linkage given the data, and incorporates prior genomic information. RESULTS: As expected, PPL results for 1q23 supported the previously observed linkage, with an estimated multipoint PPL of 99.7%. However, the PPL supported two further results: a second peak on chromosome 1 at 1p13 with a multipoint with PPL of 70% and a chromosome 17 marker (D17S784 at 17q25) with a multipoint PPL of 44%. CONCLUSIONS: The PPL-based analysis presented has the advantage over other likelihood-based linkage methods in that it avoids maximization and produces a less complex view of the strength of evidence for linkage.