The P2RX7 polymorphism rs2230912 is associated with depression: A meta-analysis

Various studies have investigated whether single nucleotide polymorphisms (SNPs) in the gene purinergic receptor P2X7 (P2RX7), and rs2230912 specifically, were associated with mood disorders. While some studies found positive evidence, a large number of studies reported no significant associations. In a previously published meta-analysis, Feng et al. did not find a significant association and only moderate odds ratios (ORs) in case-control studies. They reported significant findings only for family-based studies. We revisited this finding and conducted a meta-analysis including 8,652 cases and 11,153 controls, adding unpublished results from the Munich Antidepressant Response Signature (MARS) study. We found a significant association between rs2230912 and combined mood disorders (major depressive disorder (MDD) or bipolar disorder (BD)) for the allelic, dominant and heterozygous-disadvantage model, all withstanding the threshold of correction for multiple testing. Stratifying by disorder revealed significant findings for the MDD-subgroup (OR of 1.12 for the allelic model), while the BD-subgroup presented with a lower effect size (OR of 1.05) and no significance. P2RX7 encodes a purinergic receptor which is expressed in the brain and also localized in immune cells. Animal studies and functional studies will be necessary to enlighten its involvement in the etiology of mood disorders and its applicability for pharmacological purposes

Using polymorphisms in FKBP5 to define biologically distinct subtypes of posttraumatic stress disorder: Evidence from endocrine and gene expression studies

Context: Polymorphisms in the gene encoding the glucocorticoid receptor (GR) regulating co-chaperone FKBP5 have been shown to alter GR sensitivity and are associated with an increased risk to develop posttraumatic stress disorder (PTSD). Objective: To investigate interactions of the FKBP5 single-nucleotide polymorphism rs9296158 and PTSD symptoms on baseline cortisol level, low-dose dexamethasone suppression, and whole-blood gene expression. Design: Association of FKBP5 genotypes and PTSD symptoms with endocrine measures and genome-wide expression profiles. Setting: Waiting rooms of general medical and gynecological clinics of an urban hospital at Emory University. Participants: The 211 participants were primarily African American (90.05%) and of low socioeconomic status and had high rates of trauma and PTSD. Main Outcome Measures: Baseline and post-dexamethasone suppression cortisol measures and gene expression levels. Results: In our endocrine study, we found that only risk allele A carriers of rs9296158 showed GR supersensitivity with PTSD; in contrast, baseline cortisol levels were decreased in PTSD only in patients with the GG genotype. Expression of 183 transcripts was significantly correlated with PTSD symptoms after multiple testing corrections. When adding FKBP5 genotype and its interaction with PTSD symptoms, expression levels of an additional 32 genes were significantly regulated by the interaction term. Within these 32 genes, previously reported PTSD candidates were identified, including FKBP5 and the IL18 and STAT pathways. Significant overrepresentation of steroid hormone transcription factor binding sites within these 32 transcripts was observed, highlighting the fact that the earlier-described genotype and PTSDdependent differences in GR sensitivity could drive the observed gene expression pattern. Results were validated by reverse transcriptase-polymerase chain reaction and replicated in an independent sample (N=98). Conclusions: These data suggest that the inheritance of GR sensitivity-moderating FKBP5 polymorphisms can determine specific types of hypothalamic-pituitaryadrenal axis dysfunction within PTSD, which are also reflected in gene-expression changes of a subset of GRresponsive genes. Thus, these findings indicate that functional variants in FKBP5 are associated with biologically distinct subtypes of PTSD

DeepWAS: multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS

Genetic comorbidity between major depression and cardiometabolic traits, stratified by age at onset of major depression

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents

Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-kappa B-driven inflammation and cardiovascular risk

Aging and psychosocial stress are associated with increased inflammation and disease risk, but the underlying molecular mechanisms are unclear. Because both aging and stress are also associated with lasting epigenetic changes, a plausible hypothesis is that stress along the lifespan could confer disease risk through epigenetic effects on molecules involved in inflammatory processes. Here, by combining large-scale analyses in human cohorts with experiments in cells, we report that FKBP5, a protein implicated in stress physiology, contributes to these relations. Across independent human cohorts (total n > 3,000), aging synergized with stress-related phenotypes, measured with childhood trauma and major depression questionnaires, to epigenetically up-regulate FKBP5 expression. These age/stress-related epigenetic effects were recapitulated in a cellular model of replicative senescence, whereby we exposed replicating human fibroblasts to stress (glucocorticoid) hormones. Unbiased genome-wide analyses in human blood linked higher FKBP5 mRNA with a proinflammatory profile and altered NF-kappa B-related gene networks. Accordingly, experiments in immune cells showed that higher FKBP5 promotes inflammation by strengthening the interactions of NF-kappa B regulatory kinases, whereas opposing FKBP5 either by genetic deletion (CRISPR/Cas9-mediated) or selective pharmacological inhibition prevented the effects on NF-kappa B. Further, the age/stress-related epigenetic signature enhanced FKBP5 response to NF-kappa B through a positive feedback loop and was present in individuals with a history of acute myocardial infarction, a disease state linked to peripheral inflammation. These findings suggest that aging/stress-driven FKBP5-NF-kappa B signaling mediates inflammation, potentially contributing to cardiovascular risk, and may thus point to novel biomarker and treatment possibilities.Peer reviewe

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders

Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia

Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p <2.8 x 10(-6)) enrichment of associations at the gene level, forLOC388780(20p13; uncharacterized gene), and forVEPH1(3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (atp(T) = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase;p = 8 x 10(-13)), bipolar disorder (1.53[1.44; 1.63];p = 1 x 10(-43)), schizophrenia (1.36[1.28; 1.45];p = 4 x 10(-22)), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30];p = 3 x 10(-12)), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96];p = 5 x 10(-4)), educational attainment (0.86[0.82; 0.91];p = 2 x 10(-7)), and intelligence (0.72[0.68; 0.76];p = 9 x 10(-29)). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.Peer reviewe