Genetic risk for hospitalization of African American patients with severe mental illness reveals HLA loci.

Background: Mood disorders such as major depressive and bipolar disorders, along with posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and other psychotic disorders, constitute serious mental illnesses (SMI) and often lead to inpatient psychiatric care for adults. Risk factors associated with increased hospitalization rate in SMI (H-SMI) are largely unknown but likely involve a combination of genetic, environmental, and socio-behavioral factors. We performed a genome-wide association study in an African American cohort to identify possible genes associated with hospitalization due to SMI (H-SMI). Methods: Patients hospitalized for psychiatric disorders (H-SMI; n=690) were compared with demographically matched controls (n=4467). Quality control and imputation of genome-wide data were performed following the Psychiatric Genetic Consortium (PGC)-PTSD guidelines. Imputation of the Human Leukocyte Antigen (HLA) locus was performed using the HIBAG package. Results: Genome-wide association analysis revealed a genome-wide significant association at 6p22.1 locus in the ubiquitin D (UBD/FAT10) gene (rs362514, p=9.43x10-9) and around the HLA locus. Heritability of H-SMI (14.6%) was comparable to other psychiatric disorders (4% to 45%). We observed a nominally significant association with 2 HLA alleles: HLA-A*23:01 (OR=1.04, p=2.3x10-3) and HLA-C*06:02 (OR=1.04, p=1.5x10-3). Two other genes (VSP13D and TSPAN9), possibly associated with immune response, were found to be associated with H-SMI using gene-based analyses. Conclusion: We observed a strong association between H-SMI and a locus that has been consistently and strongly associated with SCZ in multiple studies (6p21.32-p22.1), possibly indicating an involvement of the immune system and the immune response in the development of severe transdiagnostic SMI.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

Background: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Light-strand bias and enriched zones of embedded ribonucleotides are associated with DNA replication and transcription in the human-mitochondrial genome.

Abundant ribonucleoside-triphosphate (rNTP) incorporation into DNA by DNA polymerases in the form of ribonucleoside monophosphates (rNMPs) is a widespread phenomenon in nature, resulting in DNA-structural change and genome instability. The rNMP distribution, characteristics, hotspots and association with DNA metabolic processes in human mitochondrial DNA (hmtDNA) remain mostly unknown. Here, we utilize the ribose-seq technique to capture embedded rNMPs in hmtDNA of six different cell types. In most cell types, the rNMPs are preferentially embedded on the light strand of hmtDNA with a strong bias towards rCMPs; while in the liver-tissue cells, the rNMPs are predominately found on the heavy strand. We uncover common rNMP hotspots and conserved rNMP-enriched zones across the entire hmtDNA, including in the control region, which links the rNMP presence to the frequent hmtDNA replication-failure events. We show a strong correlation between coding-sequence size and rNMP-embedment frequency per nucleotide on the non-template, light strand in all cell types, supporting the presence of transient RNA-DNA hybrids preceding light-strand replication. Moreover, we detect rNMP-embedment patterns that are only partly conserved across the different cell types and are distinct from those found in yeast mtDNA. The study opens new research directions to understand the biology of hmtDNA and genomic rNMPs.

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Important Correlates of Purpose in Life in a Diverse Population-Based Cohort: A Machine Learning Approach.

BACKGROUND: Purpose-in-life (PiL) refers to the tendency to derive meaning and purpose from daily life experiences. Individuals with higher PiL were more likely to have better physical, mental, and cognitive health in prospective studies. Here, we aimed to identify important correlates of PiL among people of diverse backgrounds. METHODS: Participants were recruited by the population-based Health and Retirement Study and provided information on 34 different sociodemographic and psychosocial factors through psychometrically validated measures. To identify important correlates of PiL, we employed regularized regression implemented by Elastic Net on the entire cohort as well as among self-identified black participants only and white participants only, respectively. RESULTS: A total of 6,620 participants were included in this study, among whom 913 were black and 5,707 were white. We identified 12 and 23 important sociodemographic and psychosocial correlates of PiL among black and white participants, respectively. Notably, all the 12 correlates in black participants were also correlates among white participants. Interestingly, when we examined both black and white participants together, being black was associated with having higher PiL. The correlates with the largest effect on PiL that were shared among black and white participants were hopelessness, perceived constraint on personal control, and self-mastery. CONCLUSION: Several sociodemographic and psychosocial factors most strongly associated with PiL were shared among black and white participants. Future studies should investigate whether interventions targeting correlates of PiL can lead to higher sense of life purpose in participants of diverse backgrounds.

Targeted long-read sequencing of the Ewing sarcoma 6p25.1 susceptibility locus identifies germline-somatic interactions with EWSR1-FLI1 binding.

Ewing sarcoma (EwS) is a rare bone and soft tissue malignancy driven by chromosomal translocations encoding chimeric transcription factors, such as EWSR1-FLI1, that bind GGAA motifs forming novel enhancers that alter nearby expression. We propose that germline microsatellite variation at the 6p25.1 EwS susceptibility locus could impact downstream gene expression and EwS biology. We performed targeted long-read sequencing of EwS blood DNA to characterize variation and genomic features important for EWSR1-FLI1 binding. We identified 50 microsatellite alleles at 6p25.1 and observed that EwS-affected individuals had longer alleles (>135 bp) with more GGAA repeats. The 6p25.1 GGAA microsatellite showed chromatin features of an EWSR1-FLI1 enhancer and regulated expression of RREB1, a transcription factor associated with RAS/MAPK signaling. RREB1 knockdown reduced proliferation and clonogenic potential and reduced expression of cell cycle and DNA replication genes. Our integrative analysis at 6p25.1 details increased binding of longer GGAA microsatellite alleles with acquired EWSR-FLI1 to promote Ewing sarcomagenesis by RREB1-mediated proliferation.

The neural basis of smile authenticity judgments and the potential modulatory role of the oxytocin receptor gene (OXTR).

Accurate perception of genuine vs. posed smiles is crucial for successful social navigation in humans. While people vary in their ability to assess the authenticity of smiles, little is known about the specific biological mechanisms underlying this variation. We investigated the neural substrates of smile authenticity judgments using functional magnetic resonance imaging (fMRI). We also tested a preliminary hypothesis that a common polymorphism in the oxytocin receptor gene (OXTR) rs53576 would modulate the behavioral and neural indices of accurate smile authenticity judgments. A total of 185 healthy adult participants (Neuroimaging arm: N = 44, Behavioral arm: N = 141) determined the authenticity of dynamic facial expressions of genuine and posed smiles either with or without fMRI scanning. Correctly identified genuine vs. posed smiles activated brain areas involved with reward processing, facial mimicry, and mentalizing. Activation within the inferior frontal gyrus and dorsomedial prefrontal cortex correlated with individual differences in sensitivity (d') and response criterion (C), respectively. Our exploratory genetic analysis revealed that rs53576 G homozygotes in the neuroimaging arm had a stronger tendency to judge posed smiles as genuine than did A allele carriers and showed decreased activation in the medial prefrontal cortex when viewing genuine vs. posed smiles. Yet, OXTR rs53576 did not modulate task performance in the behavioral arm, which calls for further studies to evaluate the legitimacy of this result. Our findings extend previous literature on the biological foundations of smile authenticity judgments, particularly emphasizing the involvement of brain regions implicated in reward, facial mimicry, and mentalizing.

Blood levels of T-Cell Receptor Excision Circles (TRECs) provide an index of exposure to traumatic stress in mice and humans.

Exposure to stress triggers biological changes throughout the body. Accumulating evidence indicates that alterations in immune system function are associated with the development of stress-associated illnesses such as major depressive disorder and post-traumatic stress disorder, increasing interest in identifying immune markers that provide insight into mental health. Recombination events during T-cell receptor rearrangement and T-cell maturation in the thymus produce circular DNA fragments called T-cell receptor excision circles (TRECs) that can be utilized as indicators of thymic function and numbers of newly emigrating T-cells. Given data suggesting that stress affects thymus function, we examined whether blood levels of TRECs might serve as a quantitative peripheral index of cumulative stress exposure and its physiological correlates. We hypothesized that chronic stress exposure would compromise thymus function and produce corresponding decreases in levels of TRECs. In male mice, exposure to chronic social defeat stress (CSDS) produced thymic involution, adrenal hypertrophy, and decreased levels of TRECs in blood. Extending these studies to humans revealed robust inverse correlations between levels of circulating TRECs and childhood emotional and physical abuse. Cell-type specific analyses also revealed associations between TREC levels and blood cell composition, as well as cell-type specific methylation changes in CD4T + and CD8T + cells. Additionally, TREC levels correlated with epigenetic age acceleration, a common biomarker of stress exposure. Our findings demonstrate alignment between findings in mice and humans and suggest that blood-borne TRECs are a translationally-relevant biomarker that correlates with, and provides insight into, the cumulative physiological and immune-related impacts of stress exposure in mammals.

Next-generation sequencing errors due to genetic variation in WRAP53 encoding TCAB1 on chromosome 17.

Next-generation sequencing (NGS) is a valuable tool, but has limitations in sequencing through repetitive runs of single nucleotides (homopolymers). Pathogenic germline variants in WRAP53 encoding telomere Cajal body protein 1 (TCAB1) are a known cause of dyskeratosis congenita. We identified a significant NGS error in WRAP53, c.1562dup, p.Ala522Glyfs*8 (rs755116516 G>-/GG/GGG) that did not validate by Sanger sequencing. This error occurs because rs755116516 G>-/GG/GGG (Chr17:7,606,714) is polymorphic, and variants at this site challenge the ability of NGS to accurately call the correct number of nucleotides in a homopolymer run. This was further complicated by the fact that chr17:7,606,721 (rs769202794) is multiallelic G>A, C, T, and that chr17:7,606,722 is also multiallelic (rs7640C>A/G/T and rs373064567C>delC). In addition to the expert interpretation of potentially clinically actionable variants, it recommended that all variants in regions of the genome with homopolymers be validated by Sanger sequencing before clinical action.

Enhanced endogenous oxytocin signaling in the brain modulates neural responses to social misalignment and promotes conformity in humans: A multi-locus genetic profile approach.

The neuropeptide oxytocin (OT) is known to promote social conformity. However, the specific neurocognitive mechanisms underlying OT-induced conformity remain unclear. We aimed to address this gap by examining how genetic variation in the oxytocin receptor gene (OXTR) is linked with behavioral conformity and its underlying neural systems. Specifically, we utilized the genotype-tissue expression database (GTEx) to create a novel multi-locus genetic profile score (MPS) that reflects the level of OXTR expression in the human brain. A total of 194 participants (Neuroimaging N = 50, Behavioral N = 144) performed a novel conformity task in which they viewed a series of word pairs depicting various moral values and virtues widely recognized in the United States. In each trial, participants indicated the relative importance of these words and subsequently learned about the majority opinion. Participants later rated the same word pairs a second time. Changes in participants' ratings between the first and second sessions were measured and analyzed with respect to social feedback, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals, and OXTR MPS. We found that participants adjusted their ratings in accordance with the majority opinions. Social misalignment between self and others activated brain areas such as the striatum and the posterior medial frontal cortex (pMFC). However, unlike most findings from previous studies, activation in the pMFC during the inconsistent social feedback negatively, rather than positively, predicted behavioral conformity. Notably, those with higher OXTR MPS had reduced pMFC activation in the face of social misalignment, which led to greater conformity. Our findings suggest that OT may promote conformity by dampening the conflict-related signals in the pMFC. They also show that OXTR MPS may be useful for studying the effect of genes on highly complex human social traits, such as conformity.

Shared mechanisms across the major psychiatric and neurodegenerative diseases.

Several common psychiatric and neurodegenerative diseases share epidemiologic risk; however, whether they share pathophysiology is unclear and is the focus of our investigation. Using 25 GWAS results and LD score regression, we find eight significant genetic correlations between psychiatric and neurodegenerative diseases. We integrate the GWAS results with human brain transcriptomes (n = 888) and proteomes (n = 722) to identify cis- and trans- transcripts and proteins that are consistent with a pleiotropic or causal role in each disease, referred to as causal proteins for brevity. Within each disease group, we find many distinct and shared causal proteins. Remarkably, 30% (13 of 42) of the neurodegenerative disease causal proteins are shared with psychiatric disorders. Furthermore, we find 2.6-fold more protein-protein interactions among the psychiatric and neurodegenerative causal proteins than expected by chance. Together, our findings suggest these psychiatric and neurodegenerative diseases have shared genetic and molecular pathophysiology, which has important ramifications for early treatment and therapeutic development.

Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder.

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N = 525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n = 186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n = 174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N = 888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.

Time of trauma prospectively affects PTSD symptom severity: The impact of circadian rhythms and cortisol.

A key feature of posttraumatic stress disorder (PTSD) is a disruption of hypothalamic-pituitary-adrenal (HPA) axis feedback sensitivity and cortisol levels. Despite known diurnal rhythmicity of cortisol, there has been little exploration of the circadian timing of the index trauma and consequent cortisol release. Stress-related glucocorticoid pulses have been shown to shift clocks in peripheral organs but not the suprachiasmatic nucleus, uncoupling the central and peripheral clocks. A sample of 425 participants was recruited in the Emergency Department following a DSM-IV-TR Criterion A trauma. The Zeitgeber time of the trauma was indexed in minutes since sunrise, which was hypothesized to covary with circadian blood cortisol levels (high around sunrise and decreasing over the day). Blood samples were collected M(SD)= 4.0(4.0) hours post-trauma. PTSD symptoms six months post-trauma were found to be negatively correlated with trauma time since sunrise (r(233) = -0.15, p = 0.02). The effect remained when adjusting for sex, age, race, clinician-rated severity, education, pre-trauma PTSD symptoms, and time of the blood draw (ß = -0.21, p = 0.00057). Cortisol levels did not correlate with blood draw time, consistent with a masking effect of the acute stress response obscuring the underlying circadian rhythm. Interactions between trauma time and expression of NPAS2 (punadjusted=0.042) and TIMELESS (punadjusted=0.029) predicted six-month PTSD symptoms. The interaction of trauma time and cortisol concentration was significantly correlated with the expression of PER1 (padjusted=0.029). The differential effect of time of day on future symptom severity suggests a role of circadian effects in PTSD development, potentially through peripheral clock disruption.

Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach.

PURPOSE: Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. BASIC PROCEDURES: We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. MAIN FINDINGS: When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). PRINCIPAL CONCLUSIONS: These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.

Genetic Evidence Supporting a Causal Role of Depression in Alzheimer's Disease.

BACKGROUND: Depression has been associated with a higher risk of Alzheimer's disease (AD) in several prospective studies; however, mechanisms underlying this association remain unclear. METHODS: We examined genetic correlation between depression and AD using linkage disequilibrium score regression. We then tested for evidence of causality between depression and AD using Mendelian randomization and genome-wide association study results. Subsequently, cis and trans quantitative trait locus analyses for the depression genome-wide association study signals were performed to resolve the genetic signals to specific DNA methylation sites, brain transcripts, and proteins. These transcripts and proteins were then examined for associations with AD and its endophenotypes. Finally, the associations between depression polygenic risk score and AD endophenotypes were examined. RESULTS: We detected a significant genetic correlation between depression and AD, suggesting that they have a shared genetic basis. Furthermore, we found that depression had a causal role in AD through Mendelian randomization but did not find evidence for a causal role of AD on depression. Moreover, we identified 75 brain transcripts and 28 brain proteins regulated by the depression genome-wide association study signals through quantitative trait locus analyses. Of these, 46 transcripts and seven proteins were associated with rates of cognitive decline over time, AD pathologies, and AD diagnosis in two separate cohorts, thus implicating them in AD. In addition, we found that a higher depression polygenic risk score was associated with a faster decline of episodic memory over time. CONCLUSIONS: Depression appears to have a causal role in AD, and this causal relationship is likely driven, in part, by the 53 brain transcripts and proteins identified in this study.

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors.

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Examining Individual and Synergistic Contributions of PTSD and Genetics to Blood Pressure: A Trans-Ethnic Meta-Analysis.

Growing research suggests that posttraumatic stress disorder (PTSD) may be a risk factor for poor cardiovascular health, and yet our understanding of who might be at greatest risk of adverse cardiovascular outcomes after trauma is limited. In this study, we conducted the first examination of the individual and synergistic contributions of PTSD symptoms and blood pressure genetics to continuous blood pressure levels. We harnessed the power of the Psychiatric Genomics Consortium-PTSD Physical Health Working Group and investigated these associations across 11 studies of 72,224 trauma-exposed individuals of European (n = 70,870) and African (n = 1,354) ancestry. Genetic contributions to blood pressure were modeled via polygenic scores (PGS) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) that were derived from a prior trans-ethnic blood pressure genome-wide association study (GWAS). Results of trans-ethnic meta-analyses revealed significant main effects of the PGS on blood pressure levels [SBP: ß = 2.83, standard error (SE) = 0.06, p < 1E-20; DBP: ß = 1.32, SE = 0.04, p < 1E-20]. Significant main effects of PTSD symptoms were also detected for SBP and DBP in trans-ethnic meta-analyses, though there was significant heterogeneity in these results. When including data from the largest contributing study - United Kingdom Biobank - PTSD symptoms were negatively associated with SBP levels (ß = -1.46, SE = 0.44, p = 9.8E-4) and positively associated with DBP levels (ß = 0.70, SE = 0.26, p = 8.1E-3). However, when excluding the United Kingdom Biobank cohort in trans-ethnic meta-analyses, there was a nominally significant positive association between PTSD symptoms and SBP levels (ß = 2.81, SE = 1.13, p = 0.01); no significant association was observed for DBP (ß = 0.43, SE = 0.78, p = 0.58). Blood pressure PGS did not significantly moderate the associations between PTSD symptoms and blood pressure levels in meta-analyses. Additional research is needed to better understand the extent to which PTSD is associated with high blood pressure and how genetic as well as contextual factors may play a role in influencing cardiovascular risk.

A Genetic Study of Cerebral Atherosclerosis Reveals Novel Associations with NTNG1 and CNOT3.

Cerebral atherosclerosis is a leading cause of stroke and an important contributor to dementia. Yet little is known about its genetic basis. To examine the association of common single nucleotide polymorphisms with cerebral atherosclerosis severity, we conducted a genomewide association study (GWAS) using data collected as part of two community-based cohort studies in the United States, the Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP). Both studies enroll older individuals and exclude participants with signs of dementia at baseline. From our analysis of 1325 participants of European ancestry who had genotype and neuropathologically assessed cerebral atherosclerosis measures available, we found a novel locus for cerebral atherosclerosis in NTNG1. The locus comprises eight SNPs, including two independent significant SNPs: rs6664221 (ß = -0.27, 95% CI = (-0.35, -0.19), p = 1.29 × 10-10) and rs10881463 (ß = -0.20, 95% CI = (-0.27, -0.13), p = 3.40 × 10-8). We further found that the SNPs may influence cerebral atherosclerosis by regulating brain protein expression of CNOT3. CNOT3 is a subunit of CCR4-NOT, which has been shown to be a master regulator of mRNA stability and translation and an important complex for cholesterol homeostasis. In summary, we identify a novel genetic locus for cerebral atherosclerosis and a potential mechanism linking this variation to cerebral atherosclerosis progression. These findings offer insights into the genetic effects on cerebral atherosclerosis.

Transcriptome-wide association study of post-trauma symptom trajectories identified GRIN3B as a potential biomarker for PTSD development.

Biomarkers that predict symptom trajectories after trauma can facilitate early detection or intervention for posttraumatic stress disorder (PTSD) and may also advance our understanding of its biology. Here, we aimed to identify trajectory-based biomarkers using blood transcriptomes collected in the immediate aftermath of trauma exposure. Participants were recruited from an Emergency Department in the immediate aftermath of trauma exposure and assessed for PTSD symptoms at baseline, 1, 3, 6, and 12 months. Three empirical symptom trajectories (chronic-PTSD, remitting, and resilient) were identified in 377 individuals based on longitudinal symptoms across four data points (1, 3, 6, and 12 months), using latent growth mixture modeling. Blood transcriptomes were examined for association with longitudinal symptom trajectories, followed by expression quantitative trait locus analysis. GRIN3B and AMOTL1 blood mRNA levels were associated with chronic vs. resilient post-trauma symptom trajectories at a transcriptome-wide significant level (N = 153, FDR-corrected p value = 0.0063 and 0.0253, respectively). We identified four genetic variants that regulate mRNA blood expression levels of GRIN3B. Among these, GRIN3B rs10401454 was associated with PTSD in an independent dataset (N = 3521, p = 0.04). Examination of the BrainCloud and GTEx databases revealed that rs10401454 was associated with brain mRNA expression levels of GRIN3B. While further replication and validation studies are needed, our data suggest that GRIN3B, a glutamate ionotropic receptor NMDA type subunit-3B, may be involved in the manifestation of PTSD. In addition, the blood mRNA level of GRIN3B may be a promising early biomarker for the PTSD manifestation and development.

Integration of peripheral transcriptomics, genomics, and interactomics following trauma identifies causal genes for symptoms of post-traumatic stress and major depression.

Posttraumatic stress disorder (PTSD) is a debilitating syndrome with substantial morbidity and mortality that occurs in the aftermath of trauma. Symptoms of major depressive disorder (MDD) are also a frequent consequence of trauma exposure. Identifying novel risk markers in the immediate aftermath of trauma is a critical step for the identification of novel biological targets to understand mechanisms of pathophysiology and prevention, as well as the determination of patients most at risk who may benefit from immediate intervention. Our study utilizes a novel approach to computationally integrate blood-based transcriptomics, genomics, and interactomics to understand the development of risk vs. resilience in the months following trauma exposure. In a two-site longitudinal, observational prospective study, we assessed over 10,000 individuals and enrolled >700 subjects in the immediate aftermath of trauma (average 5.3 h post-trauma (range 0.5-12 h)) in the Grady Memorial Hospital (Atlanta) and Jackson Memorial Hospital (Miami) emergency departments. RNA expression data and 6-month follow-up data were available for 366 individuals, while genotype, transcriptome, and phenotype data were available for 297 patients. To maximize our power and understanding of genes and pathways that predict risk vs. resilience, we utilized a set-cover approach to capture fluctuations of gene expression of PTSD or depression-converting patients and non-converting trauma-exposed controls to find representative sets of disease-relevant dysregulated genes. We annotated such genes with their corresponding expression quantitative trait loci and applied a variant of a current flow algorithm to identify genes that potentially were causal for the observed dysregulation of disease genes involved in the development of depression and PTSD symptoms after trauma exposure. We obtained a final list of 11 driver causal genes related to MDD symptoms, 13 genes for PTSD symptoms, and 22 genes in PTSD and/or MDD. We observed that these individual or combined disorders shared ESR1, RUNX1, PPARA, and WWOX as driver causal genes, while other genes appeared to be causal driver in the PTSD only or MDD only cases. A number of these identified causal pathways have been previously implicated in the biology or genetics of PTSD and MDD, as well as in preclinical models of amygdala function and fear regulation. Our work provides a promising set of initial pathways that may underlie causal mechanisms in the development of PTSD or MDD in the aftermath of trauma.