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Background: Attention-deficit/hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD) are associated, but it is unclear if this is a causal relationship or confounding. We used genetic analyses and sibling comparisons to clarify the direction of this relationship. Methods: Linkage disequilibrium score regression and 2-sample Mendelian randomization were used to test for genetic correlation (r g) and bidirectional causal effects using European ancestry genome-wide association studies of ADHD (20,183 cases and 35,191 controls) and 6 PTSD definitions (up to 320,369 individuals). Several additional variables were included in the analysis to verify the independence of the ADHD-PTSD relationship. In a population-based sibling comparison (N = 2,082,118 individuals), Cox regression models were fitted to account for time at risk, a range of sociodemographic factors, and unmeasured familial confounders (via sibling comparisons). Results: ADHD and PTSD had consistent r g (r g range, 0.43–0.52; p < .001). ADHD genetic liability was causally linked with increased risk for PTSD (β = 0.367; 95% CI, 0.186–0.552; p = 7.68 × 10 −5). This result was not affected by heterogeneity, horizontal pleiotropy (Mendelian randomization Egger intercept = 4.34 × 10 −4, p = .961), or other phenotypes and was consistent across PTSD datasets. However, we found no consistent associations between PTSD genetic liability and ADHD risk. Individuals diagnosed with ADHD were at a higher risk for developing PTSD than their undiagnosed sibling (hazard ratio = 2.37; 95% CI, 1.98–3.53). Conclusions: Our findings add novel evidence supporting the need for early and effective treatment of ADHD, as patients with this diagnosis are at significantly higher risk to develop PTSD later in life.

Despite an established link between depression and higher Alzheimer's disease (AD) risk, it is unclear whether the conditions share pathophysiology. Here, we investigated whether depression manifesting after age 50 is associated with a genetic predisposition to AD.From the population-based Health and Retirement Study cohort with biennial assessments of depressive symptoms and cognitive performance, we studied 6656 individuals of European ancestry with whole-genome genotyping. Polygenic risk scores (PRSs) for AD were estimated and examined for an association with depression in cognitively normal participants using regression modeling.Among cognitively normal participants, those with a higher AD PRS were more likely to experience depression after age 50 after accounting for the effects of genetic predisposition to depression, sex, age, and education.Genetic predisposition to AD may be one of the factors contributing to the pathogenesis of mid-life depression. Whether there is a shared genetic basis between mid-life depression and AD merits further study.

IntroductionHigher fine particulate matter (PM2.5) exposure has been found to be associated with Alzheimer’s disease (AD). PM2.5has been hypothesized to cause inflammation and oxidative stress in the brain, contributing to neuropathology. A major genetic risk factor of AD, the apolipoprotein E (APOE) gene, has also been hypothesized to modify the association between PM2.5and AD. However, little prior research exisits to support these hypotheses. Therefore, this paper aims to investigate the association between traffic-related PM2.5and AD hallmark pathology, including effect modification byAPOEgenotype, in an autopsy cohort.MethodsBrain tissue donors enrolled in the Emory Goizueta Alzheimer’s Disease Research Center (ADRC) who died before 2020 (n=224) were assessed for AD pathology including Braak Stage, Consortium to Establish a Registry for AD (CERAD) score, and the combined AD neuropathologic change (ABC score). Traffic-related PM2.5concentrations were modeled for the metro-Atlanta area during 2002-2019 with a spatial resolution of 200-250m. One-, 3-, and 5-year average PM2.5concentrations prior to death were matched to participants home address. We assessed the association between traffic-related PM2.5and AD hallmark pathology, as well as effect modification byAPOEgenotype, using adjusted ordinal logistic regression models.ResultsTraffic-related PM2.5was significantly associated with CERAD score for the 1-year exposure window (OR: 1.92; 95% CI: 1.12, 3.30), and the 3-year exposure window (OR: 1.87; 95%-CI: 1.01, 3.17). PM2.5had harmful, but non-significant associations on Braak Stage and ABC score. The strongest associations between PM2.5and neuropathology markers were among those withoutAPOEε4alleles (e.g., for CERAD and 1-year exposure window, OR: 2.31; 95% CI: 1.36, 3.94), though interaction between PM2.5andAPOEgenotype was not statistically significant.ConclusionsOur study found traffic-related PM2.5exposure was associated with CERAD score in an autopsy cohort, contributing to epidemiologic evidence that PM2.5affects Aβ deposition in the brain. This association was particularly strong among donors withoutAPOEε4alleles. Future studies should further investigate the biological mechanisms behind this assocation.

The biological processes that are disrupted in the Alzheimer’s disease (AD) brain remain incompletely understood. We recently performed a proteomic analysis of >2000 brains to better understand these changes, which highlighted alterations in astrocytes and microglia as likely key drivers of disease. Here, we extend this analysis by analyzing >1000 brain tissues using a tandem mass tag mass spectrometry (TMT-MS) pipeline, which allowed us to nearly triple the number of quantified proteins across cases. A consensus protein co-expression network analysis of this deeper dataset revealed new co-expression modules that were highly preserved across cohorts and brain regions, and strongly altered in AD. Nearly half of the protein co-expression modules, including modules significantly altered in AD, were not observed in RNA networks from the same cohorts and brain regions, highlighting the proteopathic nature of AD. Two such AD-associated modules unique to the proteomic network included a module related to MAPK signaling and metabolism, and a module related to the matrisome. Analysis of paired genomic and proteomic data within subjects showed that expression level of the matrisome module was influenced by the APOE ε4 allele, but was not related to the rate of cognitive decline after adjustment for neuropathology. In contrast, the MAPK/metabolism module was strongly associated with the rate of cognitive decline. Disease-associated modules unique to the proteome are sources of promising therapeutic targets and biomarkers for AD.

Background and ObjectivesAlzheimer dementia is a complex clinical syndrome that can be defined broadly as an amnestic multidomain dementia. We previously reported human cortical proteins that are implicated in Alzheimer dementia. To understand the pathologic correlates of these proteins for underlying disease mechanisms, we investigated cortical protein associations with common age-related neuropathologies.MethodsParticipants were community-dwelling older adults from 2 cohort studies of aging and dementia. All underwent detailed annual clinical evaluations, and brain autopsies were performed after death. We use Alzheimer disease (AD) to refer to pathologically defined disease and Alzheimer dementia to refer to the clinical syndrome. Indices for AD, cortical Lewy bodies, limbic predominant age-related TAR DNA binding protein 43 encephalopathy neuropathologic changes (LATE-NC), hippocampal sclerosis, macroscopic infarcts, microinfarcts, cerebral amyloid angiopathy, atherosclerosis, and arteriolosclerosis were quantified during uniform structured neuropathologic evaluations. High-throughput protein abundances from frozen dorsolateral prefrontal cortex were quantified with mass spectrometry–based tandem mass tag proteomics analysis. Eleven human cortical proteins implicated in Alzheimer dementia, including angiotensin-converting enzyme, calcium-regulated heat-stable protein 1 (CHSP1), procathepsin H (CATH), double C2-like domain-containing protein α, islet cell autoantigen 1–like protein, serine β-lactamase–like protein LACTB, mitochondrial, pleckstrin homology domain–containing family A member 1, replication termination factor 2, sorting nexin-32, syntaxin-4, and syntaxin-6 (STX6), were previously identified with an integrative approach. Logistic regression analysis examined the association of protein expression with each of the neuropathologic indices.ResultsA total of 391 older adults were included. We did not observe associations of these protein targets with pathologic diagnosis of AD. In contrast, multiple proteins were associated with non-AD neurodegenerative and cerebrovascular conditions. In particular, higher CHSP1 expression was associated with cortical Lewy bodies and macroscopic infarcts, and higher CATH expression was associated with LATE-NC and arteriolosclerosis. Furthermore, while higher STX6 expression increased the risk of Alzheimer dementia, the protein was not associated with any of the neuropathologic indices investigated.DiscussionCortical proteins implicated in Alzheimer dementia do not necessarily work through AD pathogenesis; rather, non-AD neurodegenerative and vascular diseases and other pathways are at play. Furthermore, some proteins are pleiotrophic and associated with both neurodegenerative and cerebrovascular pathologies.

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate

Doublecortin (DCX) has long been implicated in, and employed as a marker for, neurogenesis, yet little is known about its function in non-neurogenic brain regions, including the amygdala. This study sought first to explore, in rodents, whether fear learning and extinction modulate amygdala DCX expression and, second, to assess the utility of peripheral DCX correlates as predictive biomarkers of trauma response in rodents and humans. Pavlovian conditioning was found to alter DCX protein levels in mice 24 h later, resulting in higher DCX expression associated with enhanced learning in paradigms examining both the acquisition and extinction of fear (p

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.

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.

Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies. Wingo et al. integrate depression GWAS results with human brain proteomes to perform proteome-wide association studies followed by Mendelian randomization. They identify 25 proteins as potential causal mediators of depression, of which 20 are new.

Genome-wide association studies (GWAS) have identified many risk loci for Alzheimer's disease (AD)1,2, but how these loci confer AD risk is unclear. Here, we aimed to identify loci that confer AD risk through their effects on brain protein abundance to provide new insights into AD pathogenesis. To that end, we integrated AD GWAS results with human brain proteomes to perform a proteome-wide association study (PWAS) of AD, followed by Mendelian randomization and colocalization analysis. We identified 11 genes that are consistent with being causal in AD, acting via their cis-regulated brain protein abundance. Nine replicated in a confirmation PWAS and eight represent new AD risk genes not identified before by AD GWAS. Furthermore, we demonstrated that our results were independent of APOE e4. Together, our findings provide new insights into AD pathogenesis and promising targets for further mechanistic and therapeutic studies.

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.

Cerebral atherosclerosis contributes to dementia via unclear processes. We performed proteomic sequencing of dorsolateral prefrontal cortex in 438 older individuals and found associations between cerebral atherosclerosis and reduced synaptic signaling and between RNA splicing and increased oligodendrocyte development and myelination. Consistently, single-cell RNA sequencing showed cerebral atherosclerosis associated with higher oligodendrocyte abundance. A subset of proteins and modules associated with cerebral atherosclerosis was also associated with Alzheimer's disease, suggesting shared mechanisms.

Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological Psychiatry Background: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods. publishersversion published

Depression has been associated with a higher risk of Alzheimer's disease (AD) in several prospective studies; however, mechanisms underlying this association remain unclear.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.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.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.

ObjectiveAPOEis a strong risk factor for Alzheimer’s disease (AD) and associated with higher low-density lipoprotein cholesterol (LDL-C) levels. Moreover, LDL-C is associated with the development of clinically ascertained AD; however, whether this association is present with the underlying neuropathological manifestations of AD or whether it is independent of the effect ofAPOEis unknown and is the focus of this paper.MethodsIndividuals in the Religious Orders Study/Memory and Ageing Project cohorts with longitudinal measures of blood lipids and detailed autopsies were studied. We modelled the relationship between blood lipids and 12 age-related brain pathologies using a linear mixed model adjusted for potential confounding factors and stratified byAPOEgenotype with overall significance determined by meta-analysis. Blood lipids considered were LDL-C, high-density lipoprotein cholesterol and triglycerides. Brain pathologies included AD pathology measured by silver staining (Braak stage, a modified Consortium to Establish a Registry for Alzheimer’s Disease [CERAD] score and global AD pathology) and immunohistochemistry (beta-amyloid and neurofibrillary tangles) as well as cerebral microinfarct, cerebral macroinfarct, cerebral amyloid angiopathy, cerebral atherosclerosis, hippocampal sclerosis, TDP-43 cytoplasmic inclusions and Lewy bodies.Results559 participants (69.1% female) had complete data for analysis. They were followed for a median of 7 years and a median of 3 years prior to dementia onset. LDL-C was associated with all measures of AD neuropathology (neurofibrillary tangles, beta-amyloid, Braak stage, modified CERAD score and global AD pathology) and cerebral amyloid angiopathy independent ofAPOEafter adjusting for age, sex, cholesterol-lowering medication use, body mass index, smoking and education at false discovery rate (FDR) p-value ConclusionsThese findings implicate LDL-C in the pathophysiology of AD independent ofAPOEand suggest LDL-C is a modifiable risk factor for AD.

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.

In advanced age, some individuals maintain a stable cognitive trajectory while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by traditional neurodegenerative pathologies. Hence, to identify new processes underlying variation in cognitive trajectory, we perform an unbiased proteome-wide association study of cognitive trajectory in a discovery (n = 104) and replication cohort (n = 39) of initially cognitively unimpaired, longitudinally assessed older-adult brain donors. We find 579 proteins associated with cognitive trajectory after meta-analysis. Notably, we present evidence for increased neuronal mitochondrial activities in cognitive stability regardless of the burden of traditional neuropathologies. Furthermore, we provide additional evidence for increased synaptic abundance and decreased inflammation and apoptosis in cognitive stability. Importantly, we nominate proteins associated with cognitive trajectory, particularly the 38 proteins that act independently of neuropathologies and are also hub proteins of protein co-expression networks, as promising targets for future mechanistic studies of cognitive trajectory., Cognitive abilities tend to decline over time in advanced age, yet some individuals experience stable abilities or rapid decline. Here the authors present a proteome-wide association study of cognitive trajectory, and identify 38 proteins associated with cognitive resilience.

SummaryMitochondrial respiratory chain (RC) function requires the stoichiometric interaction among dozens of proteins but their co-regulation has not been defined in the human brain. Here, using quantitative proteomics across three independent cohorts we systematically characterized the co-regulation patterns of mitochondrial RC proteins in the human dorsolateral prefrontal cortex (DLPFC). Whereas the abundance of RC protein subunits that physically assemble into stable complexes were correlated, indicating their co-regulation, RC assembly factors exhibited modest co-regulation. Within complex I, nuclear DNA-encoded subunits exhibited >2.5-times higher co-regulation than mitochondrial (mt)DNA-encoded subunits. Moreover, mtDNA copy number was unrelated to mtDNA-encoded subunits abundance, suggesting that mtDNA content is not limiting. Alzheimer’s disease (AD) brains exhibited reduced abundance of complex I RC subunits, an effect largely driven by a 2-4% overall lower mitochondrial protein content. These findings provide foundational knowledge to identify molecular mechanisms contributing to age- and disease-related erosion of mitochondrial function in the human brain.

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 (β = −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 (p(unadjusted)=0.042) and TIMELESS (p(unadjusted)=0.029) predicted six-month PTSD symptoms. The interaction of trauma time and cortisol concentration was significantly correlated with the expression of PER1 (p(adjusted)=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.

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.

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 (β = −0.27, 95% CI = (−0.35, −0.19), p = 1.29 × 10−10) and rs10881463 (β = −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.

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 (β = −0.27, 95% CI = (−0.35, −0.19), p = 1.29 × 10−10) and rs10881463 (β = −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.

We generated an online brain pQTL resource for 7,376 proteins through the analysis of genetic and proteomic data derived from post-mortem samples of the dorsolateral prefrontal cortex of 330 older adults. The identified pQTLs tend to be non-synonymous variation, are over-represented among variants associated with brain diseases, and replicate well (77%) in an independent brain dataset. Comparison to a large study of brain eQTLs revealed that about 75% of pQTLs are also eQTLs. In contrast, about 40% of eQTLs were identified as pQTLs. These results are consistent with lower pQTL mapping power and greater evolutionary constraint on protein abundance. The latter is additionally supported by observations of pQTLs with large effects' tending to be rare, deleterious, and associated with proteins that have evidence for fewer protein-protein interactions. Mediation analyses using matched transcriptomic and proteomic data provided additional evidence that pQTL effects are often, but not always, mediated by mRNA. Specifically, we identified roughly 1.6 times more mRNA-mediated pQTLs than mRNA-independent pQTLs (550 versus 341). Our pQTL resource provides insight into the functional consequences of genetic variation in the human brain and a basis for novel investigations of genetics and disease.

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 enrolled700 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.

Background Alzheimer’s disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions. Methods A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene’s surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues. Results Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR Conclusions We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

Objective Major depressive disorder (MDD) arises from a combination of genetic and environmental risk factors and DNA methylation is one of the molecular mechanisms through which these factors can manifest. However, little is known about the epigenetic signature of MDD in brain tissue. This study aimed to investigate associations between brain tissue-based DNA methylation and late-life MDD. Methods We performed a brain epigenome-wide association study (EWAS) of late-life MDD in 608 participants from the Religious Order Study and the Rush Memory and Aging Project (ROS/MAP) using DNA methylation profiles of the dorsal lateral prefrontal cortex generated using the Illumina HumanMethylation450 Beadchip array. We also conducted an EWAS of MDD in each sex separately. Results We found epigenome-wide significant associations between brain tissue-based DNA methylation and late-life MDD. The most significant and robust association was found with altered methylation levels in the YOD1 locus (cg25594636, p value = 2.55 × 10−11; cg03899372, p value = 3.12 × 10−09; cg12796440, p value = 1.51 × 10−08, cg23982678, p value = 7.94 × 10−08). Analysis of differentially methylated regions (p value = 5.06 × 10−10) further confirmed this locus. Other significant loci include UGT8 (cg18921206, p value = 1.75 × 10−08), FNDC3B (cg20367479, p value = 4.97 × 10−08) and SLIT2 (cg10946669, p value = 8.01 × 10−08). Notably, brain tissue-based methylation levels were strongly associated with late-life MDD in men more than in women. Conclusions We identified altered methylation in the YOD1, UGT8, FNDC3B, and SLIT2 loci as new epigenetic factors associated with late-life MDD. Furthermore, our study highlights the sex-specific molecular heterogeneity of MDD.

Positive and negative affect are both associated with health outcomes. Using validated measures, we examined associations between affect, self-reported measures of health, and objective measures of systemic inflammation in a cross-sectional sample of outpatient subjects recruited from an urban county hospital. Participants (n=1055) recruited from the Grady Trauma Project in Atlanta, GA underwent standardized interviews including self-report measures of psychiatric symptoms and physical health. A subset (n=246) consented to an assay of serum C-reactive protein (CRP). Regression models including positive affect as the predictor variable with covariates of age, gender, income, trauma load, depression and PTSD symptoms, were significantly associated with physical health domain scales of the Short Form-36 Health Survey (SF-36) of general health (R(2)=0.212; p

OBJECTIVES Blacks are disproportionately affected by tobacco-related illnesses as well as traumatic events associated with psychiatric conditions and smoking. We examined the potential protective nature of resilience within this context, hypothesizing resilience differentially moderates the associations of traumatic experiences to depressive symptoms and to biomarkers of health risk among Black ever versus never smokers. METHOD Measures of resilience, traumatic experiences, depressive symptoms, and biomarkers (interleukin-6 [IL-6], C-reactive protein [CRP], allostatic load) were obtained among 852 Blacks recruited from Grady Memorial Hospital in Atlanta. RESULTS Ever smokers experienced more trauma (p < .001) and depressive symptoms (p = .01). Structural equation modeling indicated that, in ever smokers, childhood trauma was positively associated with depressive symptoms (p < .001); resilience was negatively associated with depressive symptoms (p = .01). Depressive symptoms were positively associated with IL-6 (p = .03), which was positively associated with allostatic load (p = .01). Adulthood trauma was associated with higher CRP levels (p = .03). In never smokers, childhood (p < .001) and adulthood trauma (p = .01) were associated with more depressive symptoms. Adulthood trauma was also associated with higher CRP levels (p < .001), which was positively associated with allostatic load (p < .001). Never smokers with higher resilience had a negative association between childhood trauma and depressive symptoms whereas those with lower resilience had a positive association between childhood trauma and depressive symptoms. Resilience was negatively associated with CRP levels (p < .001). CONCLUSIONS Interventions targeting resilience may prevent smoking and adverse health outcomes. (PsycINFO Database Record

Late-life depression is associated with an increased risk for dementia but we have limited knowledge of the molecular mechanisms underlying this association. Here we investigated whether brain microRNAs, important posttranscriptional regulators of gene expression, contribute to this association. Late-life depressive symptoms were assessed annually in 300 participants of the Religious Orders Study and Rush Memory and Aging Project for a mean of 7 years. Participants underwent annual cognitive testing, clinical assessment of cognitive status, and uniform neuropathologic examination after death. microRNAs were profiled from the prefrontal cortex using NanoString platform in the discovery cohort and small RNA sequencing in the replication cohort. A global microRNA association study of late-life depressive symptoms was performed using linear mixed model adjusting for the potential confounding factors. Four brain microRNAs were associated with late-life depressive symptoms at adjusted p

ObjectiveCognitive decline is a hallmark of dementia; however, the brain epigenetic signature of cognitive decline is unclear. We investigated the associations between brain tissue-based DNA methylation and cognitive trajectory.MethodsWe performed a brain epigenome-wide association study of cognitive trajectory in 636 participants from the Religious Order Study and the Rush Memory and Aging Project (ROS/MAP) using DNA methylation profiles of the dorsal lateral prefrontal cortex (dPFC). To maximize our power to detect epigenetic associations, we used the recently developed Gene Association with Multiple Traits (GAMuT) test to analyze the five measured cognitive domains simultaneously.ResultsWe found an epigenome-wide association for differential methylation of sites in the Claudin-5 (CLDN5) locus and cognitive trajectory (p-value x 9.96 × 10-7), which was robust to adjustment for cell type proportions (p-value = 8.52 x 10-7). This association was primarily driven by association with declines in episodic (p-value = 4.65 x 10-6) and working memory (p-value = 2.54 x 10-7). This association between methylation in CLDN5 and cognitive decline was independent of beta-amyloid and neurofibrillary tangle pathology and present in participants with low levels of neuropathology. In addition, only 13-31% of the association between methylation and cognitive decline was mediated through levels of neuropathology, whereas the major part of the association was independent of it.InterpretationWe identified methylation in CLDN5 as new epigenetic factor associated with cognitive trajectory. Higher levels of methylation in CLDN5 were associated with faster cognitive decline implicating the blood brain barrier in maintenance of cognitive trajectory.

Alteration of protein abundance and conformation are widely believed to be the hallmark of neurodegenerative diseases. Yet relatively little is known about the genetic variation that controls protein abundance in the healthy human brain. The genetic control of protein abundance is generally thought to parallel that of RNA expression, but there is little direct evidence to support this view. Here, we performed a large-scale protein quantitative trait locus (pQTL) analysis using single nucleotide variants (SNVs) from whole-genome sequencing and tandem mass spectrometry-based proteomic quantification of 12,691 unique proteins (7,901 after quality control) from the dorsolateral prefrontal cortex (dPFC) in 144 cognitively normal individuals. We identified 28,211 pQTLs that were significantly associated with the abundance of 864 proteins. These pQTLs were compared to dPFC expression quantitative trait loci (eQTL) in cognitive normal individuals (n=169; 81 had protein data) and a meta-analysis of dPFC eQTLs (n=1,433). We found that strong pQTLs are generally only weak eQTLs, and that the majority of strong eQTLs are not detectable pQTLs. These results suggest that the genetic control of mRNA and protein abundance may be substantially distinct and suggests inference concerning protein abundance made from mRNA in human brain should be treated with caution.