Psychosocial experiences are associated with human brain mitochondrial biology.

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

Genetic control of the human brain proteome.

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.

Effects of brain microRNAs in cognitive trajectory and Alzheimer's disease.

microRNAs (miRNAs) have a broad influence on gene expression; however, we have limited insights into their contribution to rate of cognitive decline over time or Alzheimer's disease (AD). Given this, we tested associations of 528 miRNAs with cognitive trajectory, AD hallmark pathologies, and AD clinical diagnosis using small RNA sequencing from the dorsolateral prefrontal cortex of 641 community-based donors. We found 311 miRNAs differentially expressed in AD or its endophenotypes after adjusting for technical and sociodemographic variables. Among these, 137 miRNAs remained differentially expressed after additionally adjusting for several co-occurring age-related cerebral pathologies, suggesting that some miRNAs are associated with the traits through co-occurring pathologies while others through mechanisms independent from pathologies. Pathway enrichment analysis of downstream targets of these differentially expressed miRNAs found enrichment in transcription, postsynaptic signalling, cellular senescence, and lipoproteins. In sex-stratified analyses, five miRNAs showed sex-biased differential expression for one or more AD endophenotypes, highlighting the role that sex has in AD. Lastly, we used Mendelian randomization to test whether the identified differentially expressed miRNAs contribute to the cause or are the consequence of the traits. Remarkably, 15 differentially expressed miRNAs had evidence consistent with a causal role, laying the groundwork for future mechanistic studies of miRNAs in AD and its endophenotypes.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease.

INTRODUCTION: Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association. METHODS: We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs. RESULTS: PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation. DISCUSSION: Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD. HIGHLIGHTS: First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

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.

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.

TIGAR: An Improved Bayesian Tool for Transcriptomic Data Imputation Enhances Gene Mapping of Complex Traits.

The transcriptome-wide association studies (TWASs) that test for association between the study trait and the imputed gene expression levels from cis-acting expression quantitative trait loci (cis-eQTL) genotypes have successfully enhanced the discovery of genetic risk loci for complex traits. By using the gene expression imputation models fitted from reference datasets that have both genetic and transcriptomic data, TWASs facilitate gene-based tests with GWAS data while accounting for the reference transcriptomic data. The existing TWAS tools like PrediXcan and FUSION use parametric imputation models that have limitations for modeling the complex genetic architecture of transcriptomic data. Therefore, to improve on this, we employ a nonparametric Bayesian method that was originally proposed for genetic prediction of complex traits, which assumes a data-driven nonparametric prior for cis-eQTL effect sizes. The nonparametric Bayesian method is flexible and general because it includes both of the parametric imputation models used by PrediXcan and FUSION as special cases. Our simulation studies showed that the nonparametric Bayesian model improved both imputation R2 for transcriptomic data and the TWAS power over PrediXcan when ≥1% cis-SNPs co-regulate gene expression and gene expression heritability ≤0.2. In real applications, the nonparametric Bayesian method fitted transcriptomic imputation models for 57.8% more genes over PrediXcan, thus improving the power of follow-up TWASs. We implement both parametric PrediXcan and nonparametric Bayesian methods in a convenient software tool "TIGAR" (Transcriptome-Integrated Genetic Association Resource), which imputes transcriptomic data and performs subsequent TWASs using individual-level or summary-level GWAS data.

LDL cholesterol is associated with higher AD neuropathology burden independent of APOE.

OBJECTIVE: APOE is 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 of APOE is unknown and is the focus of this paper. METHODS: Individuals 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 by APOE genotype 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. RESULTS: 559 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 of APOE after adjusting for age, sex, cholesterol-lowering medication use, body mass index, smoking and education at false discovery rate (FDR) p-value <0.05. CONCLUSIONS: These findings implicate LDL-C in the pathophysiology of AD independent of APOE and suggest LDL-C is a modifiable risk factor for AD.

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.

Alzheimer's disease genetic burden is associated with mid-life depression among persons with normal cognition.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. DISCUSSION: 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.

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L.

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.

Important Correlates of Purpose in Life Identified Through a Machine Learning Approach.

OBJECTIVE: A wealth of evidence has linked purpose in life (PiL) to better mental and physical health and healthy aging. Here, the authors aimed to determine important correlates of PiL using a machine learning approach. METHODS: Participants were recruited from retirement communities by the Rush Memory and Aging Project and assessed for childhood experience, adulthood sociodemographic factors (e.g., education, income, marital status), lifestyle and health behavior (e.g., cognitively stimulating activities, exercise, social activities, social network size), psychological factors (e.g., depression, loneliness, perceived discrimination, perceived social support), personality traits (e.g., PiL, harm avoidance), and medical conditions. Elastic Net was implemented to identify important correlates of PiL. RESULTS: A total of 1,839 participants were included in our analysis. Among the 23 variables provided to Elastic Net, 10 were identified as important correlates of PiL. In order of decreasing effect size, factors associated with lower PiL were loneliness, harm avoidance, older age, and depressive symptoms, while those associated with greater PiL were perceived social support, more social activities, more years of education, higher income, intact late-life cognitive performance, and more middle-age cognitive activities. CONCLUSION: Our findings identify potentially important modifiable factors as targets for intervention strategies to enhance PiL.

Association of HLA locus alleles with posttraumatic stress disorder.

BACKGROUND: Immune dysregulation has been widely observed in those with posttraumatic stress disorder (PTSD). An individual's immune response is shaped, in part, by the highly polymorphic Human Leukocyte Antigen (HLA) locus that is associated with major psychiatric disorders such as schizophrenia, major depression and bipolar disorder. The aim of the current study was to investigate the association between common HLA alleles and PTSD. METHODS: Genome-wide association data was used to predict alleles of 7 classical polymorphic HLA genes (A, B, C, DRB1, DQA1, DQB1, DPB1) in 403 lifetime PTSD cases and 369 trauma exposed controls of African ancestry. Association of HLA allelic variations with lifetime PTSD was analyzed using logistic regression, controlling for ancestry, sex and multiple comparisons. The effect of HLA alleles on gene expression was assessed by weighted correlation network analysis (WGCNA), using 353 subjects with available expression data. Enrichment analysis was performed using anRichment to identify associated pathways of each module. RESULTS: HLA-B*58:01 (p = 0.035), HLA-C*07:01 (p = 0.035), HLA-DQA1*01:01 (p = 0.003), HLA-DQB1*05:01 (p = 0.009) and HLA-DPB1*17:01 (p = 0.017) were more common in PTSD cases, while HLA-A*02:01 (p = 0.026), HLA-DQA1*05:05 (p = 0.011) and HLA-DRB1*11:01 (p < 0.001) were more frequent in controls. WGCNA was used to explore expression patterns of the PTSD related alleles. Gene expression modules of PTSD-related HLA alleles were enriched in various pathways, including pathways related to immune and neural activity. CONCLUSIONS: To the best of our knowledge, this is the first study to report an association of HLA alleles with PTSD. Altogether, our results support the link between the immune system, brain and PTSD.

Gene expression in cord blood links genetic risk for neurodevelopmental disorders with maternal psychological distress and adverse childhood outcomes.

Prenatal exposure to maternal stress and depression has been identified as a risk factor for adverse behavioral and neurodevelopmental outcomes in early childhood. However, the molecular mechanisms through which maternal psychopathology shapes offspring development remain poorly understood. We applied transcriptome-wide screens to 149 umbilical cord blood samples from neonates born to mothers with posttraumatic stress disorder (PTSD; n = 20), depression (n = 31) and PTSD with comorbid depression (n = 13), compared to carefully matched trauma exposed controls (n = 23) and healthy mothers (n = 62). Analyses by maternal diagnoses revealed a clear pattern of gene expression signatures distinguishing neonates born to mothers with a history of psychopathology from those without. Co-expression network analysis identified distinct gene expression perturbations across maternal diagnoses, including two depression-related modules implicated in axon-guidance and mRNA stability, as well as two PTSD-related modules implicated in TNF signaling and cellular response to stress. Notably, these disease-related modules were enriched with brain-expressed genes and genetic risk loci for autism spectrum disorder and schizophrenia, which may imply a causal role for impaired developmental outcomes. These molecular alterations preceded changes in clinical measures at twenty-four months, including reductions in cognitive and socio-emotional outcomes in affected infants. Collectively, these findings indicate that prenatal exposure to maternal psychological distress induces neuronal, immunological and behavioral abnormalities in affected offspring and support the search for early biomarkers of exposures to adverse in utero environments and the classification of children at risk for impaired development.

Blood gene expression profiles suggest altered immune function associated with symptoms of generalized anxiety disorder.

Prospective epidemiological studies found that generalized anxiety disorder (GAD) can impair immune function and increase risk for cardiovascular disease or events. Mechanisms underlying the physiological reverberations of anxiety, however, are still elusive. Hence, we aimed to investigate molecular processes mediating effects of anxiety on physical health using blood gene expression profiles of 336 community participants (157 anxious and 179 control). We examined genome-wide differential gene expression in anxiety, as well as associations between nine major modules of co-regulated transcripts in blood gene expression and anxiety. No significant differential expression was observed in women, but 631 genes were differentially expressed between anxious and control men at the false discovery rate of 0.1 after controlling for age, body mass index, race, and batch effect. Gene set enrichment analysis (GSEA) revealed that genes with altered expression levels in anxious men were involved in response of various immune cells to vaccination and to acute viral and bacterial infection, and in a metabolic network affecting traits of metabolic syndrome. Further, we found one set of 260 co-regulated genes to be significantly associated with anxiety in men after controlling for the relevant covariates, and demonstrate its equivalence to a component of the stress-related conserved transcriptional response to adversity profile. Taken together, our results suggest potential molecular pathways that can explain negative effects of GAD observed in epidemiological studies. Remarkably, even mild anxiety, which most of our participants had, was associated with observable changes in immune-related gene expression levels. Our findings generate hypotheses and provide incremental insights into molecular mechanisms mediating negative physiological effects of GAD.

Identifying latent genetic interactions in genome-wide association studies using multiple traits.

The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit ).

SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations.

Family-based heritability estimates of complex traits are often considerably larger than their single-nucleotide polymorphism (SNP) heritability estimates. This discrepancy may be due to non-additive effects of genetic variation, including variation that interacts with other genes or environmental factors to influence the trait. Variance-based procedures provide a computationally efficient strategy to screen for SNPs with potential interaction effects without requiring the specification of the interacting variable. While valuable, such variance-based tests consider only a single trait and ignore likely pleiotropy among related traits that, if present, could improve power to detect such interaction effects. To fill this gap, we propose SCAMPI (Scalable Cauchy Aggregate test using Multiple Phenotypes to test Interactions), which screens for variants with interaction effects across multiple traits. SCAMPI is motivated by the observation that SNPs with pleiotropic interaction effects induce genotypic differences in the patterns of correlation among traits. By studying such patterns across genotype categories among multiple traits, we show that SCAMPI has improved performance over traditional univariate variance-based methods. Like those traditional variance-based tests, SCAMPI permits the screening of interaction effects without requiring the specification of the interaction variable and is further computationally scalable to biobank data. We employed SCAMPI to screen for interacting SNPs associated with four lipid-related traits in the UK Biobank and identified multiple gene regions missed by existing univariate variance-based tests. SCAMPI is implemented in software for public use.

Beyond memory impairment: the complex phenotypic landscape of Alzheimer's disease.

Neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD) constitute multifaceted behavioral manifestations that reflect processes of emotional regulation, thinking, and social behavior. They are as prevalent in AD as cognitive impairment and develop independently during the progression of neurodegeneration. As studying NPSs in AD is clinically challenging, most AD research to date has focused on cognitive decline. In this opinion article we summarize emerging literature on the prevalence, time course, and the underlying genetic, molecular, and pathological mechanisms related to NPSs in AD. Overall, we propose that NPSs constitute a cluster of core symptoms in AD, and understanding their neurobiology can lead to a more holistic approach to AD research, paving the way for more accurate diagnostic tests and personalized treatments embracing the goals of precision medicine.

Joint effects of air pollution and neighborhood socioeconomic status on cognitive decline - Mediation by depression, high cholesterol levels, and high blood pressure.

Air pollution and neighborhood socioeconomic status (N-SES) are associated with adverse cardiovascular health and neuropsychiatric functioning in older adults. This study examines the degree to which the joint effects of air pollution and N-SES on the cognitive decline are mediated by high cholesterol levels, high blood pressure (HBP), and depression. In the Emory Healthy Aging Study, 14,390 participants aged 50+ years from Metro Atlanta, GA, were assessed for subjective cognitive decline using the cognitive function instrument (CFI). Information on the prior diagnosis of high cholesterol, HBP, and depression was collected through the Health History Questionnaire. Participants' census tracts were assigned 3-year average concentrations of 12 air pollutants and 16 N-SES characteristics. We used the unsupervised clustering algorithm Self-Organizing Maps (SOM) to create 6 exposure clusters based on the joint distribution of air pollution and N-SES in each census tract. Linear regression analysis was used to estimate the effects of the SOM cluster indicator on CFI, adjusting for age, race/ethnicity, education, and neighborhood residential stability. The proportion of the association mediated by high cholesterol levels, HBP, and depression was calculated by comparing the total and direct effects of SOM clusters on CFI. Depression mediated up to 87 % of the association between SOM clusters and CFI. For example, participants living in the high N-SES and high air pollution cluster had CFI scores 0.05 (95 %-CI:0.01,0.09) points higher on average compared to those from the high N-SES and low air pollution cluster; after adjusting for depression, this association was attenuated to 0.01 (95 %-CI:-0.04,0.05). HBP mediated up to 8 % of the association between SOM clusters and CFI and high cholesterol up to 5 %. Air pollution and N-SES associated cognitive decline was partially mediated by depression. Only a small portion (<10 %) of the association was mediated by HBP and high cholesterol.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions.

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.