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BackgroundGenome-wide association studies revealed a robust association between genetic variants in theLIPA(lysosomal acid lipase) gene and coronary artery diseases (CAD), but not lipid traits. QTL studies support that the risk alleles ofLIPACAD variants are associated with higherLIPAmRNA and enzyme activity in human monocytes. Yet the variant-to-function relationship and how this important locus impacts disease etiology has not been fully established. Herein, we aim to determine the causal variant(s), involved cell type, and the target gene, establish the causality of the variant-to-function relationship, and elucidate how increased myeloid LIPA impacts atherosclerosisin vivo.MethodsWe apply functional genomic datasets, post-GWAS prioritization pipelines, and molecular biology techniques, incuding eQTL, enzyme activity-QTL, high-resolution Tri-HiC, ChIP-seq, and site-directed mutagenesis and luciferase assay to connect functional variants to the candidate genes in the causal cell type. To establish how increased myeloidLIPAimpacts atherosclerosis, we generated myeloid-specificLipaoverexpression mice(LipaTg).ResultsPost-GWAS pipelines supportLIPAas the candidate causal gene at the locus. In human monocyte-derived macrophages,LIPAmRNA, protein and enzyme activity were higher in the risk allele carriers of CAD variants. High-resolution Tri-HiC and luciferase assay confirmed an intronic enhancer region showing strong interaction with theLIPApromoter. Within the enhancer region, the risk alleles of rs1412444/rs1412445 and rs1320496 demonstrate enhanced binding to PU. 1, and acted as the functional variants with risk alleles leading to increased enhancer activity. The risk allele of rs1320496 is predicted to create a motif binding site for PU.1. The functional genomic data together support thatLIPAis the candidate causal gene in the locus, and the risk alleles of CAD led to increased LIPA in a myeloid cell-specific manner. Consistently, mice with myeloid-specificLipaoverexpression on aLdlr-/-background showed significantly increased atherosclerotic lesion size and lesion macrophage area without affecting plasma cholesterol. ScRNA-seq analysis showed thatLipaTgled to reduced lipid-enriched yet increased inflammatory macrophage subsets, and activation chemokine signaling pathway. This was further confirmed by reduced neutral lipid accumulation in both plaque and peritoneal macrophages and significantly increased monocytes infiltration into the lesion inLipaTgmice.ConclusionsWe established thatLIPArisk alleles drive increased myeloid LIPA and aggravate atherosclerosis.CLINICAL PERSPECTIVEWhat is New?CAD GWAS variants at theLIPAlocus led to increased macrophage LIPA expression and enzyme activity.Myeloid-specific overexpression ofLipaexacerbates atherosclerosis.Our study connected the genetic variation to the involved cell type and the target gene, and the disease mechanism for this important locus.What are the Clinical Implications?GWAS and meta-analyses have identified over 200 loci for CAD. Establishing the candidate genes and their mechanistic studies inform novel biological mechanisms and therapeutic application.There is strong statistical evidence linkingLIPAwith CAD. By leveraging functional genomic studies and transgenic mice, our work established the direct causality thatLIPArisk alleles drive increased myeloid LIPA and aggravate atherosclerosis. Establishing the variant-to-function relationship for this locus informs that increasing myeloid LIPA may not be a therapeutic strategy for CAD, despite the essential role of LIPA in regulating lysosomal lipid metabolism.

The increasing e-cigarette use worldwide presents an urgent need to characterize their nicotine delivery property, brain stimulation and potential long-term health effects. We constructed an end-to-end system enabling combustible-cigarette (c-cigarette) and e-cigarette aerosol generation, animal exposure, and effect assessment. The system consists of (1) a 10-channel aerosol generator resembling human smoking/vaping scenarios, (2) nose-only and whole-body exposure chambers suitable for long- or short-duration studies, (3) a lab protocol for animal exposure and collecting arterial and venous blood in vivonicotine delivery after e-cigarette aerosol inhalation. Groups of Sprague-Dawley rats were exposed to e-cigarette aerosols for 1, 2 and 4 minutes, respectively. Arterial and venous blood samples were collected immediately after the exposure. We also directly compared nose-only and whole-body exposure approaches. After nose-only e-cigarette aerosol exposure, the nicotine concentration in arterial blood was substantially higher (11.32 ng/mL in average) than in veins. Similar arterio-venous concentration difference was observed in whole-body exposure experiments. In summary, we described a complete system ideal for e- and c-cigarettein vivonicotine kinetics and long-term health research. Our findings highlight arterial blood as the suitable bio-specimen for e-cigarette nicotine delivery studies.HighlightWe constructed a combustible- and e-cigarette aerosol generation - exposure - effect assessment system resembling real world human smoking/vaping scenarios.Proof-of-principle study characterizedin vivonicotine delivery from e-cigarette aerosol to arterial and venous blood at high temporal resolution.After exposure, the nicotine concentration was substantially higher (11.32 ng/mL) in arterial blood than in veins.Our results suggest arterial blood as the suitable bio-specimen to study nicotine delivery and brain stimulation.

Water-soluble inorganic (WSI) ions are major components of ambient air PM2.5 (particulate matter of diameter ≤2.5 μm); however, their potential health effects are understudied. On C57BL/6 mice, we quantified the effect of three major PM2.5 WSIs (NO3-, SO42-, and NH4+) on respiratory systems. Exposure scenarios include different WSI types, concentrations, animal development stages (young vs adult), and sex. The exposure effects were comprehensively assessed, with special focus on the respiratory function and tissue/cell level changes. Chronic PM2.5 NO3- exposure produced significant respiratory function decline, mainly presented as airflow obstruction. The decline was more profound in young mice than in adult mice. In young mice, exposure to 22 μg/m3 PM2.5 NO3- reduced FEV0.05 (forced expiratory volume in 0.05 s) by 11.3% (p = 9.6 × 10-3) and increased pulmonary neutrophil infiltration by 7.9% (p = 7.1 × 10-3). Causality tests identified that neutrophil infiltration was involved in the biological mechanism underlying PM2.5 NO3- toxicity. In contrast, the effects of PM2.5 SO42- were considerably weaker than NO3-. PM2.5 NO3- exposure was 3.4 times more potent than PM2.5 SO42- in causing reduction of the peak expiratory flow. PM2.5 NH4+ exposure had no statistically significant effects on the respiratory function. In summary, this study provided strong evidence on the adverse impacts of PM2.5 WSIs, where the impacts were most profound in young mice exposed to PM2.5 NO3-. If confirmed in humans, toxicity of PM2.5 WSI will have broad implications in environment health and policy making.

Pathogenesis of complex diseases often involves multiple organs/tissue-types. To date, the PMC57BL/6 mice (n = 40) were exposed to PMPMThis study aims to fill in a major knowledge gap and investigated the effect of PM

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association study data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm–Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.

Apolipoprotein L1 (APOL1) risk alleles in donor kidneys associate with graft loss, but whether recipient risk allele expression affects transplant outcomes is unclear. To test whether recipient APOL1 risk alleles independently correlate with transplant outcomes, we analyzed genome-wide SNP genotyping data on donors and recipients from 2 kidney transplant cohorts: Genomics of Chronic Allograft Rejection (GOCAR) and Clinical Trials in Organ Transplantation 01/17 (CTOT-01/17). We estimated genetic ancestry (quantified as the proportion of African ancestry, or pAFR) by ADMIXTURE and correlated APOL1 genotypes and pAFR with outcomes. In the GOCAR discovery set, we noted that the number of recipient APOL1 G1/G2 alleles (R-nAPOL1) associated with an increased risk of death-censored allograft loss (DCAL), independent of ancestry (HR = 2.14; P = 0.006), as well as within the subgroup of African American and Hispanic (AA/H) recipients (HR = 2.36; P = 0.003). R-nAPOL1 also associated with an increased risk of any T cell–mediated rejection (TCMR) event. These associations were validated in CTOT-01/17. Ex vivo studies of PMBCs revealed, unexpectedly, high expression levels of APOL1 in activated CD4(+)/CD8(+) T cells and NK cells. We detected enriched immune response gene pathways in risk allele carriers compared with noncarriers on the kidney transplant waitlist and among healthy controls. Our findings demonstrate an immunomodulatory role for recipient APOL1 risk alleles associated with TCMR and DCAL. We believe this finding has broader implications for immune-mediated injury to native kidneys.

Despite national and international efforts for the prevention of metabolic syndrome and its underlying diseases/disorders, its prevalence is still rising, especially in the middle-aged population. In this study, we explore the effect of high fat diet on the development of metabolic syndrome in middle-aged mice and to evaluate the potential benefits of voluntary physical exercise on the periphery as well as brain cognitive function, and to explore the potential mechanisms. We found that metabolic syndrome developed at middle age significantly impairs cognitive function and the impairment is associated with gene dysregulation in metabolic pathways that are largely affecting astrocytes in the brain. Eight-week voluntary wheel running at a frequency of three times a week, not only improves peripheral glucose control but also significantly improves learning and memory. The improvement of cognitive function is associated with restoration of gene expression involved in energy metabolism in the brain. Our study suggests that voluntary physical exercise is beneficial for metabolic syndrome-induced peripheral as well as cognitive dysfunction and can be recommended as therapeutic intervention for metabolic syndrome and associated diseases.

BACKGROUND AND AIMS Patients with inflammatory bowel disease (IBD), Crohn’s disease (CD), and ulcerative colitis (UC) have been shown to be at up to a 40% increased risk of developing Parkinson’s disease (PD), a progressive neurodegenerative disorder. Even though a genetic link between IBD and PD was established through shared causal mutations in the LRRK2 gene, it cannot fully explain the observed comorbidity. The goal of this study was to further explore the genetic overlap between these two diseases. METHODS The polygenic risk scores (PRS), representing estimated genetic determinants for IBD, CD, UC, and PD from previously reported respective genome-wide association studies, were computed using a linear combination of the estimated effects across multiple disease-associated variants in the Parkinson’s Progression Markers Initiative (PPMI, www.ppmi-info.org/data) cohort consisting of 413 PD cases and 195 healthy controls (HC) of predominantly European ancestry. We applied a generalized linear regression model to determine the relationship between IBD-related PRS and PD status while adjusting for sex, age, ethnicity, and principal components (PC1-5). A gene-set enrichment analysis was then conducted using Enrichr to examine the biological pathways associated with the genes regulated by variants intersecting between PRS-IBD and PRS-PD in various tissues relevant to IBD and PD (whole blood, visceral adipose fat, brain, and skeletal muscles). RESULTS As expected, PRS-PD was significantly elevated in PD patients (odds ratio (OR) 1.76 [95% confidence interval 1.39-2.26], adjusted p=5.34e-06). We also found that PRS-IBD, PRS-CD, and PRS-UC were significantly positively associated with PD case status (OR 1.37 [1.07-1.76], adjusted p=0.01, OR 1.46 [1.15-1.87], adjusted p=0.002, OR 1.36 [1.05-1.76], adjusted p=0.02, respectively, Figure 1). Gene-set enrichment analysis of the intersecting genes between PRS-IBD and PRS-PD across the 4 different relevant tissue types consistently identified the pathways implicating susceptibility to immune-mediated diseases and infections and immune cell differentiation and processing (Figure 2). CONCLUSION These results further support the genetic link between IBD and PD and emphasize the role of immunity, particularly pertaining to the adaptive immune system in the pathogenesis of both diseases. This is in line with the established role of autoimmunity in IBD etiology and is consistent with recent studies implicating the autoimmune system in PD development. Moreover, our findings suggest that PRS-IBD could serve as an early biomarker of PD and help stratify high-risk IBD patients for future PD prevention interventions.

Background Air pollution is a leading cause of global disease burden. Lack of suitable methods for long term measuring exposure level at individual level is crippling environmental epidemiology research of air pollution. Methods We report an integrative system, Bio3Air, for long term measurement of individual level air pollution exposure, currently focusing on ambient particulate matter (PM). The novel system in real-time quantifies individual's outdoor/indoor status, geological location, lung ventilation rate and PM concentration of individual's surrounding environment, and these metrics are subsequently incorporated in calculating PM exposure. Results The system is fully developed and tested in China, USA and Canada, and has been successfully applied in epidemiology study. Bio3Air offers high reliability, sensitivity, reproducibility (>99%) and accuracy. It has high time- and spatial- resolution (≤ 2 min and ≤ 20 m, respectively). Bio3Air achieved 91.89% consistency with “gold-standard” method (membrane collection and off-line analysis). Conclusions Bio3Air represents a substantial methodological advance in environmental health research of air pollution. It captures information relevant in measuring individual's PM exposure (e.g. real-time outdoor/indoor status, location and lung ventilation rate). Such information is typically missed by conventional approaches. Additional features of Bio3Air include easy-to-use, cost-effectiveness and automated data collection, making it a powerful tool facilitating studies of air pollution exposure and health consequences.

BACKGROUND: Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure. METHODS: During October 2016 – October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data (1) respiratory functions, (2) airway microbiome from sputum and (3) ambient PM(2.5) (PM of ≤ 2.5 micron in diameter) – level in ambient air. We investigated the impact of PM(2.5) on airway microbiome as well as the link between airway microbiome and respiratory functions using mix linear regression models. RESULTS: The respiratory function of our primary interest includes forced vital capacity (FVC) and forced expiratory volume in 1st second (FEV(1)). FEV(1)/FVC, an important respiratory function trait and key diagnosis criterion of COPD, was significantly associated with airway bacteria load (p = 0.0038); and FEV(1) was associated with airway microbiome profile (p = 0.013). Further, airway microbiome was significantly influenced by PM(2.5) exposure (p = 4.48E-11). CONCLUSIONS: To our knowledge, for the first time, we demonstrated the impact of PM(2.5) on airway microbiome, and reported the link between airway microbiome and respiratory functions. The results expand our understanding on the scope of PM(2.5) exposure’s influence on human respiratory system, and pointed to novel etiological mechanism of PM(2.5) exposure induced diseases.

Apolipoprotein L1 (APOL1) risk alleles in donor kidneys associate with graft loss but whether recipient risk allele expression impacts kidney transplant outcomes is unclear. To test whether recipient APOL1 allelic variants independently correlate with transplant outcomes, we analyzed genome-wide SNP genotyping data of donors and recipients from two kidney transplant cohorts, Genomics of Chronic Allograft Rejection (GOCAR) and Clinical Trials in Organ Transplantation 1/17 (CTOT1/17). We estimated genetic ancestry (quantified as proportion of African ancestry or pAFR) by ADMIXTURE and correlated APOL1 genotypes and pAFR with outcomes. In the GOCAR discovery set, we observed that the number of recipient APOL1 G1/G2 alleles (R-nAPOL1) associated with increased risk of death-censored allograft loss (DCAL), independent of genetic ancestry (HR = 2.14; P = 0.006), and within the subgroup of African American and Hispanic (AA/H) recipients (HR = 2.36; P = 0.003). R-nAPOL1 also associated with increased risk of any T cell-mediated rejection (TCMR) event. Analysis of the CTOT cohort validated these associations. Ex vivo studies of peripheral blood mononuclear cells revealed unanticipated high APOL1 expression in activated CD4+/CD8+ T cells and natural killer cells. We detected enriched immune response gene pathways in G1/G2 allele carriers vs. non-carriers among patients on the kidney waitlist and healthy controls. Together our findings highlight a previously unrecognized contribution of recipient APOL1 risk alleles to renal allograft outcomes. This immunomodulatory role has broader implications for immune mediated injury to native kidneys.

Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility., This study integrates Alzheimer’s disease (AD) GWAS data with myeloid cell genomics, and reports that myeloid active enhancers are most burdened by AD risk alleles. The authors also nominate candidate causal regulatory elements, variants and genes that likely modulate the risk for AD.

Water-soluble inorganic (WSI) ions are major components of ambient air PM

Background Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown. Methods We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH. Results We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI. Conclusions Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.

Epidemiological studies have long recognized risky behaviors as potentially modifiable factors for the onset and flares of inflammatory bowel disease (IBD); yet, the underlying mechanisms are largely unknown. Recently, the genetic susceptibilities to cigarette smoking, alcohol and cannabis use [i.e. substance use (SU)] have been characterized by well-powered genome-wide association studies (GWASs). We aimed to assess the impact of genetic determinants of SU on IBD risk. Using Mount Sinai Crohn’s and Colitis Registry (MSCCR) cohort of 1058 IBD cases and 188 healthy controls, we computed the polygenic risk score (PRS) for SU and correlated them with the observed IBD diagnoses, while adjusting for genetic ancestry, PRS for IBD and SU behavior at enrollment. The results were validated in a pediatric cohort with no SU exposure. PRS of alcohol consumption (DrnkWk), smoking cessation and age of smoking initiation, were associated with IBD risk in MSCCR even after adjustment for PRSIBD and actual smoking status. One interquartile range decrease in PRSDrnkWk was significantly associated to higher IBD risk (i.e. inverse association) (with odds ratio = 1.65 and 95% confidence interval: 1.32, 2.06). The association was replicated in a pediatric Crohn’s disease cohort. Colocalization analysis identified a locus on chromosome 16 with polymorphisms in IL27, SULT1A2 and SH2B1, which reached genome-wide statistical significance in GWAS (P

Background Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. Methods During 2015 – 2018, two cohorts of mother-infant dyads (N=678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2 nd (gestational week 24, [GW24]) and 3 rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to a mixture of air pollutants on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. Results Prenatal exposure to PM 2.5 , PM 10 , SO 2 and O 3 significantly reduced fetal biometry at GW24, where SO 2 had the most potent effect. For every 10 ug/m 3 increment increase of daily SO 2 exposure during the 1 st trimester shortened femur length by 2.20 mm (p=6.7E-21) translating to 5.3% reduction from population average. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p=3.5E-5) and 2.1% (p=2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3 rd trimester. Conclusions To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

AimsFibromuscular dysplasia (FMD) is a poorly understood disease that predominantly affects women during middle-life, with features that include stenosis, aneurysm, and dissection of medium-large arteries. Recently, plasma proteomics has emerged as an important means to understand cardiovascular diseases. Our objectives were: (i) to characterize plasma proteins and determine if any exhibit differential abundance in FMD subjects vs. matched healthy controls and (ii) to leverage these protein data to conduct systems analyses to provide biologic insights on FMD, and explore if this could be developed into a blood-based FMD test.Methods and resultsFemales with ‘multifocal’ FMD and matched healthy controls underwent clinical phenotyping, dermal biopsy, and blood draw. Using dual-capture proximity extension assay and nuclear magnetic resonance-spectroscopy, we evaluated plasma levels of 981 proteins and 31 lipid sub-classes, respectively. In a discovery cohort (Ncases = 90, Ncontrols = 100), we identified 105 proteins and 16 lipid sub-classes (predominantly triglycerides and fatty acids) with differential plasma abundance in FMD cases vs. controls. In an independent cohort (Ncases = 23, Ncontrols = 28), we successfully validated 37 plasma proteins and 10 lipid sub-classes with differential abundance. Among these, 5/37 proteins exhibited genetic control and Bayesian analyses identified 3 of these as potential upstream drivers of FMD. In a 3rd cohort (Ncases = 506, Ncontrols = 876) the genetic locus of one of these upstream disease drivers, CD2-associated protein (CD2AP), was independently validated as being associated with risk of having FMD (odds ratios = 1.36; P = 0.0003). Immune-fluorescence staining identified that CD2AP is expressed by the endothelium of medium-large arteries. Finally, machine learning trained on the discovery cohort was used to develop a test for FMD. When independently applied to the validation cohort, the test showed a c-statistic of 0.73 and sensitivity of 78.3%.ConclusionFMD exhibits a plasma proteogenomic and lipid signature that includes potential causative disease drivers, and which holds promise for developing a blood-based test for this disease.

Additional file 1: Table S1. A summary of genotyping and imputation platforms utilized to generate the final study data set. Table S2. Description of previously published genome-wide association studies (GWAS) in European populations that were used in polygenic risk score analyses. Table S3. Number of variants used to derive various polygenic risk scores for different traits and diseases. Table S9. Number of expression quantitative trait loci controlled by HIV-specific loci in CD14+ monocytes from Fairfax et al. [51]. Fig. S1. Fraction of expression quantitative trait loci among the HIV-specific loci (see the Methods section for details) compared to all other loci. HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides; SNP, single nucleotide polymorphism. CD14, CD14+ monocytes at baseline; INF, activated CD14+ monocytes following induction with interferon-γ; LPS2, activated CD14+ monocytes following a 2-h induction with lipopolysaccharide; LPS24, activated CD14+ monocytes following a 24-h induction with lipopolysaccharide. SNP, single nucleotide polymorphism.

Major depressive disorder (MDD) affects ~20% of the world population and is characterized by strong sexual dimorphism with females being 2–3 times more likely to develop this disorder. Previously, we demonstrated that a combination therapy with dihydrocaffeic acid (DHCA) and malvidin-glucoside (Mal-gluc) to synergistically target peripheral inflammation and stress-induced synaptic maladaptation in the brain was effective in alleviating chronic social defeat stress (CSDS)-induced depression-like phenotype in male mice. Here, we test the combination therapy in a female CSDS model for depression and compared sex-specific responses to stress in the periphery and the central nervous system. Similar to male mice, the combination treatment is also effective in promoting resilience against the CSDS-induced depression-like behavior in female mice. However, there are sex-specific differences in peripheral immune responses and differential gene regulation in the prefrontal cortex to chronic stress and to the treatment. These data indicate that while therapeutic approaches to combat stress-related disorders may be effective in both sexes, the mechanisms underlying these effects differ, emphasizing the need for inclusion of both sexes in preclinical studies using animal models.

The development of a given botanical preparation for eventual clinical application requires extensive, detailed characterizations of the chemical composition, as well as the biological availability, biological activity, and safety profiles of the botanical. These issues are typically addressed using diverse experimental protocols and model systems. Based on this consideration, in this study we established a comprehensive database and analysis framework for the collection, collation, and integrative analysis of diverse, multiscale data sets. Using this framework, we conducted an integrative analysis of heterogeneous data from in vivo and in vitro investigation of a complex bioactive dietary polyphenol-rich preparation (BDPP) and built an integrated network linking data sets generated from this multitude of diverse experimental paradigms. We established a comprehensive database and analysis framework as well as a systematic and logical means to catalogue and collate the diverse array of information gathered, which is securely stored and added to in a standardized manner to enable fast query. We demonstrated the utility of the database in (1) a statistical ranking scheme to prioritize response to treatments and (2) in depth reconstruction of functionality studies. By examination of these data sets, the system allows analytical querying of heterogeneous data and the access of information related to interactions, mechanism of actions, functions, etc., which ultimately provide a global overview of complex biological responses. Collectively, we present an integrative analysis framework that leads to novel insights on the biological activities of a complex botanical such as BDPP that is based on data-driven characterizations of interactions between BDPP-derived phenolic metabolites and their mechanisms of action, as well as synergism and/or potential cancellation of biological functions. Out integrative analytical approach provides novel means for a systematic integrative analysis of heterogeneous data types in the development of complex botanicals such as polyphenols for eventual clinical and translational applications.

Genome-wide association studies (GWAS) have identified more than thirty loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown thus impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS signals with myeloid epigenomic and transcriptomic datasets using novel analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We nominate candidate AD risk enhancers and identify their target causal genes (including AP4E1, AP4M1, APBB3, BIN1, CD2AP, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, SPPL2A, TP53INP1, ZKSCAN1, and ZYX) in sixteen loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify disease susceptibility by regulating causal gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it experimentally in human induced pluripotent stem cell (hiPSC)-derived microglia. Combined, these results strongly implicate dysfunction of the myeloid endolysosomal system in the etiology of AD.

Dietary polyphenols promote memory in models of sleep deprivation (SD), stress, and neurodegeneration. The biological properties of dietary polyphenols greatly depend upon the bioavailability of their phenolic metabolites derivatives, which are modulated by gut microbiota. We recently demonstrated that supplementation with grape-derived bioactive dietary polyphenol preparation (BDPP) improves SD-induced cognitive impairment. This study examined the role of the gut microbiota in the ability of BDPP to prevent memory impairment in response to SD. C57BL6/J mice, treated with antibiotics mix (ABX) or BDPP or both, were sleep-deprived at the end of a fear conditioning training session and fear memory was assessed the next day. Gut microbiota composition was analyzed in fecal samples and BDPP-driven phenolic acid metabolites extraction was measured in plasma. We report that the beneficial effect of BDPP on memory in SD is attenuated by ABX-induced dysbiosis. We identified specific communities of fecal microbiota that are associated with the bioavailability of BDPP-derived phenolic acids, which in turn, are associated with memory promotion. These results suggest the gut microbiota composition significantly affects the bioavailability of phenolic acids that drive the dietary polyphenols’ cognitive resilience property. Our findings provide a preclinical model with which to test the causal association of gut microbiota-polyphenols, with the ultimate goal of potential developing dietary polyphenols for the prevention/treatment of cognitive impairment.

Background Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. Methods During 2015–2018, two cohorts of mother-infant dyads (N = 678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2nd (gestational week 24, [GW24]) and 3rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to air pollutant mixture on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. Results Prenatal exposure to PM2.5, PM10, SO2 and O3 significantly reduced fetal biometry at GW24, where SO2 had the most potent effect. For every 10 μg/m3 increment increase of daily SO2 exposure during the 1st trimester shortened femur length by 2.20 mm (p = 6.7E-21) translating to 5.3% reduction from the average of the study cohort. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p = 3.5E-5) and 2.1% (p = 2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3rd trimester. Conclusions To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

The associations between diseases/traits and copy number variants (CNVs) have not been systematically investigated in genome-wide association studies (GWASs), primarily due to a lack of robust and accurate tools for CNV genotyping. Herein, we propose a novel ensemble learning framework, ensembleCNV, to detect and genotype CNVs using single nucleotide polymorphism (SNP) array data. EnsembleCNV a) identifies and eliminates batch effects at raw data level; b) assembles individual CNV calls into CNV regions (CNVRs) from multiple existing callers with complementary strengths by a heuristic algorithm; c) re-genotypes each CNVR with local likelihood model adjusted by global information across multiple CNVRs; d) refines CNVR boundaries by local correlation structure in copy number intensities; e) provides direct CNV genotyping accompanied with confidence score, directly accessible for downstream quality control and association analysis. Benchmarked on two large datasets, ensembleCNV outperformed competing methods and achieved a high call rate (93.3%) and reproducibility (98.6%), while concurrently achieving high sensitivity by capturing 85% of common CNVs documented in the 1000 Genomes Project. Given this CNV call rate and accuracy, which are comparable to SNP genotyping, we suggest ensembleCNV holds significant promise for performing genome-wide CNV association studies and investigating how CNVs predispose to human diseases.

Smoking is a major cause of respiratory conditions. To date, the genetic pleiotropy between smoking behavior and lung function/chronic obstructive pulmonary disease (COPD) have not been systematically explored. We leverage large data sets of smoking behavior, lung function and COPD, and addressed two questions, (1) whether the genetic predisposition of nicotine dependence influence COPD risk and lung function; and (2) the genetic pleiotropy follow causal or independent model. We found the genetic predisposition of nicotine dependence was associated with COPD risk, even after adjusting for smoking behavior, indicating genetic pleiotropy and independent model. Two known nicotine dependent loci (15q25.1 and 19q13.2) were associated with smoking adjusted lung function, and 15q25.1 reached genome-wide significance. At various suggestive p-value thresholds, the smoking adjusted lung function traits share association signals with cigarettes per day and former smoking, substantially greater than random chance. Empirical data showed the genetic pleiotropy between nicotine dependence and COPD or lung function. The basis of pleiotropic effect is rather complex, attributable to a large number of genetic variants, and many variants functions through independent model, where the pleiotropic variants directly affect lung function, not mediated by influencing subjects’ smoking behavior.

GWAS identified variants associated with birth weight (BW), childhood obesity (CO) and childhood BMI (CBMI), and placenta is a critical organ for fetal development and postnatal health. We examined the role of placental transcriptome and eQTLs in mediating the genetic causes for BW, CO and CBMI, and applied integrative analysis (Colocalization and MetaXcan). GWAS loci associated with BW, CO, and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs of adult tissues, only placental eQTLs contribute significantly to both anthropometry outcomes at birth (BW) and childhood phenotypes (CO/CBMI). Eight, six and one transcripts colocalized with BW, CO and CBMI risk loci, respectively. Our study reveals that placental transcription in utero likely plays a key role in determining postnatal body size, and as such may hold new possibilities for therapeutic interventions to prevent childhood obesity., Author summary Genetic studies (e.g GWAS) revealed substantial heritability on birth weight (BW), childhood obesity (CO) and childhood body mass index (CBMI), however, the etiological mechanisms and relevant tissue(s) underlying these traits/conditions are not clear. We incorporated the data from largest GWASes to date and placenta expressional quantitative trait loci (eQTL) that have been newly published, and showed the variants associated with BW, CO and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs in 7 adult tissues such as adipose and liver, only eQTLs in the placenta were found to contribute significantly not only to anthropometry outcomes at birth (BW) but also to childhood phenotypes (CO/CBMI). Further, we employed COLOC and MetaXcan analyses and identified placenta transcripts potential mediate the genetic effect of BW/CO/CBMI GWAS loci. In summary, our study strongly supports a key role for the placenta in determining BW, CO and CMBI at the molecular level, and pinpointed genes whose expression levels in placenta potentially influences BW and CO risk.

Background Increasing number of eQTL (Expression Quantitative Trait Loci) datasets facilitate genetics and systems biology research. Meta-analysis tools are in need to jointly analyze datasets of same or similar issue types to improve statistical power especially in trans-eQTL mapping. Meta-analysis framework is also necessary for ChrX eQTL discovery. Results We developed a novel tool, meta-eqtl, for fast eQTL meta-analysis of arbitrary sample size and arbitrary number of datasets. Further, this tool accommodates versatile modeling, eg. non-parametric model and mixed effect models. In addition, meta-eqtl readily handles calculation of chrX eQTLs. Conclusions We demonstrated and validated meta-eqtl as fast and comprehensive tool to meta-analyze multiple datasets and ChrX eQTL discovery. Meta-eqtl is a set of command line utilities written in R, with some computationally intensive parts written in C. The software runs on Linux platforms and is designed to intelligently adapt to high performance computing (HPC) cluster. We applied the novel tool to liver and adipose tissue data, and revealed eSNPs underlying diabetes GWAS loci.