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Cardiovascular risk models remain incomplete. Small-molecule metabolites may reflect underlying disease and, as such, serve as novel biomarkers of cardiovascular risk. We studied 2,023 consecutive patients undergoing cardiac catheterization. Mass spectrometry profiling of 69 metabolites and lipid assessments were performed in fasting plasma. Principal component analysis reduced metabolites to a smaller number of uncorrelated factors. Independent relationships between factors and time-to-clinical events were assessed using Cox modeling. Clinical and metabolomic models were compared using log-likelihood and reclassification analyses. At median follow-up of 3.1 years, there were 232 deaths and 294 death/myocardial infarction (MI) events. Five of 13 metabolite factors were independently associated with mortality: factor 1 (medium-chain acylcarnitines: hazard ratio [HR] 1.12 [95% CI, 1.04-1.21], P = .005), factor 2 (short-chain dicarboxylacylcarnitines: HR 1.17 [1.05-1.31], P = .005), factor 3 (long-chain dicarboxylacylcarnitines: HR 1.14 [1.05-1.25], P = .002); factor 6 (branched-chain amino acids: HR 0.86 [0.75-0.99], P = .03), and factor 12 (fatty acids: HR 1.19 [1.06-1.35], P = .004). Three factors independently predicted death/MI: factor 2 (HR 1.11 [1.01-1.23], P = .04), factor 3 (HR 1.13 [1.04-1.22], P = .005), and factor 12 (HR 1.18 [1.05-1.32], P = .004). For mortality, 27% of intermediate-risk patients were correctly reclassified (net reclassification improvement 8.8%, integrated discrimination index 0.017); for death/MI model, 11% were correctly reclassified (net reclassification improvement 3.9%, integrated discrimination index 0.012). Metabolic profiles predict cardiovascular events independently of standard predictors.

Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

Genetically tractable animal models provide needed strategies to resolve the biological basis of drug addiction. Intravenous self-administration (IVSA) is the gold standard for modeling psychostimulant and opioid addiction in animals, but technical limitations have precluded the widespread use of IVSA in mice. Here, we describe IVSA paradigms for mice that capture the multi-stage nature of the disorder and permit predictive modeling. In these paradigms, C57BL/6J mice with long-standing indwelling jugular catheters engaged in cocaine- or remifentanil-associated lever responding that was fixed ratio-dependent, dose-dependent, extinguished by withholding the drug, and reinstated by the presentation of drug-paired cues. The application of multivariate analysis suggested that drug taking in both paradigms was a function of two latent variables we termed incentive motivation and discriminative control. Machine learning revealed that vulnerability to drug seeking and relapse were predicted by a mouse’s a priori response to novelty, sensitivity to drug-induced locomotion, and drug-taking behavior. The application of these behavioral and statistical-analysis approaches to genetically-engineered mice will facilitate the identification of neural circuits driving addiction susceptibility and relapse and focused therapeutic development.

Background Air pollution is a major risk factor for cardiovascular disease, of which ozone is a major contributor. Several studies have found associations between ozone and cardiovascular morbidity, but the results have been inconclusive. We investigated associations between ozone and changes across biological pathways associated with cardiovascular disease. Methods Using a panel study design, 13 participants with coronary artery disease were assessed for markers of systemic inflammation, heart rate variability and repolarization, lipids, blood pressure, and endothelial function. Daily measurements of ozone and particulate matter (PM 2.5 ) were obtained from central monitoring stations. Single (ozone) and two-pollutant (ozone and PM 2.5 ) models were used to assess percent changes in measurements per interquartile ranges of pollutants. Results Per interquartile increase in ozone, changes in tissue plasminogen factor (6.6%, 95% confidence intervals (CI) = 0.4, 13.2), plasminogen activator inhibitor-1 (40.5%, 95% CI = 8.7, 81.6), neutrophils (8.7% 95% CI = 1.5, 16.4), monocytes (10.2%, 95% CI = 1.0, 20.1), interleukin-6 (15.9%, 95% CI = 3.6, 29.6), large-artery elasticity index (−19.5%, 95% CI = −34.0, −1.7), and the baseline diameter of the brachial artery (−2.5%, 95% CI = −5.0, 0.1) were observed. These associations were robust in the two-pollutant model. Conclusions We observed alterations across several pathways associated with cardiovascular disease in 13 coronary artery disease patients following ozone exposures, independent of PM 2.5 . The results support the biological plausibility of ozone-induced cardiovascular effects. The effects were found at concentrations below the EPA National Ambient Air Quality Standards for both ozone and PM 2.5 .

Rheumatoid arthritis (RA) T cells drive autoimmune features via metabolic reprogramming that reduces oxidative metabolism. Exercise training improves cardiorespiratory fitness (i.e., systemic oxidative metabolism) and thus may impact RA T cell oxidative metabolic function. In this pilot study of RA participants, we took advantage of heterogeneous responses to a high-intensity interval training (HIIT) exercise program to identify relationships between improvements in cardiorespiratory fitness with changes in peripheral T cell and skeletal muscle oxidative metabolism. In 12 previously sedentary persons with seropositive RA, maximal cardiopulmonary exercise tests, fasting blood, and vastus lateralis biopsies were obtained before and after 10 weeks of HIIT. Following HIIT, improvements in RA cardiorespiratory fitness were associated with changes in RA CD4 + T cell basal and maximal respiration and skeletal muscle carnitine acetyltransferase (CrAT) enzyme activity. Further, changes in CD4 + T cell respiration were associated with changes in naïve CD4 + CCR7 + CD45RA + T cells, muscle CrAT, and muscle medium-chain acylcarnitines and fat oxidation gene expression profiles. In summary, modulation of cardiorespiratory fitness and molecular markers of skeletal muscle oxidative metabolism during exercise training paralleled changes in T cell metabolism. Exercise training that improves RA cardiorespiratory fitness may therefore be valuable in managing pathologically related immune and muscle dysfunction. Trial registration: ClinicalTrials.gov, NCT02528344. Registered on 19 August 2015.

Background While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Results Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Conclusions Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Background Veterans of the 1990–1991 Gulf War have experienced excess health problems, most prominently the multisymptom condition Gulf War illness (GWI). The Department of Veterans Affairs (VA) Cooperative Studies Program #2006 “Genomics of Gulf War Illness in Veterans” project was established to address important questions concerning pathobiological and genetic aspects of GWI. The current study evaluated patterns of chronic ill health/GWI in the VA Million Veteran Program (MVP) Gulf War veteran cohort in relation to wartime exposures and key features of deployment, 27–30 years after Gulf War service. Methods MVP participants who served in the 1990–1991 Gulf War completed the MVP Gulf War Era Survey in 2018–2020. Survey responses provided detailed information on veterans’ health, Gulf War exposures, and deployment time periods and locations. Analyses determined associations of three defined GWI/ill health outcomes with Gulf War deployment characteristics and exposures. Results The final cohort included 14,103 veterans; demographic and military characteristics of the sample were similar to the full population of U.S. 1990–1991 Gulf War veterans. Overall, a substantial number of veterans experienced chronic ill health, as indicated by three defined outcomes: 49% reported their health as fair or poor, 31% met Centers for Disease Control and Prevention criteria for severe GWI, and 20% had been diagnosed with GWI by a healthcare provider. Health outcomes varied consistently with veterans’ demographic and military characteristics, and with exposures during deployment. All outcomes were most prevalent among youngest veterans (< 50 years), Army and Marine Corps veterans, enlisted personnel (vs. officers), veterans located in Iraq and/or Kuwait for at least 7 days, and veterans who remained in theater from January/February 1991 through the summer of 1991. In multivariable models, GWI/ill health was most strongly associated with three exposures: chemical/biological warfare agents, taking pyridostigmine bromide pills, and use of skin pesticides. Conclusions Results from this large cohort indicate that GWI/chronic ill health continues to affect a large proportion of Gulf War veterans in patterns associated with 1990-1991 Gulf War deployment and exposures. Findings establish a foundation for comprehensive evaluation of genetic factors and deployment exposures in relation to GWI risk and pathobiology.

The rs6265 (Val66Met) single-nucleotide polymorphism in the BDNF gene has been related to a number of endophenotypes that have in turn been shown to confer risk for atherosclerotic cardiovascular disease (CVD). To date, however, very few studies have examined the association of the Val66Met single-nucleotide polymorphism with CVD clinical outcomes. In a cohort of 5,510 Caucasian patients enrolled in the CATHeterization GENetics (CATHGEN) study at Duke University Hospital between 2001 and 2011, we determined the severity of coronary artery disease (CAD) and CVD event incidence through up to 11.8years of follow-up. We examined the association of Val66Met genotype with time-to-death or myocardial infarction, adjusting for age, sex, CAD risk variables, and CAD severity measures. The Val/Val genotype was associated with a higher risk than Met carriers for clinical CVD events (P=.034, hazard ratio 1.12, 95% CI 1.01-1.24). In addition, compared with Met carriers, individuals with the Val/Val genotype had a greater odds of having more diseased vessels (odds ratio 1.17, 95% CI 1.06-1.30, P=.002), and lower left ventricular ejection fraction (β=−0.72, 95% CI, −1.42 to −0.02, P=.044). The Val/Val genotype was associated with greater severity of CAD and incidence of CVD-related clinical events in a patient sample. If these findings are confirmed in further research, intervention studies in clinical groups with the Val/Val genotype could be undertaken to prevent disease and improve prognosis.

Background Air pollution-induced changes in cardiac electrophysiological properties could be a pathway linking air pollution and cardiovascular events. The evidence of air pollution effects on the cardiac conduction system is incomplete yet. We investigated short-term effects of particulate matter ≤ 2.5 μm in aerodynamic diameter (PM 2.5 ) and ozone (O 3 ) on cardiac electrical impulse propagation and repolarization as recorded in surface electrocardiograms (ECG). Methods We analyzed repeated 12-lead ECG measurements performed on 5,332 patients between 2001 and 2012. The participants came from the Duke CATHGEN Study who underwent cardiac catheterization and resided in North Carolina, United States (NC, U.S.). Daily concentrations of PM 2.5 and O 3 at each participant’s home address were predicted with a hybrid air quality exposure model. We used generalized additive mixed models to investigate the associations of PM 2.5 and O 3 with the PR interval, QRS interval, heart rate-corrected QT interval (QTc), and heart rate (HR). The temporal lag structures of the associations were examined using distributed-lag models. Results Elevated PM 2.5 and O 3 were associated with four-day lagged lengthening of the PR and QRS intervals, and with one-day lagged increases in HR. We observed immediate effects on the lengthening of the QTc interval for both PM 2.5 and O 3 , as well as delayed effects for PM 2.5 (lagged by 3 – 4 days). The associations of PM 2.5 and O 3 with the PR interval and the association of O 3 with the QRS interval persisted until up to seven days after exposure. Conclusions In patients undergoing cardiac catheterization, short-term exposure to air pollution was associated with increased HR and delays in atrioventricular conduction, ventricular depolarization and repolarization.

Background The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts ( N -range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). Results Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen’s d  < 0.259, p  < 7.80 × 10 −4 ). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p  < 0.05) confounding in the GWAS statistics. Conclusions This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.