Metabolomic Profiling of the Effects of Dapagliflozin in Heart Failure With Reduced Ejection Fraction: DEFINE-HF.

BACKGROUND: Sodium-glucose cotransporter-2 inhibitors are foundational therapy in patients with heart failure with reduced ejection fraction (HFrEF), but underlying mechanisms of benefit are not well defined. We sought to investigate the relationships between sodium-glucose cotransporter-2 inhibitor treatment, changes in metabolic pathways, and outcomes using targeted metabolomics. METHODS: DEFINE-HF (Dapagliflozin Effects on Biomarkers, Symptoms and Functional Status in Patients With HF With Reduced Ejection Fraction) was a placebo-controlled trial of dapagliflozin in HFrEF. We performed targeted mass spectrometry profiling of 63 metabolites (45 acylcarnitines [markers of fatty acid oxidation], 15 amino acids, and 3 conventional metabolites) in plasma samples at randomization and 12 weeks. Using mixed models, we identified principal components analysis-defined metabolite clusters that changed differentially with treatment and examined the relationship between change in metabolite clusters and change in Kansas City Cardiomyopathy Questionnaire scores and NT-proBNP (N-terminal probrain natriuretic peptide). Models were adjusted for relevant clinical covariates and nominal P<0.05 with false discovery rate-adjusted P<0.10 was used to determine statistical significance. RESULTS: Among the 234 DEFINE-HF participants with targeted metabolomic data, the mean age was 62.0±11.1 years, 25% were women, 38% were Black, and mean ejection fraction was 27±8%. Dapagliflozin increased ketone-related and short-chain acylcarnitine as well as medium-chain acylcarnitine principal components analysis-defined metabolite clusters compared with placebo (nominal P=0.01, false discovery rate-adjusted P=0.08 for both clusters). However, ketosis (ß-hydroxybutyrate levels >500 µmol/L) was achieved infrequently (3 [2.5%] in dapagliflozin arm versus 1 [0.9%] in placebo arm) and supraphysiologic levels were not observed. Increases in long-chain acylcarnitine, long-chain dicarboxylacylcarnitine, and aromatic amino acid metabolite clusters were associated with decreases in Kansas City Cardiomyopathy Questionnaire scores (ie, worse quality of life) and increases in NT-proBNP levels, without interaction by treatment group. CONCLUSIONS: In this study of targeted metabolomics in a placebo-controlled trial of sodium-glucose cotransporter-2 inhibitors in HFrEF, we observed effects of dapagliflozin on key metabolic pathways, supporting a role for altered ketone and fatty acid biology with sodium-glucose cotransporter-2 inhibitors in patients with HFrEF. Only physiologic levels of ketosis were observed. In addition, we identified several metabolic biomarkers associated with adverse HFrEF outcomes. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02653482.

A Randomized Controlled Trial of Mobile Health Intervention in Patients With Heart Failure and Diabetes.

BACKGROUND: Mobile health (mHealth) platforms can affect health behaviors but have not been rigorously tested in randomized trials. OBJECTIVES: We sought to evaluate the effectiveness of a pragmatic mHealth intervention in patients with heart failure (HF) and diabetes (DM). METHODS: We conducted a multicenter randomized trial in 187 patients with both HF and DM to assess an mHealth intervention to improve physical activity and medication adherence compared to usual care. The primary endpoint was change in mean daily step count from baseline through 3 months. Other outcomes included medication adherence, health-related quality of life and metabolomic profiling. RESULTS: The mHealth group had an increase in daily step count of 151 steps/day at 3 months, whereas the usual-care group had a decline of 162 steps/day (least squares mean between-group difference = 313 steps/day; 95% CI: 8 619; P = 0.044). Medication adherence, measured using the Voils Adherence Questionnaire, did not change from baseline to 3 months (LS-mean change -0.08 in mHealth vs -0.15 in usual care; P = 0.47). The mHealth group had an improvement in Kansas City Cardiomyopathy Questionnaire Overall Summary Score compared to the usual-care group (LS-mean difference = 5.5 points, 95% CI: 1.4, 9.6; P = 0.009). Thirteen metabolites, primarily medium- and long-chain acylcarnitines, changed differently between treatment groups from baseline to 3 months (P < 0.05). CONCLUSIONS: In patients with HF and DM, a 3-month mHealth intervention significantly improved daily physical activity, health-related quality of life and metabolomic markers of cardiovascular health but not medication adherence. CONDENSED ABSTRACT: Heart failure (HF) and diabetes (DM) have overlapping biological and behavioral risk factors. We conducted a multicenter randomized, clinical trial in 187 patients with both HF (regardless of ejection fraction) and DM to assess whether an mHealth intervention could improve physical activity and medication adherence. The mHealth group had an increase in mean daily step count and quality of life but not in medication adherence. Medium- and long-chain acylcarnitines changed differently in treatment groups from baseline to 3 months (P < 0.05). These data have important implications for designing effective lifestyle interventions in HF and DM.

Insulin Growth Factor Phenotypes in Heart Failure With Preserved Ejection Fraction, an INSPIRE Registry and CATHGEN Study.

BACKGROUND: The insulin-like growth factor (IGF) axis emerged as an important pathway in heart failure with preserved ejection (HFpEF). We aimed to identify IGF phenotypes associated with HFpEF in the context of high-dimensional proteomic profiling. METHODS: From the INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry), we identified 96 patients with HFpEF and matched controls. We performed targeted proteomics, including IGF-1,2, IGF binding proteins (IGFBP) 1-7 and 111 other proteins (EMD Millipore and ELISA). We used partial least square discriminant analysis (PLS-DA) to identify a set of proteins associated with prevalent HFpEF, pulmonary hypertension and 5-year all-cause mortality. K-mean clustering was used to identify IGF phenotypes. RESULTS: Patients with HFpEF had a high prevalence of systemic hypertension (95%) and coronary artery disease (74%). Using PLS-DA, we identified a set of biomarkers, including IGF1,2 and IGFBP 1,2,7, that provided a strong discrimination of HFpEF, pulmonary hypertension and mortality with an area under the curve of 0.91, 0.77 and 0.83, respectively. Using K mean clustering, we identified 3 IGF phenotypes that were independently associated with all-cause 5-year mortality after adjustment for age, NT-proBNP and kidney disease (P = 0.004). Multivariable analysis validated the prognostic value of IGFBP-1 and 2 in the CATHeterization GENetics (CATHGEN) biorepository. CONCLUSION: IGF phenotypes were associated with pulmonary hypertension and mortality in HFpEF.

Multi-dimensional characterization of prediabetes in the Project Baseline Health Study.

BACKGROUND: We examined multi-dimensional clinical and laboratory data in participants with normoglycemia, prediabetes, and diabetes to identify characteristics of prediabetes and predictors of progression from prediabetes to diabetes or reversion to no diabetes. METHODS: The Project Baseline Health Study (PBHS) is a multi-site prospective cohort study of 2502 adults that conducted deep clinical phenotyping through imaging, laboratory tests, clinical assessments, medical history, personal devices, and surveys. Participants were classified by diabetes status (diabetes [DM], prediabetes [preDM], or no diabetes [noDM]) at each visit based on glucose, HbA1c, medications, and self-report. Principal component analysis (PCA) was performed to create factors that were compared across groups cross-sectionally using linear models. Logistic regression was used to identify factors associated with progression from preDM to DM and for reversion from preDM to noDM. RESULTS: At enrollment, 1605 participants had noDM; 544 had preDM; and 352 had DM. Over 4 years of follow-up, 52 participants with preDM developed DM and 153 participants reverted to noDM. PCA identified 33 factors composed of clusters of clinical variables; these were tested along with eight individual variables identified a priori as being of interest. Six PCA factors and six a priori variables significantly differed between noDM and both preDM and DM after false discovery rate adjustment for multiple comparisons (q < 0.05). Of these, two factors (one comprising glucose measures and one of anthropometry and physical function) demonstrated monotonic/graded relationships across the groups, as did three a priori variables: ASCVD risk, coronary artery calcium, and triglycerides (q < 10-21 for all). Four factors were significantly different between preDM and noDM, but concordant or similar between DM and preDM: red blood cell indices (q = 8 × 10-10), lung function (q = 2 × 10-6), risks of chronic diseases (q = 7 × 10-4), and cardiac function (q = 0.001), along with a priori variables of diastolic function (q = 1 × 10-10), sleep efficiency (q = 9 × 10-6) and sleep time (q = 6 × 10-5). Two factors were associated with progression from prediabetes to DM: anthropometry and physical function (OR [95% CI]: 0.6 [0.5, 0.9], q = 0.04), and heart failure and c-reactive protein (OR [95% CI]: 1.4 [1.1, 1.7], q = 0.02). The anthropometry and physical function factor was also associated with reversion from prediabetes to noDM: (OR [95% CI]: 1.9 [1.4, 2.7], q = 0.02) along with a factor of white blood cell indices (OR [95% CI]: 0.6 [0.4, 0.8], q = 0.02), and the a priori variables ASCVD risk score (OR [95% CI]: 0.7 [0.6, 0.9] for each 0.1 increase in ASCVD score, q = 0.02) and triglycerides (OR [95% CI]: 0.9 [0.8, 1.0] for each 25 mg/dl increase, q = 0.05). CONCLUSIONS: PBHS participants with preDM demonstrated pathophysiologic changes in cardiac, pulmonary, and hematology measures and declines in physical function and sleep measures that precede DM; some changes predicted an increased risk of progression to DM. A factor with measures of anthropometry and physical function was the most important factor associated with progression to DM and reversion to noDM. Future studies may determine whether these changes elucidate pathways of progression to DM and related complications and whether they can be used to identify individuals at higher risk of progression to DM for targeted preventive interventions. Trial registration ClinicalTrials.gov NCT03154346.

Preliminary evidence of effects of potassium chloride on a metabolomic path to diabetes and cardiovascular disease.

INTRODUCTION: Low potassium intake can affect cardiovascular disease (CVD) risk and cardiometabolic risk factors. OBJECTIVE: We hypothesize that potassium chloride (KCl) supplementation can improve cardiovascular risk metabolomic profile. METHODS: In this secondary analysis of a pilot randomized clinical trial (RCT) of 26 participants with prediabetes randomized to KCl or placebo, we performed targeted mass-spectrometry-based metabolomic profiling on baseline and 12-week (end-of-study) plasma samples. Principal component analysis (PCA) was used to reduce the many correlated metabolites into fewer, independent factors that retain most of the information in the original data. RESULTS: Those taking KCl had significant reductions (corresponding to lower cardiovascular risk) in the branched-chain amino acids (BCAA) factor (P = 0.004) and in valine levels (P = 0.02); and non-significant reductions in short-chain acylcarnitines (SCA) factor (P = 0.11). CONCLUSIONS: KCl supplementation may improve circulating BCAA levels, which may reflect improvements in overall cardiometabolic risk profile. CLINICAL TRIALS REGISTRY: Clinicaltrials.gov identifier: NCT02236598; https://clinicaltrials.gov/ct2/show/NCT02236598.

Associations of osteopontin and NT-proBNP with circulating miRNA levels in acute coronary syndrome.

The genomic regulatory networks underlying the pathogenesis of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) are incompletely understood. As intermediate traits, protein biomarkers report on underlying disease severity and prognosis in NSTE-ACS. We hypothesized that integration of dense microRNA (miRNA) profiling with biomarker measurements would highlight potential regulatory pathways that underlie the relationships between prognostic biomarkers, miRNAs, and cardiovascular phenotypes. We performed miRNA sequencing using whole blood from 186 patients from the TRILOGY-ACS trial. Seven circulating prognostic biomarkers were measured: NH2-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity C-reactive protein, osteopontin (OPN), myeloperoxidase, growth differentiation factor 15, monocyte chemoattractant protein, and neopterin. We tested miRNAs for association with each biomarker with generalized linear models and controlled the false discovery rate at 0.05. Ten miRNAs, including known cardiac-related miRNAs 25-3p and 423-3p, were associated with NT-proBNP levels (min. P = 7.5 × 10-4) and 48 miRNAs, including cardiac-related miRNAs 378a-3p, 20b-5p and 320a, -b, and -d, were associated with OPN levels (min. P = 1.6 × 10-6). NT-proBNP and OPN were also associated with time to cardiovascular death, myocardial infarction (MI), or stroke in the sample. By integrating large-scale miRNA profiling with circulating biomarkers as intermediate traits, we identified associations of known cardiac-related and novel miRNAs with two prognostic biomarkers and identified potential genomic networks regulating these biomarkers. These results, highlighting plausible biological pathways connecting miRNAs with biomarkers and outcomes, may inform future studies seeking to delineate genomic pathways underlying NSTE-ACS outcomes.

Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.

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.

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients.

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Metabolite signature of diabetes remission in individuals with obesity undergoing weight loss interventions.

OBJECTIVE: This observational study investigated metabolomic changes in individuals with type 2 diabetes (T2D) after weight loss. We hypothesized that metabolite changes associated with T2D-relevant phenotypes are signatures of improved health. METHODS: Fasting plasma samples from individuals undergoing bariatric surgery (n = 71 Roux-en-Y gastric bypass [RYGB], n = 22 gastric banding), lifestyle intervention (n = 66), or usual care (n = 14) were profiled for 139 metabolites before and 2 years after weight loss. Principal component analysis grouped correlated metabolites into factors. Association of preintervention metabolites was tested with preintervention clinical features and changes in T2D markers. Association between change in metabolites/metabolite factors and change in T2D remission markers, homeostasis model assessment of ß-cell function, homeostasis model assessment of insulin resistance, and glycated hemoglobin (HbA1c) was assessed. RESULTS: Branched-chain amino acids (BCAAs) were associated with preintervention adiposity. Changes in BCAAs (valine, leucine/isoleucine) and branched-chain ketoacids were positively associated with change in HbA1c (false discovery rate q value ≤ 0.001) that persisted after adjustment for percentage weight change and RYGB (p ≤ 0.02). In analyses stratified by RYGB or other weight loss method, some metabolites showed association with non-RYGB weight loss. CONCLUSIONS: This study confirmed known metabolite associations with obesity/T2D and showed an association of BCAAs with HbA1c change after weight loss, independent of the method or magnitude of weight loss.

Targeted Metabolomic Profiling of Dapagliflozin in Heart Failure With Preserved Ejection Fraction: The PRESERVED-HF Trial.

BACKGROUND: Although sodium glucose co-transporter 2 inhibitors (SGLT2is) improve heart failure (HF)-related symptoms and outcomes in HF with preserved ejection fraction (HFpEF), underlying mechanisms remain unclear. In HF with reduced EF, dapagliflozin altered ketone and fatty acid metabolites vs placebo; however, metabolite signatures of SGLT2is have not been well elucidated in HFpEF. OBJECTIVES: The goal of this study was to assess whether SGLT2i treatment altered systemic metabolic pathways and their relationship to outcomes in HFpEF. METHODS: Targeted profiling of 64 metabolites was performed from 293 participants in PRESERVED-HF (Dapagliflozin in PRESERVED Ejection Fraction Heart Failure), a 12-week, placebo-controlled trial of dapagliflozin. Linear regression assessed changes in metabolite factors defined by principal components analysis (PCA) with dapagliflozin vs placebo. The relationship between changes in metabolite factors with changes in study endpoints was also assessed. RESULTS: The mean age was 70 ± 11 years, 58% were female, and 29% were Black. There were no significant differences in 12 PCA-derived metabolite factors between treatment arms, including metabolites reflecting ketone, fatty acid, or branched-chain amino acid (BCAA) pathways. Combining treatment arms, changes in BCAAs and branched-chain ketoacids were negatively associated with changes in N-terminal pro-B-type natriuretic peptide; changes in medium-/long-chain acylcarnitines were positively associated with changes in N-terminal pro-B-type natriuretic peptide and negatively associated with changes in 6-minute walk test distance; and changes in ketones were negatively associated with changes in weight, without treatment interaction. CONCLUSIONS: Leveraging targeted metabolomics in a placebo-controlled SGLT2i trial of HFpEF, dapagliflozin did not alter systemic metabolic as reflected by circulating metabolites, in contrast with reported effects in HF with reduced ejection fraction. Metabolite biomarkers reflecting BCAA, ketone, and fatty acid metabolism were associated with markers of disease severity, suggesting a role for potential novel treatment targets. (Dapagliflozin in PRESERVED Ejection Fraction Heart Failure [PRESERVED-HF]; NCT03030235).

Accelerated Epigenetic Aging Is Associated With Multiple Cardiometabolic, Hematologic, and Renal Abnormalities: A Project Baseline Health Substudy.

BACKGROUND: Epigenetic clocks estimate chronologic age using methylation levels at specific loci. We tested the hypothesis that accelerated epigenetic aging is associated with abnormal values in a range of clinical, imaging, and laboratory characteristics. METHODS: The Project Baseline Health Study recruited 2502 participants, including 1661 with epigenetic age estimates from the Horvath pan-tissue clock. We classified individuals with extreme values as having epigenetic age acceleration (EAA) or epigenetic age deceleration. A subset of participants with longitudinal methylation profiling was categorized as accelerated versus nonaccelerated. Using principal components analysis, we created phenoclusters using 122 phenotypic variables and compared individuals with EAA versus epigenetic age deceleration, and at one year of follow-up, using logistic regression models adjusted for sex (false discovery rate [Q] <0.10); in secondary exploratory analyses, we tested individual clinical variables. RESULTS: The EAA (n=188) and epigenetic age deceleration (n=195) groups were identified as having EAA estimates ≥5 years or ≤-5 years, respectively. In primary analyses, individuals with EAA had higher values for phenoclusters summarizing lung function and lipids, and lower values for a phenocluster representing physical function. In secondary analyses of individual variables, neutrophils, body mass index, and waist circumference were significantly higher in individuals with EAA (Q<0.10). No phenoclusters were significantly different between participants with accelerated (n=148) versus nonaccelerated (n=112) longitudinal aging. CONCLUSIONS: We report multiple cardiometabolic, hematologic, and physical function features characterizing individuals with EAA. These highlight factors that may mediate the adverse effects of aging and identify potential targets for study of mitigation of these effects. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03154346.

Metabolomic profiling during ex situ normothermic perfusion before heart transplantation defines patterns of substrate utilization and correlates with markers of allograft injury.

BACKGROUND: Cardiac metabolism is altered in heart failure and ischemia-reperfusion injury states. We hypothesized that metabolomic profiling during ex situ normothermic perfusion before heart transplantation (HT) would lend insight into myocardial substrate utilization and report on subclinical and clinical allograft dysfunction risk. METHODS: Metabolomic profiling was performed on serial samples of ex situ normothermic perfusate assaying biomarkers of myocardial injury in lactate and cardiac troponin I (TnI) as well as metabolites (66 acylcarnitines, 15 amino acids, nonesterified fatty acids [NEFA], ketones, and 3-hydroxybutyrate). We tested for change over time in injury biomarkers and metabolites, along with differential changes by recovery strategy (donation after circulatory death [DCD] vs donation after brain death [DBD]). We examined associations between metabolites, injury biomarkers, and primary graft dysfunction (PGD). Analyses were performed using linear mixed models adjusted for recovery strategy, assay batch, donor-predicted heart mass, and time. RESULTS: A total of 176 samples from 92 ex situ perfusion runs were taken from donors with a mean age of 35 (standard deviation 11.3) years and a median total ex situ perfusion time of 234 (interquartile range 84) minutes. Lactate trends over time differed significantly by recovery strategy, while TnI increased during ex situ perfusion regardless of DCD vs DBD status. We found fuel substrates were rapidly depleted during ex situ perfusion, most notably the branched-chain amino acids leucine/isoleucine, as well as ketones, 3-hydroxybutyrate, and NEFA (least squares [LS] mean difference from the first to last time point -1.7 to -4.5, false discovery rate q < 0.001). Several long-chain acylcarnitines (LCAC), including C16, C18, C18:1, C18:2, C18:3, C20:3, and C20:4, increased during the perfusion run (LS mean difference 0.42-0.67, q < 0.001). Many LCACs were strongly associated with lactate and TnI. The change over time of many LCACs was significantly different for DCD vs DBD, suggesting differential trends in fuel substrate utilization by ischemic injury pattern. Changes in leucine/isoleucine, arginine, C12:1-OH/C10:1-DC, and C16-OH/C14-DC were associated with increased odds of moderate-severe PGD. Neither end-of-run nor change in lactate or TnI was associated with PGD. CONCLUSIONS: Metabolomic profiling of ex situ normothermic perfusion solution reveals a pattern of fuel substrate utilization that correlates with subclinical and clinical allograft dysfunction. This study highlights a potential role for interventions focused on fuel substrate modification in allograft conditioning during ex situ perfusion to improve allograft outcomes.

Genetic and epigenetic signatures associated with plasma oxytocin levels in children and adolescents with autism spectrum disorder.

Oxytocin (OT), the brain's most abundant neuropeptide, plays an important role in social salience and motivation. Clinical trials of the efficacy of OT in autism spectrum disorder (ASD) have reported mixed results due in part to ASD's complex etiology. We investigated whether genetic and epigenetic variation contribute to variable endogenous OT levels that modulate sensitivity to OT therapy. To carry out this analysis, we integrated genome-wide profiles of DNA-methylation, transcriptional activity, and genetic variation with plasma OT levels in 290 participants with ASD enrolled in a randomized controlled trial of OT. Our analysis identified genetic variants with novel association with plasma OT, several of which reside in known ASD risk genes. We also show subtle but statistically significant association of plasma OT levels with peripheral transcriptional activity and DNA-methylation profiles across several annotated gene sets. These findings broaden our understanding of the effects of the peripheral oxytocin system and provide novel genetic candidates for future studies to decode the complex etiology of ASD and its interaction with OT signaling and OT-based interventions. LAY SUMMARY: Oxytocin (OT) is an abundant chemical produced by neurons that plays an important role in social interaction and motivation. We investigated whether genetic and epigenetic factors contribute to variable OT levels in the blood. To this, we integrated genetic, gene expression, and non-DNA regulated (epigenetic) signatures with blood OT levels in 290 participants with autism enrolled in an OT clinical trial. We identified genetic association with plasma OT, several of which reside in known autism risk genes. We also show statistically significant association of plasma OT levels with gene expression and epigenetic across several gene pathways. These findings broaden our understanding of the factors that influence OT levels in the blood for future studies to decode the complex presentation of autism and its interaction with OT and OT-based treatment.

The association of accelerated epigenetic age with all-cause mortality in cardiac catheterization patients as mediated by vascular and cardiometabolic outcomes.

BACKGROUND: Epigenetic age is a DNA methylation-based biomarker of aging that is accurate across the lifespan and a range of cell types. The difference between epigenetic age and chronological age, termed age acceleration (AA), is a strong predictor of lifespan and healthspan. The predictive capabilities of AA for all-cause mortality have been evaluated in the general population; however, its utility is less well evaluated in those with chronic conditions. Additionally, the pathophysiologic pathways whereby AA predicts mortality are unclear. We hypothesized that AA predicts mortality in individuals with underlying cardiovascular disease; and the association between AA and mortality is mediated, in part, by vascular and cardiometabolic measures. METHODS: We evaluated 562 participants in an urban, three-county area of central North Carolina from the CATHGEN cohort, all of whom received a cardiac catheterization procedure. We analyzed three AA biomarkers, Horvath epigenetic age acceleration (HAA), phenotypic age acceleration (PhenoAA), and Grim age acceleration (GrimAA), by Cox regression models, to assess whether AAs were associated with all-cause mortality. We also evaluated if these associations were mediated by vascular and cardiometabolic outcomes, including left ventricular ejection fraction (LVEF), blood cholesterol concentrations, angiopoietin-2 (ANG2) protein concentration, peripheral artery disease, coronary artery disease, diabetes, and hypertension. The total effect, direct effect, indirect effect, and percentage mediated were estimated using pathway mediation tests with a regression adjustment approach. RESULTS: PhenoAA (HR = 1.05, P < 0.0001), GrimAA (HR = 1.10, P < 0.0001) and HAA (HR = 1.03, P = 0.01) were all associated with all-cause mortality. The association of mortality and PhenoAA was partially mediated by ANG2, a marker of vascular function (19.8%, P = 0.016), and by diabetes (8.2%, P = 0.043). The GrimAA-mortality association was mediated by ANG2 (12.3%, P = 0.014), and showed weaker evidence for mediation by LVEF (5.3%, P = 0.065). CONCLUSIONS: Epigenetic age acceleration remains strongly predictive of mortality even in individuals already burdened with cardiovascular disease. Mortality associations were mediated by ANG2, which regulates endothelial permeability and angiogenic functions, suggesting that specific vascular pathophysiology may link accelerated epigenetic aging with increased mortality risks.

Prevalence and Phenotypic Burden of Monogenic Arrhythmias Using Integration of Electronic Health Records With Genetics.

BACKGROUND: Inherited primary arrhythmia syndromes and arrhythmogenic cardiomyopathies can lead to sudden cardiac arrest in otherwise healthy individuals. The burden and expression of these diseases in a real-world, well-phenotyped cardiovascular population is not well understood. METHODS: Whole exome sequencing was performed on 8574 individuals from the CATHGEN cohort (Catheterization Genetics). Variants in 55 arrhythmia-related genes (associated with 8 disorders) were identified and assessed for pathogenicity based on American College of Genetics and Genomics/Association for Molecular Pathology criteria. Individuals carrying pathogenic/likely pathogenic (P/LP) variants were grouped by arrhythmogenic disorder and matched 1:5 to noncarrier controls based on age, sex, and genetic ancestry. Long-term phenotypic data were annotated through deep electronic health record review. RESULTS: Fifty-eight P/LP variants were found in 79 individuals in 12 genes associated with 5 arrhythmogenic disorders (arrhythmogenic right ventricular cardiomyopathy, Brugada syndrome, hypertrophic cardiomyopathy, LMNA-related cardiomyopathy, and long QT syndrome). The penetrance of these P/LP variants in this cardiovascular cohort was 33%, 0%, 28%, 83%, and 4%, respectively. Carriers of P/LP variants associated with arrhythmogenic disorders showed significant differences in ECG, imaging, and clinical phenotypes compared with noncarriers, but displayed no difference in survival. Carriers of novel truncating variants in FLNC, MYBPC3, and MYH7 also developed relevant arrhythmogenic cardiomyopathy phenotypes. CONCLUSIONS: In a real-world cardiovascular cohort, P/LP variants in arrhythmia-related genes were relatively common (1:108 prevalence) and most penetrant in LMNA. While hypertrophic cardiomyopathy P/LP variant carriers showed significant differences in clinical outcomes compared with noncarriers, carriers of P/LP variants associated with other arrhythmogenic disorders displayed only ECG differences.

Protein biomarkers of cardiac remodeling and inflammation associated with HFpEF and incident events.

There is increasing evidence that HFpEF is a heterogeneous clinical entity and distinct molecular pathways may contribute to pathophysiology. Leveraging unbiased proteomics to identify novel biomarkers, this study seeks to understand the underlying molecular mechanisms of HFpEF. The discovery cohort consisted of HFpEF cases and non-HF controls from the CATHGEN study (N = 176); the validation cohort consisted of participants from the TECOS trial of patients with diabetes (N = 109). Proteins associated with HFpEF were included in a LASSO model to create a discriminative multi-protein model and assessed in the validation cohort. Survival models and meta-analysis were used to test the association of proteins with incident clinical outcomes, including HF hospitalization, mortality and HFpEF hospitalization in CATHGEN, TECOS and the Jackson Heart Study. In the derivation set, 190 proteins were associated with HFpEF in univariate analysis, of which 65 remained significant in the multivariate model. Twenty (30.8%) of these proteins validated in TECOS, including LCN2, U-PAR, IL-1ra, KIM1, CSTB and Gal-9 (OR 1.93-2.77, p < 0.01). LASSO regression yielded a 13-protein model which, when added to a clinical model inclusive of NT-proBNP, improved the AUC from 0.82 to 0.92 (p = 1.5 × 10-4). Five proteins were associated with incident HF hospitalization, four with HFpEF hospitalization and eleven with mortality (p < 0.05). We identified and validated multiple circulating biomarkers associated with HFpEF as well as HF outcomes. These biomarkers added incremental discriminative capabilities beyond clinical factors and NT-proBNP.

Altered branched-chain α-keto acid metabolism is a feature of NAFLD in individuals with severe obesity.

Hepatic de novo lipogenesis is influenced by the branched-chain α-keto acid dehydrogenase (BCKDH) kinase (BCKDK). Here, we aimed to determine whether circulating levels of the immediate substrates of BCKDH, the branched-chain α-keto acids (BCKAs), and hepatic BCKDK expression are associated with the presence and severity of nonalcoholic fatty liver disease (NAFLD). Eighty metabolites (3 BCKAs, 14 amino acids, 43 acylcarnitines, 20 ceramides) were quantified in plasma from 288 patients with bariatric surgery with severe obesity and scored liver biopsy samples. Metabolite principal component analysis factors, BCKAs, branched-chain amino acids (BCAAs), and the BCKA/BCAA ratio were tested for associations with steatosis grade and presence of nonalcoholic steatohepatitis (NASH). Of all analytes tested, only the Val-derived BCKA, α-keto-isovalerate, and the BCKA/BCAA ratio were associated with both steatosis grade and NASH. Gene expression analysis in liver samples from 2 independent bariatric surgery cohorts showed that hepatic BCKDK mRNA expression correlates with steatosis, ballooning, and levels of the lipogenic transcription factor SREBP1. Experiments in AML12 hepatocytes showed that SREBP1 inhibition lowered BCKDK mRNA expression. These findings demonstrate that higher plasma levels of BCKA and hepatic expression of BCKDK are features of human NAFLD/NASH and identify SREBP1 as a transcriptional regulator of BCKDK.

A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis.

The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 x 10(-7) and 1.16 x 10(-6)], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors.

A powerful and flexible multilocus association test for quantitative traits.

Association mapping of complex traits typically employs tagSNP genotype data to identify a trait locus within a region of interest. However, considerable debate exists regarding the most powerful strategy for utilizing such tagSNP data for inference. A popular approach tests each tagSNP within the region individually, but such tests could lose power as a result of incomplete linkage disequilibrium between the genotyped tagSNP and the trait locus. Alternatively, one can jointly test all tagSNPs simultaneously within the region (by using genotypes or haplotypes), but such multivariate tests have large degrees of freedom that can also compromise power. Here, we consider a semiparametric model for quantitative-trait mapping that uses genetic information from multiple tagSNPs simultaneously in analysis but produces a test statistic with reduced degrees of freedom compared to existing multivariate approaches. We fit this model by using a dimension-reducing technique called least-squares kernel machines, which we show is identical to analysis using a specific linear mixed model (which we can fit by using standard software packages like SAS and R). Using simulated SNP data based on real data from the International HapMap Project, we demonstrate that our approach often has superior performance for association mapping of quantitative traits compared to the popular approach of single-tagSNP testing. Our approach is also flexible, because it allows easy modeling of covariates and, if interest exists, high-dimensional interactions among tagSNPs and environmental predictors.

Proteomic profiling identifies CLEC4C expression as a novel biomarker of primary graft dysfunction after heart transplantation.

PURPOSE: Clinical models to identify patients at high risk of primary graft dysfunction (PGD) after heart transplantation (HT) are limited, and the underlying pathophysiology of this common post-transplant complication remains poorly understood. We sought to identify whether pre-transplant levels of circulating proteins reporting on immune activation and inflammation are associated with incident PGD. METHODS: The study population consisted of 219 adult heart transplant recipients identified between 2016 and 2020 at Duke University Medical Center, randomly divided into derivation (n = 131) and validation (n = 88) sets. PGD was defined using modified ISHLT criteria. Proteomic profiling was performed using Olink panels (n = 354 proteins) with serum samples collected immediately prior to transplantation. Association between normalized relative protein expression and PGD was tested using univariate and multivariable (recipient age, creatinine, mechanical circulatory support, and sex; donor age; ischemic time) models. Significant proteins identified in the derivation set (p < 0.05 in univariate models), were then tested in the validation set. Pathway enrichment analysis was used to test candidate biological processes. The predictive performance of proteins was compared to that of the RADIAL score. RESULTS: Nine proteins were associated with PGD in univariate models in the derivation set. Of these, only CLEC4C remained associated with PGD in the validation set after Bonferroni correction (OR [95% CI] = 3.04 [1.74,5.82], p = 2.8 × 10-4). Patterns of association were consistent for CLEC4C in analyses stratified by biventricular/left ventricular and isolated right ventricular PGD. Pathway analysis identified interferon-alpha response and C-type lectin signaling as significantly enriched biologic processes. The RADIAL score was a poor predictor of PGD (AUC = 0.55). CLEC4C alone (AUC = 0.66, p = 0.048) and in combination with the clinical covariates from the multivariable model (AUC = 0.69, p = 0.018) improved discrimination for the primary outcome. CONCLUSIONS: Pre-transplantation circulating levels of CLEC4C, a protein marker of plasmacytoid dendritic cells (pDCs), may identify HT recipients at risk for PGD. Further studies are needed to better understand the potential role pDCs and the innate immune response in PGD.