Publications

BACKGROUND: Exercise unmasks limitations in multi-organ system reserve capacity characteristic of heart failure with preserved ejection fraction (HFpEF). However, the metabolic and genetic underpinnings of exercise deficits, and their cumulative contribution to HFpEF severity and prognosis, remain incompletely understood.

METHODS: We used invasive cardiopulmonary exercise testing (iCPET), metabolite profiling, and genomics to simultaneously characterize seven exercise physiologic deficits in HFpEF patients: reduced exercise stroke volume and heart rate, steep pulmonary capillary wedge pressure/cardiac output (PCWP/CO) slope, elevated pulmonary vascular resistance, pulmonary mechanical limitation to exercise, impaired peripheral oxygen extraction, and obesity-related exaggerated metabolic cost of initiating exercise. We first mapped the distribution, functional, and prognostic significance of these exercise deficits. We then applied LASSO regression to identify metabolite signatures of each exercise deficit, and measured the relation of these signatures with clinical-demographic features, cardiac magnetic resonance imaging, and incident HF in 6345 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) study with ≈20-year follow-up. Finally, we mapped deficit-implicated metabolites to tissue-specific genetic variation in ≈2M individuals with HF, and in the largest genome-wide association study (GWAS) studies of HFpEF comorbidities (obesity, renal disease, diabetes) to evaluate shared metabolic mechanisms of HFpEF pathophysiology.

RESULTS: Our iCPET HFpEF cohort (61.7±14.1 years, 54% female, BMI 30.6±6.7 kg/m2 ) exhibited a broad range of compound cardiac and extra-cardiac exercise deficits. Individuals with ≥5 exercise deficits had a nearly 4-fold higher hazard of incident cardiovascular event or mortality (HR 3.90, 95% CI 1.74-8.75, P<0.0001). The metabolite signature of exercise PCWP/CO slope conferred a HR of 1.43 per SD increment, 95% CI 1.20-1.71, P<0.001 for incident HF in MESA. Addition of all iCPET deficit metabolic signatures in a single model yielded ≈20% continuous net reclassification improvement over traditional HFpEF risk factors. Genes implicated by the exercise deficit metabolome were enriched in the HF GWAS (≈2M) and shared with obesity, renal dysfunction, and diabetes, highlighting a lifelong shared predisposition to HF (including HFpEF) and its comorbidities.

CONCLUSIONS: Organ-specific responses to exercise and their circulating metabolite signatures are strongly linked to HFpEF development and prognosis. These results offer a paradigm for parsing HFpEF subphenotypes and prioritizing metabolic mechanisms of HFpEF.

BACKGROUND: Knowledge of proteomic mechanisms explaining the link between psychosocial stress and cardiovascular disease is limited. This study aimed to (1) identify plasma proteins associated with psychosocial factors and (2) assess associational pathways between psychosocial factors, identified proteins, and incident cardiovascular disease events in a discovery cohort, JHS (Jackson Heart Study), and 2 replication cohorts, the CHS (Cardiovascular Health Study), and the MESA (Multi-Ethnic Study of Atherosclerosis).

METHODS: JHS participants from exam 1 (2000-2004) with SomaScan 1.3k platform proteomics data were included (n=2143, mean age=55.3). Depressive symptoms and perceived stress scores were measured via the 20-item Centers for Epidemiological Studies scale and an 8-item perceived stress scale adapted for the JHS, respectively. Multivariable linear regression models were used to test the association between psychosocial factors and plasma proteins, controlling for age, sex, proteomics batch, and estimated glomerular function. Meta-analyses were also performed across cohorts, using Bonferroni correction for multiple testing (P<3.782×10-5). Mediation analyses with Cox proportional hazards models were used to evaluate potential proteomic pathways in the association between psychosocial factors and coronary heart disease, heart failure, and stroke in JHS.

RESULTS: Angiopoietin-2 (𝛽=0.013, SE=0.002, P<0.001), contactin-5 (𝛽=-0.013, SE=0.002, P<0.001), growth/differentiation factor 15 or macrophage inhibitory cytokine 1 (𝛽=0.011, SE=0.002, P<0.001), neural cell adhesion molecule 120 (𝛽=-0.012, SE=0.002, P<0.001), and KYNU (kynureninase; 𝛽=0.014, SE=0.003, P<0.001) were each significantly associated with depressive symptoms, with angiopoietin-2, contactin-5, macrophage inhibitory cytokine 1, and neural cell adhesion molecule 120 replicating in CHS and MESA. Leukotriene A-4 hydrolase was associated with perceived stress (𝛽=-0.0235, SE=0.005, P<0.001). Macrophage inhibitory cytokine 1 partially accounted for the association between depressive symptoms and incident coronary heart disease in JHS (23%; P=0.0009).

CONCLUSIONS: Novel associations between psychosocial factors, plasma proteins, and cardiovascular disease were identified in JHS. Circulating proteomic profiles across 3 cardiovascular disease cohorts showed differences in protein concentrations by psychosocial measures. Future investigations should identify additional potentially targetable proteomic mechanisms by which psychosocial factors contribute to disease.

Exercise benefits numerous organ systems and tissues, however limited knowledge exists about its underlying molecular pathways. Identifying the exercise-induced biochemical changes that occur in the circulation may provide further insights into how exercise confers systemic health changes. Here, we perform large-scale plasma proteomic, metabolomic, and whole blood transcriptional profiling in sedentary human participants undergoing acute endurance exercise (EE), resistance exercise (RE), or a non-exercise control (CON) in up to 7 timepoints over a 24 hour period. We observe 7066 transcript, 189 protein, and 448 metabolite changes in response to EE or RE compared to CON. Our analyses reveal numerous shared biochemical responses between EE and RE modes, but also differences in immune cell responses, lipid metabolism, and pathways reflective of tissue repair and angiogenesis. Taken together, our findings highlight novel temporal and exercise mode-specific blood-based molecular responses to acute exercise, and provide a new resource for the scientific community.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment.

METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference.

RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization.

CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants and phenotypes. Here, we examine 2157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2157 proteins follow a bimodal distribution (median r = 0.30). We evaluate protein measure associations with genetic variants, and find approximately 25-30% of the signals on each platform are likely driven by protein-altering variants. We highlight 80 proteins that correlate differently across ancestry groups likely in part due to differing protein-altering variant frequencies by ancestry. Furthermore, adjustment for protein-altering variants with opposite directions of effect by platform improves inter-platform protein measure correlation and results in more concordant genetic and phenotypic associations. Hence, protein-altering variants need to be accounted for across ancestries to facilitate platform-concordant and accurate protein measurement.

The human metabolome reflects complex metabolic states affected by genetic and environmental factors. However, metabolites associated with type 2 diabetes (T2D) risk and their determinants remain insufficiently characterized. Here we integrated blood metabolomic, genomic and lifestyle data from up to 23,634 initially T2D-free participants from ten cohorts. Of 469 metabolites examined, 235 were associated with incident T2D during up to 26 years of follow-up, including 67 associations not previously reported across bile acid, lipid, carnitine, urea cycle and arginine/proline, glycine and histidine pathways. Further genetic analyses linked these metabolites to signaling pathways and clinical traits central to T2D pathophysiology, including insulin resistance, glucose/insulin response, ectopic fat deposition, energy/lipid regulation and liver function. Lifestyle factors-particularly physical activity, obesity and diet-explained greater variations in T2D-associated versus non-associated metabolites, with specific metabolites revealed as potential mediators. Finally, a 44-metabolite signature improved T2D risk prediction beyond conventional factors. These findings provide a foundation for understanding T2D mechanisms and may inform precision prevention targeting specific metabolic pathways.

BACKGROUND: Systematic profiling of plasma proteins in population studies offers a complementary approach to discovery of novel risk factors and may provide new insights into the causes of coronary heart disease.

METHODS: To explore relationships between the circulating proteome and coronary heart disease (CHD), we evaluated associations of 4780 plasma proteins with incident CHD in the Cardiovascular Health Study (CHS, N=2856, 575 CHD events) and replicated significant associations in the Atherosclerosis Risk in Communities Study (ARIC, N = 10456; 1375 events).

RESULTS: We find that 11 proteins significantly associate with incident CHD after adjusting for risk factors; and eight significantly replicated in ARIC. Several proteins correlate with carotid intimal medial thickness and CHD associations are attenuated in participants without subclinical atherosclerosis. Macrophage metalloelastase (MMP12) is the strongest observed association (Hazard Ratio, 1.31; 95% Confidence Interval, 1.19-1.44). Mendelian randomization (MR) identifies a causal relationship between higher MMP12 and lower CHD (Odds Ratio, OR 0.94) and ischemic stroke (OR 0.90) risk, while reverse MR found that genetic propensity to CHD increased MMP12. Taken together, multivariable MR confirms a direct protective effect of higher plasma MMP12 on CHD risk and a genetic effect of atherosclerosis and CHD on elevating MMP12.

CONCLUSIONS: Proteomic analyses reveal associations with incident CHD and genomic evidence suggests that therapeutic MMP12 inhibition may confer adverse cardiovascular effects.

BACKGROUND: We report IMPROVE-DiCE (Improve Diabetic Cardiac Energetics), a 2-part open-label, phase 2a trial evaluating the safety and effectiveness of ninerafaxstat, a novel therapeutic designed to enhance cardiac energetics. Between May and September 2021, part 1 enrolled patients with type 2 diabetes and obesity without heart failure with preserved ejection fraction (HFpEF). Between January 2023 and June 2024, part 2 enrolled patients with type 2 diabetes, obesity, and HFpEF.

METHODS: Forty-two participants received 200 mg ninerafaxstat twice daily (part 1, n=21, 43% women, 72±0.5 years of age, 4-8 weeks; part 2, n=21, 29% women, 71±6 years of age, 12 weeks). Myocardial energetics (phosphocreatine-to-ATP ratio [PCr/ATP], primary outcome) and function (rest and dobutamine stress) were assessed before and after treatment using magnetic resonance imaging, 31P- and 1H magnetic resonance spectroscopy. In part 1, hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopy to assess in vivo pyruvate dehydrogenase flux (n=9) and plasma metabolomics and proteomics were also performed.

RESULTS: In part 1, in patients with diabetes and obesity but without HFpEF, the heart was characterized by impaired pyruvate dehydrogenase flux, reduced PCr/ATP, triglyceride deposition, and diastolic impairment. Treatment with ninerafaxstat was associated with improved PCr/ATP (+0.39±0.49 [95% CI, 0.16-0.62]; Cohen's d, 0.79; P=0.002) and lower myocardial triglyceride (by 34%, P=0.03). In part 2, in patients with diabetes, obesity, and symptomatic HFpEF, the heart was characterized by reduced PCr/ATP, diastolic impairment, and failure of systolic augmentation to exercise. Consistently, treatment with ninerafaxstat was associated with improvement in PCr/ATP (+0.15±0.25 [95% CI, 0.03-0.26]; Cohen's d, 0.60; P=0.02), improved systolic augmentation to exercise (+1.4 L/min, P=0.04), improved exercise capacity (6-minute walk distance +16 m, P=0.02), and improved New York Heart Association class symptom burden.

CONCLUSIONS: These mechanistic phase 2a study results show that ninerafaxstat is safely tolerated and improves myocardial energetics in participants with obesity and diabetes without or with clinically manifest HFpEF.

REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04826159.

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer insights into downstream clinical consequences. Here we explore these patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 participants (3881 with CHIP) from TOPMed and UK Biobank (UKB) with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2917 proteins by Olink in UKB), we identify 32 and 345 proteins from TOPMed and UKB, respectively, associated with CHIP and most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations show substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangle causal proteomic perturbations from TET2 CHIP. Lastly, we identify plasma proteins shared between CHIP and CAD.

Aging and age-related diseases share convergent pathways at the proteome level. Here, using plasma proteomics and machine learning, we developed organismal and ten organ-specific aging clocks in the UK Biobank (n = 43,616) and validated their high accuracy in cohorts from China (n = 3,977) and the USA (n = 800; cross-cohort r = 0.98 and 0.93). Accelerated organ aging predicted disease onset, progression and mortality beyond clinical and genetic risk factors, with brain aging being most strongly linked to mortality. Organ aging reflected both genetic and environmental determinants: brain aging was associated with lifestyle, the GABBR1 and ECM1 genes, and brain structure. Distinct organ-specific pathogenic pathways were identified, with the brain and artery clocks linking synaptic loss, vascular dysfunction and glial activation to cognitive decline and dementia. The brain aging clock further stratified Alzheimer's disease risk across APOE haplotypes, and a super-youthful brain appears to confer resilience to APOE4. Together, proteomic organ aging clocks provide a biologically interpretable framework for tracking aging and disease risk across diverse populations.