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IMPORTANCE: Blood pressure response during acute exercise (exercise blood pressure [EBP]) is associated with the future risk of hypertension and cardiovascular disease (CVD). Biochemical characterization of EBP could inform disease biology and identify novel biomarkers of future hypertension. OBJECTIVE: To identify protein markers associated with EBP and test their association with incident hypertension. DESIGN, SETTING, AND PARTICIPANTS: This study assayed 4977 plasma proteins in 681 healthy participants (from 763 assessed) of the Health, Risk Factors, Exercise Training and Genetics (HERITAGE; data collection from January 1993 to December 1997 and plasma proteomics from January 2019 to January 2020) Family Study at rest who underwent 2 cardiopulmonary exercise tests. Individuals were free of CVD at the time of recruitment. Individuals with resting SBP ≥160 mm Hg or DBP ≥100 mm Hg or taking antihypertensive drug therapy were excluded from the study. The association between resting plasma protein levels to both resting BP and EBP was evaluated. Proteins associated with EBP were analyzed for their association with incident hypertension in the Framingham Heart Study (FHS; n = 1177) and validated in the Jackson Heart Study (JHS; n = 772) and Multi-Ethnic Study of Atherosclerosis (MESA; n = 1367). Proteins associated with incident hypertension were tested for putative causal links in approximately 700 000 individuals using cis-protein quantitative loci mendelian randomization (cis-MR). Data were analyzed from January 2023 to January 2024. EXPOSURES: Plasma proteins. MAIN OUTCOMES AND MEASURES: EBP was defined as the BP response during a fixed workload (50 W) on a cycle ergometer. Hypertension was defined as BP ≥140/90 mm Hg or taking antihypertensive medication. RESULTS: Among the 681 participants in the HERITAGE Family Study, the mean (SD) age was 34 (13) years; 366 participants (54%) were female; 238 (35%) were self-reported Black and 443 (65%) were self-reported White. Proteomic profiling of EBP revealed 34 proteins that would not have otherwise been identified through profiling of resting BP alone. Transforming growth factor β receptor 3 (TGFBR3) and prostaglandin D2 synthase (PTGDS) had the strongest association with exercise systolic BP (SBP) and diastolic BP (DBP), respectively (TGFBR3: exercise SBP, β estimate, −3.39; 95% CI, −4.79 to −2.00; P = 2.33 × 10−6; PTGDS: exercise DBP β estimate, −2.50; 95% CI, −3.29 to −1.70; P = 1.18 × 10−9). In fully adjusted models, TGFBR3 was inversely associated with incident hypertension in FHS, JHS, and MESA (hazard ratio [HR]: FHS, 0.86; 95% CI, 0.75-0.97; P = .01; JHS, 0.87; 95% CI, 0.77-0.97; P = .02; MESA, 0.84; 95% CI, 0.71-0.98; P = .03; pooled cohort, 0.86; 95% CI, 0.79-0.92; P = 6 × 10−5). Using cis-MR, genetically predicted levels of TGFBR3 were associated with SBP, hypertension, and CVD events (SBP: β, −0.38; 95% CI, −0.64 to −0.11; P = .006; hypertension: odds ratio [OR], 0.99; 95% CI, 0.98-0.99; P < .001; heart failure with hypertension: OR, 0.86; 95% CI, 0.77-0.97; P = .01; CVD: OR, 0.84; 95% CI, 0.77-0.92; P = 8 × 10−5; cerebrovascular events: OR, 0.77; 95% CI, 0.70-0.85; P = 5 × 10−7). CONCLUSIONS AND RELEVANCE: Plasma proteomic profiling of EBP identified a novel protein, TGFBR3, which may protect against elevated BP and long-term CVD outcomes.

Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48–0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.

The US Dietary Guidelines (USDG) form the basis of nutrition guidelines, but the research informing the 3 USDG dietary patterns (Healthy US-Style [H-US], Mediterranean [Med], and vegetarian [Veg]) has been drawn largely from observational studies among White populations.

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIAmuscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

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ObjectivesWe investigated whether high responsiveness or low responsiveness to exercise training aggregates in the same individuals across seven cardiometabolic traits.MethodsA total of 564 adults (29.2% black, 53.7% female) from the HERITAGE family study completed a 20-week endurance training programme (at 55%–75% of participants’ maximal oxygen uptake (VO2max)) with VO2max, per cent body fat, visceral adipose tissue, fasting levels of insulin, high-density lipoprotein cholesterol, small low-density lipoprotein particles and inflammatory marker GlycA measured before and after training. For each exercise response trait, we created ethnicity-specific, sex-specific and generation-specific quintiles. High responses were defined as those within the 20th percentile representing the favourable end of the response trait distribution, low responses were defined as the 20th percentile from the least favourable end, and the remaining were labelled as average responses.ResultsOnly one individual had universally high or low responses for all seven cardiometabolic traits. Almost half (49%) of the cohort had at least one high response and one low response across the seven traits. About 24% had at least one high response but no low responses, 24% had one or more low responses but no high responses, and 2.5% had average responses across all traits.ConclusionsInterindividual variation in exercise responses was evident in all the traits we investigated, and responsiveness did not aggregate consistently in the same individuals. While adherence to an exercise prescription is known to produce health benefits, targeted risk factors may not improve.

IMPORTANCE: Obesity is a major determinant of disease burden worldwide. Polygenic risk scores (PRSs) have been posited as key predictors of obesity. How a PRS can be translated to the clinical encounter (especially in the context of fitness, activity, and parental history of overweight) remains unclear. OBJECTIVE: To quantify the relative importance of a PRS, fitness, activity, parental history of overweight, and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) in young adulthood on BMI trends over 25 years. DESIGN, SETTING, AND PARTICIPANTS: This population-based prospective cohort study at 4 US centers included white individuals and black individuals with assessments of polygenic risk of obesity, fitness, activity, and BMI in young adulthood (in their 20s) and up to 25 years of follow-up. Data collected between March 1985 and August 2011 were analyzed from April 25, 2019, to September 29, 2019. MAIN OUTCOMES AND MEASURES: Body mass index at the initial visit and 25 years later. RESULTS: This study evaluated an obesity PRS from a recently reported study of 1608 white individuals (848 women [52.7%]) and 909 black individuals (548 women [60.3%]) across the United States. At baseline (year 0), mean (SD) overall BMI was 24.2 (4.5), which increased to 29.6 (6.9) at year 25. Among white individuals, the PRS (combined with age, sex, self-reported parental history of overweight, and principal components of ancestry) explained 11.9% (at year 0) and 13.6% (at year 25) of variation in BMI. Although the addition of fitness increased the explanatory capability of the model (24.0% variance at baseline and up to 18.1% variance in BMI at year 25), baseline BMI in young adulthood was the strongest factor, explaining 52.3% of BMI in midlife in combination with age, sex, and self-reported parental history of overweight. Accordingly, models that included baseline BMI (especially BMI surveillance over time) were better in predicting BMI at year 25 compared with the PRS. In fully adjusted models, the effect sizes for fitness and the PRS on BMI were comparable in opposing directions. The added explanatory capacity of the PRS among black individuals was lower than among white individuals. Among white individuals, addition of baseline BMI and surveillance of BMI over time was associated with improved precision of predicted BMI at year 25 (mean error in predicted BMI 0 kg/m2 [95% CI, −11.4 to 11.4] to 0 kg/m2 [95% CI, −8.5 to 8.5] for baseline BMI and mean error 0 kg/m2 [95% CI, −5.3 to 5.3] for BMI surveillance). CONCLUSIONS AND RELEVANCE: Cardiorespiratory fitness in young adulthood and a PRS are modestly associated with midlife BMI, although future BMI is associated with BMI in young adulthood. Fitness has a comparable association with future BMI as does the PRS. Caution should be exercised in the widespread use of polygenic risk for obesity prevention in adults, and close clinical surveillance and fitness may have prime roles in limiting the adverse consequences of elevated BMI on health.

Proteins are effector molecules that mediate the functions of genes1,2and modulate comorbidities3–10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12–16coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.

IMPORTANCE: Metabolic responses to exercise training are variable. Metabolite profiling may aid in the clinical assessment of an individual’s responsiveness to exercise interventions. OBJECTIVE: To investigate the association between a novel circulating biomarker of hepatic fat, dimethylguanidino valeric acid (DMGV), and metabolic health traits before and after 20 weeks of endurance exercise training. DESIGN, SETTING, AND PARTICIPANTS: This study involved cross-sectional and longitudinal analyses of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a 20-week, single-arm endurance exercise clinical trial performed in multiple centers between 1993 and 1997. White participants with sedentary lifestyles who were free of cardiometabolic disease were included. Metabolomic tests were performed using a liquid chromatography, tandem mass spectrometry method on plasma samples collected before and after exercise training in the HERITAGE study. Metabolomics and data analysis were performed from August 2017 to May 2018. EXPOSURES: Plasma DMGV levels. MAIN OUTCOME AND MEASURES: The association between DMGV levels and measures of body composition, plasma lipids, insulin, and glucose homeostasis before and after exercise training. RESULTS: Among the 439 participants included in analyses from HERITAGE, the mean (SD) age was 36 (15) years, 228 (51.9%) were female, and the median (interquartile range) body mass index was 25 (22-28). Baseline levels of DMGV were positively associated with body fat percentage, abdominal visceral fat, very low-density lipoprotein cholesterol, and triglycerides, and inversely associated with insulin sensitivity, low-density lipoprotein cholesterol, high-density lipoprotein size, and high-density lipoprotein cholesterol (range of β coefficients, 0.17-0.46 [SEs, 0.026-0.050]; all P < .001, after adjusting for age and sex). After adjusting for age, sex, and baseline traits, baseline DMGV levels were positively associated with changes in small high-density lipoprotein particles (β, 0.14 [95% CI, 0.05-0.23]) and inversely associated with changes in medium and total high-density lipoprotein particles (β, −0.15 [95% CI, −0.24 to −0.05] and −0.19 [95% CI, −0.28 to −0.10], respectively), apolipoprotein A1 (β, −0.14 [95% CI, −0.23 to −0.05]), and insulin sensitivity (β, −0.13; P = 3.0 × 10−3) after exercise training. CONCLUSIONS AND RELEVANCE: Dimethylguanidino valeric acid is an early marker of cardiometabolic dysfunction that is associated with attenuated improvements in lipid traits and insulin sensitivity after exercise training. Levels of DMGV may identify individuals who require additional therapies beyond guideline-directed exercise to improve their metabolic health.

There is evidence from human twin and family studies as well as mouse and rat selection experiments that there are considerable interindividual differences in the response of cardiorespiratory fitness (CRF) and other cardiometabolic traits to a given exercise programme dose. We developed this consensus statement on exercise response variability following a symposium dedicated to this topic. There is strong evidence from both animal and human studies that exercise training doses lead to variable responses. A genetic component contributes to exercise training response variability.In this consensus statement, we (1) briefly review the literature on exercise response variability and the various sources of variations in CRF response to an exercise programme, (2) introduce the key research designs and corresponding statistical models with an emphasis on randomised controlled designs with or without multiple pretests and post-tests, crossover designs and repeated measures designs, (3) discuss advantages and disadvantages of multiple methods of categorising exercise response levels—a topic that is of particular interest for personalised exercise medicine and (4) outline approaches that may identify determinants and modifiers of CRF exercise response. We also summarise gaps in knowledge and recommend future research to better understand exercise response variability.

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Supplemental Digital Content is available in the text.

Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling, we show that endurance training induces profound changes in gene regulatory networks linking signaling and selective control of translation to energy metabolism and tissue remodeling. We discovered that knockdown of the mTOR-independent factor Eif6, which we predicted to be a key regulator of this process, affects mitochondrial respiration efficiency, ROS production, and exercise performance. Our work demonstrates the validity of a data-driven approach to understanding muscle homeostasis.

Introduction:Angiopoietin like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of lipoprotein lipase and modifiable by regular exercise. However, the molecular underpinning of these novel biomarkers has not been fully elucidated. The purpose of this study was to examine the associations between plasma metabolites and ANGPTL3/8 and 4/8 before and after exercise training.Methods:Measurements were taken before and after 20 weeks of exercise training in 630 adults (36% Black, 56% women, mean age 35 yrs) of the HERITAGE Family Study. Meso Scale Discovery immunoassays were used to measure ANGPTL3/8 and 4/8 in serum. Plasma metabolites (n=300 named) were measured using LC-MS and the HILIC-pos method. Linear mixed models tested the association between metabolites and each trait at baseline and post-training with full covariate adjustment. Significance was set to FDR<0.05.Results:A total of 111 and 93 metabolites were significantly associated with ANGPTL3/8 at baseline or post-training, respectively (Figure 1A). A total of 69 metabolites were associated with ANGPTL3/8 at both time points, including ketone bodies, acylcarnitines, and DMGV, while 24 metabolites were only associated at post-training including citric acid, methionine, and glycine. A total of 89 and 40 metabolites were significantly associated with ANGPTL4/8 at baseline or post-training, respectively (Figure 1B). A total of 13 metabolites were associated with ANGPTL4/8 at both time points including glycine and lysophospholipids, whereas 27 metabolites were associated only at post-training including hydroxyproline, N-Lignoceroyl Taurine, and methylguanidine.Conclusions:We identified several plasma metabolites associated with ANGPTL3/8 and 4/8 before and after exercise training. Our findings indicate potential metabolic pathways related to the exercise responsiveness of ANGPTL3/8 and 4/8, including glucose-alanine cycle, urea cycle, and glycine and methionine metabolism.

Introduction:Angiopoietin like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of lipoprotein lipase and modifiable by regular exercise. However, the molecular biomarkers related to their exercise responses have not been fully elucidated. The purpose of this study was to examine the associations between plasma proteins and ANGPTL3/8 and 4/8 before and after exercise training.Methods:Measurements were taken before and after 20 weeks of exercise training in 630 adults (36% Black, 56% women, mean age 35 yrs) of the HERITAGE Family Study. Meso Scale Discovery immunoassays were used to measure ANGPTL3/8 and ANGPTL4/8 complexes in serum. Plasma proteins (n=4979 aptamers) were quantified using SomaScan. Linear mixed models tested the association between plasma proteins and each trait at baseline and post- training with full covariate adjustment. Significance was set to FDR<0.05.Results:A total of 862 and 126 proteins were significantly associated with ANGPTL3/8 at baseline or post-training, respectively, with 80 proteins associated at both time points, including PCSK9 and PLTP (Figure 1A). Conversely, 46 proteins were only associated with ANGPTL3/8 at post-training, 23 of which whose levels significantly changed with training including NRP1, ghrelin, HHIP, and APOA1. A total of 433 and 71 proteins were significantly associated with ANGPTL4/8 at baseline or post-training, respectively, with 46 proteins associated with both time points (Figure 1B). A total of 25 proteins were only associated with ANGPTL4/8 at post-training, 12 of which whose levels significantly changed with training including ghrelin, COL6A2, and MMP16.Conclusions:We identified a subset of proteins uniquely associated with exercise-induced changes in ANGPTL3/8 and 4/8. Thus, the responsiveness of ANGPTL3/8 and 4/8 to regular exercise may be related to cholesterol esterification, lipoprotein remodeling, inflammatory response, and regulation of fibrinolysis and coagulation among other biological pathways.

Regular exercise has many favorable effects on human health, which may be mediated in part by the release of circulating bioactive factors during each bout of exercise. Limited data exist regarding the kinetic responses of plasma proteins during and after acute exercise. Proteomic profiling of 4163 proteins was performed using a large-scale, affinity-based platform in 75 middle-aged adults who were referred for treadmill exercise stress testing. Plasma proteins were quantified at baseline, peak exercise, and 1-h postexercise, and those with significant changes at both exercise timepoints were further examined for their associations with cardiometabolic traits and change with aerobic exercise training in the HEalth, RIsk factors, exercise Training And GEnetics Family Study, a 20-week exercise intervention study. A total of 765 proteins changed (false discovery rate < 0.05) at peak exercise compared to baseline, and 128 proteins changed (false discovery rate < 0.05) at 1-h postexercise. The 56 proteins that changed at both timepoints included midkine, brain-derived neurotrophic factor, metalloproteinase inhibitor 4, and coiled-coil domain-containing protein 126 and were enriched for secreted proteins. The majority had concordant direction of change at both timepoints. Across all proteins assayed, gene set enrichment analysis showed increased abundance of coagulation-related proteins at 1-h postexercise. Forty-five proteins were associated with at least one measure of adiposity, lipids, glucose homeostasis, or cardiorespiratory fitness in HEalth, RIsk factors, exercise Training And GEnetics, and 20 proteins changed with aerobic exercise training. We identified hundreds of novel proteins that change during acute exercise, most of which resolved by 1 h into recovery. Proteins with sustained changes during exercise and recovery may be of particular interest as circulating biomarkers and pathways for further investigation in cardiometabolic diseases. These data will contribute to a biochemical roadmap of acute exercise that will be publicly available for the entire scientific community.

Introduction:Although exercise training is known to alter body composition, the molecular biomarkers and mechanisms related to these changes have not been fully elucidated. The purpose of this study was to examine the associations between plasma proteins and body composition traits before and after exercise training.Methods:Measurements were taken before and after 20 weeks of standardized, endurance training in self-identified Black and White adults of the HERITAGE Family Study (n=647). Plasma proteins were measured using an affinity-based platform (n=4979 aptamers). 11 body composition traits were measured using underwater weighing, CT scans, and anthropometry: BMI, body surface area, fat mass, fat free mass, %fat, waist circumference, waist-to-hip ratio, body weight, and abdominal visceral, subcutaneous, and total fat. Linear mixed models were used to test the association between plasma proteins and each trait at baseline and in response to training with full covariate adjustment (Table 1). Significance was set to FDR<0.05.Results:On average, subjects were [mean and (SD)] 35 (14) years old, 33% Black, 54% female, and had BMI 26.2 (5.2) kg/m2. The number of significant associations between proteins and traits at baseline and in response to exercise training ranged from 645-1714 and 0-42, respectively (Table 1). While leptin was among the top associated proteins at both time points for almost all traits, our analysis revealed many novel associations between changes in proteins with changes in body composition. Changes in DLK-1 significantly associated with changes in 9 of 11 traits but was not associated with baseline measures.Conclusions:Numerous plasma proteins were associated with body composition traits at baseline, with fewer associated with trait responses to training. Notably, we identified a subset of proteins uniquely associated with exercise-induced changes in body composition traits.

Introduction.C-reactive protein (CRP) and GlycA are established biomarkers of inflammation. Regular exercise tends to decrease CRP and GlycA levels. However, the spectrum of molecules associated with the anti-inflammatory effects of regular exercise are less well understood. Hypothesis.We hypothesized that distinct metabolite signatures exist for both baseline levels and exercise responsiveness of CRP and GlycA. Methods.Measures were performed before and after 20 weeks of endurance exercise training in 652 Black and White adults from the HERITAGE Family Study. A total of 300 targeted plasma metabolites were measured using LC-MS. High-sensitivity CRP and GlycA were measured using automated assays and NMR spectroscopy (LabCorp), respectively. Linear mixed models were used to test: 1) Association of baselinemetabolites with baselinehsCRP and GlycA and 2) Association of changesin metabolite with changesin hsCRP and GlycA. Models were adjusted for age, sex, race, BMI, with family membership as a random variable, with change models also adjusting for baseline trait value. Significance was determined as FDR<0.05. Results.Baseline levels and changes of hsCRP and GlycA were moderately correlated (r=0.51 and 0.31, p<0.0001 for both, respectively). At baseline, 40 and 94 metabolites were associated with hsCRP and GlycA, respectively, with 30 metabolites associated with both phenotypes. The top baseline associations for both traits included multiple species of lysophosphatidylcholine (LPC) and phosphatidylethanolamine (PE), while cortisol, biliverdin, and bilirubin were among the metabolites associated with GlycA only. The changes in only one metabolite were associated with concomitant changes in CRP, while no associations were found for change in GlycA. Conclusions.Plasma metabolite associations with baseline hsCRP overlapped with those associated with baseline GlycA levels. Several unique metabolite associations with baseline GlycA were identified, including molecules in established inflammatory pathways. Metabolite changes with exercise were not associated with changes in either measure. These findings have implications for the use of metabolites as signatures of systemic inflammation vs as targets of lifestyle interventions.

Introduction:The blood pressure (BP) response during acute exercise (acute exercise blood pressure (AEBP)) is related to future risk of hypertension (HTN) and cardiovascular disease (CVD). Biochemical characterization of AEBP could identify novel biomarkers of CVD risk and inform understanding of its biology.Methods:We applied an aptamer-based proteomics platform to assay ~5000 proteins at rest in 681 healthy individuals of the HERITAGE Family Study (mean age 34y, 54% women) who underwent an acute exercise perturbation. AEBP was measured during submaximal exercise on a cycle ergometer. We then performed a proteomic association study of resting BP and AEBP. Top protein associations with acute exercise SBP and DBP were analyzed for their association with incident HTN and CVD in the Framingham Heart Study (FHS). Putative causal effects of AEBP-related proteins were investigated by Mendelian randomization (MR), using cis-protein quantitative loci genetic instruments.Results:We identified new markers of AEBP, many of which are secreted proteins that span biological processes relevant to vascular function including transforming-growth factor beta-receptor 3 (β = -3.39, p = 2.33e-6), prostaglandin D2-synthase (β = -2.50, p = 1.18e-10-9), and angiopoietin-related protein 4 (β = 2.44, p = 1.05e-4). The addition of 12 AEBP-associated proteins to clinical information informed future risk of HTN and CVD among normotensive community-dwelling individuals (clinical model, clinical proteomic model AUCs: incident HTN 0.69, 0.73; coronary heart disease 0.73, 0.76; heart failure 0.83, 0.87). MR analysis of AEBP-associated proteins supported a potential causal relationship between 5 proteins and BP regulation (TGFBR3, ANGPTL4, CGA FSHB, PTGDS, KLK8).Conclusions:We identified new blood biomarkers of BP regulation that were elicited only by an acute exercise perturbation and highlight novel potential causal pathways.

INTRODUCTION:Although exercise training can improve body composition, the molecular biomarkers and mechanisms related to these changes have not been fully elucidated.HYPOTHESIS:We hypothesized that distinct metabolite signatures exist for both baseline levels and exercise responsiveness of body composition traits, with substantial overlap across traits.METHODS:Measurements were taken before and after 20 weeks of endurance training in self-identified Black and White adults of the HERITAGE Family Study (n=652). 300 targeted plasma metabolites were measured using LC-MS. Underwater weighing, CT scans, and anthropometric measurements were used to derive the 11 body composition traits included in this study: BMI, body surface area, fat mass, fat free mass, %fat, waist circumference, waist-to-hip ratio, body weight, and abdominal visceral, subcutaneous, and total fat. Linear mixed models were used to test the association between plasma metabolites and each body composition trait at baseline and in response to training with full covariate adjustment. Significance was set to FDR<0.05.Results:On average, subjects were [mean and (SD)] 35 (14) years old, 33% Black, 54% female, and had BMI of 26.2 (5.2) kg/m2. The number of metabolites significantly associated with body composition traits at baseline ranged from 57-141 (Table 1). DMGV was among the top 3 associated metabolites at baseline for all 11 traits, while SM(d18:1/16:1) was associated with 8 of 11 baseline traits. Few if any significant associations were found between change in metabolites and change in body composition measures in response to exercise training (range: 0-10) (Table 1).CONCLUSIONS:Although numerous metabolites were associated with body composition traits at baseline, few associations were observed with trait responses to training. These results suggest that intrinsic body composition and its response to exercise training may have differing underlying metabolic signatures.

Introduction:Lipoproteins are among the strongest predictors of CVD and are altered through regular exercise. However, the molecular changes underlying the potential benefits of exercise on plasma lipoproteins are unclear.Methods:Proteins (n=4979) were quantified from the plasma of 647 Black and White adults (56% women, mean age = 34.9 yrs) before and after 20-weeks of endurance exercise training using SomaScan. All subjects had complete data for 7 lipoprotein traits that improved with training: HDL-C, TG, large TG rich lipoprotein particles (LTRLP), small LDL particles (SLDLP), large HDL particles (LHDLP), TRLP size, and LDLP size. Fully adjusted linear mixed models were used to test the association of 1) baseline proteins with baseline lipoproteins and 2) delta proteins with delta lipoproteins (delta = post training - baseline value). Significance was determined as FDR<0.05.Results:We identified numerous proteins associated with baseline levels of at least one of the seven lipoprotein traits (range: 48-1099) and whose changes in response to regular exercise were associated with concomitant changes in lipoproteins (range: 4-95) (Table 1). Substantial overlap was found between proteins associated with lipoproteins across timepoints, with 16 proteins associated with 4 or more lipoprotein traits at both timepoints. Plasma abundance of 12/16 proteins significantly changed with training (FDR <0.05). Additionally, for these proteins plasma abundance changed in concordance with the beneficial direction of the associated lipoprotein trait (e.g., proteins associated with atheroprotective lipoprotein traits increased with training and proteins associated with atherogenic traits decreased).Conclusions:Beneficial alterations to plasma lipoproteins with regular exercise are reflected in changes to the plasma proteome. Proteins identified here may represent novel markers of the benefits of regular exercise and of systemic lipoprotein metabolism.

Introduction:Type 2 diabetes (T2D) is a cardiovascular disease risk equivalent and likely results from broad metabolic changes, which high throughput proteomics have helped to unravel. Prior studies are limited by proteomic coverage, cross sectional design, and lack of physiologic phenotyping.Hypothesis:Complementary proteomic studies of incident T2D and physiologic responses to an intravenous glucose tolerance test (IVGTT) will identify novel proteins with roles in glucose homeostasis and future risk of T2D.Methods:Cardiovascular Health Study (CHS) and HERITAGE study participants without diabetes underwent SomaScan®profiling of 4,776 plasma proteins. HERITAGE participants underwent IVGTT, from which insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG) were derived. We used Cox regression to test protein associations with 18-year incident T2D in CHS, and multivariable linear regression to test protein associations with IVGTT measures in HERITAGE.Results:In CHS (N = 2631, 74 ± 5 years, 62% female, 14% Black), 57 proteins were significantly associated with incident T2D after comprehensive covariate and multiple testing adjustment. Of these, 44, 9, and 8 were associated with SI, AIRG, and SGrespectively in HERITAGE (N = 752, 35 ± 14 years, 55% female, 38% Black) (Figure). Notable findings include beta-glucuronidase, which associated with increased T2D risk (HR 1.46 per SD increase in log2protein level) and lower SG, suggesting a role in insulin-independent glucose disposal, and thrombospondin-2, which associated with increased T2D risk (HR 1.26 per SD), lower AIRG, and not with SI, indicating that it may be a marker of pancreatic dysfunction.Conclusions:By integrating proteomics from two complementary prospective cohorts using different but related outcomes, we identified 34 novel protein-T2D associations, and characterized their relationship with physiologic axes of glucose metabolism.

Background:High-throughput metabolite profiling allows for the assessment of thousands of metabolites that may participate in exercise-related pathways. Here, we characterize plasma metabolite changes in healthy individuals undergoing endurance exercise training (ET) to identify biochemical features of VO2max and/or those responsive to ET.Methods:We measured 444 known metabolites and 3221 non-targeted metabolite peaks using liquid chromatography tandem mass spectrometry and VO2max using CPET before and after 20 weeks of supervised, endurance ET in 654 sedentary participants (mean age=34y; 39% self-identified Black) from the HERITAGE Study. Multivariate linear regression assessed the relation between metabolites and baseline VO2max (ml·kg–1·min–1), adjusting for age, sex, and race. Changes after ET were determined using paired ttests. We used a false discovery rate (q) <0.05 to determine statistical significance.Results:494 metabolites were associated with VO2max, the majority (375/494) of which were non-targeted (unknown) metabolites with greater effect sizes than targeted peaks [β range: -29.66 - 17.80 and -22.76 - 12.87 for unknown and known metabolites]. We recapitulated known metabolite associations with VO2max including DMGV, branched chain amino acids, and uric acid (Figure 1). 110 of 560 metabolites that changed after ET were associated with VO2max, including non-targeted peaks that concordantly changed after ET (e.g. metabolite peaks positively associated with VO2max that increased with ET; m/z385.3056 and 695.5086; β for VO2max = 9.82 and -19.33, q= 5.56e-7 and 2.61e-17, and log fold-change = 0.03 and -0.01, q=9.58e-13 and 1.93e-4, respectively).Conclusions:We identified novel metabolite peaks associated with VO2max that concordantly changed after ET. Non-targeted metabolomic profiling reveals new markers related to VO2max and exercise response, motivating ongoing work to unambiguously identify these compounds.

IMPORTANCE: Although cardiorespiratory fitness (CRF) is prognostic in older adults, the effect of CRF during early adulthood on long-term cardiovascular structure, function, and prognosis is less clear. OBJECTIVE: To examine whether CRF in young adults is associated with long-term clinical outcome and subclinical cardiovascular disease (CVD). DESIGN, SETTING, AND PARTICIPANTS: Prospective study of 4872 US adults aged 18 to 30 years who underwent treadmill exercise testing at a baseline study visit from March 25, 1985, to June 7, 1986, and 2472 individuals who underwent a second treadmill test 7 years later. Median follow-up was 26.9 years, with assessment of obesity, left ventricular mass and strain, coronary artery calcification (CAC), and vital status and incident CVD. Follow-up was complete on August 31, 2011, and data were analyzed from recruitment through the end of follow-up. MAIN OUTCOMES AND MEASURES: The presence of CAC was assessed by computed tomography at years 15 (2000-2001), 20 (2005-2006), and 25 (2010-2011), and left ventricular mass was assessed at years 5 (1990-1991) and 25 (with global longitudinal strain). Incident CVD and all-cause mortality were adjudicated. RESULTS: Of the 4872 individuals, 273 (5.6%) died and 193 (4.0%) experienced CVD events during follow-up. After comprehensive adjustment, each additional minute of baseline exercise test duration was associated with a 15% lower hazard of death (hazard ratio [HR], 0.85; 95% CI, 0.80-0.91; P &lt; .001) and a 12% lower hazard of CVD (HR, 0.88; 95% CI, 0.81-0.96; P = .002). Higher levels of baseline CRF were associated with significantly lower left ventricular mass index (β = −0.24; 95% CI, −0.45 to −0.03; P = .02) and significantly better lobal longitudinal strain (β = −0.09; 95% CI, −0.14 to −0.05; P &lt; .001) at year 25. Fitness was not associated with CAC. A 1-minute reduction in fitness by year 7 was associated with 21% and 20% increased hazards of death (HR, 1.21; 95% CI, 1.07-1.37; P = .002) and CVD (HR, 1.20; 95% CI, 1.06-1.37; P = .006), respectively, along with a more impaired strain (β = 0.15; 95% CI, 0.08-0.23; P &lt; .001). No association between change in fitness and CAC was found. CONCLUSIONS AND RELEVANCE: Higher levels of fitness at baseline and improvement in fitness early in adulthood are favorably associated with lower risks for CVD and mortality. Fitness and changes in fitness are associated with myocardial hypertrophy and dysfunction but not CAC. Regular efforts to ascertain and improve CRF in young adulthood may play a critical role in promoting cardiovascular health and interrupting early CVD pathogenesis.

Background:Mass spectrometry (MS) profiling has identified over 250 proteins associated with HDL that are thought to underlie the diverse atheroprotective properties of HDL particles and thus may be important biomarkers of cardiovascular disease (CVD) risk. Likewise, recent studies have identified circulating plasma proteins as biomarkers of CVD risk factors and health outcomes. However, few studies have compared the HDL proteome with the circulating plasma proteome.Purpose:The purpose of this analysis was to examine the relationship between the abundance of individual proteins measured in whole plasma and the HDL-sized plasma fraction.Methods:We examined the HDL-sized and circulating plasma proteomes in 156 Black (30%) and White men and women (61%) from the HERITAGE Family Study. HDL was isolated from plasma via gel filtration chromatography and untargeted MS analysis was performed via nano-HPLC-MS/MS. The whole plasma proteome was measured using a modified aptamer (SOMAscan) assay. The correlations between protein abundances in HDL and whole plasma were examined for 101 HDL-associated proteins present in at least 40% of the sample.Results:The abundance of 56 proteins in HDL-sized and whole plasma were significantly (5% FDR) correlated with the strongest correlation for Haptoglobin levels (r=0.83, p=1.1x10-40) (Table 1). The remaining significant correlations ranged from weak to moderate (r= 0.18-0.64) and were found among a mix of frequently and occasionally observed HDL proteins.Discussion:We found that protein abundance measured in HDL-sized and whole plasma were moderately to strongly correlated for several proteins, whereas 45% of protein levels showed no association between HDL-sized and whole plasma fractions. Given the inherit differences in measurement techniques and sources of proteins, it appears that the plasma HDL-sized proteome is mostly distinct from the circulating whole plasma proteome as measured by the SOMAscan assay.

It is not known whether the genes involved with endurance performance during young adulthood are also involved with changes in performance. We examined the associations of gene variants with symptom-limited exercise test duration at baseline and decrease in duration over 20 years.

Introduction:Proteins are important regulators of cardiometabolic health that are increasingly recognized as being modulated by exercise.Hypothesis:We measured approximately 5,000 plasma proteins before and after an endurance exercise training (ET) program to test the hypothesis that proteomic changes are related to adaptations in maximal oxygen uptake (ΔVO2max) and long-term health outcomes.Methods:We applied an affinity-based proteomics platform before and after ET in 654 sedentary participants (mean age = 35, 35% black) from the HERITAGE Study. Subjects performed graded cycle ergometry, exercising at 75% VO2max, 3x/week over the final 6 weeks of a 20-week program. Changes in plasma protein levels after ET were determined using paired ttests. Multivariate linear regression assessed the relationship between Δprotein and ΔVO2max after ET. Statistical significance was determined using a false discovery rate (FDR) <0.05. Multivariate cox proportional hazards regression estimated hazard ratios (HR) of protein levels and all-cause mortality in the Framingham Heart Study (FHS) and Malmo Diet and Cancer Study (MDCS).Results:455 proteins changed after ET, including 306 proteins that increased. Proteins related to the extracellular matrix (ECM) were overrepresented among biologic processes and pathways in enrichment analyses. Absolute changes in five proteins after ET were related to ΔVO2max [FTH1: (β = -31.8, q = 0.009), CDH5 (β = 28.3, q = 0.028), FAP (β = 28.0, q = 0.025), ANGPT2 (β = 28.1, q = 0.028), PRELP (β = 26.6, q = 0.044) after adjustment for age, sex, race, BMI, and baseline VO2max. Fibroblast activation protein (FAP), was positively associated with baseline VO2max (β = 43.6, p = 0.02) and inversely related to all-cause mortality in FHS and MDCS (HR = 0.84 and 0.86, p = 0.0002 and 0.004, respectively).Conclusions:Endurance exercise leads to large-scale plasma proteomic changes, including increased levels of ECM-related proteins. Several novel proteins modulated by ET were associated with ΔVO2max, including FAP, a serine protease relevant in wound healing and metabolism that is inversely associated with mortality in two separate cohorts. External validation and additional efforts to understand FAP’s mechanistic relevance are warranted.

Background:Glycine is a non-essential amino acid that has been inversely associated to coronary heart disease (CHD), with recent data suggesting that this relationship may be mediated by lower blood pressure. Here we tested the hypothesis that circulating levels of glycine are inversely associated with both resting blood pressure (BP) and BP response to exercise - a future predictor of hypertension, and that levels would increase after an endurance exercise training (ET) program.Methods:We used targeted mass spectrometry to measure glycine levels before and after ET in 441 normotensive Caucasian individuals (mean age = 36) from the HERITAGE Family Study. Subjects performed graded supervised cycle ergometry, such that they exercised at 75% VO2max, 50 min/session, 3x/week over the final 6 weeks of a 20-week program. Multivariate linear regression was performed to assess the relationship between glycine and both resting systolic (SBP) and diastolic blood pressure (DBP) at rest and at 50 Watts (W) of cycle ergometry, both before and after the ET program. Changes in plasma glycine levels after ET were determined using paired ttests. Statistical significance was set at p <0.05.Results:Baseline glycine levels were inversely associated with baseline SBP (? = -1.65, p = 0.001) and DBP (? = -1.11, p = 0.002) as well as SBP and DBP at 50W prior to ET (? = -2.33 and -1.35, p = 0.008 and 0.004, respectively) after adjusting for age, sex and BMI. Baseline glycine levels were inversely associated with the changes in SBP and DBP at 50W after ET (? = -2.07 and -1.16, p = 7.1 x 10-6and p = 5.1 x 10-5) after adjustment for age, sex, BMI, and the baseline value of each outcome variable. Glycine levels had a -1.6% median percent change after ET (p-value for paired Student ttest = 0.008).Conclusions:Glycine levels are inversely related to both resting BP and BP during submaximal exercise in apparently healthy subjects, and decrease after chronic ET. Baseline glycine levels are associated with decreased BP responses to submaximal exercise after endurance ET. Additional studies are needed to test for a causal relationship between glycine and blood pressure reduction, and whether alternative exercise modalities may influence glycine levels to a greater extent.