Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.

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.

Plasma Proteomics of Exercise Blood Pressure and Incident Hypertension.

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 ß 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, ß estimate, -3.39; 95% CI, -4.79 to -2.00; P = 2.33 × 10-6; PTGDS: exercise DBP ß 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: ß, -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.

Associations of an HDL apolipoproteomic index with cardiometabolic risk factors before and after exercise training in the HERITAGE Family Study.

BACKGROUND AND AIMS: Previous studies have derived and validated an HDL apolipoproteomic score (pCAD) that predicts coronary artery disease (CAD) risk. However, the associations between pCAD and markers of cardiometabolic health in healthy adults are not known, nor are the effects of regular exercise on pCAD. METHODS: A total of 641 physically inactive adults free of cardiovascular disease from the HERITAGE Family Study completed 20 weeks of exercise training. The pCAD index (range 0-100) was calculated using measurements of apolipoproteins A-I, C-I, C-II, C-III, and C-IV from ApoA-I-tagged serum (higher index = higher CAD risk). The associations between pCAD index and cardiometabolic traits at baseline and their training responses were assessed with Spearman correlation and general linear models. A Bonferroni correction of p < 8.9 × 10-04 was used to determine statistical significance. RESULTS: The mean ± SD baseline pCAD index was 29 ± 32, with 106 (16.5 %) participants classified as high CAD risk. At baseline, pCAD index was positively associated with blood pressure, systemic inflammation, and body composition. HDL size, VO2max, and HDL-C were negatively associated with pCAD index at baseline. Of those classified as high CAD risk at baseline, 52 (49 %) were reclassified as normal risk after training. Following training, pCAD index changes were inversely correlated (p < 1.4 × 10-04) with changes in HDL-C, HDL size, and LDL size. CONCLUSIONS: A higher pCAD index was associated with a worse cardiometabolic profile at baseline but improved with regular exercise. The results from this study highlight the potential role of HDL apolipoproteins as therapeutic targets for lifestyle interventions, particularly in high-risk individuals.

Effects of exercise training on ANGPTL3/8 and ANGPTL4/8 and their associations with cardiometabolic traits.

Angiopoietin-like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of LPL and novel therapeutic targets for dyslipidemia. However, the effects of regular exercise on ANGPTL3/8 and ANGPTL4/8 are unknown. We characterized ANGPTL3/8 and ANGPTL4/8 and their relationship with in vivo measurements of lipase activities and cardiometabolic traits before and after a 5-month endurance exercise training intervention in 642 adults from the HERITAGE (HEalth, RIsk factors, exercise Training And GEnetics) Family Study. At baseline, higher levels of both ANGPTL3/8 and ANGPTL4/8 were associated with a worse lipid, lipoprotein, and cardiometabolic profile, with only ANGPTL3/8 associated with postheparin LPL and HL activities. ANGPTL3/8 significantly decreased with exercise training, which corresponded with increases in LPL activity and decreases in HL activity, plasma triglycerides, apoB, visceral fat, and fasting insulin (all P < 5.1 × 10-4). Exercise-induced changes in ANGPTL4/8 were directly correlated to concomitant changes in total cholesterol, LDL-C, apoB, and HDL-triglycerides and inversely related to change in insulin sensitivity index (all P < 7.0 × 10-4). In conclusion, exercise-induced decreases in ANGPTL3/8 and ANGPTL4/8 were related to concomitant improvements in lipase activity, lipid profile, and cardiometabolic risk factors. These findings reveal the ANGPTL3-4-8 model as a potential molecular mechanism contributing to adaptations in lipid metabolism in response to exercise training.

Omics-driven investigation of the biology underlying intrinsic submaximal working capacity and its trainability.

Submaximal exercise capacity is an indicator of cardiorespiratory fitness with clinical and public health implications. Submaximal exercise capacity and its response to exercise programs are characterized by heritability levels of about 40%. Using physical working capacity (power output) at a heart rate of 150 beats/min (PWC150) as an indicator of submaximal exercise capacity in subjects of the HERITAGE Family Study, we have undertaken multi-omics and in silico explorations of the underlying biology of PWC150 and its response to 20 wk of endurance training. Our goal was to illuminate the biological processes and identify panels of genes associated with human variability in intrinsic PWC150 (iPWC150) and its trainability (dPWC150). Our bioinformatics approach was based on a combination of genome-wide association, skeletal muscle gene expression, and plasma proteomics and metabolomics experiments. Genes, proteins, and metabolites showing significant associations with iPWC150 or dPWC150 were further queried for the enrichment of biological pathways. We compared genotype-phenotype associations of emerging candidate genes with reported functional consequences of gene knockouts in mouse models. We investigated the associations between DNA variants and multiple muscle and cardiovascular phenotypes measured in HERITAGE subjects. Two panels of prioritized genes of biological relevance to iPWC150 (13 genes) and dPWC150 (6 genes) were identified, supporting the hypothesis that genes and pathways associated with iPWC150 are different from those underlying dPWC150. Finally, the functions of these genes and pathways suggested that human variation in submaximal exercise capacity is mainly driven by skeletal muscle morphology and metabolism and red blood cell oxygen-carrying capacity.NEW & NOTEWORTHY Multi-omics and in silico explorations of the genes and underlying biology of submaximal exercise capacity and its response to 20 wk of endurance training were undertaken. Prioritized genes were identified: 13 genes for variation in submaximal exercise capacity in the sedentary state and 5 genes for the response level to endurance training, with no overlap between them. Genes and pathways associated with submaximal exercise capacity in the sedentary state are different from those underlying trainability.

Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma.

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

Plasma Proteomic Kinetics in Response to Acute Exercise.

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 Family Study, 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.

Inverse association between apolipoprotein C-II and cardiovascular mortality: role of lipoprotein lipase activity modulation.

AIMS: Apolipoprotein C-II (ApoC-II) is thought to activate lipoprotein lipase (LPL) and is therefore a possible target for treating hypertriglyceridemia. Its relationship with cardiovascular risk has not been investigated in large-scale epidemiologic studies, particularly allowing for apolipoprotein C-III (ApoC-III), an LPL antagonist. Furthermore, the exact mechanism of ApoC-II-mediated LPL activation is unclear. METHODS AND RESULTS: ApoC-II was measured in 3141 LURIC participants of which 590 died from cardiovascular diseases during a median (inter-quartile range) follow-up of 9.9 (8.7-10.7) years. Apolipoprotein C-II-mediated activation of the glycosylphosphatidylinositol high-density lipoprotein binding protein 1 (GPIHBP1)-LPL complex was studied using enzymatic activity assays with fluorometric lipase and very low-density lipoprotein (VLDL) substrates. The mean ApoC-II concentration was 4.5 (2.4) mg/dL. The relationship of ApoC-II quintiles with cardiovascular mortality exhibited a trend toward an inverse J-shape, with the highest risk in the first (lowest) quintile and lowest risk in the middle quintile. Compared with the first quintile, all other quintiles were associated with decreased cardiovascular mortality after multivariate adjustments including ApoC-III as a covariate (all P < 0.05). In experiments using fluorometric substrate-based lipase assays, there was a bell-shaped relationship for the effect of ApoC-II on GPIHBP1-LPL activity when exogenous ApoC-II was added. In ApoC-II-containing VLDL substrate-based lipase assays, GPIHBP1-LPL enzymatic activity was almost completely blocked by a neutralizing anti-ApoC-II antibody. CONCLUSION: The present epidemiologic data suggest that increasing low circulating ApoC-II levels may reduce cardiovascular risk. This conclusion is supported by the observation that optimal ApoC-II concentrations are required for maximal GPIHBP1-LPL enzymatic activity.

Plasma proteomic changes in response to exercise training are associated with cardiorespiratory fitness adaptations.

Regular exercise leads to widespread salutary effects, and there is increasing recognition that exercise-stimulated circulating proteins can impart health benefits. Despite this, limited data exist regarding the plasma proteomic changes that occur in response to regular exercise. Here, we perform large-scale plasma proteomic profiling in 654 healthy human study participants before and after a supervised, 20-week endurance exercise training intervention. We identify hundreds of circulating proteins that are modulated, many of which are known to be secreted. We highlight proteins involved in angiogenesis, iron homeostasis, and the extracellular matrix, many of which are novel, including training-induced increases in fibroblast activation protein (FAP), a membrane-bound and circulating protein relevant in body-composition homeostasis. We relate protein changes to training-induced maximal oxygen uptake adaptations and validate our top findings in an external exercise cohort. Furthermore, we show that FAP is positively associated with survival in 3 separate, population-based cohorts.

Genetic control of body weight by the human brain proteome.

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with body weight but the biological relevance of most remains unexplored. Given the critical role of the brain in body weight regulation, we set out to determine whether genetic variants linked with body mass index (BMI) could be mapped to brain proteins. Using genetic colocalization, we mapped 25 loci from the largest BMI GWAS (n = 806,834) to brain protein concentrations obtained from publicly available datasets. We also performed a proteome-wide Mendelian randomization on 696 brain proteins followed by genetic colocalization and identified 35 additional brain proteins. Only a minority of these proteins (<30%) had a colocalization signal with cortex gene expression levels, highlighting the value of moving beyond gene expression levels and examining brain protein levels. In conclusion, we identified 60 unique proteins expressed in the brain that may be critical regulators of body weight in humans.

Plasma Proteomic Risk Markers of Incident Type 2 Diabetes Reflect Physiologically Distinct Components of Glucose-Insulin Homeostasis.

High-throughput proteomics allows researchers to simultaneously explore the roles of thousands of biomarkers in the pathophysiology of diabetes. We conducted proteomic association studies of incident type 2 diabetes and physiologic responses to an intravenous glucose tolerance test (IVGTT) to identify novel protein contributors to glucose homeostasis and diabetes risk. We tested 4,776 SomaScan proteins measured in relation to 18-year incident diabetes risk in participants from the Cardiovascular Health Study (N = 2,631) and IVGTT-derived measures in participants from the HERITAGE Family Study (N = 752). We characterize 51 proteins that were associated with longitudinal diabetes risk, using their respective 39, 9, and 8 concurrent associations with insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG). Twelve of the 51 diabetes associations appear to be novel, including ß-glucuronidase, which was associated with increased diabetes risk and lower SG, suggesting an alternative pathway to insulin for glucose disposal; and plexin-B2, which also was associated with increased diabetes risk, but with lower AIRG, and not with SI, indicating a mechanism related instead to pancreatic dysfunction. Other novel protein associations included alcohol dehydrogenase-1C, fructose-bisphosphate aldolase-B, sorbitol dehydrogenase with elevated type 2 diabetes risk, and a leucine-rich repeat containing protein-15 and myocilin with decreased risk. ARTICLE HIGHLIGHTS: Plasma proteins are associated with the risk of incident diabetes in older adults independent of various demographic, lifestyle, and biochemical risk factors. These same proteins are associated with subtle differences in measures of glucose homeostasis earlier in life. Proteins that are associated with lower insulin sensitivity in individuals without diabetes tend to be associated with appropriate compensatory mechanisms, such as a stronger acute insulin response or higher glucose effectiveness. Proteins that are associated with future diabetes risk, but not with insulin insensitivity, tend to be associated with lower glucose effectiveness and/or impaired acute insulin response.

Effect of individual characteristics and aerobic training on the %HRR-%V̇O2R relationship.

This study aimed to assess if, during incremental exercise, considering individual characteristics can make the relationship between the percentages of heart rate (HRR) and oxygen uptake (V̇O2R) reserve either 1:1 or more accurate. Cycle ergometer data of the maximal incremental exercise tests performed by 450 healthy and sedentary participants (17-66 years) of the HERITAGE Family Study, grouped for sex, ethnicity, age, body fat, resting HR, and V̇O2max, were used to calculate the individual linear regressions between %HRR and %V̇O2R. The mean slope and intercept of the individual linear regressions of each subgroup were compared with 1 and 0 (identity line), respectively, using Hotelling tests followed by post-hoc one-sample t-tests. Two multiple linear regressions were also performed, using either the slopes or intercepts of the individual linear regressions as dependent variables and sex, age, resting HR, and V̇O2max as independent variables. The mean %HRR-%V̇O2R relationships of all subgroups differed from the identity line. Moreover, individual linear regression intercepts (8.9 ± 16.0) and slopes (0.971 ± 0.190) changed (p < 0.001) after 20 weeks of aerobic training (13.1 ± 11.1 and 0.891 ± 0.122). The multiple linear regressions could explain only 3.8% and 1.3% of the variance in the intercepts and slopes, whose variability remained high (standard error of estimate of 15.8 and 0.189). In conclusion, the %HRR-%V̇O2R relationship differs from the identity line regardless of individual characteristics and their difference increased after aerobic training. Moreover, due to the high interindividual variability, using a single equation for the whole population seems not suitable for representing the %HRR-%V̇O2R relationship of a given subject, even when several individual characteristics are considered.HighlightsThe association between %HRR and %V̇O2R is not 1:1 even when individuals are grouped by age, sex, ethnicity, body composition, HRrest, and V̇O2max.Using several subject characteristics to identify the individual's %HRR-%V̇O2R relationship does not meaningfully increase its prediction accuracy or reduce the interindividual variability of %HRR-%V̇O2R relationshipsUsing a single equation for the whole population is not suitable for representing the relationship of a given subject; hence, individual relationships should be preferred when prescribing the intensity of aerobic exercise.The individual %HRR-%V̇O2R relationship should be periodically assessed due to the potential training induced changes in the relationship.

Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals.

Integrating genetic information with metabolomics has provided new insights into genes affecting human metabolism. However, gene-metabolite integration has been primarily studied in individuals of European Ancestry, limiting the opportunity to leverage genomic diversity for discovery. In addition, these analyses have principally involved known metabolites, with the majority of the profiled peaks left unannotated. Here, we perform a whole genome association study of 2,291 metabolite peaks (known and unknown features) in 2,466 Black individuals from the Jackson Heart Study. We identify 519 locus-metabolite associations for 427 metabolite peaks and validate our findings in two multi-ethnic cohorts. A significant proportion of these associations are in ancestry specific alleles including findings in APOE, TTR and CD36. We leverage tandem mass spectrometry to annotate unknown metabolites, providing new insight into hereditary diseases including transthyretin amyloidosis and sickle cell disease. Our integrative omics approach leverages genomic diversity to provide novel insights into diverse cardiometabolic diseases.

Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods.

High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K (N = 1301 reagents), the SomaScan5K platform (N = 4979 reagents), and the Olink Explore (N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.

The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers.

The aim of the HERITAGE Family Study was to investigate individual differences in response to a standardized endurance exercise program, the role of familial aggregation, and the genetics of response levels of cardiorespiratory fitness and cardiovascular disease and diabetes risk factors. Here we summarize the findings and their potential implications for cardiometabolic health and cardiorespiratory fitness. It begins with overviews of background and planning, recruitment, testing and exercise program protocol, quality control measures, and other relevant organizational issues. A summary of findings is then provided on cardiorespiratory fitness, exercise hemodynamics, insulin and glucose metabolism, lipid and lipoprotein profiles, adiposity and abdominal visceral fat, blood levels of steroids and other hormones, markers of oxidative stress, skeletal muscle morphology and metabolic indicators, and resting metabolic rate. These summaries document the extent of the individual differences in response to a standardized and fully monitored endurance exercise program and document the importance of familial aggregation and heritability level for exercise response traits. Findings from genomic markers, muscle gene expression studies, and proteomic and metabolomics explorations are reviewed, along with lessons learned from a bioinformatics-driven analysis pipeline. The new opportunities being pursued in integrative -omics and physiology have extended considerably the expected life of HERITAGE and are being discussed in relation to the original conceptual model of the study.

Regular exercise and patterns of response across multiple cardiometabolic traits: the HERITAGE family study.

OBJECTIVES: We investigated whether high responsiveness or low responsiveness to exercise training aggregates in the same individuals across seven cardiometabolic traits. METHODS: A 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. RESULTS: Only 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. CONCLUSIONS: Interindividual 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.

Dietary Mediators of the Genetic Susceptibility to Obesity-Results from the Quebec Family Study.

BACKGROUND: Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity. OBJECTIVE: This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity. METHODS: This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach. RESULTS: The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (ß = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (ß = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (ß = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (ß = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (ß = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (ß = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC. CONCLUSIONS: The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.