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On Sept 29, 2013, the Framingham Heart Study will celebrate 65 years since the examination of the first volunteer in 1948. During this period, the study has provided substantial insight into the epidemiology and risk factors of cardiovascular disease. The origins of the study are closely linked to the cardiovascular health of President Franklin D Roosevelt and his premature death from hypertensive heart disease and stroke in 1945. In this Review we describe the events leading to the foundation of the Framingham Heart Study, and provide a brief historical overview of selected contributions from the study.

Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling. We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI) was associated with 69 of 217 metabolites (P<0.00023 for all), including aromatic (tyrosine, phenylalanine) and branched chain amino acids (valine, isoleucine, leucine). Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate), the tryptophan pathway (kynurenine, kynurenic acid), and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance [IR] and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine) were distinct from those associated with baseline glucose or other traits. Obesity status appeared to \"modify\" the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals. In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance, and dyslipidemia, but not with fasting glucose or blood pressure traits.

Atrial fibrillation contributes to substantial increases in morbidity and mortality. We aimed to develop a risk score to predict individuals' absolute risk of developing the condition, and to provide a framework for researchers to assess new risk markers. We assessed 4764 participants in the Framingham Heart Study from 8044 examinations (55% women, 45–95 years of age) undertaken between June, 1968, and September, 1987. Thereafter, participants were monitored for the first event of atrial fibrillation for a maximum of 10 years. Multivariable Cox regression identified clinical risk factors associated with development of atrial fibrillation in 10 years. Secondary analyses incorporated routine echocardiographic measurements (5152 participants, 7156 examinations) to reclassify the risk of atrial fibrillation and to assess whether these measurements improved risk prediction. 457 (10%) of the 4764 participants developed atrial fibrillation. Age, sex, body-mass index, systolic blood pressure, treatment for hypertension, PR interval, clinically significant cardiac murmur, and heart failure were associated with atrial fibrillation and incorporated in a risk score (p<0·05, except body-mass index p=0·08), clinical model C statistic 0·78 (95% CI 0·76–0·80). Risk of atrial fibrillation in 10 years varied with age: more than 15% risk was recorded in 53 (1%) participants younger than 65 years, compared with 783 (27%) older than 65 years. Additional incorporation of echocardiographic measurements to enhance the risk prediction model only slightly improved the C statistic from 0·78 (95% CI 0·75–0·80) to 0·79 (0·77–0·82), p=0·005. Echocardiographic measurements did not improve risk reclassification (p=0·18). From clinical factors readily accessible in primary care, our risk score could help to identify risk of atrial fibrillation for individuals in the community, assess technologies or markers for improvement of risk prediction, and target high-risk individuals for preventive measures. US National Institutes of Health.

A recent study adds to growing evidence that natriuretic peptides, secreted by the heart, influence fat metabolism. Mice with impaired clearance of these peptides had reduced fat mass and a metabolism shifted toward the consumption of excess calories. The intimate connection between metabolic disorders and cardiovascular risk is underscored by the focus on “cardiometabolic disease” in practice guidelines and the biomedical literature. Conventional wisdom suggests that the causality flows in one direction: metabolic conditions such as obesity or insulin resistance lead to cardiovascular abnormalities. However, there is increasing recognition that the heart is not just a passive bystander in the process but may play an active role in the defense against metabolic disease, as evidenced by a recent study by Bordicchia et al. 1 The fact that the heart can influence the function of other organs in an endocrine . . .

Despite considerable advances in the treatment of cardiovascular disease, it remains the leading cause of death in developed countries. Assessment of classic cardiovascular risk factors — including high blood pressure, diabetes and smoking — has a central role in disease prevention. However, many individuals with coronary heart disease (a narrowing of the blood vessels that supply the heart) have only one, or none, of the classic risk factors. Thus, new biomarkers are needed to augment the information obtained from traditional indicators and to illuminate disease mechanisms.

Amino acid profiles could aid in diabetes risk assessment, as a five-amino-acid signature had highly significant associations with the development of future diabetes in two large, independent cohorts. Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography–tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine. A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.

Elevated plasma levels of branched chain amino acids detected prior to pancreatic cancer diagnosis may result from whole body tissue breakdown occurring during the early stages of this disease. Most patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed with advanced disease and survive less than 12 months 1 . PDAC has been linked with obesity and glucose intolerance 2 , 3 , 4 , but whether changes in circulating metabolites are associated with early cancer progression is unknown. To better understand metabolic derangements associated with early disease, we profiled metabolites in prediagnostic plasma from individuals with pancreatic cancer (cases) and matched controls from four prospective cohort studies. We find that elevated plasma levels of branched-chain amino acids (BCAAs) are associated with a greater than twofold increased risk of future pancreatic cancer diagnosis. This elevated risk was independent of known predisposing factors, with the strongest association observed among subjects with samples collected 2 to 5 years before diagnosis, when occult disease is probably present. We show that plasma BCAAs are also elevated in mice with early-stage pancreatic cancers driven by mutant Kras expression but not in mice with Kras -driven tumors in other tissues, and that breakdown of tissue protein accounts for the increase in plasma BCAAs that accompanies early-stage disease. Together, these findings suggest that increased whole-body protein breakdown is an early event in development of PDAC.

Black individuals have lower plasma natriuretic peptide (NP) concentrations than white individuals. However, race-based differences in the NP response to physiological perturbations are unknown. In this physiological trial (NCT#03070184), we measured the NP [mid-regional atrial NP (MR-proANP), N-terminal pro-B-type NP (NT-proBNP), and BNP] response to physiological perturbations among healthy, self-identified Black and white participants aged 18-40 years. The primary and secondary outcomes were the change in plasma NP concentrations at 6 weeks after metoprolol (initiated at 50 mg/day and doubled every 2 weeks) and standardized, aerobic exercise (70% of their maximal oxygen uptake on a salt-standardized background), respectively. Among 40 Black [median age: 27 (22, 32) years; 21 (52.5%) women] and 40 white [median age: 25 (20, 30) years; 19 (47.5%) women] participants, exercise increased MR-proANP (Black: 35%; white: 43%), NT-proBNP (Black: 11%; white: 23%), and BNP (Black: 59%; white: 61%) in both self-reported races. Exercise was associated with an increase in plasma MR-proANP (p interaction : 0.25) and BNP (p interaction : 0.87) concentrations which did not vary by self-reported race. However, the increase in plasma NT-proBNP concentrations were higher in white participants than in Black participants. (p interaction : 0.04) Similarly, metoprolol therapy increased MR-proANP (Black: 18%; white: 16%), NT-proBNP (Black: 95%; white: 99%), and BNP (Black: 45%; white: 74%) in both self-reported races. The metoprolol-associated increase in plasma MR-proANP (p interaction : 0.85), NT-proBNP (p interaction : 0.94), and BNP (p interaction : 0.21) concentrations were similar by self-reported race. In conclusion, the higher increase in plasma NT-proBNP concentrationsamong white patients after exercise suggests that exercise may induce significant physiological variations in NP levels. ClinicalTrials.gov ID: NCT03070184. Although Black individuals have been shown to have lower natriuretic peptide concentrations compared to white individuals, the differences in the NP response to physiological perturbations in these two groups are unknown. Here, the authors conduct a physiological clinical trial among young, healthy, normotensive adults to show that white individuals may have a higher increase in NP concentrations compared to Black participants in response to physiological perturbations such as exercise.

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

Unbiased, \"nontargeted\" metabolite profiling techniques hold considerable promise for biomarker and pathway discovery, in spite of the lack of successful applications to human disease. By integrating nontargeted metabolomics, genetics, and detailed human phenotyping, we identified dimethylguanidino valeric acid (DMGV) as an independent biomarker of CT-defined nonalcoholic fatty liver disease (NAFLD) in the offspring cohort of the Framingham Heart Study (FHS) participants. We verified the relationship between DMGV and early hepatic pathology. Specifically, plasma DMGV levels were correlated with biopsy-proven nonalcoholic steatohepatitis (NASH) in a hospital cohort of individuals undergoing gastric bypass surgery, and DMGV levels fell in parallel with improvements in post-procedure cardiometabolic parameters. Further, baseline DMGV levels independently predicted future diabetes up to 12 years before disease onset in 3 distinct human cohorts. Finally, we provide all metabolite peak data consisting of known and unidentified peaks, genetics, and key metabolic parameters as a publicly available resource for investigations in cardiometabolic diseases.