Capillary blood self-collection for high-throughput proteomics.

In this study, we sought to compare protein concentrations obtained from a high-throughput proteomics platform (Olink) on samples collected using capillary blood self-collection (with the Tasso+ device) versus standard venipuncture (control). Blood collection was performed on 20 volunteers, including one sample obtained via venipuncture and two via capillary blood using the Tasso+ device. Tasso+ samples were stored at 2°C-8°C for 24-hs (Tasso-24) or 48-h (Tasso-48) prior to processing to simulate shipping times from a study participant's home. Proteomics were analyzed using Olink (384 Inflammatory Panel). Tasso+ blood collection was successful in 37/40 attempts. Of 230 proteins included in our analysis, Pearson correlations (r) and mean coefficient of variation (CV) between Tasso-24 or Tasso-48 versus venipuncture were variable. In the Tasso-24 analysis, 34 proteins (14.8%) had both a correlation r > 0.5 and CV < 0.20. In the Tasso-48 analysis, 68 proteins (29.6%) had a correlation r > 0.5 and CV < 0.20. Combining the Tasso-24 and Tasso-48 analyses, 26 (11.3%) proteins met these thresholds. We concluded that protein concentrations from Tasso+ samples processed 24-48 h after collection demonstrated wide technical variability and variable correlation with a venipuncture gold-standard. Use of home capillary blood self-collection for large-scale proteomics should be limited to select proteins with good agreement with venipuncture.

Metabolic liability for weight gain in early adulthood.

While weight gain is associated with a host of chronic illnesses, efforts in obesity have relied on single "snapshots" of body mass index (BMI) to guide genetic and molecular discovery. Here, we study >2,000 young adults with metabolomics and proteomics to identify a metabolic liability to weight gain in early adulthood. Using longitudinal regression and penalized regression, we identify a metabolic signature for weight liability, associated with a 2.6% (2.0%-3.2%, p = 7.5 × 10-19) gain in BMI over ≈20 years per SD higher score, after comprehensive adjustment. Identified molecules specified mechanisms of weight gain, including hunger and appetite regulation, energy expenditure, gut microbial metabolism, and host interaction with external exposure. Integration of longitudinal and concurrent measures in regression with Mendelian randomization highlights the complexity of metabolic regulation of weight gain, suggesting caution in interpretation of epidemiologic or genetic effect estimates traditionally used in metabolic research.

Human metabolic chambers reveal a coordinated metabolic-physiologic response to nutrition.

The emerging field of precision nutrition is based on the notion that inter-individual responses across diets of different calorie-macronutrient content may contribute to inter-individual differences in metabolism, adiposity, and weight gain. Free-living diet studies have been traditionally challenged by difficulties in controlling adherence to prescribed calories and macronutrient content and rarely allow a period of metabolic stability prior to metabolic measures (to minimize influences of weight changes). In this context, key physiologic measures central to precision nutrition responses may be most precisely quantified via whole room indirect calorimetry over 24-h, in which precise control of activity and nutrition can be achieved. In addition, these studies represent unique "N of 1" human crossover metabolic-physiologic experiments during which specific molecular pathways central to nutrient metabolism may be discerned. Here, we quantified 263 circulating metabolites during a ≈40-day inpatient admission in which up to 94 participants underwent seven monitored 24-h nutritional interventions of differing macronutrient composition in a whole-room indirect calorimeter to capture precision metabolic responses. Broadly, we observed heterogenous responses in metabolites across dietary chambers, with the exception of carnitines which tracked with 24-h respiratory quotient. We identified excursions in shared metabolic species (e.g., carnitines, glycerophospholipids, amino acids) that mapped onto gold-standard calorimetric measures of substrate oxidation preference and lipid availability. These findings support a coordinated metabolic-physiologic response to nutrition, highlighting the relevance of these controlled settings to uncover biological pathways of energy utilization during precision nutrition studies.

Proteomics, Human Environmental Exposure, and Cardiometabolic Risk.

BACKGROUND: The biological mechanisms linking environmental exposures with cardiovascular disease pathobiology are incompletely understood. We sought to identify circulating proteomic signatures of environmental exposures and examine their associations with cardiometabolic and respiratory disease in observational cohort studies. METHODS: We tested the relations of >6500 circulating proteins with 29 environmental exposures across the built environment, green space, air pollution, temperature, and social vulnerability indicators in ≈3000 participants of the CARDIA study (Coronary Artery Risk Development in Young Adults) across 4 centers using penalized and ordinary linear regression. In >3500 participants from FHS (Framingham Heart Study) and JHS (Jackson Heart Study), we evaluated the prospective relations of proteomic signatures of the envirome with cardiovascular disease and mortality using Cox models. RESULTS: Proteomic signatures of the envirome identified novel/established cardiovascular disease-relevant pathways including DNA damage, fibrosis, inflammation, and mitochondrial function. The proteomic signatures of the envirome were broadly related to cardiometabolic disease and respiratory phenotypes (eg, body mass index, lipids, and left ventricular mass) in CARDIA, with replication in FHS/JHS. A proteomic signature of social vulnerability was associated with a composite of cardiovascular disease/mortality (1428 events; FHS: hazard ratio, 1.16 [95% CI, 1.08-1.24]; P=1.77×10-5; JHS: hazard ratio, 1.25 [95% CI, 1.13-1.38]; P=6.38×10-6; hazard ratioexpressed as per 1 SD increase in proteomic signature), robust to adjustment for known clinical risk factors. CONCLUSIONS: Environmental exposures are related to an inflammatory-metabolic proteome, which identifies individuals with cardiometabolic disease and respiratory phenotypes and outcomes. Future work examining the dynamic impact of the environment on human cardiometabolic health is warranted.

Targeted Proteomics Reveals Functional Targets for Early Diabetes Susceptibility in Young Adults.

BACKGROUND: The circulating proteome may encode early pathways of diabetes susceptibility in young adults for surveillance and intervention. Here, we define proteomic correlates of tissue phenotypes and diabetes in young adults. METHODS: We used penalized models and principal components analysis to generate parsimonious proteomic signatures of diabetes susceptibility based on phenotypes and on diabetes diagnosis across 184 proteins in >2000 young adults in the CARDIA (Coronary Artery Risk Development in Young Adults study; mean age, 32 years; 44% women; 43% Black; mean body mass index, 25.6±4.9 kg/m2), with validation against diabetes in >1800 individuals in the FHS (Framingham Heart Study) and WHI (Women's Health Initiative). RESULTS: In 184 proteins in >2000 young adults in CARDIA, we identified 2 proteotypes of diabetes susceptibility-a proinflammatory fat proteotype (visceral fat, liver fat, inflammatory biomarkers) and a muscularity proteotype (muscle mass), linked to diabetes in CARDIA and WHI/FHS. These proteotypes specified broad mechanisms of early diabetes pathogenesis, including transorgan communication, hepatic and skeletal muscle stress responses, vascular inflammation and hemostasis, fibrosis, and renal injury. Using human adipose tissue single cell/nuclear RNA-seq, we demonstrate expression at transcriptional level for implicated proteins across adipocytes and nonadipocyte cell types (eg, fibroadipogenic precursors, immune and vascular cells). Using functional assays in human adipose tissue, we demonstrate the association of expression of genes encoding these implicated proteins with adipose tissue metabolism, inflammation, and insulin resistance. CONCLUSIONS: A multifaceted discovery effort uniting proteomics, underlying clinical susceptibility phenotypes, and tissue expression patterns may uncover potentially novel functional biomarkers of early diabetes susceptibility in young adults for future mechanistic evaluation.

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver.

Metabolic dysfunction-associated steatotic liver disease (MASLD) prevalence is increasing in parallel with an obesity pandemic, calling for novel strategies for prevention and treatment. We defined a circulating proteome of human MASLD across ≈7000 proteins in ≈5000 individuals from diverse, at-risk populations across the metabolic health spectrum, demonstrating reproducible diagnostic performance and specifying both known and novel metabolic pathways relevant to MASLD (central carbon and amino acid metabolism, hepatocyte regeneration, inflammation, fibrosis, insulin sensitivity). A parsimonious proteomic signature of MASLD was associated with a protection from MASLD and its related multi-system metabolic consequences in >26000 free-living individuals, with an additive effect to polygenic risk. The MASLD proteome was encoded by genes that demonstrated transcriptional enrichment in liver, with spatial transcriptional activity in areas of steatosis in human liver biopsy and dynamicity for select targets in human liver across stages of steatosis. We replicated several top relations from proteomics and spatial tissue transcriptomics in a humanized "liver-on-a-chip" model of MASLD, highlighting the power of a full translational approach to discovery in MASLD. Collectively, these results underscore utility of blood-based proteomics as a dynamic "liquid biopsy" of human liver relevant to clinical biomarker and mechanistic applications.

Implications of metabolism on multi-systems healthy aging across the lifespan.

Aging is increasingly thought to involve dysregulation of metabolism in multiple organ systems that culminate in decreased functional capacity and morbidity. Here, we seek to understand complex interactions among metabolism, aging, and systems-wide phenotypes across the lifespan. Among 2469 adults (mean age 74.7 years; 38% Black) in the Health, Aging and Body Composition study we identified metabolic cross-sectionally correlates across 20 multi-dimensional aging-related phenotypes spanning seven domains. We used LASSO-PCA and bioinformatic techniques to summarize metabolome-phenome relationships and derive metabolic scores, which were subsequently linked to healthy aging, mortality, and incident outcomes (cardiovascular disease, disability, dementia, and cancer) over 9 years. To clarify the relationship of metabolism in early adulthood to aging, we tested association of these metabolic scores with aging phenotypes/outcomes in 2320 participants (mean age 32.1, 44% Black) of the Coronary Artery Risk Development in Young Adults (CARDIA) study. We observed significant overlap in metabolic correlates across the seven aging domains, specifying pathways of mitochondrial/cellular energetics, host-commensal metabolism, inflammation, and oxidative stress. Across four metabolic scores (body composition, mental-physical performance, muscle strength, and physical activity), we found strong associations with healthy aging and incident outcomes, robust to adjustment for risk factors. Metabolic scores for participants four decades younger in CARDIA were related to incident cardiovascular, metabolic, and neurocognitive performance, as well as long-term cardiovascular disease and mortality over three decades. Conserved metabolic states are strongly related to domain-specific aging and outcomes over the life-course relevant to energetics, host-commensal interactions, and mechanisms of innate immunity.

Proteomic architecture of frailty across the spectrum of cardiovascular disease.

While frailty is a prominent risk factor in an aging population, the underlying biology of frailty is incompletely described. Here, we integrate 979 circulating proteins across a wide range of physiologies with 12 measures of frailty in a prospective discovery cohort of 809 individuals with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation. Our aim was to characterize the proteomic architecture of frailty in a highly susceptible population and study its relation to clinical outcome and systems-wide phenotypes to define potential novel, clinically relevant frailty biology. Proteomic signatures (specifically of physical function) were related to post-intervention outcome in AS, specifying pathways of innate immunity, cell growth/senescence, fibrosis/metabolism, and a host of proteins not widely described in human aging. In published cohorts, the "frailty proteome" displayed heterogeneous trajectories across age (20-100 years, age only explaining a small fraction of variance) and were associated with cardiac and non-cardiac phenotypes and outcomes across two broad validation cohorts (N > 35,000) over ≈2-3 decades. These findings suggest the importance of precision biomarkers of underlying multi-organ health status in age-related morbidity and frailty.

Physical Activity Over the Lifecourse and Cardiovascular Disease.

Despite improvements in cardiovascular care in recent decades, cardiovascular disease (CVD) remains a leading cause of death worldwide. At its core, CVD is a largely preventable disease with diligent risk factor management and early detection. As highlighted in the American Heart Association's Life's Essential 8, physical activity plays a central role in CVD prevention at an individual and population level. Despite pervasive knowledge of the numerous cardiovascular and noncardiovascular health benefits of physical activity, physical activity has steadily decreased over time and unfavorable changes in physical activity occur throughout people's lives. Here, we use a lifecourse framework to examine the evidence reporting on the association of physical activity with CVD. From in utero to older adults, we review and discuss the evidence detailing how physical activity may prevent incident CVD and mitigate CVD-related morbidity and death across all life stages.

Metabolic Signatures of Cardiac Dysfunction, Multimorbidity, and Post-Transcatheter Aortic Valve Implantation Death.

Background Studies in mice and small patient subsets implicate metabolic dysfunction in cardiac remodeling in aortic stenosis, but no large comprehensive studies of human metabolism in aortic stenosis with long-term follow-up and characterization currently exist. Methods and Results Within a multicenter prospective cohort study, we used principal components analysis to summarize 12 echocardiographic measures of left ventricular structure and function pre-transcatheter aortic valve implantation in 519 subjects (derivation). We used least absolute shrinkage and selection operator regression across 221 metabolites to define metabolic signatures for each structural pattern and measured their relation to death and multimorbidity in the original cohort and up to 2 validation cohorts (N=543 for overall validation). In the derivation cohort (519 individuals; median age, 84 years, 45% women, 95% White individuals), we identified 3 axes of left ventricular remodeling, broadly specifying systolic function, diastolic function, and chamber volumes. Metabolite signatures of each axis specified both known and novel pathways in hypertrophy and cardiac dysfunction. Over a median of 3.1 years (205 deaths), a metabolite score for diastolic function was independently associated with post-transcatheter aortic valve implantation death (adjusted hazard ratio per 1 SD increase in score, 1.54 [95% CI, 1.25-1.90]; P<0.001), with similar effects in each validation cohort. This metabolite score of diastolic function was simultaneously associated with measures of multimorbidity, suggesting a metabolic link between cardiac and noncardiac state in aortic stenosis. Conclusions Metabolite profiles of cardiac structure identify individuals at high risk for death following transcatheter aortic valve implantation and concurrent multimorbidity. These results call for efforts to address potentially reversible metabolic biology associated with risk to optimize post-transcatheter aortic valve implantation recovery, rehabilitation, and survival.

Beta-blocker use and mortality among patients with systolic heart failure and pacemaker rhythm.

AIMS: Beta-blockers are proven to improve survival among patients with heart failure with reduced ejection fraction. Their efficacy in patients with heart failure with reduced ejection fraction and pacemaker devices has not been demonstrated. Our aim was to test the hypothesis that beta-blocker therapy is associated with improved survival in patients with chronic heart failure and a pacemaker rhythm on electrocardiogram (ECG). METHODS AND RESULTS: This is a post hoc analysis from the GISSI-HF randomized clinical trial. We evaluated efficacy of beta-blockers by creating Cox proportional hazards models adjusting for pacemaker rhythm and heart rate, among other variables. Interactions between pacemaker rhythm, heart rate, and beta-blocker were also examined. Of the 6975 patients enrolled in the GISSI-HF trial, 813 (11.7%) had a pacemaker rhythm on baseline ECG. Of these 813 patients, 511 (62.9%) were receiving beta-blocker therapy. The effect of beta-blocker therapy on mortality was assessed using multivariable Cox proportional hazards adjusted for 27 co-variates. In the whole cohort, beta-blocker therapy was significantly associated with reduced mortality (hazard ratio 0.79 [0.72-0.87], P < 0.001), without interaction between beta-blockers, pacemaker rhythm and heart rate. Beta-blocker therapy was beneficial in the sub-group restricted to baseline pacemaker rhythm (hazard ratio 0.62 [0.49-0.79], P < 0.001). CONCLUSIONS: Beta-blocker therapy is associated with improved survival among patients with heart failure and a pacemaker rhythm on ECG. Further studies are necessary to analyse differences between atrial and ventricular pacemakers.

The inflammatory proteome, obesity, and medical weight loss and regain in humans.

OBJECTIVE: Weight regain occurs after medical weight loss via mechanisms of post-weight-loss "metabolic adaptation." The relationship of inflammatory proteins with weight loss/regain was studied to determine a role for inflammation in metabolic adaptation. METHODS: Seventy-four proteins central to inflammation and immune regulation (Olink) were analyzed in plasma from up to 490 participants in a trial of medical weight-loss maintenance. Cross-sectional and longitudinal associations of proteins with weight were measured using linear and mixed effects regression models and t testing, with replication in the Framingham Heart Study. RESULTS: Broad changes in the inflammatory proteome were observed among the study cohort (60% women, 35% African American) with initial weight loss of ≈8 kg from a median 94 kg at study entry (33/74 proteins; 7 increased; 26 decreased), many of which tracked with weight regain of median ≈2 kg over the next 30 months. Ten proteins were associated with different rates of weight regain, some specifying pathways of chemotaxis and innate immune responses. Several of the observed protein associations were also linked to prevalent obesity in the Framingham Heart Study. CONCLUSIONS: Broad changes in the inflammatory proteome track with changes in weight and may identify specific pathways that modify patterns of weight regain.

Association of Longitudinal Activity Measures and Diabetes Risk: An Analysis From the National Institutes of Health All of Us Research Program.

CONTEXT: Prior studies of the relationship between physical activity and incident type 2 diabetes mellitus (T2DM) relied primarily on questionnaires at a single time point. OBJECTIVE: We sought to investigate the relationship between physical activity and incident T2DM with an innovative approach using data from commercial wearable devices linked to electronic health records in a real-world population. METHODS: Using All of Us participants' accelerometer data from their personal Fitbit devices, we used a time-varying Cox proportional hazards models with repeated measures of physical activity for the outcome of incident T2DM. We evaluated for effect modification with age, sex, body mass index (BMI), and sedentary time using multiplicative interaction terms. RESULTS: From 5677 participants in the All of Us Research Program (median age 51 years; 74% female; 89% White), there were 97 (2%) cases of incident T2DM over a median follow-up period of 3.8 years between 2010 to 2021. In models adjusted for age, sex, and race, the hazard of incident diabetes was reduced by 44% (95% CI, 15%-63%; P = 0.01) when comparing those with an average daily step count of 10 700 to those with 6000. Similar benefits were seen comparing groups based on average duration of various intensities of activity (eg, lightly active, fairly active, very active). There was no evidence for effect modification by age, sex, BMI, or sedentary time. CONCLUSION: Greater time in any type of physical activity intensity was associated with lower risk of T2DM irrespective of age, sex, BMI, or sedentary time.

Global Longitudinal Strain and Biomarkers of Cardiac Damage and Stress as Predictors of Outcomes After Transcatheter Aortic Valve Implantation.

Background Global longitudinal strain (GLS) is a sensitive measure of left ventricular function and a risk marker in severe aortic stenosis. We sought to determine whether biomarkers of cardiac damage (cardiac troponin) and stress (NT-proBNP [N-terminal pro-B-type natriuretic peptide]) could complement GLS to identify patients with severe aortic stenosis at highest risk. Methods and Results From a multicenter prospective cohort of patients with symptomatic severe aortic stenosis who underwent transcatheter aortic valve implantation, we measured absolute GLS (aGLS), cardiac troponin, and NT-proBNP at baseline in 499 patients. Left ventricular ejection fraction <50% was observed in 19% and impaired GLS (aGLS <15%) in 38%. Elevations in cardiac troponin and NT-proBNP were present in 79% and 89% of those with impaired GLS, respectively, as compared with 63% and 60% of those with normal GLS, respectively (P<0.001 for each). aGLS <15% was associated with increased mortality in univariable analysis (P=0.009), but, in a model with both biomarkers, aGLS, and clinical covariates included, aGLS was not associated with mortality; elevation in each biomarker was associated with an increased hazard of mortality (adjusted hazard ratio, >2; P≤0.002 for each) when the other biomarker was elevated, but not when the other biomarker was normal (interaction P=0.015). Conclusions Among patients with symptomatic severe aortic stenosis undergoing transcatheter aortic valve implantation, elevations in circulating cardiac troponin and NT-proBNP are more common as GLS worsens. Biomarkers of cardiac damage and stress are independently associated with mortality after transcatheter aortic valve implantation, whereas GLS is not. These findings may have implications for risk stratification of asymptomatic patients to determine optimal timing of valve replacement.

Association of change in QRS duration with chronic heart failure outcomes.

QRS duration is an established risk factor among patients with heart failure. How change in QRS duration relates to heart failure outcomes has had limited study. In this post-hoc analysis of the Beta-Blocker Evaluation of Survival Trial, we demonstrated that QRS duration change from baseline to 3 months is independently associated with long-term survival and left ventricle ejection fraction.

Long-Term Outcomes and Risk Stratification of Patients With Heart Failure With Recovered Ejection Fraction.

This study aimed to understand the long-term outcomes of patients with heart failure with recovered ejection fraction, identify predictors of adverse events, and develop a risk stratification model. From an academic healthcare system, we retrospectively identified 133 patients (median age 66, 38% female, 30% ischemic etiology) who had an improvement in left ventricular ejection fraction (LVEF) from <40% to ≥53%. Significant predictors of all-cause mortality, hospitalization, and future reduction in LVEF were identified through Cox regression analysis. Kaplan-Meier survival was 70% at 5 years. Freedom from hospitalization was 58% at 1 year, and the risk of future LVEF reduction to <40% was 28% at 3 years. Diuretic dose and B-type natriuretic peptide (BNP) at the time of LVEF recovery were the strongest predictors of mortality and hospitalization in multivariate-adjusted analysis (BNP hazard ratio 1.13 per 100 pg/ml increase [p <0.01]; furosemide-equivalent dose hazard ratio 1.19 per 40 mg increase [p = 0.02]). An all-cause mortality Cox proportional hazard risk model incorporating New York Heart Association functional class, BNP and diuretic dose at the time of recovery showed excellent risk discrimination (c-statistic 0.79) and calibration. In conclusion, patients with heart failure with recovered ejection fraction have heterogenous clinical outcomes and are not "cured." A risk model using New York Heart Association functional class, BNP, and diuretic dose can accurately stratify mortality risk.

Optimal Threshold of Left Ventricular Ejection Fraction for Aortic Valve Replacement in Asymptomatic Severe Aortic Stenosis: A Systematic Review and Meta-Analysis.

Background The optimal threshold of left ventricular ejection fraction (LVEF) that should prompt aortic valve replacement (AVR) in asymptomatic patients with high-gradient severe aortic stenosis (AS) is controversial. The aim of this study was to assess the relationship between LVEF and mortality benefit in comparing early AVR versus watchful waiting in asymptomatic patients with severe AS. Methods and Results MEDLINE, Embase, Web of Science, and Google Scholar were searched for observational studies and randomized controlled trials on adults with asymptomatic severe AS. Severe AS was defined by a peak aortic velocity ≥4 m/s and/or mean aortic valve gradient ≥40 mm Hg and/or calculated aortic valve area <1.0 cm2 or an indexed valve area <0.6 cm2. Studies comparing AVR with conservative management were included and meta-analysis on all-cause mortality was performed. Ten eligible studies were identified with a total of 3332 patients. In 5 observational studies comparing early AVR versus watchful waiting, our meta-analysis showed early AVR was associated with lower mortality with a hazard ratio (HR) of 0.41 (CI, 0.23-0.71; P<0.01). In 4 observational studies comparing AVR versus no AVR, our meta-analysis showed AVR was associated with lower mortality with a HR of 0.31 (CI, 0.17-0.58; P<0.001). In a meta-regression analysis pooling all 10 studies, there was no statistically significant correlation between study mean LVEF and the size of mortality benefit of AVR (P=0.83). Conclusions Among asymptomatic patients with high-gradient severe AS, AVR was associated with a mortality benefit across the spectrum of LVEF. Our study calls into question the need of an LVEF threshold for recommending AVR in this patient population.

Improvement of ejection fraction and mortality in ischaemic heart failure.

OBJECTIVE: The frequency and predictors of improvement in left ventricular ejection fraction (LVEF) in ischaemic cardiomyopathy and its association with mortality is poorly understood. We sought to assess the predictors of LVEF improvement ≥10% and its effect on mortality. METHODS: We compared characteristics of patients enrolled in The Surgical Treatment for Ischaemic Heart Failure (STICH) trial with and without improvement of LVEF ≥10% at 24 months. A logistic regression model was constructed to determine the independent predictors of LVEF improvement. A Cox proportional hazards model was created to assess the independent association of improvement in LVEF ≥10% with mortality. RESULTS: Of the 1212 patients enrolled in STICH, 618 underwent echocardiographic assessment of LVEF at baseline and 24 months. Of the patients randomised to medical therapy plus coronary artery bypass graft surgery (CABG), 58 (19%) had an improvement in LVEF >10% compared with 51 (16%) patients assigned to medical therapy alone (p=0.30). Independent predictors of LVEF improvement >10% included prior myocardial infarction (OR 0.44, 95% CI: 0.28 to 0.71, p=0.001) and lower baseline LVEF (OR 0.94, 95% CI: 0.91 to 0.97, p<0.001). Improvement in LVEF >10% (HR 0.61, 95% CI: 0.44 to 0.84, p=0.004) and randomisation to CABG (HR 0.72, 95% CI: 0.57 to 0.90, p=0.004) were independently associated with a reduced hazard of mortality. CONCLUSIONS: Improvement of LVEF ≥10% at 24 months was uncommon in patients with ischaemic cardiomyopathy, did not differ between patients assigned to CABG and medical therapy or medical therapy alone and was independently associated with reduced mortality. TRIAL REGISTRATION NUMBER: NCT00023595.

A model of long-term metabolic progression of type 2 diabetes mellitus for evaluating treatment strategies.

AIM: To develop a novel metabolic computer model of the natural lifetime progression of type 2 diabetes that generates dynamic risk factor trajectories consistent with prespecified lifetime therapeutic strategies, in order to enhance the long-term economic and outcome modelling of type 2 diabetes and its complications. METHODS: The main model drivers of progressive disease were changes in insulin sensitivity and islet beta-cell function derived from an analysis of follow-up results from the Belfast Diet Study. These were related to clinical measures through an adaptation of the homeostasis model assessment. Established causal relationships estimating body mass index, lipids and blood pressure from measures of glycaemia and plasma insulin were calibrated using Third National Health and Nutrition Examination Survey (USA) data, standardizing for age, sex, ethnicity and smoking. The effects of individual interventions were calibrated using published trial evidence, in line with the current understanding of the main modes of action of each agent. RESULTS: A comparison of the effects of common therapies using the model showed both similarities and differences. Large improvements in glycaemic control from lifestyle modifications, further enhanced by oral glucose-lowering drugs or insulin, were reproduced. Projections comparing lifetime therapeutic strategies suggest that simple guidelines may not always be valid. CONCLUSION: This novel mathematical model using evidence from the long-term natural history of type 2 diabetes is able to project the expected effects of various antihyperglycaemic therapies. Coupled with an economic model, this metabolic model may provide a mechanism for healthcare professionals and policymakers to evaluate different long-term strategies for the management of type 2 diabetes.