Association of Life's Simple 7 lifestyle metric with cardiometabolic disease-free life expectancy in older British men.

BACKGROUND: Cardiometabolic diseases (CMD), including myocardial infarction, stroke, and type 2 diabetes, are leading causes of disability and mortality globally, particularly for people at an older age. The impact of adhering to the Life's Simple 7 (LS7) on the number of years an individual will live without CMD in older adults remains less studied. METHODS: This study included a cohort of 2662 British men aged 60-79 years free of CMD at baseline from the British Regional Heart Study (BRHS). Each LS7 factor (BMI, blood pressure, blood glucose, total cholesterol, smoking, physical activity, and diet) was categorized as poor, intermediate, or ideal, and a composite LS7 adherence was determined by summing the number of LS7 ideal levels achieved. Flexible parametric Royston-Parmar proportional-hazards model was applied to estimate CMD-free life expectancy. RESULTS: Here we show that compared to men with the lowest LS7 adherence [with 18.42 years (95% CI: 16.93, 19.90) of CMD-free life at age 60], men having an ideal LS7 adherence are estimated to gain an additional 4.37 years (95% CI: 2.95, 5.79) of CMD-free life. The CMD-free life gain benefits are consistent across social class groups of manual and non-manual workers. Among LS7 factors, achieving an ideal physical activity provides the largest CMD-free survival benefit: 4.84 years (95% CI: 3.37, 6.32) of additional CMD-free life compared with the physically inactive group. CONCLUSIONS: Our study quantifies and highlights the benefits of adhering to the LS7 ideal levels for living a longer life without CMD in older adults.

Cardiometabolic diseases, including heart attack, stroke, and type 2 diabetes, are leading causes of disability and deaths globally. To benefit cardiometabolic health, the American Heart Association made a number of recommendations, known as the Life's Simple 7 lifestyle metric, including not smoking, having adequate physical activity, following a healthy diet pattern, and managing healthy body weight, healthy blood pressure, cholesterol, and blood sugar levels. Our study showed that adopting a healthy lifestyle following these recommendations could potentially increase the cardiometabolic disease-free life expectancy by more than four years for British men at age 60, with achieving an ideal physical activity level provided the largest survival benefit. Our findings highlight the need for public health efforts and interventions to support older adults in achieving optimal cardiometabolic health, particularly with regards to physical activity.

Utilizing multimodal AI to improve genetic analyses of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors contain multiple high-dimensional clinical data (HDCD) modalities (e.g., ECG, Photoplethysmography (PPG), and MRI) for each individual. Access to multimodal HDCD provides a unique opportunity for genetic studies of complex traits because different modalities relevant to a single physiological system (e.g., circulatory system) encode complementary and overlapping information. We propose a novel multimodal deep learning method, M-REGLE, for discovering genetic associations from a joint representation of multiple complementary HDCD modalities. We showcase the effectiveness of this model by applying it to several cardiovascular modalities. M-REGLE jointly learns a lower representation (i.e., latent factors) of multimodal HDCD using a convolutional variational autoencoder, performs genome wide association studies (GWAS) on each latent factor, then combines the results to study the genetics of the underlying system. To validate the advantages of M-REGLE and multimodal learning, we apply it to common cardiovascular modalities (PPG and ECG), and compare its results to unimodal learning methods in which representations are learned from each data modality separately, but the downstream genetic analyses are performed on the combined unimodal representations. M-REGLE identifies 19.3% more loci on the 12-lead ECG dataset, 13.0% more loci on the ECG lead I + PPG dataset, and its genetic risk score significantly outperforms the unimodal risk score at predicting cardiac phenotypes, such as atrial fibrillation (Afib), in multiple biobanks.

NMR metabolomic modeling of age and lifespan: A multicohort analysis.

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

Prospective associations between diet quality, dietary components, and risk of cardiometabolic multimorbidity in older British men.

PURPOSE: Cardiometabolic multimorbidity (CMM) is a major public health challenge. This study investigated the prospective relationships between diet quality, dietary components, and risk of CMM in older British men. METHODS: We used data from the British Regional Heart Study of 2873 men aged 60-79 free of myocardial infarction (MI), stroke, and type 2 diabetes (T2D) at baseline. CMM was defined as the coexistence of two or more cardiometabolic diseases, including MI, stroke, and T2D. Sourcing baseline food frequency questionnaire, the Elderly Dietary Index (EDI), which was a diet quality score based on Mediterranean diet and MyPyramid for Older Adults, was generated. Cox proportional hazards regression and multi-state model were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: During a median follow-up of 19.3 years, 891 participants developed first cardiometabolic disease (FCMD), and 109 developed CMM. Cox regression analyses found no significant association between baseline EDI and risk of CMM. However, fish/seafood consumption, a dietary component of the EDI score, was inversely associated with risk of CMM, with HR 0.44 (95% CI 0.26, 0.73) for consuming fish/seafood 1-2 days/week compared to less than 1 day/week after adjustment. Further analyses with multi-state model showed that fish/seafood consumption played a protective role in the transition from FCMD to CMM. CONCLUSIONS: Our study did not find a significant association of baseline EDI with CMM but showed that consuming more fish/seafood per week was associated with a lower risk of transition from FCMD to CMM in older British men.

Dementia in the older population is associated with neocortex content of serum amyloid P component.

Despite many reported associations, the direct cause of neurodegeneration responsible for cognitive loss in Alzheimer's disease and some other common dementias is not known. The normal human plasma protein, serum amyloid P component, a constituent of all human fibrillar amyloid deposits and present on most neurofibrillary tangles, is cytotoxic for cerebral neurones in vitro and in experimental animals in vivo. The neocortical content of serum amyloid P component was immunoassayed in 157 subjects aged 65 or more with known dementia status at death, in the large scale, population-representative, brain donor cohort of the Cognitive Function and Ageing Study, which avoids the biases inherent in studies of predefined clinico-pathological groups. The serum amyloid P component values were significantly higher in individuals with dementia, independent of serum albumin content measured as a control for plasma in the cortex samples. The odds ratio for dementia at death in the high serum amyloid P component tertile was 5.24 (95% confidence interval 1.79-15.29) and was independent of Braak tangle stages and Thal amyloid-ß phases of neuropathological severity. The strong and specific association of higher brain content of serum amyloid P component with dementia, independent of neuropathology, is consistent with a pathogenetic role in dementia.

Risk Factors and Prevalence of Dilated Cardiomyopathy in Sub-Saharan Africa: Protocol for a Systematic Review.

BACKGROUND: Cardiomyopathies, defined as diseases involving mainly the heart muscles, are linked to an estimated 5.9 of 100,000 deaths globally. In sub-Saharan Africa, cardiomyopathies constitute 21.4% of heart failure cases, with dilated cardiomyopathy (DCM) being the most common form. The etiology of DCM is heterogeneous and is broadly categorized as genetic or nongenetic, as well as a mixed disease in which genetics interact with intrinsic and environmental factors. Factors such as age, gender, family history, and ethnicity are nonmodifiable, whereas modifiable risk factors include poor nutrition, physical inactivity, and excessive alcohol consumption, among others. However, the relative contribution of the different risk factors to the etiology of DCM is not known in sub-Saharan Africa, and the prevalence of DCM among heart failure patients has not been systematically studied in the region. OBJECTIVE: The aim of this review is to synthesize available literature from sub-Saharan Africa on the prevalence of DCM among patients with heart failure, as well as the literature on factors associated with DCM. This paper outlines the protocol that will be followed to conduct the systematic review. METHODS: A limited search of the PubMed database will be performed to identify relevant keywords contained in the title, abstract, and subject descriptors using initial search terms "heart failure," "cardiomyopathy," and "sub-Saharan Africa." These search terms and their synonyms will then be used in an extensive search in PubMed, and will address the first research question on prevalence. To address the second research question on risk factors, the terms "heart failure," "cardiomyopathy," and "cardiovascular risk factors" in "Sub-Saharan Africa" will be used, listing them one by one. Articles published from 2000 and in the English language will be included. Indexed articles in PubMed and Embase will be included, as well as the first 300 articles retrieved from a Google Scholar search. Collected data will be organized in Endnote and then uploaded to the Rayyan web app for systematic reviews. Two reviewers will independently select articles against the inclusion criteria. Discrepancies in reviewer selections will be resolved by an arbitrator. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting systematic reviews will be applied. A map of sub-Saharan Africa with colors to show disease prevalence in each country will be included. For quantitative data, where possible, odds ratios (for categorical outcome data) or standardized mean differences (for continuous data) and their 95% CIs will be calculated. RESULTS: The primary outcomes will be the prevalence of DCM among patients with heart failure and cardiovascular risk factors associated with DCM in sub-Saharan Africa. The literature search will begin on January 1, 2021, and data analysis is expected to be completed by April 30, 2021. CONCLUSIONS: This review will provide information on the current status of the prevalence and associated factors of DCM, and possibly identify gaps, including paucity of data or conflicting results that need to be addressed to improve our understanding of DCM in sub-Saharan Africa. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/18229.

Circulating Fatty Acids and Risk of Coronary Heart Disease and Stroke: Individual Participant Data Meta-Analysis in Up to 16 126 Participants.

Background We aimed at investigating the association of circulating fatty acids with coronary heart disease (CHD) and stroke risk. Methods and Results We conducted an individual-participant data meta-analysis of 5 UK-based cohorts and 1 matched case-control study. Fatty acids (ie, omega-3 docosahexaenoic acid, omega-6 linoleic acid, monounsaturated and saturated fatty acids) were measured at baseline using an automated high-throughput serum nuclear magnetic resonance metabolomics platform. Data from 3022 incident CHD cases (13 104 controls) and 1606 incident stroke cases (13 369 controls) were included. Logistic regression was used to model the relation between fatty acids and odds of CHD and stroke, adjusting for demographic and lifestyle variables only (ie, minimally adjusted model) or with further adjustment for other fatty acids (ie, fully adjusted model). Although circulating docosahexaenoic acid, but not linoleic acid, was related to lower CHD risk in the fully adjusted model (odds ratio, 0.85; 95% CI, 0.76-0.95 per standard unit of docosahexaenoic acid), there was evidence of high between-study heterogeneity and effect modification by study design. Stroke risk was consistently lower with increasing circulating linoleic acid (odds ratio for fully adjusted model, 0.82; 95% CI, 0.75-0.90). Circulating monounsaturated fatty acids were associated with higher CHD risk across all models and with stroke risk in the fully adjusted model (odds ratio, 1.22; 95% CI, 1.03-1.44). Saturated fatty acids were not related to increased CHD risk in the fully adjusted model (odds ratio, 0.94; 95% CI, 0.82-1.09), or stroke risk. Conclusions We found consistent evidence that linoleic acid was associated with decreased risk of stroke and that monounsaturated fatty acids were associated with increased risk of CHD. The different pattern between CHD and stroke in terms of fatty acids risk profile suggests future studies should be cautious about using composite events. Different study designs are needed to assess which, if any, of the associations observed is causal.