Cardiometabolic Disease Research Articles

Polygenic Risk Score Implementation into Clinical Practice for Primary Prevention of Cardiometabolic Disease

Background: Cardiovascular disease is a leading cause of mortality globally and a major contributor to disability. Traditional risk factors, as initially established in the FRAMINGHAM study, have helped to stratify populations and identify patients for early intervention. Incorporating genetic factors enhances risk stratification tools, enabling the earlier identification of individuals at increased risk and facilitating more targeted and effective risk factor modifications. While monogenic risk variants are present in a minority of the population, polygenic risk scores (PRS) are collections of multiple single-nucleotide variants that collectively provide summative risk and capture a more accurate risk score for a greater number of people. PRS have demonstrated clear utility in cardiometabolic diseases by predicting onset, progression, and therapeutic response. Methods: A structured and exploratory hybrid search strategy was employed, combining keyword-based database searches and supplementary techniques to comprehensively synthesize the literature on PRS implementation in clinical practice. Discussion: A comprehensive overview of PRS in cardiometabolic diseases and their potential avenues for integration into primary care is discussed. First, we examine the implementation of genetic screening, risk communication, and intervention strategies through the lens of the American Heart Association’s implementation criteria, focusing on their efficacy, minimization of harm, and logistical considerations. Then, we explores how the varied perceptions of patients and practitioners towards PRS can influence both adoption and utilization. Lastly, we addresses the need for the development of clear guidelines and regulations to support this process, ensuring PRS integration is both scientifically sound and ethically responsible. Future directions: Initiatives aimed at advancing personalized approaches to disease prevention will enhance health outcomes. Developing guidelines for the responsible use of PRS by establishing benefits, while mitigating risk, will a key factor in implementation for clinical utility. Conclusions: For integration into clinical practice, we must address both patient and provider concerns and experience. Standardized guidelines and training will help to effectively implement PRS into clinical practice. Developing these resources will be essential for PRS to fulfill its potential in personalized, patient-centered care.

Revealing the nutritious treasures: an extensive investigation of health benefits of cultured dairy foods.

Cultured milk products including yogurt, buttermilk, and lassi have made their way into South Asian cuisine for hundreds of years and are extraordinarily beneficial to human health. With a study background on lactic acid bacteria (LAB), these products are scientifically proved to aid in strengthening the immune system, for their anti-mutagenic effects, suitability for those who are lactose intolerant, and for protection against cancer, osteoporosis, and gut disorders. As of now, no scientific attention has been given to the microbial diversity of cultured milk products despite its prominent production and importance in the culture. New emerging approaches for studying the genetic composition and metabolic features of microbial communities, such as metagenomics and metabolomics, will open up important sources of knowledge and be a significant tool for informing conservation. These products are highly valued worldwide in the management of cardiometabolic diseases (CMDs), which encompass hypertension, type 2 diabetes, and obesity. The aim of this article will therefore advocate for the health benefits as well as cultural importance of cultured milk products. Indian fermented milk products, along with their historical development, cultural, and research aspects, thereby, highlighting the potential of this kind of product in promoting global health through functional food application, with a focus on recent advancements in their therapeutic potential and applications.

Higher plasma levels of endocannabinoids and analogues are correlated with a worse cardiometabolic profile in middle-aged adults.

The increase in age-related comorbidities, such as cardiometabolic diseases, has become a global health priority. There is a growing need to find new parameters capable of improving the detection of cardiometabolic risk factors, and circulating endocannabinoids (eCBs) are a promising tool in this context. Here, we aimed to investigate the relationship between plasma levels of eCBs and their analogues with body composition and cardiometabolic risk factors in middle-aged adults. Seventy-two individuals (54% women; 53.6 ± 5.1 years old) were included in this study. Plasma levels of eCBs and analogues were determined using liquid chromatography-tandem mass spectrometry. Body composition was measured by dual-energy X-ray absorptiometry. Cardiometabolic risk factors (i.e., glucose and lipid profile, blood pressure, liver and renal parameters, and gonadal hormones) were also assessed. The plasma levels of 1- and 2-arachidonylglycerol (1-AG&2-AG) were positively correlated with adiposity (all r ≥ 0.23, P < 0.05). Interestingly, the plasma levels of 1-AG&2-AG, arachidonoylethanolamide, and palmitoyl-ethanolamide were positively correlated with the homeostatic model assessment index - Insulin Resistance (HOMA-IR) (all r ≥ 0.32, P < 0.01). Our results also showed that high levels of 1-AG&2-AG, arachidonoylethanolamide, linoleoyl ethanolamide, and palmitoleoyl ethanolamide were correlated with poorer liver (all r ≥ 0.27, P < 0.05), kidney (all r ≥ 0.24, P < 0.05), and gonadal function parameters (testosterone: all r > 0.26, P < 0.05, SHBG: 1-AG&2-AG r=-0.33, P < 0.01). The plasma levels of some eCBs and analogues are correlated with a worse cardiometabolic profile in middle-aged adults.

Brain Penetrant NLRP3 Inhibitors: The Discovery of a Panacea?

The NLRP3 inflammasome has attracted much interest as a drug target; however, many of the first wave of inhibitors were derived from a single aryl sulfonylurea starting point. The physicochemical properties of this molecule and most derivatives are not amenable to high brain penetration, thus limiting their potential effectiveness against disease targets where this is required. The disclosure of a novel pyridazine phenol scaffold facilitated a second wave of research toward brain-penetrant molecules, which may enable the discovery of novel treatments for Alzheimer's disease, Parkinson's disease, multiple sclerosis and cardiometabolic diseases.

Plasma proteomic signatures of adiposity are associated with cardiovascular risk factors and type 2 diabetes risk in a multi-ethnic Asian population.

The biomarkers connecting obesity and cardiometabolic diseases are not fully understood. We aimed to (i) evaluate the associations between body mass index (BMI), waist circumference (WC), and ∼5,000 plasma proteins (SomaScan v4), (ii) identify protein signatures of BMI and WC, and (iii) evaluate the associations between the protein signatures and cardiometabolic health including metabolically unhealthy obesity and type 2 diabetes incidence in the Singapore Multi-Ethnic Cohort (MEC1). Among 410 BMI-associated and 385 WC-associated proteins, we identified protein signatures of BMI and WC and validated them in an independent dataset across two timepoints and externally in the Atherosclerosis Risk in Communities (ARIC) study. The BMI- and WC-protein signatures were highly correlated with total and visceral body fat, respectively. Furthermore, the protein signatures were significantly associated with cardiometabolic risk factors and metabolically unhealthy obesity. In prospective analyses, the protein signatures were strongly associated with type 2 diabetes risk in MEC1 (odds ratio per SD increment in WC-protein signature = 2.84, 95% CI 2.47 to 3.25) and ARIC (hazard ratio = 1.98, 95% CI 1.88 to 2.08). Our protein signatures have potential uses for the monitoring of metabolically unhealthy obesity.

Glucocorticoids and HPA axis regulation in the stress-obesity connection: A comprehensive overview of biological, physiological and behavioural dimensions.

Chronic stress, characterized by increased long-term exposure to the glucocorticoid hormone cortisol, is increasingly linked to obesity development. Still, various knowledge gaps persist, including on underlying pathophysiological mechanisms. The aim of the current review is to provide the latest insights on the connection between stress and obesity. We discuss three biological stress systems-the autonomic nervous system, the hypothalamus-pituitary-adrenal (HPA) axis and the immune system-and their link with obesity, with a particular focus on the HPA axis. The role of cortisol and its regulatory variations (including glucocorticoid rhythmicity and altered sensitivity) in adipose tissue biology and obesity development is discussed. Moreover, we highlight the physiological, affective, cognitive and behavioural dimensions of the stress response offering a deeper understanding of how stress contributes to obesity development and vice versa. Finally, stress as a treatment target for obesity is discussed. We conclude that the link between stress and obesity is complex and multifaceted, influenced by physiological, affective, cognitive and behavioural stress response mechanisms, which especially when chronically present, play a key role in the development of obesity and associated cardiometabolic diseases. This necessitates integrated approaches tailored to individual needs, including lifestyle modifications, behavioural interventions, psychosocial support and possible additional pharmacological interventions.

Misalignment Between Circadian Preference and Accelerometer-Derived Sleep-Wake Cycle With Increased Risk of Cardiometabolic Diseases

BackgroundThe relationship of circadian misalignment, sleep-wake cycle, and cardiometabolic diseases (CMDs) remains unclear. ObjectivesThis prospective study investigated the associations between circadian misalignment and CMDs, including type 2 diabetes (T2D), coronary heart disease (CHD), and stroke, and explored potential mechanisms. MethodsData from 60,965 participants without pre-existing CMDs from the UK Biobank study and followed for an average of 7.9 years were analyzed. Circadian misalignment was determined by comparing self-reported chronotype and accelerometer-derived sleep timing. Incident CMDs were documented via multiple medical registries and self-reported information. Cox proportional hazards models were applied to estimate HRs and 95% CIs for these associations. ResultsA U-shaped relationship between circadian misalignment and both T2D and CHD was observed. Compared to individuals with aligned midsleep and circadian preferences (the third quintile, Q3), those with advanced and delayed circadian misalignment had higher risks of T2D (HR: 1.22 [95% CI: 1.03-1.45] for Q1 and 1.39 [95% CI: 1.18-1.62] for Q5). Delayed circadian misalignment also associated with higher CHD risk (HR: 1.15 [95% CI: 1.01-1.31] for Q4 and 1.16 [95% CI: 1.02-1.33] for Q5). The association between delayed circadian misalignment and CMDs was greater in women (T2D, Pinteraction = 0.03) and younger adults (CHD, Pinteraction = 0.02). Early (HR: 1.19 [95% CI: 1.06-1.34]), rather than late, chronotype was associated with an increased T2D risk. ConclusionsBoth advanced and delayed circadian misalignment were associated with an increased CMD risk, highlighting the potential health benefits of aligning sleep-wake cycles with individual circadian preferences.

Trends in prevalence and multimorbidity of metabolic, cardiovascular, and chronic kidney diseases among US adults with depression from 2005 to 2020

BackgroundComorbid depression and cardiometabolic diseases are prevalent and increase risk of mortality. However, trends in the prevalence and multimorbidity of cardiometabolic diseases in depression are unclear. MethodsData of adults aged≥20 years with depression from the National Health and Nutrition Examination Survey 2005–2020 were analyzed. Joinpoint regression analysis was used to estimate trends in the prevalence of dyslipidemia, hypertension, diabetes, chronic kidney disease, non-alcoholic fatty liver disease, and cardiovascular disease as well as having≥3 of these diseases. Differences in the prevalence of these diseases in depression vs no depression were assessed using Poisson regressions after applying propensity score weighting. ResultsA total of 3412 adults with depression were included. The prevalence of cardiometabolic diseases as well as having≥3 diseases remained high and stable in the overall sample from 2005 to 2020 (P for trend>0.05). In 2017–2020, the prevalence ranged from 17.1 % (95 % CI, 12.7 %–21.5 %) for cardiovascular disease to 58.4 % (95 % CI, 50.4 %–66.3 %) for dyslipidemia; 40.7 % (95 % CI, 34.4 %–46.9 %) had≥3 diseases. The prevalence of diabetes, cardiovascular disease, and having≥3 diseases was 23 %–85 % higher in adults with depression than those without. LimitationsThe utilization of self-reported data and/or one-time laboratory measurements may misclassify participants. ConclusionsPrevalence of cardiometabolic diseases was high and multimorbidity was common in US adults with depression. Addressing the prevention, treatment, and management of cardiometabolic diseases in depression requires greater public health and clinical attention.

Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population

Manually extracted imaging-based body composition measures from a single-slice area (A) have shown associations with clinical outcomes in patients with cardiometabolic disease and cancer. With advances in artificial intelligence, fully automated volumetric (V) segmentation approaches are now possible, but it is unknown whether these measures carry prognostic value to predict mortality in the general population. Here, we developed and tested a deep learning framework to automatically quantify volumetric body composition measures from whole-body magnetic resonance imaging (MRI) and investigated their prognostic value to predict mortality in a large Western population. The framework was developed using data from two large Western European population-based cohort studies, the UK Biobank (UKBB) and the German National Cohort (NAKO). Body composition was defined as (i) subcutaneous adipose tissue (SAT), (ii) visceral adipose tissue (VAT), (iii) skeletal muscle (SM), SM fat fraction (SMFF), and (iv) intramuscular adipose tissue (IMAT). The prognostic value of the body composition measures was assessed in the UKBB using Cox regression analysis. Additionally, we extracted body composition areas for every level of the thoracic and lumbar spine (i) to compare the proposed volumetric whole-body approach to the currently established single-slice area approach on the height of the L3 vertebra and (ii) to investigate the correlation between volumetric and single slice area body composition measures on the level of each vertebral body. In 36,317 UKBB participants (mean age 65.1±7.8 years, age range 45-84 years; 51.7% female; 1.7% [634/36,471] all-cause deaths; median follow-up 4.8 years), Cox regression revealed an independent association between VSM (adjusted hazard ratio [aHR]: 0.88, 95% confidence interval [CI] [0.81-0.91], p=0.00023), VSMFF (aHR: 1.06, 95% CI [1.02-1.10], p=0.0043), and VIMAT (aHR: 1.19, 95% CI [1.05-1.35], p=0.0056) and mortality after adjustment for demographics (age, sex, BMI, race) and cardiometabolic risk factors (alcohol consumption, smoking status, hypertension, diabetes, history of cancer, blood serum markers). This association was attenuated when using traditional single-slice area measures. Highest correlation coefficients (R) between volumetric and single-slice area body composition measures were located at vertebra L5 for SAT (R=0.820) and SMFF (R=0.947), at L3 for VAT (R=0.892), SM (R=0.944), and at L4 for IMAT (R=0.546) (all p<0.0001). A similar pattern was found in 23,725 NAKO participants (mean age 53.9±8.3 years, age range 40-75; 44.9% female). Automated volumetric body composition assessment from whole-body MRI predicted mortality in a large Western population beyond traditional clinical risk factors. Single slice areas were highly correlated with volumetric body composition measures but their association with mortality attenuated after multivariable adjustment. As volumetric body composition measures are increasingly accessible using automated techniques, identifying high-risk individuals may help to improve personalised prevention and lifestyle interventions. This project was conducted using data from the German National Cohort (NAKO) (www.nako.de). The NAKO is funded by the Federal Ministry of Education and Research (BMBF) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, and 01ER1801A/B/C/D], federal states of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association. This research has been conducted using the UK Biobank Resource under Application Number 80337. MJ was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-518480401. VKR was funded by American Heart Association Career Development Award 935176 and National Heart, Lung, and Blood Institute-K01HL168231.

Digital Health Technologies for Cardiometabolic Disease and Diabetes: A Perspective From the U.S. Food and Drug Administration.

Digital Health Technologies for Cardiometabolic Disease and Diabetes: A Perspective From the U.S. Food and Drug Administration.

Effects of α-Mangostin-Loaded Self-Nanoemulsion (MG-SNE) and Physical Exercise on The Reduction of Waist Circumference in Wistar Rats

BACKGROUND : Waist circumference (WC) is a marker of intra-abdominal adipose tissue and a risk factor for cardiometabolic disease. A higher risk of coronary heart disease was associated with an increased WC. Garcinia mangostana Linn's anti-inflammatory activity would reduce abdominal fat deposition and WC. Additionally, Garcinia mangostana Linn's potential would increase in nanotechnology. AIMS : To demonstrate that WC in Wistar rats induced by an atherogenic diet can be decreased by α-Mangostin-loaded self-nanoemulsion (MG-SNE) treatment combined with physical activity. METHOD : Experimental research with Randomized Control Trial design using a total sample of 15 male white rats (Rattus novergicus strain Wistar) weighing 300 grams and aged between 6 and 8 weeks, split into 3 groups given physical exercise for 8 weeks along with 3 different doses of medication (group K received Atorvastatin 1.44 mg once; group P1 received Garcinia mangostana Linn pericarp extract, at a dose of 800 mg/kg, divided into 3 administrations; and group P2 received MG-SNE 50 mg/kg once). Waist circumference was measured using a metline, before and after treatment. RESULT : WC decreased in Groups K, P1, and P2, with deltas of -5.00±21.21 mm, -12.50±24.75 mm, and -17.50±12.58 mm. The greatest decrease in WC was P2. There was no significant difference, according to the paired test between the pre-test and posttest in all groups. The p value &gt;0.05 was determined to indicate that there were no significant differences between the groups. CONCLUSION : WC in Wistar rats induced by an atherogenic diet can be decreased by MG-SNE treatment combined with physical exercise.

Associations between subjective and objective well-being and risk of cardiometabolic disease: A prospective cohort study from the UK biobank

BackgroundThe distinct and combined impacts of subjective well-being (SWB) and objective well-being (OWB) on cardiometabolic diseases and cardiometabolic multimorbidity remain largely unknown. Methods141,086 participants (mean age 56 years) were included from the UK Biobank study from 2006 to 2010. The SWB included happiness and life satisfaction. The OWB represents the level of satisfaction with objective conditions which was created using latent class analysis. Cardiometabolic diseases comprise diabetes and cardiovascular disease, including coronary heath disease and stroke. The Cox models were used to estimate the hazard ratio (HR) and 95 % confidence intervals (95 % CI) of the individual and combined associations between SWB and OWB with the risk of cardiometabolic diseases. ResultsDuring a median follow-up of 12 years (1,693,800 person-years), 16,678 new-onset cardiometabolic diseases were reported. In full-adjusted model, the HR (95 % CI) among men with high SWB was 0.93 (0.82–1.05), 0.85 (0.79–0.92) and 0.71 (0.57–0.87), for diabetes, cardiovascular disease, and cardiometabolic multimorbidity, compared to low SWB, respectively. Among women with high SWB, the HR (95 % CI) was 0.71 (0.62–0.81), 0.76 (0.69–0.83) and 0.55 (0.42–0.72) for diabetes, cardiovascular disease and cardiometabolic multimorbidity, respectively. Low OWB increases the cardiometabolic diseases risk by from 16 % to 103 %. Notably, high SWB was associated with lower cardiometabolic diseases risk among individuals with low OWB. LimitationsPotential recall bias and residual confounding are the main limitations. ConclusionsWe found that both high SWB and OWB were significantly associated with a lower risk of cardiometabolic diseases, more evident among women. The association between SWB and cardiometabolic diseases was independent of OWB.

Lifestyle interventions for cardiometabolic health.

Unhealthy lifestyle behaviors such as poor diets and physical inactivity account for most of the cardiometabolic disease (CMD) burden, including type 2 diabetes and cardiovascular diseases. Much of this burden is mediated by the effects of unhealthy lifestyle behaviors on overweight and obesity, and disproportionally impacts certain population groups-including those from disadvantaged socioeconomic backgrounds. Combined lifestyle interventions (CLIs), which target multiple behaviors, have the potential to prevent CMD, but their implementation, reach and effectiveness in routine practice are often limited. Considering the increasing availability of effective but expensive pharmaceutical options for weight loss, we review the short-term and long-term benefits and cost-effectiveness of CLIs on overweight, obesity and associated CMDs, in controlled studies and in routine care. Against the backdrop of changing living environments, we discuss the effective components of CLIs and the many challenges associated with implementing them. Finally, we outline future directions for research and implications for policy and practice to improve lifestyle behaviors and cardiometabolic health at the population level.

Codesign with citizens to prevent cardiometabolic diseases in disadvantaged neighbourhoods: an interview study on needs and priorities among stakeholders in Sweden

ObjectivesCardiometabolic diseases are a global health concern, affecting socioeconomically disadvantaged groups more adversely. Effective public health interventions targeting preventable risk factors like physical inactivity and unhealthy diets are needed. Codesign...

Bayesian Mendelian Randomization Analysis for Latent Exposures Leveraging GWAS Summary Statistics for Traits Co-Regulated by the Exposures.

Mendelian Randomization analysis is a popular method to infer causal relationships between exposures and outcomes, utilizing data from genome-wide association studies (GWAS) to overcome limitations of observational research by treating genetic variants as instrumental variables. This study focuses on a specific problem setting, where causal signals may exist among a series of correlated traits, but the exposures of interest, such as biological functions or lower-dimensional latent factors that regulate the observable traits, are not directly observable. We propose a Bayesian Mendelian randomization analysis framework that allows joint analysis of the causal effects of multiple latent exposures on a disease outcome leveraging GWAS summary-level association statistics for traits co-regulated by the exposures. We conduct simulation studies to show the validity and superiority of the method in terms of type I error control and power due to a more flexible modeling framework and a more stable algorithm compared to an alternative approach and traditional single- and multi-exposure analysis approaches not specifically designed for the problem. We have also applied the method to reveal evidence of the causal effects of psychiatric factors, including compulsive, psychotic, neurodevelopmental, and internalizing factors, on neurodegenerative, autoimmune, digestive, and cardiometabolic diseases.

The mediating role of remnant cholesterol in the associations of Angiopoietin-like 8 with all-cause, CVD, and cancer death: the China Cardiometabolic Disease and Cancer Cohort (4C) study.

To investigate the potential mediating effect of remnant cholesterol (RC) in the associations between angiopoietin-like 8 (ANGPTL8) and the risk of all-cause, cardiovascular disease (CVD), and cancer death. This prospective observational study included 3278 individuals from China. Binary logistic regression and mediation analyses were conducted to investigate the mediating effect of RC in the associations between ANGPTL8 and all-cause, CVD, and cancer death. During up to 5-year follow-up, a total of 265 deaths (8.08%) were documented. Both increased levels of ANGPTL8 and RC were associated with a higher risk of death for all-cause, CVD, and cancer risk. The level of RC ≥ 33 mg/dL could identify individuals at a higher risk of death independent of low-density lipoprotein cholesterol (LDL-C) levels in Chinese general populations. Furthermore, RC significantly mediated the relationship between increased ANGPTL8 levels and higher risk of all-cause, CVD, and cancer death (proportion of mediation effect: 13.10%, 9.22%, and 6.07%, respectively, all p < 0.05). Both increased circulating levels of ANGPTL8 and RC are the risk factors for all-cause, CVD, and cancer death and RC partially mediates the association between ANGPTL8 and death risk.

Routine measurement of cardiometabolic disease risk factors in primary care in England before, during, and after the COVID-19 pandemic: A population-based cohort study.

This study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels. A cohort of individuals aged ≥18 years in England with records in the primary care-COVID-19 General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) were identified. Their records of 12 risk factor measurements were extracted between November 2018 and March 2024. Number of measurements per 1,000 individuals were calculated by age group, sex, ethnicity, and area deprivation quintile. The observed number of measurements were compared to a composite expectation band, derived as the union of the 95% confidence intervals of 2 estimates: (1) a projected trend based on data prior to the COVID-19 pandemic; and (2) an assumed stable trend from before pandemic. Point estimates were calculated as the mid-point of the expectation band. A cohort of 49,303,410 individuals aged ≥18 years were included. There was sharp drop in all measurements in March 2020 to February 2022, but overall recovered to the expected levels during March 2022 to February 2023 except for blood pressure, which had prolonged recovery. In March 2023 to March 2024, blood pressure measurements were below expectation by 16% (-19 per 1,000) overall, in people aged 18 to 39 (-23%; -18 per 1,000), 60 to 79 (-17%; -27 per 1,000), and ≥80 (-31%; -57 per 1,000). There was suggestion that recovery in blood pressure measurements was socioeconomically patterned. The second most deprived quintile had the highest deviation (-20%; -23 per 1,000) from expectation compared to least deprived quintile (-13%; -15 per 1,000). There was a substantial reduction in routine measurements of cardiometabolic risk factors following the COVID-19 pandemic, with variable recovery. The implications for missed diagnoses, worse prognosis, and health inequality are a concern.

A Mendelian randomization study of alcohol use and cardiometabolic disease risk in a multi-ancestry population from the Million Veteran Program.

Observational studies link moderate alcohol consumption to reduced risk of cardiometabolic diseases, including coronary heart disease (CHD) and type 2 diabetes mellitus (T2D). Mendelian randomization (MR) studies suggest that these associations are due to confounding. We present observed and genetically proxied associations between alcohol consumption and the incidence of CHD and T2D among African Americans (AA), European Americans (EA), and Hispanic Americans (HA) from the Million Veteran Program. We conducted two retrospective, nested case-control studies of 33,053 CHD and 28,278 T2D cases matched to five controls each at the time of the event (index date). We used the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) score closest in time prior to the index date to estimate alcohol exposure. Models were adjusted for smoking, body mass index (BMI), chronic kidney disease, rheumatoid arthritis, and the use of statins or antihypertensive medications. MR analyses used either a single variant in ADH1B or a genetic score (GS) as instrumental variables. Observational analysis showed a U-shaped association of alcohol consumption with CHD and T2D risk. However, in MR analyses, neither ADH1B genotype-predicted (in 36,465 AAs, 146,464 EAs, and 11,342 HAs) nor GS-predicted (in EAs) alcohol consumption was associated with CHD risk. Similarly, T2D was not associated with alcohol consumption predicted either by ADH1B genotype (in 42,008 AAs, 109,351 EAs, and 13,538 HAs) or GS (in EAs). Multivariable MR analyses that adjusted for the effects of blood pressure and smoking also showed no association between alcohol consumption and cardiometabolic diseases. We replicate prior observational studies that show a U-shaped association between alcohol consumption and cardiometabolic diseases, but MR findings show no causal association between these traits. This is largely consistent with previous MR analyses in EAs and expands the literature by providing similar findings in AA and HA populations.

Plasma uric acid levels and risk of dementia in a population-based cohort study

BackgroundGiven the opposing properties of uric acid (UA), which are intracellular prooxidant action and extracellular antioxidant action, the association of circulating UA levels with dementia remains controversial. We aimed to ascertain whether both lower and higher plasma UA levels are associated with the risk of incident dementia among middle-aged and older population. Methods1685 participants (530 men and 1155 women) aged 40–69 years at baseline (1990–1993) were randomly selected for plasma UA measurement from base cohort participants who responded to the baseline questionnaire and provided blood samples. They were followed for dementia (disabling dementia requiring care; hereinafter dementia) from 2006 to 2016 using certification records for national long-term care insurance in Japan. A Cox proportional hazards model adjusted for various lifestyle factors and past medical history (cardiometabolic disease) was applied for overall participants and sex. ResultsDementia was diagnosed in 240 participants (14.2 % overall: 16.0 % in men and 13.4 % in women). No statistically significant association with plasma UA was found in overall participants. Compared to participants with UA of 5.1–6.0 mg/dL, men with ≥6.1 mg/dL showed fully adjusted hazard ratios of 1.46 (95 % confidence interval: 0.78–2.75) for 6.1–7.0 mg/dL and 1.89 (0.97–3.66) for ≥7.1 mg/dL, while women with ≥6.1 mg/dL showed 1.13 (0.54–2.38). ConclusionsNo statistically significant association between plasma UA level and risk of dementia was found in overall participants or by sex.

Recent advances in applying metabolomics to uncover dietary impact on cardiometabolic health.

Cardiometabolic diseases are a major global health concern, with diet playing a crucial role in their prevention and management. Recent advancements in the identification of metabolic signatures related to dietary patterns offer a more objective assessment of individualized dietary exposure and provide deeper insights into diet-disease associations. Recent studies have shown that distinct metabolic signatures are associated with the adherence to various dietary patterns. These signatures show even stronger associations with cardiometabolic disease incidence, independent of traditional risk factors and self-reported adherence to such dietary patterns. Emerging dietary approaches, such as sustainable diets, health outcome-focused diets, and population data-driven dietary patterns, also hold promise for improving cardiometabolic health. Additionally, metabolic signatures could offer insights into diet-disease associations in underrepresented populations, addressing genetic and lifestyle differences. Application of metabolomics provides a more precise understanding of how dietary patterns influence cardiometabolic health. Although the number of studies remains limited, and current evidence is inconsistent, the approach has significant potential for improving clinical and public health strategies. Future research should prioritize prospective studies and address population- and outcome-specific dietary needs to enable targeted interventions that optimize cardiometabolic health.