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BACKGROUND AND AIM: It is crucial to identify a diabetes diagnosis early. Create a predictive model utilizing machine learning (ML) to identify new cases of diabetes in primary health care (PHC).

METHODS: A case-control study utilizing data on PHC visits for sex-, age, and PHC-matched controls. Stochastic gradient boosting was used to construct a model for predicting cases of diabetes based on diagnostic codes from PHC consultations during the year before index (diagnosis) date and number of consultations. Variable importance was estimated using the normalized relative influence (NRI) score. Risks of having diabetes were calculated using odds ratios of marginal effects (OR_ME). Four groups by age and sex were studied, age-groups 35-64 years and ≥ 65 years in men and women, respectively.

RESULTS: The most important predictive factors were hypertension with NRI 21.4-29.7 %, and obesity 4.8-15.2 %. The NRI for other top ten diagnoses and administrative codes generally ranged 1.0-4.2 %.

CONCLUSIONS: Our data confirm the known risk patterns for predicting a new diagnosis of diabetes, and the need to test blood glucose frequently. To assess the full potential of ML for risk prediction purposes in clinical practice, future studies could include clinical data on life-style patterns, laboratory tests and prescribed medication.

Background: Metabolic syndrome (MetS) is characterized by coexisting risk factors for type 2 diabetes and cardiovascular disease. Diet is of importance in their aetiology, and gut microbiota (GM) may constitute a link between diet and metabolic health. Understanding the interplay between diet and GM could contribute novel insights for future dietary guidelines, and aid in preventive actions to motivate adherence to dietary guidelines. Objective: We intended to create a Swedish dietary guideline index (SweDGI) measuring adherence to 12 Swedish dietary guidelines and examine whether SweDGI and its components are associated with GM α-diversity (Shannon index) and prevalent MetS, and if the association between the Shannon index and MetS differs depending on SweDGI. Design: SweDGI was based on food-frequency data assessed 2014–2018 in 10,396 diabetes-free participants from the Malmö and Uppsala-sites of the Swedish CArdioPulmonary bioImage Study (SCAPIS) (50–64 y, 53% women). We estimated the Shannon index from shotgun metagenomic sequencing-data to assess microbial richness and evenness. We used a general linear model to examine cross-sectional SweDGI-Shannon associations and logistic regression for associations with MetS. Results: Most guidelines were followed by less than half of the participants. Men showed poorer adherence. Higher SweDGI was linked to higher Shannon index (P-trend across five SweDGI-groups = 1.7 × 10-12). Most guidelines contributed to this observation. Higher SweDGI and Shannon index were associated with lower MetSprevalence, where the lowest prevalence was observed among those with both high SweDGI and high Shannon index (odds ratio:0.43; 95% confidence interval:0.35, 0.52). Both the Shannon index and SweDGI were associated with MetS, independently of the level of the other factor (P-interaction = 0.82). Conclusions: We created a new index to comprehensively reflect adherence to the Swedish dietary guidelines in sub-cohorts within the large multicentre SCAPIS study. Better adherence was associated with a richer and more even GM and lower prevalence of MetS. The inverse association between the Shannon index and MetS was consistent at different levels of adherence to dietary guidelines. © 2024 Ulrika Ericson et al.

BACKGROUND: Previous population-based studies investigating the relationship between physical activity and the gut microbiota have relied on self-reported activity, prone to reporting bias. Here, we investigated the associations of accelerometer-based sedentary (SED), moderate-intensity (MPA), and vigorous-intensity (VPA) physical activity with the gut microbiota using cross-sectional data from the Swedish CArdioPulmonary bioImage Study.

METHODS: In 8416 participants aged 50-65, time in SED, MPA, and VPA were estimated with hip-worn accelerometer. Gut microbiota was profiled using shotgun metagenomics of faecal samples. We applied multivariable regression models, adjusting for sociodemographic, lifestyle, and technical covariates, and accounted for multiple testing.

FINDINGS: Overall, associations between time in SED and microbiota species abundance were in opposite direction to those for MPA or VPA. For example, MPA was associated with lower, while SED with higher abundance of Escherichia coli. MPA and VPA were associated with higher abundance of the butyrate-producers Faecalibacterium prausnitzii and Roseburia spp. We observed discrepancies between specific VPA and MPA associations, such as a positive association between MPA and Prevotella copri, while no association was detected for VPA. Additionally, SED, MPA and VPA were associated with the functional potential of the microbiome. For instance, MPA was associated with higher capacity for acetate synthesis and SED with lower carbohydrate degradation capacity.

INTERPRETATION: Our findings suggest that sedentary and physical activity are associated with a similar set of gut microbiota species but in opposite directions. Furthermore, the intensity of physical activity may have specific effects on certain gut microbiota species.

FUNDING: European Research Council, Swedish Heart-Lung Foundation, Swedish Research Council, Knut and Alice Wallenberg Foundation.

OBJECTIVES: Identify the windows of opportunity for the diagnosis of chronic kidney disease (CKD) and the prevention of its adverse outcomes and quantify the potential population gains of such prevention.

DESIGN AND SETTING: Observational, population-wide study of residents in the Stockholm and Skåne regions of Sweden between 1 January 2015 and 31 December 2020.

PARTICIPANTS: All patients who did not yet have a diagnosis of CKD in healthcare but had CKD according to laboratory measurements of CKD biomarkers available in electronic health records.

OUTCOME MEASURES: We assessed the proportions of the patient population that received a subsequent diagnosis of CKD in healthcare, that used guideline-directed pharmacological therapy (statins, renin-angiotensin aldosterone system inhibitors (RAASi) and/or sodium-glucose cotransporter-2 inhibitors (SGLT2i)) and that experienced adverse outcomes (all-cause mortality, cardiovascular mortality or major adverse cardiovascular events (MACE)). The potential to prevent adverse outcomes in CKD was assessed using simulations of guideline-directed pharmacological therapy in untreated subsets of the study population.

RESULTS: We identified 99 382 patients with undiagnosed CKD during the study period. Only 33% of those received a subsequent diagnosis of CKD in healthcare after 5 years. The proportion that used statins or RAASi was of similar size to the proportion that didn't, regardless of how advanced their CKD was. The use of SGLT2i was negligible. In simulations of optimal treatment, 22% of the 21 870 deaths, 27% of the 14 310 cardiovascular deaths and 39% of the 22 224 MACE could have been avoided if every patient who did not use an indicated medication for their laboratory-confirmed CKD was treated with guideline-directed pharmacological therapy for CKD.

CONCLUSIONS: While we noted underdiagnosis and undertreatment of CKD in this large contemporary population, we also identified a substantial realisable potential to improve CKD outcomes and reduce its burden by treating patients early with guideline-directed pharmacological therapy.

Background Plasma osteopontin (pOPN) is a promising aging-related biomarker among individuals with and without kidney disease. The interaction between sex, pOPN levels, and global and cardiorenal outcomes among older individuals was not previously evaluated.Methods In this study we investigated the association of pOPN with 24-month global mortality, major cardiovascular events (MACEs), MACEs + cardiovascular (CV) mortality, and renal decline among older individuals; we also evaluated whether sex modified observed associations. pOPN levels were measured in a cohort of 2013 outpatients (908 men and 1105 women) aged 75 years or more enrolled in the context of a multicenter prospective cohort study in Europe. Multivariable linear regression, Cox and Fine Gray models, and linear mixed regression models were fitted to evaluate whether sex modified the associations between biomarkers and study outcomes.Results In total, 2013 older participants with a median age of 79 years, 54.9% of whom women, were included in the study; increased pOPN levels were associated with all-cause mortality specifically among women [reduced fully adjusted model resulting from backward selection, hazard ratio, 95% confidence interval (CI): 1.84, 1.20-2.89]. Addition of pOPN to models containing age, eGFR, and albumin-to-creatinine ratio (ACR) improved the time-dependent area under the curve (AUC) at 6, 12, and 24 months, among women only. No significant association was found between the biomarker levels, MACE, and MACE + CV mortality. Conversely, increased baseline pOPN was associated with eGFR decline in all patients (-0.45, 95%CI: -0.68 to -0.22 ml/min/1.73 m2 year) but with slightly steeper declines in women compared to men (-0.57, -0.99 to -0.15 vs -0.47, -0.88 to -0.07).Conclusions pOPN levels were significantly lower in women than in men but associated with all-cause mortality in women only; increase in serum pOPN was associated with eGFR decline over time in all patients, but with stronger associations among women. Assessment of pOPN may help identifying older female participants at risk of poor outcomes.

INTRODUCTION: Proteomics may help discover novel biomarkers and underlying mechanisms for cardiovascular disease. This could be useful for childhood cancer survivors as they show an increased risk of cardiovascular disease. The aim of this study was to investigate circulating cardiovascular proteins in young adult survivors of childhood cancer and their relationship to previously reported subclinical cardiovascular disease.

METHODS: Ninety-two cardiovascular proteins were measured in 57 childhood cancer survivors and in 52 controls. For proteins that were significantly different between childhood cancer survivors and controls, we performed correlations between protein levels and measures of peripheral arterial stiffness (carotid distensibility and stiffness index, and augmentation index) and endothelial dysfunction (reactive hyperemia index).

RESULTS: Leptin was significantly higher in childhood cancer survivors compared to controls (normalized protein expression units: childhood cancer survivors 6.4 (1.5) versus 5.1 (1.7), p < 0.0000001) after taking multiple tests into account. Kidney injury molecule-1, MER proto-oncogene tyrosine kinase, selectin P ligand, decorin, alpha-1-microglobulin/bikunin precursor protein, and pentraxin 3 showed a trend towards group differences (p < 0.05). Among childhood cancer survivors, leptin was associated with anthracycline treatment after adjustment for age, sex, and body mass index (p < 0.0001). Higher leptin correlated with lower carotid distensibility after adjustment for age, sex, body mass index, and treatments with radiotherapy and anthracyclines (p = 0.005).

CONCLUSION: This proteomics approach identified that leptin is higher in young asymptomatic adult survivors of childhood cancer than in healthy controls and is associated with adverse vascular changes. This could indicate a role for leptin in driving the cardiovascular disease burden in this population.

BACKGROUND: Growth differentiation factor 15 (GDF-15) is a robust prognostic biomarker in patients with cardiovascular (CV) disease, and a better understanding of its clinical determinants is desirable. We aimed to study the associations between GDF-15 levels and traditional CV risk factors, indicators of atherosclerotic burden, and cardiac geometry and dysfunction in outpatients with peripheral arterial disease (PAD).

METHODS: An explorative cross-sectional study (Study of Atherosclerosis in Vastmanland, Västerås, Sweden) included 439 outpatients with carotid or lower extremity PAD. The mean age was 70 years (standard deviation [SD] 7), and 59% of the patients were men. Plasma levels of GDF-15 were obtained along with potential determinants, including medical history, biochemical data, echocardiographic measures of cardiac geometry and function, ankle-brachial index (ABI), and carotid ultrasonographic data on intima-media thickness (IMT) and occurrence of carotid stenosis. The relations between GDF-15 concentrations (transformed with the natural logarithm) and the different determinants were evaluated using uni- and multivariable linear regression models. All pre-specified variables were included in the multivariable models.

RESULTS: The multivariable analysis identified independent relations of GDF-15 with several of the included variables (adjusted R ² = 0.48). Diabetes (beta coefficient [β] of 0.37, 95% confidence interval [95% CI] 0.25 to 0.50), low-density lipoprotein (LDL) cholesterol (β = -0.22, 95% confidence interval [CI]: -0.34 to -0.09), and physical activity (β = -0.16, 95% CI: -0.25 to -0.06) had the strongest associations. In contrast, no significant independent associations with GDF-15 level were observed for cardiac geometry and function, ABI, IMT, or carotid stenosis.

CONCLUSIONS: Circulating GDF-15 is more strongly associated with traditional CV risk factors, especially diabetes, LDL cholesterol, and physical activity than with specific indicators of atherosclerotic burden or cardiac dysfunction. To better understand the pathophysiological role of GDF-15 and its link to clinical outcomes in patients with PAD, future studies should focus on the metabolic processes involved in atherosclerotic disease.

INTRODUCTION: Data is limited on influence of forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) in a large adult population, including individuals with normal spirometry at baseline.

METHODS: Using the UK Biobank cohort, a multivariable Cox regression analysis was conducted on 406,424 individuals to examine the association between FEV₁ and FVC, categorized into three groups based on their percentage of predicted values (%pred) (≥80, 60-80 and < 60), and overall mortality, cardiovascular mortality, myocardial infarction, stroke, and heart failure over approximately 12.5 years. Moreover, a subgroup analysis was conducted on 295,459 individuals who had normal spirometry.

RESULTS: Reduced FEV₁ and FVC %pred values were associated with an elevated risk across all studied outcomes. Individuals with the lowest FEV₁ and FVC %pred values (<60 %) exhibited HR of 1.83 (95 % CI 1.74-1.93) and 1.98 (95 % CI 1.76-2.22) for overall mortality, and 1.96 (95 % CI 1.83-2.1) and 2.26 (95 % CI 1.94-2.63) for cardiovascular mortality. Moreover, a graded association was observed between lower FEV₁ and FVC %pred, even among never smokers and individuals with normal spirometry at baseline.

DISCUSSION: Reduced FEV₁ and FVC represent robust risk factors for cardiovascular disease and mortality. The fact that the increased risk was evident also at FEV₁ and FVC levels exceeding 80 %pred challenges the contemporary classification of lung function categories and the notion that the entire FEV₁- and FVC-range above 80 % of predicted represents a normal lung function.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation. We report a genome-wide association study and multi-trait analysis of DCM (14,256 cases) and three left ventricular traits (36,203 UK Biobank participants). We identified 80 genomic risk loci and prioritized 62 putative effector genes, including several with rare variant DCM associations (MAP3K7, NEDD4L and SSPN). Using single-nucleus transcriptomics, we identify cellular states, biological pathways, and intracellular communications that drive pathogenesis. We demonstrate that polygenic scores predict DCM in the general population and modify penetrance in carriers of rare DCM variants. Our findings may inform the design of genetic testing strategies that incorporate polygenic background. They also provide insights into the molecular etiology of DCM that may facilitate the development of targeted therapeutics.

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation. © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license