70-year legacy of the Framingham Heart Study

M6A modification in cardiovascular disease: With a focus on programmed cell death

N6-methyladenosine (m6A) methylation is one of the most predominant internal RNA modifications in eukaryotes and has become a hot spot in the field of epigenetics in recent years. Cardiovascular diseases (CVDs) are a leading cause of death globally. Emerging evidence demonstrates that RNA modifications, such as the m6A modification, are associated with the development and progression of many diseases, including CVDs. An increasing body of studies has indicated that programmed cell death (PCD) plays a vital role in CVDs. However, the molecular mechanisms underlying m6A modification and PCD in CVDs remain poorly understood. Herein, elaborating on the highly complex connections between the m6A mechanisms and different PCD signaling pathways and clarifying the exact molecular mechanism of m6A modification mediating PCD have significant meaning in developing new strategies for the prevention and therapy of CVDs. There is great potential for clinical application.

Development and External Validation of a Multidimensional Deep Learning Model to Dynamically Predict Kidney Outcomes in IgA Nephropathy

Key Points

Background

Accurately predicting kidney outcomes in IgA nephropathy is crucial for clinical decision making. Insufficient use of longitudinal data in previous studies has limited the accuracy and interpretability of prediction models for failing to reflect the chronic nature of IgA nephropathy. The aim of this study was to establish a multivariable dynamic deep learning model using comprehensive longitudinal data for the prediction of kidney outcomes in IgA nephropathy.

Methods

In this retrospective cohort study of 2056 patients with IgA nephropathy from 18 kidney centers, a total of 28,317 data points were collected by the sliding window method. Among them, 15,462 windows in a single center were randomly assigned to training (80%) and validation (20%) sets and 8797 windows in 18 kidney centers were assigned to an independent test set. Interpretable multivariable long short-term memory, a deep learning model, was implemented to predict kidney outcomes (kidney failure or 50% decline in kidney function) based on time-invariant variables measured at biopsy and time-variant variables measured during follow-up. Risk performance was evaluated using the Kaplan–Meier analysis and C-statistic. Trajectory analysis was performed to assess the various trends of clinical variables during follow-up.

Results

The model achieved a higher C-statistic (0.93; 95% confidence interval, 0.92 to 0.95) on the test set than the machine learning prediction model that we developed in a previous study using only baseline information (C-statistic, 0.84; 95% confidence interval, 0.80 to 0.88). The Kaplan–Meier analysis showed that groups with lower predicted risks from the full model survived longer than groups with higher risks. Time-variant variables demonstrated higher importance scores than time-invariant variables. Within time-variant variables, more recent measurements showed higher importance scores. Further interpretation showed that certain trajectory groups of time-variant variables such as serum creatinine and urine protein were associated with elevated risks of adverse outcomes.

Conclusions

In IgA nephropathy, a deep learning model can be used to accurately and dynamically predict kidney prognosis based on longitudinal data, and time-variant variables show strong ability to predict kidney outcomes.

Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models

INTRODUCTION

Identification of individuals with mild cognitive impairment (MCI) who are at risk of developing Alzheimer's disease (AD) is crucial for early intervention and selection of clinical trials.

METHODS

We applied natural language processing techniques along with machine learning methods to develop a method for automated prediction of progression to AD within 6 years using speech. The study design was evaluated on the neuropsychological test interviews of n = 166 participants from the Framingham Heart Study, comprising 90 progressive MCI and 76 stable MCI cases.

RESULTS

Our best models, which used features generated from speech data, as well as age, sex, and education level, achieved an accuracy of 78.5% and a sensitivity of 81.1% to predict MCI-to-AD progression within 6 years.

DISCUSSION

The proposed method offers a fully automated procedure, providing an opportunity to develop an inexpensive, broadly accessible, and easy-to-administer screening tool for MCI-to-AD progression prediction, facilitating development of remote assessment.

HIGHLIGHTS

Voice recordings from neuropsychological exams coupled with basic demographics can lead to strong predictive models of progression to dementia from mild cognitive impairment. The study leveraged AI methods for speech recognition and processed the resulting text using language models. The developed AI-powered pipeline can lead to fully automated assessment that could enable remote and cost-effective screening and prognosis for Alzehimer's disease.

Bidirectional Association Between Atrial Fibrillation and Myocardial Infarction, and Relation to Mortality in the Framingham Heart Study

BACKGROUND

Individuals with both atrial fibrillation (AF) and myocardial infarction (MI) have higher mortality compared with individuals with only 1 condition. Whether mortality differs according to the temporal order of AF and MI is unclear.

METHODS AND RESULTS

We included participants from the FHS (Framingham Heart Study) from 1960 and onwards. We assessed the hazard ratio (HR) of new-onset AF and MI, and mortality according to MI and AF status (prevalent and interim) using multivariable-adjusted Cox proportional hazards models. Interim diseases were modeled as time-varying variables. For the analysis of new-onset AF, 10 923 participants (55% women; mean±SD age, 54±8 years) were included. For new-onset MI, 10 804 participants (55% women; mean±SD age, 54±8 years) were included. Compared with no MI, the hazard of new-onset AF was higher in participants with prevalent (HR, 1.60 [95% CI, 1.32-1.94]) and interim MI (HR, 3.96 [95% CI, 3.18-4.91]). Both ST-segment-elevation MI and non-ST-segment-elevation MI were associated with new-onset AF. Interim AF, not prevalent AF, was associated with higher hazard rate of new-onset MI (HR, 2.21 [95% CI, 1.67-2.92]). Interim AF was associated with both ST-segment-elevation MI and non-ST-segment-elevation MI. Mortality was significantly greater among participants with AF and MI compared with participants with 1 of the 2, regardless of temporal order.

CONCLUSIONS

We report a bidirectional association between AF and MI, which was observed for both non-ST-segment-elevation MI and ST-segment-elevation MI. Participants with both AF and MI had considerably higher mortality compared with participants with only 1 of the 2 conditions, regardless of order.

Association between health literacy and Framingham risk score

High health literacy (HL) plays a critical role in preventing or delaying the onset of cardiovascular diseases (CVDs) and can improve disease management and control. The present study aims to determine the association between HL and non-laboratory-based (office-based) Framingham 10-year risk score of CVD. This cross-sectional study was conducted on 648 people aged 30-65 in the health centers of Jahrom. The Health Literacy Instrument for Adults (HELIA) was used to assess HL. The non-laboratory-based Framingham risk score (FRS) was utilized to determine the 10-year risk of CVDs. Risk factors such as age, gender, diabetes, current smoking status, systolic blood pressure (SBP), hypertension (HTN) treatment, and body mass index (BMI) were applied in the non-laboratory-based model. The average age of the subjects was 44.7 ± 10.5 years, among which 49.2% were males. The prevalence of diabetes, HTN, and smoking equaled 8.5%, 15.7%, and 10%, respectively. In addition, the average BMI was 26.1 ± 3.6 kg/m2. Based on the non-laboratory-based Framingham 10-year risk score of CVD, 72.5%, 13.9%, and 13.6% of the subjects were in the low, moderate, and high risk groups, respectively. Based on the HL grouping, the levels of insufficient, borderline, sufficient, and excellent HL were 19.3%, 26.4%, 34.6%, and 19.7%, respectively. A significant association was observed between 10-year CVD risk and HL grouping. In addition, a negative correlation was reported at the individual level between HL and non-laboratory-based FRS among the whole population (r = - 0.39, p < 0.001), men (r = - 0.32, p < 0.001), and women (r = - 0.42, p < 0.001). A higher HL score is associated with a lower risk of CVD. In addition, the adjusted logistic regression analysis showed that there was a strong association between elevated CVD risk (≥ 10%) and HL (OR 6.1, 95% CI 2.9-12.6) among inadequate HL participants compared with excellent HL individuals. Thus, designing and implementing training programs to increase HL, especially among those who are at risk of CVDs, should be regarded as an important issue for the prevention of such diseases.

Diet, Pace of Biological Aging, and Risk of Dementia in the Framingham Heart Study

OBJECTIVE

People who eat healthier diets are less likely to develop dementia, but the biological mechanism of this protection is not well understood. We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging.

METHODS

We analyzed Framingham Offspring Cohort data. We included participants ≥60 years-old, free of dementia and having dietary, epigenetic, and follow-up data. We assessed healthy diet as long-term adherence to the Mediterranean-Dash Intervention for Neurodegenerative Delay diet (MIND, over 4 visits spanning 1991-2008). We measured the pace of aging from blood DNA methylation data collected in 2005-2008 using the DunedinPACE epigenetic clock. Incident dementia and mortality were defined using study records compiled from 2005 to 2008 visit through 2018.

RESULTS

Of n = 1,644 included participants (mean age 69.6, 54% female), n = 140 developed dementia and n = 471 died over 14 years of follow-up. Greater MIND score was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. In mediation analysis, slower DunedinPACE accounted for 27% of the diet-dementia association and 57% of the diet-mortality association.

INTERPRETATION

Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention. However, a large fraction of the diet-dementia association remains unexplained and may reflect direct connections between diet and brain aging that do not overlap other organ systems. Investigation of brain-specific mechanisms in well-designed mediation studies is warranted. ANN NEUROL 2024;95:1069-1079.

[Predictive indicators and risk model construction for coronary artery lesions in Kawasaki disease children over 5 years old]

OBJECTIVES

To study predictive indicators for coronary artery lesions (CAL) and construct a risk prediction model for CAL in Kawasaki disease (KD) children over 5 years old.

METHODS

A retrospective analysis of KD children over 5 years old at Wuhan Children's Hospital of Tongji Medical College of Huazhong University of Science and Technology from January 2018 to January 2023 was conducted. Among them, 47 cases were complicated with CAL, and 178 cases were not. Multivariate logistic regression analysis was used to explore predictive indicators for CAL in KD children over 5 years old and construct a risk prediction model. The receiver operating characteristic curve was used to evaluate the effectiveness of the prediction model. Finally, the Framingham risk scoring method was used to quantify the predictive indicators, calculate the contribution of each indicator to the prediction of CAL in KD children over 5 years old, and construct a risk prediction scoring model.

RESULTS

The multivariate logistic regression analysis showed that the duration of fever before the initial intravenous immunoglobulin (IVIG) treatment (OR=1.374, 95%CI: 1.117-1.689), levels of hypersensitive C-reactive protein (hs-CRP; OR=1.008, 95%CI: 1.001-1.015), and serum ferritin levels (OR=1.002, 95%CI: 1.001-1.003) were predictive indicators for CAL in KD children over 5 years old. The optimal cutoff values for predicting CAL were: duration of fever before initial IVIG treatment of 6.5 days (AUC=0.654, 95%CI: 0.565-0.744), hs-CRP of 110.50 mg/L (AUC=0.686, 95%CI: 0.597-0.774), and ferritin of 313.62 mg/L (AUC=0.724, 95%CI: 0.642-0.805). According to the Framingham risk scoring method, the low, medium, and high-risk states of CAL occurrence were defined as probabilities of <10%, 10%-20%, and >20%, respectively, with corresponding scores of 0-4 points, 5-6 points, and ≥7 points.

CONCLUSIONS

In KD children over 5 years old, those with a longer duration of fever before initial IVIG treatment, higher levels of hs-CRP, or elevated serum ferritin levels are more likely to develop CAL.

Modifiable risk factors and risk of myocardial infarction in offspring with parental disease

AIMS

Children of patients with early-onset myocardial infarction (MI) are at increased risk, but the importance of concordant versus discordant parent-offspring risk factor profiles on MI risk is largely unknown. We quantified the long-term absolute risk of MI according to shared risk factors in adulthood.

METHODS

We sampled data on familial predisposed offspring and their parents from the Framingham Heart Study. Early MI was defined as a history of parental MI onset before age 55 in men or 65 in women. Individuals were matched 3:1 with non-predisposed offspring. Cardiovascular risk factors included obesity, smoking, hypertension, high cholesterol, and diabetes. We estimated the absolute 20-year incidence of MI using the Aalen-Johansen estimator.

RESULTS

At age 40, the 20-year risk of MI varied by cholesterol level (high cholesterol 25.7% [95% confidence interval 11.2%; 40.2%] vs. non-high cholesterol 3.4% [0.5; 6.4]) among predisposed individuals and this difference was greater than in controls (high cholesterol 9.3% [1.5; 17.0] vs. non-high cholesterol 2.5% [1.1; 3.8]). Similar results were observed for prevalent hypertension (26.7% [10.8; 42.5] vs. 4.0% [0.9; 7.1] in predisposed vs. 10.8% [3.2; 18.3] and 2.1% [0.8; 3.4] in controls). Among offspring without risk factors, parental risk factors carried a residual impact on 20-year MI risk in offspring (0% [0; 11.6] for 0-1 parental risk factors versus 3.3% [0; 9.8] for ≥2 parent risk factors at age 40, versus 2.9% [0; 8.4] and 8.5% [0; 19.8] at age 50 years).

CONCLUSION

Children of patients with early-onset MI have low absolute risks of MI in the absence of midlife cardiovascular risk factors, especially if the parent also had a low risk factor burden prior to MI.

Comparing the effect of imputation reference panel composition in four distinct Latin American cohorts

Genome-wide association studies have been useful in identifying genetic risk factors for various phenotypes. These studies rely on imputation and many existing panels are largely composed of individuals of European ancestry, resulting in lower levels of imputation quality in underrepresented populations. We aim to analyze how the composition of imputation reference panels affects imputation quality in four target Latin American cohorts. We compared imputation quality for chromosomes 7 and X when altering the imputation reference panel by: 1) increasing the number of Latin American individuals; 2) excluding either Latin American, African, or European individuals, or 3) increasing the Indigenous American (IA) admixture proportions of included Latin Americans. We found that increasing the number of Latin Americans in the reference panel improved imputation quality in the four populations; however, there were differences between chromosomes 7 and X in some cohorts. Excluding Latin Americans from analysis resulted in worse imputation quality in every cohort, while differential effects were seen when excluding Europeans and Africans between and within cohorts and between chromosomes 7 and X. Finally, increasing IA-like admixture proportions in the reference panel increased imputation quality at different levels in different populations. The difference in results between populations and chromosomes suggests that existing and future reference panels containing Latin American individuals are likely to perform differently in different Latin American populations.

Alcohol consumption as a socially contagious phenomenon in the Framingham Heart Study social network

We use longitudinal social network data from the Framingham Heart Study to examine the extent to which alcohol consumption is influenced by the network structure. We assess the spread of alcohol use in a three-state SIS-type model, classifying individuals as abstainers, moderate drinkers, and heavy drinkers. We find that the use of three-states improves on the more canonical two-state classification, as the data show that all three states are highly stable and have different social dynamics. We show that when modelling the spread of alcohol use, it is important to model the topology of social interactions by incorporating the network structure. The population is not homogeneously mixed, and clustering is high with abstainers and heavy drinkers. We find that both abstainers and heavy drinkers have a strong influence on their social environment; for every heavy drinker and abstainer connection, the probability of a moderate drinker adopting their drinking behaviour increases by [Formula: see text] and [Formula: see text], respectively. We also find that abstinent connections have a significant positive effect on heavy drinkers quitting drinking. Using simulations, we find that while both are effective, increasing the influence of abstainers appears to be the more effective intervention compared to reducing the influence of heavy drinkers.

The impact of concomitant chronic total occlusion on clinical outcomes in patients undergoing transcatheter aortic valve replacement: a large single-center analysis

Background

Coronary artery disease (CAD) is a common finding in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR). However, the impact on prognosis of chronic total occlusions (CTOs), a drastic expression of CAD, remains unclear.

Methods and results

We retrospectively reviewed 1,487 consecutive TAVR cases performed at a single tertiary care medical center. Pre-TAVR angiograms were analyzed for the presence of a CTO. At the time of TAVR, 11.2% (n = 167) patients had a CTO. There was no significant association between the presence of a CTO and in-hospital or 30-day mortality. There was also no difference in long-term survival. LV ejection fraction and mean aortic gradients were lower in the CTO group.

Conclusions

Our analysis suggests that concomitant CTO lesions in patients undergoing TAVR differ in their risk profile and clinical findings to patients without CTO. CTO lesion per se were not associated with increased mortality, nevertheless CTOs which supply non-viable myocardium in TAVR population were associated with increased risk of death. Additional research is needed to evaluate the prognostic significance of CTO lesions in TAVR patients.

Exposome in ischaemic heart disease: beyond traditional risk factors

Ischaemic heart disease represents the leading cause of morbidity and mortality, typically induced by the detrimental effects of risk factors on the cardiovascular system. Although preventive interventions tackling conventional risk factors have helped to reduce the incidence of ischaemic heart disease, it remains a major cause of death worldwide. Thus, attention is now shifting to non-traditional risk factors in the built, natural, and social environments that collectively contribute substantially to the disease burden and perpetuate residual risk. Of importance, these complex factors interact non-linearly and in unpredictable ways to often enhance the detrimental effects attributable to a single or collection of these factors. For this reason, a new paradigm called the 'exposome' has recently been introduced by epidemiologists in order to define the totality of exposure to these new risk factors. The purpose of this review is to outline how these emerging risk factors may interact and contribute to the occurrence of ischaemic heart disease, with a particular attention on the impact of long-term exposure to different environmental pollutants, socioeconomic and psychological factors, along with infectious diseases such as influenza and COVID-19. Moreover, potential mitigation strategies for both individuals and communities will be discussed.

Characteristics, Treatment, and In-Hospital Outcomes of Older Patients With STEMI Without Standard Modifiable Risk Factors

Background

Strategies targeting standard modifiable cardiovascular risk factors (SMuRFs), including hypertension, diabetes, hypercholesterolemia, and smoking, have been well established to prevent coronary heart disease. However, few studies have evaluated the management and outcomes of older patients without SMuRFs after myocardial infarction.

Objectives

The authors sought to evaluate the profile of patients with ST-segment elevation myocardial infarction (STEMI) aged ≥75 years without SMuRFs.

Methods

This study is based on the CCC-ACS (Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome) project. Patients aged ≥75 years with a first presentation of STEMI were enrolled in this study between November 2014 and December 2019. Modified Poisson regression was used to evaluate the association between SMuRF-less and in-hospital outcomes.

Results

Among 10,775 patients with STEMI aged ≥75 years, 1,633 (15.16%) had no SMuRFs. Compared with those with SMuRF, SMuRF-less patients received less evidence-based treatment. In-hospital mortality was similar among patients with and without SMuRFs (5.44% vs 5.14%; P = 0.630). However, after adjustment for patient characteristics and treatment, being SMuRF-less was significantly associated with a reduced risk of mortality (RR: 0.80; 95% CI: 0.65-0.99; P = 0.043). SMuRF-less patients also had a significantly reduced risk of in-hospital death when only adjusting for in-hospital treatment (RR: 0.78; 95% CI: 0.63-0.98; P = 0.030), regardless of patient characteristics.

Conclusions

Approximately 1 in 7 STEMI patients in China ≥75 years old had no SMuRFs. The similar mortality in patients with and without SMuRF can be partially explained by the inadequate in-hospital treatment of SMuRF-less patients. The quality of care for older patients without SMuRF should be improved. (CCC Project-Acture Coronary Syndrome; NCT02306616).

Association of Loneliness with Functional Connectivity MRI, Amyloid-β PET, and Tau PET Neuroimaging Markers of Vulnerability for Alzheimer's Disease

Background

Loneliness has been declared an "epidemic" associated with negative physical, mental, and cognitive health outcomes such as increased dementia risk. Less is known about the relationship between loneliness and advanced neuroimaging correlates of Alzheimer's disease (AD).

Objective

To assess whether loneliness was associated with advanced neuroimaging markers of AD using neuroimaging data from Framingham Heart Study (FHS) participants without dementia.

Methods

In this cross-sectional observational analysis, we used functional connectivity MRI (fcMRI), amyloid-β (Aβ) PET, and tau PET imaging data collected between 2016 and 2019 on eligible FHS cohort participants. Loneliness was defined as feeling lonely at least one day in the past week. The primary fcMRI marker was Default Mode Network intra-network connectivity. The primary PET imaging markers were Aβ deposition in precuneal and FLR (frontal, lateral parietal and lateral temporal, retrosplenial) regions, and tau deposition in the amygdala, entorhinal, and rhinal regions.

Results

Of 381 participants (mean age 58 [SD 10]) who met inclusion criteria for fcMRI analysis, 5% were classified as lonely (17/381). No association was observed between loneliness status and network changes. Of 424 participants (mean age 58 [SD = 10]) meeting inclusion criteria for PET analyses, 5% (21/424) were lonely; no associations were observed between loneliness and either Aβ or tau deposition in primary regions of interest.

Conclusions

In this cross-sectional study, there were no observable associations between loneliness and select fcMRI, Aβ PET, and tau PET neuroimaging markers of AD risk. These findings merit further investigation in prospective studies of community-based cohorts.

Diabetic Cardiomyopathy: 2023 Update by the International Multidisciplinary Board of Experts

Diabetes mellitus (DM) is considered by many the pandemic of the 21st century and is associated with multiple organ damages. Among these, cardiovascular complications are responsible for an incredible burden of mortality and morbidity in Western Countries. The study of the pathological mechanisms responsible for the cardiovascular complications in DM patients is key for the development of new therapeutic strategies. The metabolic disorders caused by hyperglycemia, insulin resistance, and dyslipidemia, results in a cascade of pathomorphological changes favoring the atherosclerotic process and leading to myocardial remodeling. Parallel to this, oxidative stress, calcium overload, mitochondrial dysfunction, activation of protein kinase C signaling pathways, myocardial lipomatosis, and low-grade inflammation of the myocardium - are the main pathways responsible for the diabetic cardiomyopathy development. This review aims to appraise and discuss the pathogenetic mechanisms behind the diabetic cardiomyopathy development.

Cardiovascular Disease in Anti-neutrophil Cytoplasm Antibody-Associated Vasculitis

PURPOSE OF REVIEW

Anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) is a rare, multisystem, autoimmune disease characterised by microvascular inflammation. Over the past 20 years, advances in immunological management have improved short-term patient outcomes. Longer-term patient outcomes remain poor with cardiovascular disease now the leading cause of death in AAV. Here, we examine the potential pathways that contribute to the increased risk of cardiovascular disease in AAV and the current evidence to manage this risk.

RECENT FINDINGS

The incidence of cardiovascular disease in AAV exceeds that expected by traditional risk factors alone, suggesting a contribution from disease-specific factors. Similarly, it is unclear how different immunosuppressive therapies contribute to and modify cardiovascular risk, and there is a paucity of data examining the efficacy of traditional cardioprotective medications in AAV. There is a lack of evidence-based cardiovascular risk assessment tools and cardioprotective therapies in patients with AAV which should be addressed to improve long-term outcomes.

Alcohol intake including wine drinking is associated with decreased platelet reactivity in a large population sample

BACKGROUND

Alcohol consumption is linked to decreased platelet function. Whether this link is dependent on sex or type of beverage remains unclear.

METHODS

Cross-sectional data were obtained from the Framingham Heart Study (N = 3427). Alcohol consumption was assessed by using standardized medical history and Harvard semi-quantitative food frequency questionnaires. Five bioassays measured 120 platelet reactivity traits across agonists in whole-blood and platelet-rich plasma samples. Linear mixed-effects models adjusted for age, sex and aspirin use, hypertension, body mass index, cholesterol, high-density lipoprotein, triglycerides, smoking and diabetes evaluated associations between platelet reactivity and alcohol consumption. Beta effects, the regression coefficients that estimate the amount of change in each unit of the predictor variable whereas all other predictor variables remain fixed, for heavy alcohol consumption were compared with effects of aspirin use.

RESULTS

Alcohol consumption was associated with decreased platelet reactivity, with more associations among wine and liquor compared with beer. Many platelet-alcohol associations in the full sample (86%, P < 0.01) had larger effect sizes in females. Lower light transmission aggregometry adenosine diphosphate (1.82 µM) maximum aggregation (P = 2.6E-3, 95% CI = -0.07, -0.02, β = -0.042) and area under the curve (P = 7.7E-3, 95% CI = -0.07, -0.01, β = -0.039) were associated with white wine consumption; however, red wine had no associations with platelet reactivity. The effect of aspirin use was on average 11.3 (±4.0) times greater than that of heavy drinking in our full sample.

CONCLUSIONS

We confirm associations between alcohol consumption and decreased platelet reactivity. Effects appeared larger for liquor and wine intake and in our female cohort. Red wine consumption is not associated with lower platelet function, contrasting with prior population studies. Although we report an inhibitory relationship between alcohol intake and platelet function, these effects appear much smaller than that of aspirin use.

Inflammation in Heart Failure-Future Perspectives

Chronic heart failure is a terminal point of a vast majority of cardiac or extracardiac causes affecting around 1-2% of the global population and more than 10% of the people above the age of 65. Inflammation is persistently associated with chronic diseases, contributing in many cases to the progression of disease. Even in a low inflammatory state, past studies raised the question of whether inflammation is a constant condition, or if it is, rather, triggered in different amounts, according to the phenotype of heart failure. By evaluating the results of clinical studies which focused on proinflammatory cytokines, this review aims to identify the ones that are independent risk factors for heart failure decompensation or cardiovascular death. This review assessed the current evidence concerning the inflammatory activation cascade, but also future possible targets for inflammatory response modulation, which can further impact the course of heart failure.

Effectiveness of multimodal participant recruitment in SPARK, a large, online longitudinal research study of autism

Background

SPARK launched in 2016 to build a US cohort of autistic individuals and their family members. Enrollment includes online consent to share data and optional consent to provide saliva for genomic analysis. SPARK's recruitment strategies include social media and support of a nation-wide network of clinical sites. This study evaluates SPARK's recruitment strategies to enroll a core study population.

Methods

Individuals who joined between January 31, 2018, and May 29, 2019 were included in the analysis. Data include sociodemographic characteristics, clinical site referral, the website URL used to join, how the participant heard about SPARK, enrollment completion (online registration, study consents, and returning saliva sample), and completion of the baseline questionnaire. Logistic regressions were performed to evaluate the odds of core participant status (completing enrollment and baseline questionnaire) by recruitment strategy.

Results

In total, 31,715 individuals joined during the study period, including 40% through a clinical site. Overall, 88% completed online registration, 46% returned saliva, and 38% were core participants. Those referred by a clinical site were almost twice as likely to be core participants. Those who directly visited the SPARK website or performed a Google search were more likely to be core participants than those who joined through social media.

Discussion

Being a core participant may be associated with the "personal" connection and support provided by a clinical site and/or site staff, as well as greater motivation to seek research opportunities. Findings from this study underscore the value of adopting a multimodal recruitment approach that combines social media and a physical presence.

Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study

Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.

Gene Regulatory Networks in Coronary Artery Disease

PURPOSE OF REVIEW

Coronary artery disease is a complex disorder and the leading cause of mortality worldwide. As technologies for the generation of high-throughput multiomics data have advanced, gene regulatory network modeling has become an increasingly powerful tool in understanding coronary artery disease. This review summarizes recent and novel gene regulatory network tools for bulk tissue and single cell data, existing databases for network construction, and applications of gene regulatory networks in coronary artery disease.

RECENT FINDINGS

New gene regulatory network tools can integrate multiomics data to elucidate complex disease mechanisms at unprecedented cellular and spatial resolutions. At the same time, updates to coronary artery disease expression data in existing databases have enabled researchers to build gene regulatory networks to study novel disease mechanisms. Gene regulatory networks have proven extremely useful in understanding CAD heritability beyond what is explained by GWAS loci and in identifying mechanisms and key driver genes underlying disease onset and progression. Gene regulatory networks can holistically and comprehensively address the complex nature of coronary artery disease. In this review, we discuss key algorithmic approaches to construct gene regulatory networks and highlight state-of-the-art methods that model specific modes of gene regulation. We also explore recent applications of these tools in coronary artery disease patient data repositories to understand disease heritability and shared and distinct disease mechanisms and key driver genes across tissues, between sexes, and between species.

Protocol for Brain Magnetic Resonance Imaging and Extraction of Imaging-Derived Phenotypes from the China Phenobank Project

Imaging-derived phenotypes (IDPs) have been increasingly used in population-based cohort studies in recent years. As widely reported, magnetic resonance imaging (MRI) is an important imaging modality for assessing the anatomical structure and function of the brain with high resolution and excellent soft-tissue contrast. The purpose of this article was to describe the imaging protocol of the brain MRI in the China Phenobank Project (CHPP). Each participant underwent a 30-min brain MRI scan as part of a 2-h whole-body imaging protocol in CHPP. The brain imaging sequences included T1-magnetization that prepared rapid gradient echo, T2 fluid-attenuated inversion-recovery, magnetic resonance angiography, diffusion MRI, and resting-state functional MRI. The detailed descriptions of image acquisition, interpretation, and post-processing were provided in this article. The measured IDPs included volumes of brain subregions, cerebral vessel geometrical parameters, microstructural tracts, and function connectivity metrics.

Genetically Predicted Causal Effects of Gut Microbiota and Gut Metabolites on Digestive Tract Cancer: A Two-Sample Mendelian Randomization Analysis

Background

Evidence from numerous observational studies and clinical trials has linked gut microbiota and metabolites to digestive tract cancer. However, the causal effect between these factors remains uncertain.

Methods

Data for this study were obtained from the MiBioGen, TwinsUK Registry, and FinnGen (version R8). Two-sample Mendelian randomization analysis with inverse variance weighting method was primarily used, and the results were validated by heterogeneity analysis, pleiotropy test, and sensitivity analysis.

Results

At P < 5 × 10-8, our analysis identified four gut microbiotas as risk factors for digestive tract cancer and six as risk factors for colorectal cancer. Conversely, one gut microbiota exhibited protection against bile duct cancer, and two showed protective effects against stomach cancer. At P < 1 × 10-5, our investigation revealed five, six, three, eight, eight, and eight gut microbiotas as risk factors for esophageal, stomach, bile duct, liver, pancreatic, and colorectal cancers, respectively. In contrast, four, two, eight, two, two, and five gut microbiotas exhibited protective effects against these cancers. Additionally, GABA, a metabolite of gut microbiota, displayed a significant protective effect against colorectal cancer.

Conclusion

In conclusion, specific gut microbiota and metabolites play roles as risk factors or protective factors for digestive tract cancer, and a causal relationship between them has been established, offering novel insights into gut microbiota-mediated cancer development.

Clinical and Histopathologic Characteristics of Pediatric Patients With Primary Membranous Nephropathy

Introduction

Primary membranous nephropathy (PMN) is uncommon in children. Therefore, data on the clinical course of affected children are scarce. In recent years, several novel antigens have been implicated in the pathogenesis of PMN. However, the histopathologic characteristics of pediatric patients with PMN remain poorly represented in the literature.

Methods

We have retrospectively analyzed the clinical presentation and outcomes data of 21 children with PMN from 3 centers in the United States. In addition, we have identified novel antigens in biopsy specimens from these patients and correlated their presence or absence to clinical outcomes. Finally, we compared the results of the novel antigen staining from our clinical cohort to a validation cohort of 127 biopsy specimens from children with PMN at Arkana Laboratories.

Results

The data from the 2 cohorts demonstrated similar overall antigen positivity rates of 62% to 63%, with phospholipase A2 receptor (PLA2R) and exostosin 1 (EXT1) being the most commonly found antigens. Results from the clinical cohort showed that overall, the kidney prognosis for children with PMN was good, with 17 of 21 patients entering a complete or partial remission. Children who were positive for PLA2R or EXT1 were significantly more likely to enter remission than those in the antigen negative group.

Conclusion

Approximately 60% of pediatric membranous cases are positive for a novel antigen on kidney biopsy and the clinical prognosis is generally favorable. More studies are needed to understand the clinical implications of each specific novel antigen.

Alcohol consumption and epigenetic age acceleration across human adulthood

The alcohol-associated biological aging remains to be studied across adulthood. We conducted linear regression analyses to investigate the associations between alcohol consumption and two DNA methylation-based biological age acceleration metrics in 3823 Framingham Heart Study participants (24-92 years and 53.8% women) adjusting for covariates. We also investigated whether the two epigenetic aging metrics mediated the association of alcohol consumption with hypertension. We found that higher long-term average alcohol consumption was significantly associated with biological age acceleration assessed by GrimAge acceleration (GAA) and PhenoAge acceleration (PAA) in middle-aged (45-64 years, n = 1866) and older (65-92 years, n = 1267) participants while not in young participants (24-44 years, n = 690). For example, one additional standard drink of alcohol (~14 grams of ethanol per day) was associated with a 0.71 ± 0.15-year (p = 2.1e-6) and 0.60 ± 0.18-year (p = 7.5e-4) increase in PAA in middle-aged and older participants, respectively, but the association was not significant in young participants (p = 0.23). One additional standard serving of liquor (~14 grams of ethanol) was associated with a greater increase in GAA (0.82-year, p = 4.8e-4) and PAA (1.45-year, p = 7.4e-5) than beer (GAA: 0.45-year, p = 5.2e-4; PAA: 0.48-year, p = 0.02) and wine (GAA: 0.51-year, p = 0.02; PAA: 0.91-year, p = 0.008) in middle-aged participant group. We observed that up to 28% of the association between alcohol consumption and hypertension was mediated by GAA or PAA in the pooled sample. Our findings suggest that alcohol consumption is associated with greater biological aging quantified by epigenetic aging metrics, which may mediate the association of alcohol consumption with quantitative traits, such as hypertension.

The Women's Soccer Health Study: From Head to Toe

OBJECTIVES

Women are under-represented in the sports literature despite increasing rates of sports participation. Our objective was to investigate the risks and benefits of an elite women's soccer career in five health domains: general, musculoskeletal, reproductive endocrinology, post-concussion, and mental.

METHODS

An online survey was distributed to retired US college, semi-professional, professional, and national team soccer players using personal networks, email, and social media. Short validated questionnaires were used to evaluate the health domains, including the Patient-Reported Outcomes Measurement Information System (PROMIS), Single Assessment Numerical Evaluation (SANE), Post-Concussion Symptom Scale (PCSS), and Patient Health Questionnaire (PHQ).

RESULTS

A total of 560 eligible players responded to the survey over a 1-year period. The highest competitive levels were 73% college, 16% semi-professional, 8% professional, and 4% national team. The mean number of years since retirement was 12 (SD = 9), and 17.0% retired for involuntary reasons. The mean SANE scores (0-100 scale as percentage of normal) were knee = 75% (SD = 23), hip = 83% (SD = 23), and shoulder = 87% (SD = 21). The majority (63%) reported that their current activity level included participation in impact sports. A substantial proportion of players reported menstrual irregularities during their careers: 40% had fewer periods with increasing exercise and 22% had no periods for ≥ 3 months. The players (n = 44) who felt that post-concussion symptoms were due to soccer reported more time-loss concussions (F[2] = 6.80, p = 0.002) and symptom severity (F[2] = 30.26, p < 0.0001). Players who recently retired (0-5 years) reported the highest anxiety/depression scores and lowest satisfaction rates compared with those who retired 19+ years ago.

CONCLUSION

Health concerns include musculoskeletal injuries, post-concussion symptoms, and lower mental health in the early years following retirement. This comprehensive survey provides initial results that will lay the foundation for further analyses and prioritize research studies that can help all female athletes.

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants

Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.

Tau Positron Emission Tomography and Neurocognitive Function Among Former Professional American-Style Football Players

American-style football (ASF) players experience repetitive head impacts that may result in chronic traumatic encephalopathy neuropathological change (CTE-NC). At present, a definitive diagnosis of CTE-NC requires the identification of localized hyperphosphorylated Tau (p-Tau) after death via immunohistochemistry. Some studies suggest that positron emission tomography (PET) with the radiotracer [18F]-Flortaucipir (FTP) may be capable of detecting p-Tau and thus establishing a diagnosis of CTE-NC among living former ASF players. To assess associations between FTP, football exposure, and objective neuropsychological measures among former professional ASF players, we conducted a study that compared former professional ASF players with age-matched male control participants without repetitive head impact exposure. Former ASF players and male controls underwent structural magnetic resonance imaging and PET using FTP for p-Tau and [11C]-PiB for amyloid-β. Former players underwent neuropsychological testing. The ASF exposure was quantified as age at first exposure, professional career duration, concussion signs and symptoms burden, and total years of any football play. Neuropsychological testing included measures of memory, executive functioning, and depression symptom severity. P-Tau was quantified as FTP standardized uptake value ratios (SUVR) and [11C]-PiB by distribution volume ratios (DVR) using cerebellar grey matter as the reference region. There were no significant differences in [18F]-FTP uptake among former ASF players (n = 27, age = 50 ± 7 years) compared with control participants (n = 11, age = 55 ± 4 years), nor did any participant have significant amyloid-β burden. Among ASF participants, there were no associations between objective measures of neurocognitive functioning and [18F]-FTP uptake. There was a marginally significant difference, however, between [18F]-FTP uptake isolated to the entorhinal cortex among players in age-, position-, and race-adjusted models (p = 0.05) that may represent an area of future investigation. The absence of increased [18F]-FTP uptake in brain regions previously implicated in CTE among former professional ASF players compared with controls questions the utility of [18F]-FTP PET for clinical evaluation in this population.

Hypomethylation of ABCG1 in peripheral blood as a potential marker for the detection of coronary heart disease

BACKGROUND

Novel molecular biomarkers for the risk assessment and early detection of coronary heart disease (CHD) are urgently needed for disease prevention. Altered methylation of ATP-binding cassette subfamily G member 1 (ABCG1) has been implicated in CHD but was mostly studied in Caucasians. Exploring the potential relationship between ABCG1 methylation in blood and CHD among the Chinese population would yield valuable insights.

METHODS

Peripheral blood samples were obtained from a case-control study (287 CHD patients vs. 277 controls) and a prospective nested case-control study (171 CHD patients and 197 matched controls). DNA extraction and bisulfite-specific PCR amplification techniques were employed for sample processing. Quantitative assessment of methylation levels was conducted using mass spectrometry. Statistical analyses involved the utilization of logistic regression and nonparametric tests.

RESULTS

We found hypomethylation of ABCG1 in whole blood was associated with the risk of CHD in both studies, which was enhanced in heart failure (HF) patients, female and younger subjects. When combined with baseline characteristics, altered ABCG1 methylation showed improved predictive effect for differentiating CHD cases, ischemic cardiomyopathy (ICM) cases, younger than 60 years CHD cases, and female CHD cases from healthy controls (area under the curve (AUC) = 0.68, 0.71, 0.74, and 0.73, respectively).

CONCLUSIONS

We demonstrated a robust link between ABCG1 hypomethylation in whole blood and CHD risk in the Chinese population and provided novel evidence indicating that aberrant ABCG1 methylation in peripheral blood can serve as an early detection biomarker for CHD patients.

Machine Learning for Risk Factor Identification and Cardiovascular Mortality Prediction Among Patients with Osteoporosis

Risk prediction tools are increasingly popular aids in clinical decision-making. However, the underlying models are often trained on data from general patient cohorts and may not be representative of and suitable for use with targeted patient groups in actual clinical practice, such as in the case of osteoporosis patients who may be at elevated risk of mortality. We developed and internally validated a cardiovascular mortality risk prediction model tailored to individuals with osteoporosis using a range of machine learning models. We compared the performance of machine learning models with existing expert-based models with respect to data-driven risk factor identification, discrimination, and calibration. The proposed models were found to outperform existing cardiovascular mortality risk prediction tools for the osteoporosis population. External validation of the model is recommended.Clinical Relevance- This study presents the performance of machine learning models for cardiovascular death prediction among osteoporotic patients as well as the risk factors identified by the models to be important predictors.

Diet, pace of biological aging, and risk of dementia in the Framingham Heart Study

INTRODUCTION

We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging.

METHODS

We analyzed Framingham Offspring Cohort data (≥60y). We measured healthy diet using the Dietary Guideline for Americans (DGA, 3 visits 1991-2008), pace of aging using the DunedinPACE epigenetic clock (2005-2008), and incident dementia and mortality using records (compiled 2005-2018).

RESULTS

Of n=1,525 included participants (mean age 69.7, 54% female), n=129 developed dementia and n=432 died over follow-up. Greater DGA adherence was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. Slower DunedinPACE accounted for 15% of the DGA association with dementia and 39% of the DGA association with mortality.

DISCUSSION

Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention.

Exploring Artificial Intelligence in Anesthesia: A Primer on Ethics, and Clinical Applications

The field of anesthesia has always been at the forefront of innovation and technology, and the integration of Artificial Intelligence (AI) represents the next frontier in anesthesia care. The use of AI and its subtypes, such as machine learning, has the potential to improve efficiency, reduce costs, and ameliorate patient outcomes. AI can assist with decision making, but its primary advantage lies in empowering anesthesiologists to adopt a proactive approach to address clinical issues. The potential uses of AI in anesthesia can be schematically grouped into clinical decision support and pharmacologic and mechanical robotic applications. Tele-anesthesia includes strategies of telemedicine, as well as device networking, for improving logistics in the operating room, and augmented reality approaches for training and assistance. Despite the growing scientific interest, further research and validation are needed to fully understand the benefits and limitations of these applications in clinical practice. Moreover, the ethical implications of AI in anesthesia must also be considered to ensure that patient safety and privacy are not compromised. This paper aims to provide a comprehensive overview of AI in anesthesia, including its current and potential applications, and the ethical considerations that must be considered to ensure the safe and effective use of the technology.

Matching science to reality: how to deploy a participant-driven digital brain health platform

Introduction

Advances in digital technologies for health research enable opportunities for digital phenotyping of individuals in research and clinical settings. Beyond providing opportunities for advanced data analytics with data science and machine learning approaches, digital technologies offer solutions to several of the existing barriers in research practice that have resulted in biased samples.

Methods

A participant-driven, precision brain health monitoring digital platform has been introduced to two longitudinal cohort studies, the Boston University Alzheimer's Disease Research Center (BU ADRC) and the Bogalusa Heart Study (BHS). The platform was developed with prioritization of digital data in native format, multiple OS, validity of derived metrics, feasibility and usability. A platform including nine remote technologies and three staff-guided digital assessments has been introduced in the BU ADRC population, including a multimodal smartphone application also introduced to the BHS population. Participants select which technologies they would like to use and can manipulate their personal platform and schedule over time.

Results

Participants from the BU ADRC are using an average of 5.9 technologies to date, providing strong evidence for the usability of numerous digital technologies in older adult populations. Broad phenotyping of both cohorts is ongoing, with the collection of data spanning cognitive testing, sleep, physical activity, speech, motor activity, cardiovascular health, mood, gait, balance, and more. Several challenges in digital phenotyping implementation in the BU ADRC and the BHS have arisen, and the protocol has been revised and optimized to minimize participant burden while sustaining participant contact and support.

Discussion

The importance of digital data in its native format, near real-time data access, passive participant engagement, and availability of technologies across OS has been supported by the pattern of participant technology use and adherence across cohorts. The precision brain health monitoring platform will be iteratively adjusted and improved over time. The pragmatic study design enables multimodal digital phenotyping of distinct clinically characterized cohorts in both rural and urban U.S. settings.

Risk of death by suicide following self-harm presentations to healthcare: development and validation of a multivariable clinical prediction rule (OxSATS)

BACKGROUND

Assessment of suicide risk in individuals who have self-harmed is common in emergency departments, but is often based on tools developed for other purposes.

OBJECTIVE

We developed and validated a predictive model for suicide following self-harm.

METHODS

We used data from Swedish population-based registers. A cohort of 53 172 individuals aged 10+ years, with healthcare episodes of self-harm, was split into development (37 523 individuals, of whom 391 died from suicide within 12 months) and validation (15 649 individuals, 178 suicides within 12 months) samples. We fitted a multivariable accelerated failure time model for the association between risk factors and time to suicide. The final model contains 11 factors: age, sex, and variables related to substance misuse, mental health and treatment, and history of self-harm. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis guidelines were followed for the design and reporting of this work.

FINDINGS

An 11-item risk model to predict suicide was developed using sociodemographic and clinical risk factors, and showed good discrimination (c-index 0.77, 95% CI 0.75 to 0.78) and calibration in external validation. For risk of suicide within 12 months, using a 1% cut-off, sensitivity was 82% (75% to 87%) and specificity was 54% (53% to 55%). A web-based risk calculator is available (Oxford Suicide Assessment Tool for Self-harm or OxSATS).

CONCLUSIONS

OxSATS accurately predicts 12-month risk of suicide. Further validations and linkage to effective interventions are required to examine clinical utility.

CLINICAL IMPLICATIONS

Using a clinical prediction score may assist clinical decision-making and resource allocation.

Cause-specific excess mortality after first diagnosis of bipolar disorder: population-based cohort study

BACKGROUND

Bipolar disorder (BD) is associated with increased mortality, but evidence on cause-specific mortality is limited.

OBJECTIVE

To investigate cause-specific premature excess mortality in BD.

METHODS

Finnish nationwide cohort study of individuals with and without a diagnosis of BD who were aged 15-64 years during 2004-2018. Standardised mortality ratios (SMRs) with 95% CIs were calculated for BD using the mortality rates in the Finnish general population without BD as weights. Causes of death were defined by the International Classification of Diseases, 10th revision codes.

FINDINGS

Of the included 47 018 individuals with BD, 3300 (7%) died during follow-up. Individuals with BD had sixfold higher mortality due to external causes (SMR: 6.01, 95% CI: 5.68, 6.34) and twofold higher mortality due to somatic causes (SMR: 2.06, 95% CI: 1.97, 2.15). Of the deaths due to external causes, 83% (1061/1273) were excess deaths, whereas 51% (1043/2027) of the deaths due to somatic causes were excess. About twice the number of potential years of life were lost in excess due to external causes than due to somatic causes. Alcohol-related causes contributed more to excess mortality than deaths due to cardiovascular disease.

CONCLUSION

External causes of death contributed more to the mortality gap than somatic causes after controlling for age-specific background general population mortality.

CLINICAL IMPLICATION

A balanced consideration between therapeutic response, different treatment options and risk of cause-specific mortality is needed to prevent premature mortality in BD and to reduce the mortality gap.

Cardiovascular disease incidence prediction by machine learning and statistical techniques: a 16-year cohort study from eastern Mediterranean region

BACKGROUND

Cardiovascular diseases (CVD) are the predominant cause of early death worldwide. Identification of people with a high risk of being affected by CVD is consequential in CVD prevention. This study adopts Machine Learning (ML) and statistical techniques to develop classification models for predicting the future occurrence of CVD events in a large sample of Iranians.

METHODS

We used multiple prediction models and ML techniques with different abilities to analyze the large dataset of 5432 healthy people at the beginning of entrance into the Isfahan Cohort Study (ICS) (1990-2017). Bayesian additive regression trees enhanced with "missingness incorporated in attributes" (BARTm) was run on the dataset with 515 variables (336 variables without and the remaining with up to 90% missing values). In the other used classification algorithms, variables with more than 10% missing values were excluded, and MissForest imputes the missing values of the remaining 49 variables. We used Recursive Feature Elimination (RFE) to select the most contributing variables. Random oversampling technique, recommended cut-point by precision-recall curve, and relevant evaluation metrics were used for handling unbalancing in the binary response variable.

RESULTS

This study revealed that age, systolic blood pressure, fasting blood sugar, two-hour postprandial glucose, diabetes mellitus, history of heart disease, history of high blood pressure, and history of diabetes are the most contributing factors for predicting CVD incidence in the future. The main differences between the results of classification algorithms are due to the trade-off between sensitivity and specificity. Quadratic Discriminant Analysis (QDA) algorithm presents the highest accuracy (75.50 ± 0.08) but the minimum sensitivity (49.84 ± 0.25); In contrast, decision trees provide the lowest accuracy (51.95 ± 0.69) but the top sensitivity (82.52 ± 1.22). BARTm.90% resulted in 69.48 ± 0.28 accuracy and 54.00 ± 1.66 sensitivity without any preprocessing step.

CONCLUSIONS

This study confirmed that building a prediction model for CVD in each region is valuable for screening and primary prevention strategies in that specific region. Also, results showed that using conventional statistical models alongside ML algorithms makes it possible to take advantage of both techniques. Generally, QDA can accurately predict the future occurrence of CVD events with a fast (inference speed) and stable (confidence values) procedure. The combined ML and statistical algorithm of BARTm provide a flexible approach without any need for technical knowledge about assumptions and preprocessing steps of the prediction procedure.

Physiology and Biomarkers for Surveillance of Occupational Lung Disease

Respiratory surveillance is the process whereby a group of exposed workers are regularly tested (or screened) for those lung diseases which occur as a result of a specific work exposure. Surveillance is performed by assessing various measures of biological or pathological processes (or biomarkers) for change over time. These traditionally include questionnaires, lung physiological assessments (especially spirometry), and imaging. Early detection of pathological processes or disease can enable removal of a worker from a potentially harmful exposure at an early stage. In this article, we summarize the physiological biomarkers currently used for respiratory surveillance, while commenting on differences in interpretative strategies between different professional groups. We also briefly review the many new techniques which are currently being assessed for respiratory surveillance in prospective research studies and which are likely to significantly broaden and enhance this field in the near future.

Family History of Modifiable Risk Factors and Association With Future Cardiovascular Disease

Background A parental history of cardiovascular disease (CVD) confers greater risk of future CVD among offspring. Whether the presence of parental modifiable risk factors contribute to or modify CVD risk in offspring is unclear. Methods and Results We studied 6278 parent-child trios in the multigenerational longitudinal Framingham Heart Study. We assessed parental history of CVD and modifiable risk factors (smoking, hypertension, diabetes, obesity, and hyperlipidemia). Multivariable Cox models were used to evaluate the association of parental history and future CVD among offspring. Among 6278 individuals (mean age 45±11 years), 44% had at least 1 parent with history of CVD. Over a median follow-up of 15 years, 353 major CVD events occurred among offspring. Parental history of CVD conferred 1.7-fold increased hazard of future CVD (hazard ratio [HR], 1.71 [95% CI, 1.33-2.21]). Parental obesity and smoking status were associated with higher hazard of future CVD (obesity: HR, 1.32 [95% CI, 1.06-1.64]; smoking: HR, 1.34 [95% CI, 1.07-1.68], attenuated after adjusting for offspring smoking status). By contrast, parental history of hypertension, diabetes, and hypercholesterolemia were not associated with future CVD in offspring (P>0.05 for all). Furthermore, parental risk factors did not modify the association of parental CVD history on future offspring CVD risk. Conclusions Parental history of obesity and smoking were associated with a higher hazard of future CVD in offspring. By contrast, other parental modifiable risk factors did not alter offspring CVD risk. In addition to parental CVD, the presence of parental obesity should prompt a focus on disease prevention.

Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis

BACKGROUND

Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk.

OBJECTIVE

The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF.

METHODS

Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m²), as well as the relation between self-reported physical activity and predicted 5-year AF risk.

RESULTS

We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk.

CONCLUSIONS

Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.

The impact of chronic total occlusions in patients undergoing transcatheter aortic valve replacement: A systematic review and meta-analysis

Coronary artery disease (CAD) is frequently encountered in patients evaluated for transcatheter aortic valve replacement (TAVR) due to severe aortic stenosis. The prognostic relevance of chronic total occlusions (CTOs) in this setting is poorly understood. We conducted a search of MEDLINE and EMBASE to identify studies evaluating patients who underwent TAVR and evaluated outcomes depending on the presence of coronary CTOs. Pooled analysis was performed to estimate the rate and risk ratio for mortality. Four studies involving 25,432 patients fulfilled the inclusion criteria. The follow up ranged from in-hospital outcomes to 8-years follow-up. Coronary artery disease was present in 67.8% to 75.5% of patients in 3 studies which reported this variable. The prevalence of CTOs varied between 2% and 12.6% in this cohort. The presence of CTOs was associated with increase in length of stay (8.1 ± 8.2 vs. 5.9 ± 6.5, p < 0.01), cardiogenic shock (5.1% vs. 1.7%, p < 0.01), acute myocardial infarction (5.8% vs. 2.8%, p = 0.02) and acute kidney injury (18.6% vs. 13.9%, p = 0.048). The pooled 1-year death rate revealed 41 deaths in 165 patients in the CTO group and 396 deaths in 1663 patients with no CTO ((24.8%) vs. (23.8%)). The meta-analysis of death with CTO versus no CTO showed a nonsignificant trend toward increased mortality with CTOs (risk ratio 1.11 95% CI 0.90-1.40, I²  = 0%). Our analysis suggests that concomitant CTO lesions in patients undergoing TAVR are common, and its presence was associated with increased in-hospital complications. However, CTO presence by itself was not associated with increased long-term mortality, only a nonsignificant trend toward an increased risk of death in patients with CTO was found. Further studies are warranted to assess the prognostic relevance of CTO lesion in TAVR patients.

Association of MRI Visible Perivascular Spaces and Neurofilament Light Chain: The Framingham Heart Study

BACKGROUND

Neurofilament light chain (NfL) is a marker of neuronal injury. Perivascular spaces (PVS) visible on magnetic resonance imaging (MRI) represent cerebral small vessel disease (CSVD) but their role as markers of neuronal injury needs further clarification.

OBJECTIVE

To relate PVS burden according to brain topography and plasma NfL.

METHODS

Framingham Heart Study (FHS) participants with brain MRI and NfL measurements were included. PVS were rated in the basal ganglia (BG) and centrum semiovale (CSO) using validated methods and categorized based on counts. A mixed region variable representing high burden PVS in either BG or CSO was assessed. Multivariable linear regression analyses were used to relate PVS burden to log-transformed NfL levels in models adjusted for age, sex, FHS cohort, time between MRI and clinic exam, and image view (model 1), vascular risk factors (model 2), and white matter hyperintensity volume, covert brain infarcts, and cerebral microbleeds (model 3).

RESULTS

Among 1,457 participants (68.1±8.5 years, 45% males), NfL levels increased with higher PVS burden. Multivariable analysis showed an association of high PVS burden strictly in BG with NfL (β= 0.117, 95% CI 0.014-0.221; p = 0.027), but attenuated in model 3. The associations were mainly in participants≥65 years (β= 0.122, 95% CI 0.015-0.229, p = 0.026), women (β= 0.156, 95% CI 0.024-0.288, p = 0.021), and APOE ɛ4 non-carriers (β= 0.140, 95% CI 0.017-0.263, p = 0.026).

CONCLUSIONS

The association of strictly BG high PVS burden with NfL suggests a role for PVS as markers of neuroaxonal injury, but our results are hypothesis generating and require further replication.

Appraisal of Cardiovascular Risk Factors, Biomarkers, and Ocular Imaging in Cardiovascular Risk Prediction

Cardiovascular disease remains a leading cause of death worldwide despite the use of available cardiovascular disease risk prediction tools. Identification of high-risk individuals via risk stratification and screening at sub-clinical stages, which may be offered by ocular screening, is important to prevent major adverse cardiac events. Retinal microvasculature has been widely researched for potential application in both diabetes and cardiovascular disease risk prediction. However, the conjunctival microvasculature as a tool for cardiovascular disease risk prediction remains largely unexplored. The purpose of this review is to evaluate the current cardiovascular risk assessment methods, identifying gaps in the literature that imaging of the ocular microcirculation may have the potential to fill. This review also explores the themes of machine learning, risk scores, biomarkers, medical imaging, and clinical risk factors. Cardiovascular risk classification varies based on the population assessed, the risk factors included, and the assessment methods. A more tailored, standardised and feasible approach to cardiovascular risk prediction that utilises technological and medical imaging advances, which may be offered by ocular imaging, is required to support cardiovascular disease prevention strategies and clinical guidelines.

The IL-1 Family and Its Role in Atherosclerosis

The IL-1 superfamily of cytokines is a central regulator of immunity and inflammation. The family is composed of 11 cytokines (with agonist, antagonist, and anti-inflammatory properties) and 10 receptors, all tightly regulated through decoy receptor, receptor antagonists, and signaling inhibitors. Inflammation not only is an important physiological response against infection and injury but also plays a central role in atherosclerosis development. Several clinical association studies along with experimental studies have implicated the IL-1 superfamily of cytokines and its receptors in the pathogenesis of cardiovascular disease. Here, we summarize the key features of the IL-1 family, its role in immunity and disease, and how it helps shape the development of atherosclerosis.

Association of cerebral white matter hyperintensities with coronary artery calcium in a healthy population: a cross-sectional study

In brain magnetic resonance imaging (MRI), white matter hyperintensity (WMH) is a commonly encountered finding and is known to reflect cerebral small vessel disease. The aim of our study was to investigate the association of coronary artery calcium (CAC) with WMH and elucidate the relationship between WMH and atherosclerotic risk factors in a large-scale healthy population. This retrospective study included 1337 individuals who underwent brain MRI and CAC scoring computed tomography at healthcare centers affiliated with a tertiary hospital. Cerebral WMH was defined as Fazekas score greater than 2 on brain MRI. Intracranial artery stenosis (ICAS) was also assessed and determined to be present when stenosis was more than 50% on angiography. The associations of risk factors, CAC score, and ICAS with cerebral WMH were assessed by multivariable regression analysis. In multivariable analysis, categories of higher CAC scores showed increased associations with both periventricular and deep WMHs in a dose-dependent relationship. The presence of ICAS was also significantly related to cerebral WMH, and among the clinical variables, age and hypertension were independent risk factors. In conclusion, CAC showed a significant association with cerebral WMH in a healthy population, which might provide evidence for referring to the CAC score to identify individuals with risk of cerebral WMH.

Gaps and opportunities in sepsis translational research

Infection initiates sepsis, but the clinical disease arises through the innate immune response of the host. A rapidly evolving understanding of the biology of that response has not been paralleled by the development of successful new treatment. The COVID-19 pandemic has begun to change this revealing the promise of distinct therapeutic approaches and the feasibility of new approaches to evaluate them. We review the history of mediator-targeted therapy for sepsis and explore the conceptual, biological, technological, and organizational challenges that must be addressed to enable the development of effective treatments for a leading cause of global morbidity and mortality.

The Vascular System: Anatomical, Physiological, Pathological, and Aging Considerations

The vascular system is one of the earliest recognized anatomical systems. It is composed of 3 parts; arterial, capillary, and venous, each with their own unique anatomy and physiology. Blood flow through this system is compromised in aging, atherosclerosis and peripheral vascular disease, and the practicing anesthesiologist must understand both the physiology and pathophysiology of the vascular tree.