High-Resolution Digital Phenotypes from Consumer Wearables Enhance Prediction of Cardiometabolic Risk Markers

Background: Consumer-grade wearable devices enable detailed recordings of heart rate and step counts in free-living conditions. Recent studies have shown that summary statistics from these wearable recordings have potential uses for longitudinal monitoring of health and disease states. However, the relationship between higher resolution physiological dynamics from wearables and known markers of health and disease remains largely uncharacterized. Objective: We aimed to (i) derive high resolution digital phenotypes from observational wearable recordings, (ii) characterize their ability to predict modifiable markers of cardiometabolic disease, and (iii) study their connections with genetic predispositions for cardiometabolic disease and with lifestyle factors. Methods: We introduce a principled framework to extract interpretable high resolution phenotypes from wearable data recorded in free-living conditions. The proposed framework standardizes handling of data irregularities, encodes contextual information about underlying physiological state at any given time, and generates a set of 66 minimally redundant features across active, sedentary and sleep states. We applied our approach on a multimodal dataset, from the SingHEART study (NCT02791152), that comprises of heart rate and step count time series from wearables, clinical screening profiles, whole genome sequences and lifestyle survey responses from 692 healthy volunteers. We employed machine learning to model non-linear relationships between the high resolution phenotypes and clinical risk markers for blood pressure, lipid and weight abnormalities. For each risk type, we performed model comparisons based on Brier Skill Scores (BSS) to assess predictive value of the high resolution features over and beyond typical baselines. We then examined associations between the wearable-derived features, polygenic risk for cardiometabolic disease, and lifestyle habits and health perceptions. Results: Compared to typical summary statistic measures like resting heart rate, we find that the high-resolution features collectively have greater predictive value for modifiable clinical markers associated with cardiometabolic disease risk (average improvement in Brier Skill Score=52.3%, P<.001). Further, we show that heart rate dynamics from different activity states contain distinct information about type of cardiometabolic risk, with dynamics in sedentary states being most predictive of lipid abnormalities and patterns in active states being most predictive of blood pressure abnormalities (P<.001). Finally, our results reveal that subtle heart rate dynamics in wearable recordings serve as physiological correlates of genetic predisposition for cardiometabolic disease, lifestyle habits and health perceptions. Conclusions: High resolution digital phenotypes recorded by consumer wearables in free-living states have the potential to enhance prediction of cardiometabolic disease risk, and could enable more proactive and personalized health management. Clinical Trial Registration ID #NCT02791152. Keywords: Wearable device, heart rate, cardiometabolic disease, risk prediction, digital phenotypes, polygenic risk scores, time series analysis, machine learning, free-living

The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene

Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk. We used genetic approaches to identify inflammatory mechanisms associated with kynurenine variability and their relationship to cardiometabolic disease. We identified single-nucleotide polymorphisms (SNPs) previously associated with plasma kynurenine, including a missense-variant (rs3184504) in the inflammatory gene SH2B3/LNK. We examined the association between rs3184504 and plasma kynurenine in independent human samples, and measured kynurenine levels in SH2B3-knock-out mice and during human LPS-evoked endotoxemia. We conducted phenome scanning to identify clinical phenotypes associated with each kynurenine-related SNP and with a kynurenine polygenic score using the UK-Biobank (n = 456,422), BioVU (n = 62,303), and Electronic Medical Records and Genetics (n = 32,324) databases. The SH2B3 missense variant associated with plasma kynurenine levels and SH2B3−/− mice had significant tissue-specific differences in kynurenine levels.LPS, an acute inflammatory stimulus, increased plasma kynurenine in humans. Mendelian randomization showed increased waist-circumference, a marker of central obesity, associated with increased kynurenine, and increased kynurenine associated with C-reactive protein (CRP). We found 30 diagnoses associated (FDR q < 0.05) with the SH2B3 variant, but not with SNPs mapping to genes known to regulate tryptophan-kynurenine metabolism. Plasma kynurenine may be a biomarker of acute and chronic inflammation involving the SH2B3 pathways. Its regulation lies upstream of CRP, suggesting that kynurenine may be a biomarker of one inflammatory mechanism contributing to increased cardiometabolic disease risk.

Identification of Robust Metabotypes Associated With Increased Cardiometabolic Disease Risk- an Approach for Improved Prevention Through Precision Nutrition

Objectives We hypothesize that individuals can be grouped into robust metabolic phenotypes (metabotypes) based on biochemical, anthropometric, gut microbial and metabolomics data and that such metabotypes will reflect differences in cardiometabolic disease risk and can act as targets for tailored nutritional prevention. We furthermore hypothesize that diet-gut microbiota interactions will be major determinants of the metabotypes. Methods Metabotyping is currently performed based on baseline data from 628 Danish adults from a validation sub-study of the Danish Diet Cancer and Health-Next Generation cohort. Participants were followed for one year, also providing data at 6 and 12 months. Dietary data was obtained by food frequency questionnaire and repeated 24h recalls and data on physical activity, smoking, sociodemographic factors, disease prevalence and use of medication was collected by questionnaires. Untargeted metabolomics and gut microbiota are currently determined. Metabotypes will be identified using clustering algorithms, variable optimization and data integration of the plasma metabolome, the 16S rRNA microbiota and 14 biochemical and anthropometric variables. Differences in habitual diet and physical activity across metabotypes will be determined as well as main metabotype determinants and potential plasma metabolite biomarkers. We will also assess the reproducibility of the metabotypes and biomarkers over time. Results Two clusters of individuals were identified by using the currently available clinical and anthropometric data. One of the clusters presented with mean values consistent with overweight, hypertension and dyslipidemia. Next, we will integrate the plasma metabolomics and gut microbial data into the analysis to determine the metabotypes. Conclusions We have identified one higher risk group and one lower risk group for cardiometabolic disease and will identify and characterize metabotypes based on more extensive data. Future research will assess whether individuals belonging to different metabotypes respond differently to dietary interventions. Funding Sources Formas, Sweden.

Neutral Effect of Increased Dairy Product Intake, as Part of a Lifestyle Modification Program, on Cardiometabolic Health in Adolescent Girls With Overweight/Obesity: A Secondary Analysis From a Randomized Controlled Trial

Background: The presence of obesity and some cardiometabolic disease risk factors in childhood and adolescence track into adulthood. Intake of dairy products has been shown to be inversely related to adiposity and cardiometabolic variables in youth. However, limited research has examined cardiometabolic disease risk factors following increased dairy product consumption as part of a lifestyle modification intervention in youth with overweight/obesity. This secondary analysis aimed to determine whether 12 weeks of increased dairy consumption, as part of a lifestyle modification program, affects cardiometabolic variables in adolescent females (range: 10–18 years) with overweight/obesity (BMI &gt; 85th centile).Methods: Participants were randomized into two groups: higher dairy intake (RDa; four servings/day [to reflect previous Canada's Food Guide recommendations]; n = 23) or low dairy intake (LDa; 0–2 servings/day; n = 23). Both RDa and LDa participated in a 12-week, eucaloric, lifestyle modification intervention consisting of exercise training, and nutritional counseling. Adiposity (percent body fat [%BF]), dietary intake, and measures of cardiometabolic health were measured pre- and post-intervention.Results: There were no significant changes over time within groups or differences over time between groups for triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), TC/HDL ratio, low-density lipoprotein cholesterol (LDL), glucose, insulin, homeostatic model assessment of insulin resistance, adiponectin, and tumor necrosis factor alpha (TNF-α) (main effects of time and interactions, p &gt; 0.05). Leptin decreased over the 12-week lifestyle intervention in both groups (main effect of time, p = 0.02). After combining the groups (n = 46), significant correlations were found between change in %BF and change in some cardiometabolic variables (HDL [r = −0.40], TC/HDL ratio [r = 0.42], LDL [r = 0.36], and TNF-α [r = 0.35], p &lt; 0.05). After controlling for change in dairy product intake, the correlations were unchanged.Conclusion: Our findings demonstrate that increased dairy product consumption, as part of a lifestyle modification, weight management intervention, had a neutral effect on cardiometabolic disease risk factors in adolescent females with overweight/obesity. Change in dairy product intake did not influence the relationships between change in adiposity and change in cardiometabolic variables. Future research designed to primarily assess the effect of increased dairy product consumption on cardiometabolic disease risk factors in this population is warranted.Clinical Trial Registration:Clinicaltrials.gov; NCT#02581813.

Stress and Cardiometabolic Disease Risk for Indigenous Populations throughout the Lifespan

Background: Indigenous people experience the greatest cardiometabolic disease disparity in the Unites States, yet high cardiometabolic disease risk factors do not fully explain the extent of the cardiometabolic disease disparity for Indigenous people. Stress, trauma, and racism occur at high rates within Indigenous communities and have not been well explored as significant contributors to cardiometabolic disease disparities despite emerging literature, and therefore will be described here. Methods: This descriptive study explores the relationship between cardiometabolic disease risks and Indigenous-specific stressors (e.g., early childhood stress and trauma, adulthood stress and trauma, and historical and intergenerational trauma) using current literature. Indigenous-specific protective factors against cardiometabolic disease are also reviewed. Results. Increasing research indicates that there is a relationship between Indigenous-specific stressful and traumatic life experiences and increased cardiometabolic disease risk. Mental health and psychophysiology play an important role in this relationship. Effective interventions to reduce cardiometabolic disease risk in Indigenous communities focus on ameliorating the negative effects of these stressors through the use of culturally specific health behaviors and activities. Conclusions: There is increasing evidence that cultural connection and enculturation are protective factors for cardiometabolic disease, and may be galvanized through Indigenous-led training, research, and policy change.

Effect of an office-based intervention on visceral adipose tissue: the WorkACTIVE-P randomized controlled trial

Office-based activity reduces sedentariness, yet no randomized controlled trials (RCTs) have assessed how such activity influences visceral adipose tissue (VAT). This study examined the effect of an office-based, multicomponent activity intervention on VAT. The WorkACTIVE-P RCT enrolled sedentary office workers (body mass index: 31.4 (standard deviation (SD) 4.4) kg/m2) to an intervention (n = 20) or control (n = 20) group. For 3 months, the intervention group received an office-based pedal desk, further to an intervention promoting its use and increased walking. The control group maintained habitual activity. At baseline and follow-up, VAT, cardiometabolic disease risk markers, physical activity, and food intake were measured. Steps/day were not altered relative to control (P ≥ 0.51), but the pedal desk was utilized for 127 (SD 61) min/day. The intervention reduced VAT relative to control (−0.15 kg; 95% confidence interval (CI) = −0.29 to −0.01; P = 0.04). Moreover, the intervention decreased fasting glucose compared with control (−0.29 mmol/L; 95% CI = −0.51 to −0.06; P = 0.01), but no differences in other cardiometabolic disease markers or food intake were revealed (P ≥ 0.11). A multicomponent intervention decreased VAT in office workers who were overweight or obese. Though longer-term studies are needed, office-based, multicomponent activity regimens may lower cardiometabolic disease risk. Trial registered at ClinicalTrials.gov (NCT02561611). Novelty: In WorkACTIVE-P, a multicomponent activity intervention decreased visceral adipose tissue relative to control in office workers. The intervention also reduced glucose compared with control, though other metabolic risk markers and food intake were not altered. Such multicomponent interventions could help reduce cardiometabolic disease risk, but longer studies are needed.