Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study.

Low physical activity (PA) measured by accelerometers and low heart rate variability (HRV) measured from short-term ECG recordings are associated with worse cognitive function. Wearable long-term ECG monitors are now widely used, and some devices also include an accelerometer. The objective of this study was to evaluate whether PA or HRV measured from long-term ECG monitors was associated with cognitive function among older adults. A total of 1590 ARIC participants had free-living PA and HRV measured over 14 days using the Zio® XT Patch [aged 72-94 years, 58% female, 32% Black]. Cognitive function was measured by cognitive factor scores and adjudicated dementia or mild cognitive impairment (MCI) status. Adjusted linear or multinomial regression models examined whether higher PA or higher HRV was cross-sectionally associated with higher factor scores or lower odds of MCI/dementia. Each 1-unit increase in the total amount of PA was associated with higher global cognition (ß = 0.30, 95% CI: 0.16-0.44) and executive function scores (ß = 0.38, 95% CI: 0.22-0.53) and lower odds of MCI (OR = 0.38, 95% CI: 0.22-0.67) or dementia (OR = 0.25, 95% CI: 0.08-0.74). HRV (i.e., SDNN and rMSSD) was not associated with cognitive function. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia.

Proteomic analysis of diabetes genetic risk scores identifies complement C2 and neuropilin-2 as predictors of type 2 diabetes: the Atherosclerosis Risk in Communities (ARIC) Study.

AIMS/HYPOTHESIS: Genetic predisposition to type 2 diabetes is well-established, and genetic risk scores (GRS) have been developed that capture heritable liabilities for type 2 diabetes phenotypes. However, the proteins through which these genetic variants influence risk have not been thoroughly investigated. This study aimed to identify proteins and pathways through which type 2 diabetes risk variants may influence pathophysiology. METHODS: Using a proteomics data-driven approach in a discovery sample of 7241 White participants in the Atherosclerosis Risk in Communities Study (ARIC) cohort and a replication sample of 1674 Black ARIC participants, we interrogated plasma levels of 4870 proteins and four GRS of specific type 2 diabetes phenotypes related to beta cell function, insulin resistance, lipodystrophy, BMI/blood lipid abnormalities and a composite score of all variants combined. RESULTS: Twenty-two plasma proteins were identified in White participants after Bonferroni correction. Of the 22 protein-GRS associations that were statistically significant, 10 were replicated in Black participants and all but one were directionally consistent. In a secondary analysis, 18 of the 22 proteins were found to be associated with prevalent type 2 diabetes and ten proteins were associated with incident type 2 diabetes. Two-sample Mendelian randomisation indicated that complement C2 may be causally related to greater type 2 diabetes risk (inverse variance weighted estimate: OR 1.65 per SD; p=7.0 × 10-3), while neuropilin-2 was inversely associated (OR 0.44 per SD; p=8.0 × 10-3). CONCLUSIONS/INTERPRETATION: Identified proteins may represent viable intervention or pharmacological targets to prevent, reverse or slow type 2 diabetes progression, and further research is needed to pursue these targets.

Performance of the Glucose Management Indicator (GMI) in Type 2 Diabetes.

BACKGROUND: The glucose management indicator (GMI) is an estimated measure of hemoglobin A1c (HbA1c) recommended for the management of persons with diabetes using continuous glucose monitoring (CGM). However, GMI was derived primarily in young adults with type 1 diabetes, and its performance in patients with type 2 diabetes is poorly characterized. METHODS: We conducted a prospective cohort study in 144 adults with obstructive sleep apnea and type 2 diabetes not using insulin (mean age: 59.4 years; 45.1% female). HbA1c was measured at the study screening visit. Participants simultaneously wore 2 CGM sensors (Dexcom G4 and Abbott Libre Pro) for up to 4 weeks (2 weeks at baseline and 2 weeks at the 3-month follow-up visit). GMI was calculated using all available CGM data for each sensor. RESULTS: Median wear time was 27 days (IQR: 23-29) for the Dexcom G4 and 28 days (IQR: 24-29) for the Libre Pro. The mean difference between HbA1c and GMI was small (0.12-0.14 percentage points) (approximately 2 mmol/mol). However, the 2 measures were only moderately correlated (r = 0.68-0.71), and there was substantial variability in GMI at any given value of HbA1c (root mean squared error: 0.66-0.69 percentage points [7 to 8 mmol/mol]). Between 36% and 43% of participants had an absolute difference between HbA1c and GMI ≥0.5 percentage points (≥5 mmol/mol), and 9% to 18% had an absolute difference >1 percentage points (>11 mmol/mol). Discordance was higher in the Libre Pro than the Dexcom G4. CONCLUSIONS: GMI may be an unreliable measure of glycemic control for patients with type 2 diabetes and should be interpreted cautiously in clinical practice.Clinicaltrials.gov Registration Number: NCT02454153.

Within-Person and Between-Sensor Variability in Continuous Glucose Monitoring Metrics.

BACKGROUND: The within-person and between-sensor variability of metrics from different interstitial continuous glucose monitoring (CGM) sensors in adults with type 2 diabetes not taking insulin is unclear. METHODS: Secondary analysis of data from 172 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea randomized clinical trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors for up to 2 weeks at baseline and again at the 3-month follow-up visit. RESULTS: At baseline (up to 2 weeks of CGM), mean glucose for both the Abbott and Dexcom sensors was approximately 150 mg/dL (8.3 mmol/L) and time in range (70180 mg/dL [3.910.0 mmol/L]) was just below 80. When comparing the same sensor at 2 different time points (two 2-week periods, 3 months apart), the within-person coefficient of variation (CVw) in mean glucose was 17.4 (Abbott) and 14.2 (Dexcom). CVw for percent time in range: 20.1 (Abbott) and 18.6 (Dexcom). At baseline, the Pearson correlation of mean glucose from the 2 sensors worn simultaneously was r 0.86, root mean squared error (RMSE), 13 mg/dL (0.7 mmol/L); for time in range, r 0.88, RMSE, 8 percentage points. CONCLUSIONS: Substantial variation was observed within sensors over time and across 2 different sensors worn simultaneously on the same individuals. Clinicians should be aware of this variability when using CGM technology to make clinical decisions.ClinicalTrials.gov Identifier: NCT02454153.

Comparison of Proteomic Measurements Across Platforms in the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: The plasma proteome can be quantified using different types of highly multiplexed technologies, including aptamer-based and proximity-extension immunoassay methods. There has been limited characterization of how these protein measurements correlate across platforms and with absolute measures from targeted immunoassays. METHODS: We assessed the comparability of (a) highly multiplexed aptamer-based (SomaScan v4; Somalogic) and proximity-extension immunoassay (OLINK Proseek® v5003; Olink) methods in 427 Atherosclerosis Risk in Communities (ARIC) Study participants (Visit 5, 2011-2013), and (b) 18 of the SomaScan protein measurements against targeted immunoassays in 110 participants (55 cardiovascular disease cases, 55 controls). We calculated Spearman correlations (r) between the different measurements and compared associations with case-control status. RESULTS: There were 417 protein comparisons (366 unique proteins) between the SomaScan and Olink platforms. The average correlation was r = 0.46 (range: -0.21 to 0.97; 79 [19%] with r ≥ 0.8). For the comparison of SomaScan and targeted immunoassays, 6 of 18 assays (growth differentiation factor 15 [GDF15], interleukin-1 receptor-like 1 [ST2], interstitial collagenase [MMP1], adiponectin, leptin, and resistin) had good correlations (r ≥ 0.8), 2 had modest correlations (0.5 ≤ r < 0.8; osteopontin and interleukin-6 [IL6]), and 10 were poorly correlated (r < 0.5; metalloproteinase inhibitor 1 [TIMP1], stromelysin-1 [MMP3], matrilysin [MMP7], C-C motif chemokine 2 [MCP1], interleukin-10 [IL10], vascular cell adhesion protein 1 [VCAM1], intercellular adhesion molecule 1 [ICAM1], interleukin-18 [IL18], tumor necrosis factor [TNFα], and visfatin) overall. Correlations for SomaScan and targeted immunoassays were similar according to case status. CONCLUSIONS: There is variation in the quantitative measurements for many proteins across aptamer-based and proximity-extension immunoassays (approximately 1/2 showing good or modest correlation and approximately 1/2 poor correlation) and also for correlations of these highly multiplexed technologies with targeted immunoassays. Design and interpretation of protein quantification studies should be informed by the variation across measurement techniques for each protein.

Glycated Albumin and Risk of Mortality in the US Adult Population.

BACKGROUND: Glycated albumin is of growing interest as an alternative biomarker of glycemia. However, the association of glycated albumin with long-term outcomes in the general population is uncharacterized. We evaluated the associations of glycated albumin and hemoglobin A1c (HbA1c) with mortality in US adults. METHODS: We conducted a prospective analysis of 12 915 participants in the National Health and Nutrition Examination Survey 1999-2004. We used Cox regression to characterize associations of glycated albumin and HbA1c with all-cause and cardiovascular mortality through 2014. We categorized glycated albumin based on percentiles corresponding to clinical cut-points for HbA1c. No diagnosed diabetes: <5.0% (<12th percentile), 5.0% to 5.6% (12th-82nd percentile, reference), 5.7% to 6.4% (83rd-97th percentile), and ≥6.5% (≥98th percentile). Diagnosed diabetes: <7.0% (<50th percentile), 7.0% to 8.9% (50th-83rd percentile), and ≥9.0% (≥84th percentile). RESULTS: Among US adults (mean age 46 years), the prevalence of diagnosed diabetes was 6.8%. Glycated albumin and HbA1c were highly correlated (r = 0.76). Over the median 16.8 years follow-up, there were 2818 deaths (652 cardiovascular). Adults with diagnosed diabetes and glycated albumin ≥84th percentile had the highest risk for all-cause mortality [hazard ratio (HR) 3.96, 95% CI 3.06-5.13] and cardiovascular mortality (HR 6.80, 95% CI 4.20-11.03). HbA1c had associations with all-cause and cardiovascular mortality that were similar to those for glycated albumin. CONCLUSIONS: Among US adults, increased values of glycated albumin and HbA1c were associated with all-cause and cardiovascular mortality, particularly in persons with diagnosed diabetes. Glycated albumin may be a useful alternative test of glycemia.

The performance of glycated albumin as a biomarker of hyperglycemia and cardiometabolic risk in children and adolescents in the United States.

OBJECTIVE: Diabetes and prediabetes are growing concerns among US youth. Fasting glucose (FG) and HbA1c are standard diabetes screening tests, but HbA1c may be unreliable in some settings and fasting is burdensome in children. Glycated albumin (GA) is a non-fasting test that was recently cleared for clinical use in the United States, but studies in youth without diabetes are limited. RESEARCH DESIGN AND METHODS: We conducted a cross-sectional analysis in 6826 youth without diabetes aged 8-19 years in the 1999-2004 National Health and Nutrition Examination Survey. We evaluated the associations of GA with HbA1c, FG, and cardiometabolic risk factors. RESULTS: GA was poorly correlated with HbA1c (ρ = 0.074) and FG (ρ = -0.047) and was negatively associated with body mass index (BMI) and cardiometabolic risk factors. Compared to youth in the highest tertile of GA (≥13.5%), those in the lowest GA tertile (<12.4%) had a higher prevalence of obesity (29.9% vs. 7.6%), low high-density lipoprotein cholesterol (29.7% vs. 16.5%), and hypertensive blood pressure (4.0% vs. 2.7%). These inverse associations persisted after adjustment for age, sex, race/ethnicity, serum albumin, and C-reactive protein. CONCLUSIONS: GA was poorly correlated with traditional markers of hyperglycemia in youth without diabetes. Counterintuitively, there was a negative association between GA and BMI. Among youth without diabetes, GA does not identify youth at high cardiometabolic risk, and it does not appear to be an appropriate biomarker for screening of hyperglycemia.

Glycaemic markers and all-cause mortality in older adults with and without diabetes: the Atherosclerosis Risk in Communities (ARIC) study.

AIMS/HYPOTHESIS: There is controversy regarding the performance of HbA1c in old age. We evaluated the prognostic value of HbA1c and other glycaemic markers (fructosamine, glycated albumin, fasting glucose) with mortality risk in older adults (66-90 years). METHODS: This was a prospective analysis of 5636 participants (31% with diagnosed diabetes, mean age 76, 58% female, 21% black) in the Atherosclerosis Risk in Communities (ARIC) study, baseline 2011-2013. We used Cox regression to examine associations of glycaemic markers (modelled in categories) with mortality risk, stratified by diagnosed diabetes status. RESULTS: During a median of 6 years of follow-up, 983 deaths occurred. Among older adults with diabetes, 30% had low HbA1c (<42 mmol/mol [<6.0%]) and 10% had high HbA1c (≥64 mmol/mol [≥8.0%]); low (HR 1.32 [95% CI 1.04, 1.68]) and high (HR 1.86 [95% CI 1.32, 2.62]) HbA1c were associated with mortality risk vs HbA1c 42-52 mmol/mol (6.0-6.9%) after demographic adjustment. Low fructosamine and glycated albumin were not associated with mortality risk. Both low and high fasting glucose were associated with mortality risk. After further adjustment for lifestyle and clinical risk factors, high HbA1c (HR 1.81 [95% CI 1.28, 2.56]), fructosamine (HR 1.96 [95% CI 1.43-2.69]), glycated albumin (HR 1.81 [95% CI 1.33-2.47]) and fasting glucose (HR 1.81 [95% CI 1.24, 2.66]) were associated with mortality risk. Low HbA1c and fasting glucose were no longer significantly associated with mortality risk. Among participants without diabetes, associations of glycaemic markers with mortality risk were less robust. CONCLUSIONS/INTERPRETATION: Elevated HbA1c, fructosamine, glycated albumin and fasting glucose were associated with risk of mortality in older adults with diabetes. Low HbA1c and fasting glucose may be markers of poor prognosis but are possibly confounded by health status. Our findings support the clinical use of HbA1c in older adults with diabetes. Graphical abstract.

Proton Pump Inhibitor Use, Hypomagnesemia and Risk of Cardiovascular Diseases: The Atherosclerosis Risk in Communities (ARIC) Study.

GOALS: The goal of this study was to evaluate whether proton pump inhibitor (PPI) use is cross-sectionally associated with hypomagnesemia and whether hypomagnesemia mediates the prospective association between PPIs and cardiovascular disease (CVD) risk. BACKGROUND: Use of PPIs has been associated with hypomagnesemia, primarily in case reports or within insurance databases. Both PPI use and low serum magnesium (Mg) have been associated with modestly higher CVD risk. Yet, the interrelation between PPI use and Mg in relation to CVD risk is unclear. STUDY: The 4436 Atherosclerosis Risk in Communities participants without prevalent CVD at visit 5 (baseline, 2011-2013) were included. Multivariable relative risk regression was used for cross-sectional analyses between PPI and hypomagnesemia prevalence (≤0.75 mmol/L). Incident CVD (defined by atrial fibrillation, coronary heart disease, CVD mortality, heart failure, stroke) was identified through 2017. Multivariable Cox regression was used to examine the PPI-CVD association. RESULTS: Participants were mean±SD aged 75±5 years; 63% were women, 23% Black, and 24% were PPI users. PPI users had 1.24-fold (95% confidence interval: 1.08-1.44) higher prevalence of hypomagnesemia than nonusers. Over a median 5 years of follow-up, 684 incident CVD events occurred. PPI users had higher CVD risk [hazard ratio (95% confidence interval) 1.31 (1.10-1.57)] than nonusers. The effect estimate was largely unchanged when hypomagnesemia was added to the model as a potential mediator. CONCLUSIONS: In this elderly community-based study, PPI users had a higher prevalence of hypomagnesemia than in nonusers. PPI users also had higher CVD risk than nonusers; however, it appears unlikely that hypomagnesemia explains associations of PPIs with CVD risk.

Refining Prediction of Atrial Fibrillation-Related Stroke Using the P2-CHA2DS2-VASc Score.

BACKGROUND: In people with atrial fibrillation (AF), periods of sinus rhythm present an opportunity to detect prothrombotic atrial remodeling through measurement of P-wave indices (PWIs)-prolonged P-wave duration, abnormal P-wave axis, advanced interatrial block, and abnormal P-wave terminal force in lead V1. We hypothesized that the addition of PWIs to the CHA2DS2-VASc score would improve its ability to predict AF-related ischemic stroke. METHODS: We included 2229 participants from the ARIC study (Atherosclerosis Risk in Communities) and 700 participants from MESA (Multi-Ethnic Study of Atherosclerosis) with incident AF who were not on anticoagulants within 1 year of AF diagnosis. PWIs were obtained from study visit ECGs before development of AF. AF was ascertained using study visit ECGs and hospital records. Ischemic stroke cases were based on physician adjudication of hospital records. We used Cox proportional hazards models to estimate hazard ratios and 95% CIs of PWIs for ischemic stroke. Improvement in 1-year stroke prediction was assessed by C-statistic, categorical net reclassification improvement, and relative integrated discrimination improvement. RESULTS: Abnormal P-wave axis was the only PWI associated with increased ischemic stroke risk (hazard ratio, 1.84; 95% CI, 1.33-2.55) independent of CHA2DS2-VASc variables, and that resulted in meaningful improvement in stroke prediction. The ß estimate was approximately twice that of the CHA2DS2-VASc variables, and thus abnormal P-wave axis was assigned 2 points to create the P2-CHA2DS2-VASc score. This improved the C-statistic (95% CI) from 0.60 (0.51-0.69) to 0.67 (0.60-0.75) in ARIC and 0.68 (0.52-0.84) to 0.75 (0.60-0.91) in MESA (validation cohort). In ARIC and MESA, the categorical net reclassification improvements (95% CI) were 0.25 (0.13-0.39) and 0.51 (0.18-0.86), respectively, and the relative integrated discrimination improvement (95% CI) were 1.19 (0.96-1.44) and 0.82 (0.36-1.39), respectively. CONCLUSIONS: Abnormal P-wave axis-an ECG correlate of left atrial abnormality- improves ischemic stroke prediction in AF. Compared with CHA2DS2-VASc, the P2-CHA2DS2-VASc is a better prediction tool for AF-related ischemic stroke.

Circulating electrolytes and the prevalence of atrial fibrillation and supraventricular ectopy: The Atherosclerosis Risk in Communities (ARIC) study.

BACKGROUND AND AIMS: Evaluating associations of circulating electrolytes with atrial fibrillation (AF) and burden of supraventricular arrhythmias can give insights into arrhythmia pathogenesis. METHODS AND RESULTS: We conducted a cross-sectional analysis of 6398 participants of the Atherosclerosis Risk in Communities (ARIC) study, ages 71-90, with data on serum electrolytes (magnesium, calcium, potassium, phosphorus, chloride, sodium). Prevalence of AF was determined from electrocardiograms and history of AF hospitalizations. A subset of 317 participants also underwent electrocardiographic recordings for up to 14 days using the Zio® patch. Burden of other supraventricular arrhythmias [premature atrial contractions (PACs), supraventricular tachycardia] was determined with the Zio® patch. We used logistic and linear regression adjusting for potential confounders to determine associations of electrolytes with arrhythmia prevalence and burden. Among 6394 eligible participants, 614 (10%) had AF. Participants in the top quintiles of magnesium [odds ratio (OR) 0.82, 95% confidence interval (CI) 0.62, 1.08], potassium (OR 0.82, 95%CI 0.68, 1.00), and phosphorus (OR 0.73, 95%CI 0.59, 0.89) had lower AF prevalence compared to those in the bottom quintiles. No clear association was found for circulating chloride, calcium or sodium. Higher concentrations of circulating calcium were associated with lower prevalence of PACs in the 12-lead electrocardiogram, while higher concentrations of potassium, chloride and sodium were associated with higher PAC prevalence. Circulating electrolytes were not significantly associated with burden of PACs or supraventricular tachycardia among 317 participants with extended electrocardiographic monitoring. CONCLUSION: Concentrations of circulating electrolytes present complex associations with selected supraventricular arrhythmias. Future studies should evaluate underlying mechanisms.

Association between excessive daytime sleepiness and measures of supraventricular arrhythmia burden: evidence from the Atherosclerosis Risk in Communities (ARIC) study.

PURPOSE: Excessive daytime sleepiness is a common sleep complaint among older adults. Assessment of excessive daytime sleepiness is used to screen for obstructive sleep apnea, which may be linked to atrial fibrillation (AF) and other sustained arrhythmias. Using data from the Atherosclerosis Risk in Communities (ARIC) Study cohort, we examined the association of excessive daytime sleepiness with measures of arrhythmia burden derived from a continuous ECG recording device in a community-based sample of older adults. METHODS: Participating older adults (N = 2306, mean age: 78.9 ± 4.5 years, 57.8% female) wore a Zio® XT Patch for 14 days. Excessive daytime sleepiness was assessed with the Epworth Sleepiness Scale. Measures of AF and supraventricular arrhythmia burden were derived from the Zio® XT Patch. Multiple adjusted logistic, multinomial, and linear regression models were used to assess associations of excessive daytime sleepiness with AF, AF burden, and supraventricular arrhythmia burden. RESULTS: Approximately 18% of the sample had excessive daytime sleepiness, and 8.5% had AF. After adjustment, excessive daytime sleepiness was not significantly associated with AF (odds ratio (OR), 1.20; Confidence Interval (CI), 0.81-1.75), continuous AF burden (OR, 1.36; CI, 0.85-2.16), or measures of supraventricular arrhythmia burden (SVE burden: ß 0.01; 95% CI, -0.09-0.11; SVT burden: ß 0.02; 95% CI, -0.04-0.08). CONCLUSION: In this community-based sample of older adults, excessive daytime sleepiness was not associated with measures of arrhythmia burden. Future studies with objective measures of sleep are needed to further examine the role of sleep in the development and progression of arrhythmia burden.

Serum magnesium and burden of atrial and ventricular arrhythmias: The Atherosclerosis Risk in Communities (ARIC) Study.

INTRODUCTION: Low serum magnesium (Mg) is associated with an increased incidence of atrial and ventricular arrhythmias. A richer phenotyping of arrhythmia indices, such as burden or frequency, may provide etiologic insights. OBJECTIVES: To evaluate cross-sectional associations of serum Mg with burden of atrial arrhythmias [atrial fibrillation (AF), premature atrial contractions (PAC), supraventricular tachycardia (SVT)], and ventricular arrhythmias [premature ventricular contractions (PVC), non-sustained ventricular tachycardia (NSVT)] over 2-weeks of ECG monitoring. METHODS: We included 2513 ARIC Study visit 6 (2016-2017) participants who wore the Zio XT Patch-a leadless, ambulatory ECG-monitor-for up to 2-weeks. Serum Mg was modeled categorically and continuously. AF burden was categorized as intermittent or continuous based on the percent of analyzable time spent in AF. Other arrhythmia burdens were defined by the average number of abnormal beats per day. Linear regression was used for continuous outcomes; logistic and multinomial regression were used for categorical outcomes. RESULTS: Participants were mean ± SD age 79 ± 5 years, 58% were women and 25% black. Mean serum Mg was 0.82 ± 0.08 mmol/L and 19% had hypomagnesemia (<0.75 mmol/L). Serum Mg was inversely associated with PVC burden and continuous AF. The AF association was no longer statistically significant with further adjustment for traditional lifestyle risk factors, only the association with PVC burden remained significant. There were no associations between serum Mg and other arrhythmias examined. CONCLUSIONS: In this community-based cohort of older adults, we found little evidence of independent cross-sectional associations between serum Mg and arrhythmia burden.

Metabolic Syndrome and Risk of Ischemic Stroke in Atrial Fibrillation: ARIC Study.

Background and Purpose- Metabolic syndrome (MetS), a prothrombotic state, is associated with an increased risk of atrial fibrillation (AF) and stroke. The CHA2DS2-VASc score does not account for the MetS components of prehypertension, prediabetes mellitus, abdominal obesity, elevated triglycerides, and low HDL (high-density lipoprotein). Data are limited on the association of MetS with stroke in AF, independent of CHA2DS2-VASc variables. Our aim was to identify MetS components associated with ischemic stroke in participants with AF in the ARIC study (Atherosclerosis Risk in Communities). Methods- We included 1172 participants with incident AF within 5 years of measurement of MetS components. MetS was defined by ATP criteria and International Diabetes Federation criteria. Incident ischemic stroke was physician adjudicated. Multivariable Cox proportional hazards regression was used to assess the association of MetS components with stroke. Results- After a median follow-up of 14.8 years, there were 113 ischemic stroke cases. Of the individual MetS components, low HDL was borderline associated with increased stroke risk (hazard ratio, 1.48 [95% CI, 0.99-2.21]) after adjustment for CHA2DS2-VASc variables while the remaining MetS variables were not associated with stroke risk. The presence of ≥3 components of MetS was not significantly associated with ischemic stroke after adjustment for CHA2DS2-VASc variables (hazard ratio, 1.38 [95% CI, 0.91-2.11]). The risk of stroke increased by 13% for each additional component of MetS; however, this association was borderline significant (hazard ratio, 1.13 [95% CI, 0.99-1.28]). Conclusions- The presence of MetS was not significantly associated with ischemic stroke after adjustment for CHA2DS2-VASc variables. Consideration of MetS is unlikely to improve stroke prediction in AF.

Urinary 2,5-dicholorophenol and 2,4-dichlorophenol concentrations and prevalent disease among adults in the National Health and Nutrition Examination Survey (NHANES).

OBJECTIVE: To test cross-sectional associations between urinary concentrations of 2,5-dichlorophenol (2,5-DCP) and 2,4-dichlorophenol (2,4-DCP) with the prevalence of cardiovascular disease (CVD), cancer, lung disease, thyroid problems and liver conditions. METHODS: Logistic regression was used to evaluate associations of urinary concentrations of 2,5-DCP and 2,4-DCP with prevalence of various medical conditions among 3617 National Health and Nutrition Examination Survey participants from 2007-2008 and 2009-2010. ORs and 95% CIs for each disease were estimated. All regression models were adjusted for urinary creatinine. RESULTS: We observed a monotonically increasing association between quartiles of 2,5-DCP and prevalence of CVD. After adjustment for sociodemographic and lifestyle characteristics, participants with the highest versus lowest quartile of urinary 2,5-DCP had an OR=1.84 (95% CI 1.26 to 2.70) (p linear trend=0.006). The association was similar with further adjustment for established clinical CVD risk factors. Higher 2,5-DCP was also associated with prevalence of all cancers combined (ORQ4 vs Q1=1.50 (95% CI 1.00 to 2.26); p trend=0.05) and, in exploratory analyses, with gynaecological cancers (ORQ4 vs Q1=4.15 (95% CI 1.51 to 11.40; p trend=0.01)). No associations were detected between 2,5-DCP and lung diseases, thyroid problems or liver conditions, nor between 2,4-DCP and prevalent disease. CONCLUSION: In this nationally representative study, higher urinary 2,5-DCP concentrations were associated with greater prevalence of CVD and all cancers combined. Further examination may be warranted to assess whether chronic exposure to 2,5-DCP is associated with incidence of adverse health outcomes.

Markers of vitamin D metabolism and incidence of clinically diagnosed abdominal aortic aneurysm: The Atherosclerosis Risk in Communities Study.

Little is known about whether markers of vitamin D metabolism are associated with the development of abdominal aortic aneurysm (AAA), though these markers have been linked to other cardiovascular diseases. We tested the hypotheses that risk of AAA is higher among individuals with low serum concentrations of 25-hydroxy vitamin D [25(OH)D], and among those with elevated concentrations of calcium, fibroblast growth factor 23 (FGF23), phosphorus, and parathyroid hormone (PTH) using data from a cohort of black and white individuals with long-term follow-up. Markers of vitamin D metabolism were measured using serum collected in 1990-1992 from ARIC study participants (mean ± SD age 56.9 ± 5.7 years, 43.2% male, 23.9% black). A total of 12,770 participants were followed until 2011 for incident AAA. Multivariable-adjusted Cox regression models were used. A total of 449 incident AAA events occurred over a median follow-up of 19.7 years. For the association between serum calcium and risk of incident AAA there was evidence of interaction by sex ( p-interaction 0.02). Among women, in the fully adjusted model, the hazard ratio (95% confidence interval) comparing the highest to lowest quartile was 2.43 (1.25-4.73), whereas in men it was 1.01 (0.72-1.43). Not associated with risk of incident AAA were 25(OH)D, FGF23, phosphorus, and PTH. In this large prospective cohort, there was little evidence that markers of vitamin D metabolism are associated with risk of incident AAA. The positive association of calcium with AAA among women may warrant further investigation and replication in other populations.

Abnormal P-Wave Axis and Ischemic Stroke: The ARIC Study (Atherosclerosis Risk In Communities).

BACKGROUND AND PURPOSE: Abnormal P-wave axis (aPWA) has been linked to incident atrial fibrillation and mortality; however, the relationship between aPWA and stroke has not been reported. We hypothesized that aPWA is associated with ischemic stroke independent of atrial fibrillation and other stroke risk factors and tested our hypothesis in the ARIC study (Atherosclerosis Risk In Communities), a community-based prospective cohort study. METHODS: We included 15 102 participants (aged 54.2±5.7 years; 55.2% women; 26.5% blacks) who attended the baseline examination (1987-1989) and without prevalent stroke. We defined aPWA as any value outside 0 to 75° using 12-lead ECGs obtained during study visits. Each case of incident ischemic stroke was classified in accordance with criteria from the National Survey of Stroke by a computer algorithm and adjudicated by physician review. Multivariable Cox regression was used to estimate hazard ratios and 95% confidence intervals for the association of aPWA with stroke. RESULTS: During a mean follow-up of 20.2 years, there were 657 incident ischemic stroke cases. aPWA was independently associated with a 1.50-fold (95% confidence interval, 1.22-1.85) increased risk of ischemic stroke in the multivariable model that included atrial fibrillation. When subtyped, aPWA was associated with a 2.04-fold (95% confidence interval, 1.42-2.95) increased risk of cardioembolic stroke and a 1.32-fold (95% confidence interval, 1.03-1.71) increased risk of thrombotic stroke. CONCLUSIONS: aPWA is independently associated with ischemic stroke. This association seems to be stronger for cardioembolic strokes. Collectively, our findings suggest that alterations in atrial electric activation may predispose to cardiac thromboembolism independent of atrial fibrillation.

Glucose Color Index: Development and Validation of a Novel Measure of the Shape of Glycemic Variability.

BACKGROUND: Standard continuous glucose monitoring (CGM) metrics: mean glucose, standard deviation, coefficient of variation, and time in range, fail to capture the shape of variability in the CGM time series. This information could facilitate improved diabetes management. METHODS: We analyzed CGM data from 141 adults with type 2 diabetes in the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants in HYPNOS wore CGM sensors for up to two weeks at two time points, three months apart. We calculated the log-periodogram for each time period, summarizing using disjoint linear models. These summaries were combined into a single value, termed the Glucose Color Index (GCI), using canonical correlation analysis. We compared the between-wear correlation of GCI with those of standard CGM metrics and assessed associations between GCI and diabetes comorbidities in 398 older adults with type 2 diabetes from the Atherosclerosis Risk in Communities (ARIC) study. RESULTS: The GCI achieved a test-retest correlation of R = .75. Adjusting for standard CGM metrics, the GCI test-retest correlation was R = .55. Glucose Color Index was significantly associated (p < .05) with impaired physical functioning, frailty/pre-frailty, cardiovascular disease, chronic kidney disease, and dementia/mild cognitive impairment after adjustment for confounders. CONCLUSION: We developed and validated the GCI, a novel CGM metric that captures the shape of glucose variability using the periodogram signal decomposition. Glucose Color Index was reliable within participants over a three-month period and associated with diabetes comorbidities. The GCI suggests a promising avenue toward the development of CGM metrics which more fully incorporate time series information.

Plasma Neuronal Growth Regulator 1 May Link Physical Activity to Reduced Risk of Type 2 Diabetes: A Proteome-Wide Study of ARIC Participants.

Habitual physical activity (PA) impacts the plasma proteome and reduces the risk of developing type 2 diabetes (T2D). Using a large-scale proteome-wide approach in Atherosclerosis Risk in Communities study participants, we aimed to identify plasma proteins associated with PA and determine which of these may be causally related to lower T2D risk. PA was associated with 92 plasma proteins in discovery (P < 1.01 × 10-5), and 40 remained significant in replication (P < 5.43 × 10-4). Eighteen of these proteins were independently associated with incident T2D (P < 1.25 × 10-3), including neuronal growth regulator 1 (NeGR1; hazard ratio per SD 0.85; P = 7.5 × 10-11). Two-sample Mendelian randomization (MR) inverse variance weighted analysis indicated that higher NeGR1 reduces T2D risk (odds ratio [OR] per SD 0.92; P = 0.03) and was consistent with MR-Egger, weighted median, and weighted mode sensitivity analyses. A stronger association was observed for the single cis-acting NeGR1 genetic variant (OR per SD 0.80; P = 6.3 × 10-5). Coupled with previous evidence that low circulating NeGR1 levels promote adiposity, its association with PA and potential causal role in T2D shown here suggest that NeGR1 may link PA exposure with metabolic outcomes. Further research is warranted to confirm our findings and examine the interplay of PA, NeGR1, adiposity, and metabolic health.