Magnesium-Rich Diet Score is Inversely Associated with Incident Cardiovascular Disease: The Atherosclerosis in Communities (ARIC) Study.

BACKGROUND: Numerous studies have shown inverse associations between serum magnesium (Mg) and risk of cardiovascular disease (CVD), but studies of dietary Mg have not been consistent. AIM: To examine the association of a Mg-rich diet score with risks of CVD, coronary heart disease (CHD), and ischemic stroke in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: There were 15,022 Black and White adults without prevalent CVD at baseline (1987-89) included in this analysis. Diet was assessed at two visits 6 years apart using an interviewer-administered 66-item food frequency questionnaire. A Mg-rich diet score was created that included servings of whole grain products, nuts, vegetables, fruit, legumes, coffee, and tea. Cox proportional hazard regression evaluated associations of incident CVD, CHD and stroke across quintiles of Mg-rich diet score, adjusting for demographics, lifestyle factors, and clinical characteristics. RESULTS: Over >30 years of follow-up, there were 3,531 incident CVD events (2,562 CHD, 1,332 ischemic stroke). Participants who consumed more Mg-rich foods were older, female, White, had lower blood pressure, fewer were not current smokers, and more reported being physically active. A Mg-rich diet was inversely associated with incident CVD (HRQ5 vs Q1=0.87, 95%CI: 0.77-0.98, ptrend=0.02) CHD (HRQ5 vs Q1=0.82, 95%CI: 0.71-0.95, ptrend=0.01); however, the diet-stroke association was null (HRQ5 vs Q1=1.00, 95%CI: 0.82-1.22, ptrend=0.97). CONCLUSIONS: Consuming a diet including Mg-rich foods, such as whole grains, nuts, vegetables, fruits, legumes, coffee and tea, is associated with lower risk of CVD and CHD, but not ischemic stroke.

This study showed an inversely association between a magnesium-rich (mg-rich) diet score and risk of cardiovascular disease (CVD) in adults aged 45-64 at baseline (1987-89) and followed for over 30 years. The mg-rich diet score was created by summing the reported number of daily servings consumed from whole grain products, fruit, vegetables, legumes, nuts, coffee and tea.A mg-rich diet score may be associated with lower risk of developing CVD and coronary heart disease, but not ischemic stroke.

Plasma proteomic comparisons change as coverage expands for SomaLogic and Olink.

The number of assays on highly-multiplexed proteomic platforms has grown tenfold over the past 15 years from less than 1,000 to >11,000. The leading aptamer-based and antibody-based platforms have different strengths. For example, Eldjarn et al1 demonstrated that the aptamer-based SomaScan 5k (4,907 assays, assessed in the Icelandic 36K) and the antibody-based Olink Explore 3072 (2,931 assays, assessed in the UK BioBank) had a similar number of cis-pQTLs among all targets (2,120 vs. 2,101) but Olink had a greater number of cis-pQTLs among the overlapping targets (1,164 vs. 1,467). Analysis of split plasma measures showed the SomaScan assays to be more precise: median coefficient of variation (CV) of 9.9% vs. 16.5% for Olink.1 Precision of the newest versions of the platforms-SomaScan 11k (>11,000 assays, released in December 2023) and Olink Explore HT (>5,400 assays, released in July 2023)-has not yet been established. We assessed the reproducibility of the SomaScan 11k and Olink Explore HT using split plasma samples from 102 Atherosclerosis Risk in Communities (ARIC) Study participants. We found that the SomaScan 11k assays had a median CV of 6.8% (vs 6.6% for the subset of assays available on the SomaScan 5k) and the Olink Explore HT assays had a median CV of 35.7% (vs 19.8% for the subset of assays available on the Olink Explore 3072). Across Olink assays, the CVs were strongly negatively correlated with protein detectability, i.e., percent of samples above the limit of detection (LOD). For the 4,443 overlapping assays, the distribution of between-platform correlations was bimodal with a peak at r~0 and with another smaller peak at r~0.8. These findings on precision are consistent with the updated results by Eldjarn et al1 but indicate that precision of these two leading platforms in human plasma has diverged as the number of included proteins has increased.

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.

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.

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

BACKGROUND: Low physical activity (PA) measured from 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. These monitors can provide long-term HRV data and, if embedded with an accelerometer, they can also provide PA data. Whether PA or HRV measured from long-term ECG monitors is associated with cognitive function among older adults is unknown. METHODS: Free-living PA and HRV were measured simultaneously over 14-days using the Zio ® XT Patch among 1590 participants in the Atherosclerosis Risk in Communities Study [aged 72-94 years, 58% female, 32% Black]. Total amount of PA was estimated by total mean amplitude deviation (TMAD) from the 14-day accelerometry raw data. HRV indices (SDNN and rMSSD) were measured from the 14-day ECG raw data. Cognitive factor scores for global cognition, executive function, language, and memory were derived using latent variable methods. Dementia or mild cognitive impairment (MCI) status was adjudicated. 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. Models were adjusted for demographic and medical comorbidities. RESULTS: Each 1-unit higher in total amount of PA was significantly associated with 0.30 higher global cognition factor scores (95% CI: 0.16-0.44), 0.38 higher executive function factor scores (95% CI: 0.22-0.53), and 62% lower odds of MCI (OR: 0.38, 95% CI: 0.22-0.67) or 75% lower odds of dementia (OR: 0.25, 95% CI: 0.08-0.74) versus unimpaired cognition. Neither HRV measure was significantly associated with cognitive function or dementia. CONCLUSIONS: PA derived from a 2-week ECG monitor with an embedded accelerometer was significantly associated with higher cognitive test performance and lower odds of MCI/dementia among older adults. By contrast, HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia. CLINICAL PERSPECTIVE: What Is New?: This cross-sectional study evaluated associations between physical activity (PA) and heart rate variability (HRV) measured over 14 days from a wearable ECG monitor with cognitive function.Higher total amount of PA was associated with higher global cognition and executive function, as well as lower odds of mild cognitive impairment or dementia.HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes.What Are the Clinical Implications?: These findings replicate positive associations between PA and cognitive function using accelerometer data from a wearable ECG monitor with an embedded accelerometer.These findings raise the possibility of using wearable ECG monitors (with embedded accelerometers) as a promising tool for digital phenotyping of dementia.

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.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Precision subclassification of type 2 diabetes: a systematic review.

BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

In people with type 2 diabetes there may be differences in the way people present, including for example, their symptoms, body weight or how much insulin they make. We looked at recent publications describing research in this area to see whether it is possible to separate people with type 2 diabetes into different subgroups and, if so, whether these groupings were useful for patients. We found that it is possible to group people with type 2 diabetes into different subgroups and being in one subgroup can be more strongly linked to the likelihood of developing complications over others. This might mean that in the future we can treat people in different subgroups differently in ways that improves their treatment and their health but it requires further study.

Associations between diet quality and NT-proBNP in U.S. adults, NHANES 1999-2004.

Objective: N-terminal pro-brain-type natriuretic peptide (NT-proBNP) is a marker of cardiac wall stress and is a predictor of cardiovascular disease. Higher diet quality is associated with lower risk of cardiovascular disease. The association between diet quality and subclinical cardiovascular disease assessed by NT-proBNP is uncharacterized. We investigated the associations between diet quality, using Healthy Eating Index-2015 (HEI-2015), and NT-proBNP from the National Health and Nutrition Examination Survey (NHANES) 1999-2004. Methods: We included 9,782 adults from NHANES 1999-2004 without self-reported cardiovascular disease. The HEI-2015 ranges from 0 to 100, with higher scores indicating better diet quality. The HEI-2015 was categorized into sex-specific quintiles. Regression models were used to quantify associations between the overall HEI-2015 score and its 13 components with log-transformed NT-proBNP. The beta coefficients were converted to percent differences. Results: Among 9,782 participants, mean age was 45 years, 48% were men, and 72% were non-Hispanic White adults. After adjusting for sociodemographic characteristics, lifestyle factors, and medical history, those in the highest vs. lowest HEI-2015 quintile had an 8.5% (95% CI: -14.6% to -2.0%) lower NT-proBNP level. There was a dose-response association between HEI-2015 and NT-proBNP (P value for trend = 0.01). Each 1-unit higher in sodium and added sugars score indicating lower intake was associated with lower NT-proBNP by 7.7% (95% CI: -12.8% to -2.2%) and 6.5% (95% CI: -12.0% to -0.7%), respectively. Conclusion: Higher diet quality, especially lower intakes of sodium and added sugars, was associated with lower serum levels of NT-proBNP.

Prognostic value of insulin resistance and hyperglycemia biomarkers for long-term risks of cardiometabolic outcomes.

We found that individuals in the top tertile of HOMA-IR and with HbA1c-defined prediabetes have elevated risk of cardiometabolic outcomes.

Global Prevalence of Prediabetes.

OBJECTIVE: To estimate the global, regional, and national prevalence of prediabetes, defined by impaired glucose tolerance (IGT) or impaired fasting glucose (IFG). RESEARCH DESIGN AND METHODS: We reviewed 7,014 publications for high-quality estimates of IGT (2-h glucose, 7.8-11.0 mmol/L [140-199 mg/dL]) and IFG (fasting glucose, 6.1-6.9 mmol/L [110-125 mg/dL]) prevalence for each country. We used logistic regression to generate prevalence estimates for IGT and IFG among adults aged 20-79 years in 2021 and projections for 2045. For countries without in-country data, we extrapolated estimates from countries with available data with similar geography, income, ethnicity, and language. Estimates were standardized to the age distribution for each country from the United Nations. RESULTS: Approximately two-thirds of countries did not have high-quality IGT or IFG data. There were 50 high-quality studies for IGT from 43 countries and 43 high-quality studies for IFG from 40 countries. Eleven countries had data for both IGT and IFG. The global prevalence of IGT in 2021 was 9.1% (464 million) and is projected to increase to 10.0% (638 million) in 2045. The global prevalence of IFG in 2021 was 5.8% (298 million) and is projected to increase to 6.5% (414 million) in 2045. The 2021 prevalence of IGT and IFG was highest in high-income countries. In 2045, the largest relative growth in cases of IGT and IFG would be in low-income countries. CONCLUSIONS: The global burden of prediabetes is substantial and growing. Enhancing prediabetes surveillance is necessary to effectively implement diabetes prevention policies and interventions.

Prevalence and Correlates of Elevated NT-proBNP in Pregnant Women in the General U.S. Population.

BACKGROUND: Physiologic changes in N-terminal pro-B-type natriuretic peptide (NT-proBNP) across trimesters of pregnancy have not been well studied. OBJECTIVES: The authors aimed to measure NT-proBNP in adult women, by pregnancy status and trimester, in a nationally representative sample from the National Health and Nutrition Examination Survey 1999 to 2004. METHODS: We conducted a cross-sectional analysis of 2,134 women (546 pregnant) aged 20 to 40 years without a history of cardiovascular disease. RESULTS: Among pregnant women in the first trimester, the prevalence of elevated NT-proBNP (>125 pg/mL) was 20.0% (SE, 6.6%) compared to 2.4% (SE, 0.8%) among women in the third trimester and 8.0% among nonpregnant women. After adjustment for demographics and cardiovascular risk factors, NT-proBNP was 44% higher (absolute difference 26.4 [95% CI: 11.2-41.6] pg/mL) in the first trimester of pregnancy compared to nonpregnant women. Among pregnant women only, adjusted NT-proBNP was 46% lower (absolute difference -22.2 [95% CI: -36.9 to -7.5] pg/mL) in women in the third trimester compared to women in the first trimester. NT-proBNP was inversely associated with body mass index and with systolic blood pressure. CONCLUSIONS: Women in the first trimester of pregnancy had significantly higher NT-proBNP than those in the third trimester and compared to similarly aged nonpregnant women. The dynamic nature of NT-proBNP should be taken into consideration when ordering NT-proBNP lab tests in pregnant women.

Systematic review of precision subclassification of type 2 diabetes.

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Effects of Positive Airway Pressure Therapy on Glycemic Variability in Patients With Type 2 Diabetes and OSA: A Randomized Controlled Trial.

BACKGROUND: Glycemic variability is associated with increased risk for cardiovascular disease in patients with type 2 diabetes independent of glycosylated hemoglobin A1c (HbA1c) levels. Given the conflicting evidence on the effect of positive airway pressure (PAP) therapy for OSA on HbA1c, elucidating its effect on glycemic variability has value. RESEARCH QUESTION: Does the use of PAP therapy for OSA improve glycemic variability in patients with type 2 diabetes? STUDY DESIGN AND METHODS: A randomized controlled trial was conducted in 184 patients with type 2 diabetes and moderate-to-severe OSA. Participants received either 3 months of PAP therapy with lifestyle counseling or lifestyle counseling alone. End points included the SD of glucose levels along with other metrics derived from continuous glucose monitoring and self-monitoring of blood glucose. RESULTS: No differences were noted in either primary or secondary continuous glucose monitoring end points between the two groups. Average use of PAP therapy was 5.4 h/night (SD, 1.6). Exploratory analyses by sex showed significant differences in the primary and secondary outcomes. In female participants, PAP therapy was associated with improvement in the SD of glucose levels, with a mean difference in change between intervention and control groups of 3.5 mg/dL (P = .02). PAP therapy was also associated with lower post-dinner and bedtime glucose levels: 20.1 mg/dL (P < .01) and 34.6 mg/dL (P < .01), respectively. INTERPRETATION: PAP therapy did not improve glycemic control or variability in patients with moderate-to-severe OSA and type 2 diabetes. Exploratory analyses suggested that PAP therapy may improve glucose variability in female participants. Post-dinner and bedtime glucose levels were higher in those who did not receive PAP therapy. TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT02454153; URL: www. CLINICALTRIALS: gov.

Circulating Magnesium and Risk of Major Adverse Cardiac Events among Patients with Atrial Fibrillation in the ARIC Cohort.

Background: Serum magnesium (Mg) has been reported to be inversely associated with the risk of atrial fibrillation (AF), coronary artery disease (CAD), and major adverse cardiovascular events (MACE). The association between serum Mg and the risk of MACE, heart failure (HF), stroke, and all-cause mortality among patients with AF has not been evaluated. Objective: We aim to examine whether higher serum Mg is associated with a lower risk of MACE, heart failure (HF), stroke, and all-cause mortality among patients with AF. Methods: We evaluated prospectively 413 participants of the Atherosclerosis Risk in Communities (ARIC) Study with a diagnosis of AF at the time of Mg measurement participating in visit 5 (2011-2013). Serum Mg was modeled in tertiles and as a continuous variable in standard deviation units. Endpoints (HF, MI, stroke, cardiovascular (CV) death, all-cause mortality, and MACE) were identified and modeled separately using Cox proportional hazard regression adjusting for potential confounders. Results: During a mean follow-up of 5.8 years, there were 79 HFs, 34 MIs, 24 strokes, 80 CV deaths, 110 MACEs, and 198 total deaths. After adjustment for demographic and clinical variables, participants in the second and third tertiles of serum Mg had lower rates of most endpoints, with the strongest inverse association for the incidence of MI (HR 0.20, 95% CI 0.07, 0.61) comparing top to bottom tertile. Serum Mg modeled linearly as a continuous variable did not show clear associations with endpoints except MI (HR 0.50, 95% CI 0.31, 0.80). Due to the limited number of events, the precision of most estimates of association was relatively low. Conclusions: Among patients with AF, higher serum Mg was associated with a lower risk of developing incident MI and, to a lesser extent, other CV endpoints. Further studies in larger patients with AF cohorts are needed to evaluate the role of serum Mg in preventing adverse CV outcomes in these patients.

Inverse Associations between Measures of Adiposity and Glycated Albumin in US Adults, NHANES 1999-2004.

BACKGROUND: Glycated albumin (GA) is a short-term measure of glycemic control. Several studies have demonstrated an inverse association between body mass index (BMI) and GA, which may affect its performance as a biomarker of hyperglycemia. We investigated cross-sectional associations between GA and multiple measures of adiposity, and compared its performance as a glycemic biomarker by obesity status, in a nationally representative sample of US adults. METHODS: We measured GA in adults from the 1999-2004 National Health and Nutrition Examination Survey. Separately in adults with and without diabetes, we assessed associations of GA with adiposity measures (BMI, waist circumference, trunk fat, total body fat, and fat mass index) in sex-stratified multivariable regression models. We compared sensitivity and specificity of GA to identify elevated hemoglobin A1c (HbA1c), by obesity status. RESULTS: In covariate-adjusted regression models, all adiposity measures were inversely associated with GA in adults without diabetes (ß=-0.48 to -0.22%-point GA per 1 SD adiposity measure; n = 9750) and with diabetes (ß=-1.73 to -0.92%-point GA per SD). Comparing adults with vs without obesity, GA exhibited lower sensitivity (43% vs 54%) with equivalent specificity (99%) to detect undiagnosed diabetes (HbA1c ≥ 6.5%). Among adults with diagnosed diabetes (n = 1085), GA performed well to identify above-target glycemia (HbA1c ≥ 7.0%), with high specificity (>80%) overall but lower sensitivity in those with vs without obesity (81% vs 93%). CONCLUSIONS: Inverse associations between GA and adiposity were present in people with and without diabetes. GA is highly specific but may not be sufficiently sensitive for diabetes screening in adults with obesity.

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.

Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study.

OBJECTIVE: The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis. RESEARCH DESIGN AND METHODS: In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments. RESULTS: There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10-5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk. CONCLUSIONS: We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.

Performance of glycated albumin as a biomarker of hyperglycemia in pregnancy: Results from the National Health and Nutrition Examination Survey 1999-2004.

AIM: We sought to evaluate the performance of glycated albumin (GA) as a measure of hyperglycemia in pregnant women. METHODS: We used data from 555 pregnant women aged 20-40 years who participated in NHANES 1999-2004 and did not report a pre-pregnancy diagnosis of diabetes. We used Pearson's correlations and evaluated the area under the curve (AUC) for GA to detect elevated concentrations of random glucose, HbA1c, or fasting glucose (subset). We compared results to 1607 nonpregnant women aged 20-40 without diabetes. RESULTS: In pregnant women, 1.9 % had HbA1c ≥ 39 mmol/mol (≥5.7 %), 9.1 % had random glucose ≥ 5.3 mmol/L (≥95 mg/dL), and 10.7 % had fasting glucose ≥ 5.3 mmol/L. In pregnancy, GA was poorly correlated with HbA1c (r = 0.08) and random glucose (r = 0.17). BMI was positively associated with HbA1c (r = 0.33) and random glucose (r = 0.25) but was inversely associated with GA (r = -0.27). GA had poor discrimination for detecting hyperglycemia in pregnant women, defined as HbA1c ≥ 39 mmol/mol (AUC = 0.634) or random glucose ≥ 5.3 mmol/L (AUC = 0.628). Similar patterns were observed among nonpregnant women. CONCLUSIONS: GA is not a sensitive test to screen for hyperglycemia in pregnancy. GA was inversely associated with adiposity in pregnant women without diabetes. Pregnancy-related weight gain may complicate interpretation of repeated GA measurements.