Peter D. Reaven

Studies linking mitochondrial DNA (mtDNA) with complex traits are often limited by small sample sizes or focused on specific phenotypes in clinically selected cohorts. Here, we use data from >600,000 participants in the Million Veteran Program (MVP) to perform a multi-ancestry analysis of mitochondrial DNA (mtDNA) variation and cardiometabolic phenotypes across European (EUR), African (AFR), Admixed American (AMR), and East Asian (EAS) populations. After validating 248 mtDNA loci, we identify 10 ancestry-stratified single-variant associations (8 EUR, 2 AFR) and 23 additional signals in sex- and type 2 diabetes (T2D)–stratified analyses. Four variants tagging haplogroup J, D-loop MT228G > A, MT-ND3 MT10398A > G (p.Thr114Ala), MT-ND5 MT13708G > A (p.Ala458Thr), and MT-CYB MT14798T > C (p.Phe18Leu), are associated with hypothyroidism in EUR and replicated in UK Biobank (UKBB) with concordant effects. In EUR females, MT-RNR1 MT1555A > G increases the risk of carditis and heart failure phenotypes, supporting prior reports of maternally inherited cardiomyopathy. Gene-based rare-variant tests (minor allele frequency ≤2%) yield 26 associations (12 EUR, 10 AFR, 2 AMR, 2 EAS), including mitochondrial tRNA burdens linked to primary cardiomyopathy (females) and exophthalmos (males). Twenty-three of the 33 single-variant signals map to the endocrine/metabolic category, indicating significant enrichment (Fisher’s exact P = 0.003). These results define ancestry- and context-specific contributions of mtDNA to cardiometabolic disease, with a notable concentration in endocrine traits, and provide a framework for mtDNA analysis across diverse biobank cohorts.

OBJECTIVE: Use of continuous glucose monitors (CGM) improves glucose control and reduces hypoglycemia, but data are lacking for its possible role in reducing other serious clinical events. RESEARCH DESIGN AND METHODS: We conducted a target trial emulation (TTE) analysis in patients with type 1 diabetes (T1D) comparing all-cause mortality between CGM users and non–CGM users using observational health records from the Veterans Health Administration. Participants included adult T1D patients who had their second endocrine visit (time zero) during years 2017–2020. Each patient was cloned to both treatment strategies but was censored if observed care deviated from the assigned strategy (artificial censoring) during the 6-month grace period. Inverse probability weights accounted for artificial censoring, and negative outcomes examined residual confounding. RESULTS: Of the 8,423 individuals initially assigned to both treatment groups, 1,039 were prescribed CGM devices, while 7,399 were not censored or assigned CGM during the grace period. Mortality was lower with CGM initiation, yielding adjusted risk ratios of 0.90 (95% CI 0.71–0.97) to 0.84 (CI 0.72–0.97) over 1–4 years of follow-up. Similar risk ratios were seen with different grace periods (3 or 9 months). Those age >65 years or not on insulin pumps appeared to have greater benefit, but effects did not vary by HbA1c, race or ethnicity, or frailty. Risk ratios did not differ between groups for incident nondiabetes outcomes, including outpatient or inpatient musculoskeletal or gastrointestinal conditions. CONCLUSIONS: In this large TTE of CGM initiation in older T1D patients, CGM use was associated with reduced risk for all-cause mortality.

Aims: Assess the prevalence of overweight and obesity and the association between weight and cardiometabolic risk factors among veterans with type 1 diabetes ( T1D ). Materials and Methods: Persons with T1D , between the ages of 21 and 75 years, were identified from Veterans Health Administration administrative databases. Prevalence of weight categories was determined using data between 2022 and 2023, while longitudinal trends were examined in 2‐year intervals from 2016–2017 to 2022–2023. Differences in prevalence were adjusted for baseline characteristics and differences in cardiometabolic risk factors were adjusted for age, sex and race/ethnicity. Results: Nine thousand seven hundred twelve T1D veterans met inclusion criteria. Prevalence of overweight and obesity in 2022–2023 was 39.7% and 32.4%, respectively, and differed by race/ethnicity. Prevalence rates have risen steadily since 2016, most notably in those ages 21–39. Compared to normal weight veterans, overweight and obese veterans were older ( p = 0.003), more frequently male ( p = 0.024), and were more likely to be on anti‐obesity ( p < 0.001) and other cardioprotective medicines. Levels of cardiometabolic risk factors (blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and estimated glomerular filtration rate) were worse at higher weight categories (all p < 0.001) and appeared linearly related to body mass index ( BMI) . Several risk factors demonstrated age– BMI interactions, with younger veterans demonstrating greater changes in these risk factors with rising BMI . Conclusions: There is a high and rising prevalence of obesity among adult veterans with T1D , and a strong association of obesity with adverse cardiometabolic risk factors remains even in T1D . These trends highlight the need for a better understanding of mechanisms of weight gain in T1D and improved weight management strategies.

Background: It is not well established whether blood pressure variability (BPV) is associated with risk of incident heart failure (HF) as well as with subclinical markers of HF and myocardial injury. We investigated these relationships in the Multi-Ethnic Study of Atherosclerosis (MESA). Methods: We examined the association between visit-to-visit BPV (estimated by variability independent of the mean—VIM) and HF in MESA (2000-2012), a community-based cohort study of 6814 individuals free of clinical cardiovascular disease (including HF) at baseline, using Cox models and joint longitudinal-survival models. VIM was calculated from Exams 1 to 5. Serial measurements (Exams 1 and 5) of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin-T (hs-cTnT) were used to test the early onset and directionality of the relationships by logistic regression. Results: Over a median of 9.4 years of follow-up, VIM-SBP was associated with HF in adjusted Cox models including CVD risk factors (HR = 1.33 [95% CI, 1.03-1.69]), as well as in joint longitudinal-survival models. BPV was associated with elevated Exam 5 NT-proBNP (>125 pg/mL) after multivariable adjustment (VIM-SBP: OR = 1.26 [95% CI, 1.17-1.37]; VIM-DBP: OR = 1.23 [95% CI, 1.14-1.33]) and Exam 5 elevation in hs-cTnT (for VIM-SBP, OR = 1.27). Conclusions: BPV was associated with incident HF and longitudinal increases of subclinical markers of HF and myocardial injury in a multi-ethnic community-based cohort. These data indicate that visit-to-visit BPV may contribute to the development of HF.

Background: Although use of continuous glucose monitoring (CGM) has been linked with improved glucose control, including reductions in hemoglobin A1c and episodes of hypoglycemia, there has been little investigation of its possible role in reducing other serious clinical events. Objective: To estimate the effect of starting CGM in patients with type 2 diabetes (T2D) on mortality. Research Design: A cohort study comparing mortality between propensity score-matched CGM users and non-CGM users over 18 months. Setting: Veterans Affairs Health Care System. Participants: Adult patients with T2D receiving insulin who were identified as CGM users or non-CGM users between January 1, 2015, and December 31, 2020. Measurements: Primary outcome of all-cause mortality; secondary outcomes of serious all-cause hospitalization, cardiovascular events, and admissions related to hyperglycemia and hypoglycemia. Results: A total of 12,729 patients with T2D (94% male with mean age 66) who were new CGM users were 1:1 matched with non-CGM users. Total follow-up time was 17,676 and 17,034 person-years for CGM and non-CGM users. Risk for mortality was lower in CGM users (hazard ratio or HR 0.79: 95% confidence interval or CI 0.73–0.86), as were risks for all-cause hospitalization (0.91: 0.86, 0.96), cardiovascular events (0.84: 0.73, 0.96), and admissions for hyperglycemia (0.88: 0.81, 0.95). Lower risk for mortality persisted after accounting for early deaths, COVID-19, recent onset of diabetes, subsequent use of insulin pumps or newer diabetes medications, or when stratifying by frequency of CGM use, frailty index or mortality risk (all HRs: 0.83 or less, range of CI: 0.60–0.94). No differences between CGM and non-CGM users were seen with negative control outcomes. Limitations: Unmeasured health factors, behaviors, or other confounders may exist. Conclusion: In a large national cohort, initiation of CGM was associated with lower mortality in T2D patients using insulin and indicates use of CGM may have benefits that extend beyond glucose lowering.

OBJECTIVE: Investigate the association between continuous glucose monitoring (CGM)-derived glucose metrics and all-cause mortality in patients with type 1 or type 2 diabetes (T1D or T2D). RESEARCH DESIGN AND METHODS: We analyzed data from 2,752 adults (≥21 years old) with diabetes (65% T2D) from the Veterans Affairs Healthcare System who received Dexcom CGM between 2015 and 2020. All participants had ≥10 days of CGM data over landmark (LM) periods (14 days, 3 months, and 6 months) merged with electronic health records. All-cause mortality was assessed over 5 years from CGM initiation. Cox models evaluated associations between mortality and CGM metrics: mean glucose (MG, mg/dL), time in range (TIR, %), time above range (TAR, %), coefficient of variation (CV), and glycemic risk index (GRI, %). RESULTS: Mean age at CGM initiation was 64 years, and median CGM use was nearly 3 years. There were 407 deaths. In separate multivariable Cox models (adjusting for mortality-related variables), higher MG, TAR, CV, and GRI and lower TIR during the 6-month LM were associated with 5-year mortality (hazard ratios: MG 1.18, TAR 1.20, GRI 1.23, CV 1.18, and TIR 0.83; all P ≤ 0.01) and those associations remained significant after adjusting for LM HbA1c. Results were similar with shorter CGM LM observation windows. The association between CV and mortality was independent of other CGM metrics and appeared strongest in those with lower HbA1c levels. CONCLUSIONS: CGM-derived metrics were associated with all-cause mortality in patients with diabetes and may better capture long-term risk associated with glucose fluctuations and periods of hypo- and hyperglycemia than HbA1c.

Background: Achieving optimal glycemic control for persons with diabetes remains difficult. Real-world continuous glucose monitoring (CGM) data can illuminate previously underrecognized glycemic fluctuations. We aimed to characterize glucose trajectories in individuals with Type 1 and Type 2 diabetes, and to examine how baseline glycemic control, CGM usage frequency, and regional differences shape these patterns. Methods: We linked Dexcom CGM data (2015–2020) with Veterans Health Administration electronic health records, identifying 892 Type 1 and 1716 Type 2 diabetes patients. Analyses focused on the first three years of CGM use, encompassing over 2.1 million glucose readings. We explored temporal trends in average daily glucose and time-in-range values. Results: Both Type 1 and Type 2 cohorts exhibited a gradual rise in mean daily glucose over time, although higher CGM usage frequency was associated with lower overall glucose or attenuated increases. Notable weekly patterns emerged: Sundays consistently showed the highest glucose values, whereas Wednesdays tended to have the lowest. Seasonally, glycemic control deteriorated from October to February and rebounded from April to August, with more pronounced fluctuations in the Northeast compared to the Southwest U.S. Conclusions: Our findings underscore the importance of recognizing day-of-week and seasonal glycemic variations in diabetes management. Tailoring interventions to account for these real-world fluctuations may enhance patient engagement, optimize glycemic control, and ultimately improve health outcomes.

Objective: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for patients with type 1 and type 2 diabetes (T1D and T2D) in the national Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. Research Design and Methods: This observational study used Dexcom CGM device data linked with EHR (from 2015 to 2020) for a large national cohort of patients with diabetes. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. Results: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged 3 weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 h over nearly 3 years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups, and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. Conclusions: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both patients with T1D and T2D within the Veterans Affairs Healthcare System and is similar across major race/ethnic groups and age-groups.

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828-T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828-T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828-T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.