Publications by authors named "Sridharan Raghavan"

34 Publications

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.

Ann Epidemiol 2021 Jul 17. Epub 2021 Jul 17.

Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO.

Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine learning derived HTE remains unclear. We examined generalizability of HTE detected using causal forests in two similarly designed randomized trials in type II diabetes patients. Methods We evaluated published HTE of intensive versus standard glycemic control on all-cause mortality from the Action to Control Cardiovascular Risk in Diabetes study (ACCORD) in a second trial, the Veterans Affairs Diabetes Trial (VADT). We then applied causal forests to VADT, ACCORD, and pooled data from both studies and compared variable importance and subgroup effects across samples. Results HTE in ACCORD did not replicate in similar subgroups in VADT, but variable importance was correlated between VADT and ACCORD (Kendall's tau-b 0.75). Applying causal forests to pooled individual-level data yielded seven subgroups with similar HTE across both studies, ranging from risk difference of all-cause mortality of -3.9% (95% CI -7.0, -0.8) to 4.7% (95% CI 1.8, 7.5). Conclusions Machine learning detection of HTE subgroups from randomized trials may not generalize across study samples even when variable importance is correlated. Pooling individual-level data may overcome differences in study populations and/or differences in interventions that limit HTE generalizability.
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http://dx.doi.org/10.1016/j.annepidem.2021.07.003DOI Listing
July 2021

Genetic Risk Score for Type 2 Diabetes and Traits Related to Glucose-Insulin Homeostasis in Youth: The Exploring Perinatal Outcomes Among Children (EPOCH) Study.

Diabetes Care 2021 09 13;44(9):2018-2024. Epub 2021 Jul 13.

Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO.

Objective: The metabolic phenotype of youth-onset type 2 diabetes (T2D) differs from that of adult-onset T2D, but little is known about genetic contributions. We aimed to evaluate the association between a T2D genetic risk score (GRS) and traits related to glucose-insulin homeostasis among healthy youth.

Research Design And Methods: We used data from 356 youth (mean age 16.7 years; 50% female) in the Exploring Perinatal Outcomes Among Children (EPOCH) cohort to calculate a standardized weighted GRS based on 271 single nucleotide polymorphisms associated with T2D in adults. We used linear regression to assess associations of the GRS with log-transformed fasting glucose, 2-h glucose, HOMA of insulin resistance (HOMA-IR), oral disposition index, and insulinogenic index adjusted for age, sex, BMI score, in utero exposure to maternal diabetes, and genetic principal components. We also evaluated effect modification by BMI score, in utero exposure to maternal diabetes, and ethnicity.

Results: Higher weighted GRS was associated with lower oral disposition index (β = -0.11; 95% CI -0.19, -0.02) and insulinogenic index (β = -0.08; 95% CI -0.17, -0.001), but not with fasting glucose (β = 0.01; 95% CI -0.01, 0.02), 2-h glucose (β = 0.03; 95% CI -0.0004, 0.06), or HOMA-IR (β = 0.02; 95% CI -0.04, 0.07). BMI score and in utero exposure to maternal diabetes increased the effect of the GRS on glucose levels.

Conclusions: Our results suggest that T2D genetic risk factors established in adults are relevant to glucose-insulin homeostasis in youth and that maintaining a healthy weight may be particularly important for youth with high genetic risk of T2D.
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http://dx.doi.org/10.2337/dc21-0464DOI Listing
September 2021

Genetic Interactions with Intrauterine Diabetes Exposure in Relation to Obesity: The EPOCH and Project Viva Studies.

Pediatr Rep 2021 Jun 1;13(2):279-288. Epub 2021 Jun 1.

Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.

To examine whether BMI-associated genetic risk variants modify the association of intrauterine diabetes exposure with childhood BMI z-scores, we assessed the interaction between 95 BMI-associated genetic variants and in utero exposure to maternal diabetes among 459 children in the Exploring Perinatal Outcomes among Children historical prospective cohort study (n = 86 exposed; 373 unexposed) in relation to age- and sex-standardized childhood BMI z-scores (mean age = 10.3 years, standard deviation = 1.5 years). For the genetic variants showing a nominally significant interaction, we assessed the relationship in an additional 621 children in Project Viva, which is an independent longitudinal cohort study, and used meta-analysis to combine the results for the two studies. Seven of the ninety-five genetic variants tested exhibited a nominally significant interaction with in utero exposure to maternal diabetes in relation to the offspring BMI z-score in EPOCH. Five of the seven variants exhibited a consistent direction of interaction effect across both EPOCH and Project Viva. While none achieved statistical significance in the meta-analysis after accounting for multiple testing, three variants exhibited a nominally significant interaction with in utero exposure to maternal diabetes in relation to offspring BMI z-score: rs10733682 near (interaction β = 0.39; standard error (SE) = 0.17), rs17001654 near (β = 0.53; SE = 0.22), and rs16951275 near (β = 0.37; SE = 0.17). BMI-associated genetic variants may enhance the association between exposure to in utero diabetes and higher childhood BMI, but larger studies of in utero exposures are necessary to confirm the observed nominally significant relationships.
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http://dx.doi.org/10.3390/pediatric13020036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293453PMC
June 2021

Transporting experimental results with entropy balancing.

Stat Med 2021 08 20;40(19):4310-4326. Epub 2021 May 20.

Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA.

We show how entropy balancing can be used for transporting experimental treatment effects from a trial population onto a target population. This method is doubly robust in the sense that if either the outcome model or the probability of trial participation is correctly specified, then the estimate of the target population average treatment effect is consistent. Furthermore, we only require the sample moments of the effect modifiers drawn from the target population to consistently estimate the target population average treatment effect. We compared the finite-sample performance of entropy balancing with several alternative methods for transporting treatment effects between populations. Entropy balancing techniques are efficient and robust to violations of model misspecification. We also examine the results of our proposed method in an applied analysis of the Action to Control Cardiovascular Risk in Diabetes Blood Pressure trial transported to a sample of US adults with diabetes taken from the National Health and Nutrition Examination Survey cohort.
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http://dx.doi.org/10.1002/sim.9031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487904PMC
August 2021

Differences in High- and Low-Value Cardiovascular Testing by Health Insurance Provider.

J Am Heart Assoc 2021 02 28;10(3):e018877. Epub 2021 Jan 28.

Division of Cardiology University of Colorado Anschutz Medical Campus Aurora CO.

Background Quality of care incentives and reimbursements for cardiovascular testing differ between insurance providers. We hypothesized that there are differences in the use of guideline-concordant testing between Medicaid versus commercial insurance patients <65 years, and between Medicare Advantage versus Medicare fee-for-service patients ≥65 years. Methods and Results Using data from the Colorado All-Payer Claims Database from 2015 to 2018, we identified patients eligible to receive a high-value test recommended by guidelines: assessment of left ventricular function among patients hospitalized with acute myocardial infarction or incident heart failure, or a low-value test that provides minimal patient benefit: stress testing prior to low-risk surgery or routine stress testing within 2 years of percutaneous coronary intervention or coronary artery bypass graft surgery. Among 145 616 eligible patients, 37% had fee-for-service Medicare, 18% Medicare Advantage, 22% Medicaid, and 23% commercial insurance. Using multilevel logistic regression models adjusted for patient characteristics, Medicaid patients were less likely to receive high-value testing for acute myocardial infarction (odds ratio [OR], 0.84 [0.73-0.98]; =0.03) and heart failure (OR, 0.59 [0.51-0.70]; <0.01) compared with commercially insured patients. Medicare Advantage patients were more likely to receive high-value testing for acute myocardial infarction (OR, 1.35 [1.15-1.59]; <0.01) and less likely to receive low-value testing after percutaneous coronary intervention/ coronary artery bypass graft (OR, 0.63 [0.55-0.72]; <0.01) compared with Medicare fee-for-service patients. Conclusions Guideline-concordant testing was less likely to occur among patients with Medicaid compared with commercial insurance, and more likely to occur among patients with Medicare Advantage compared with fee-for-service Medicare. Insurance plan features may provide valuable targets to improve guideline-concordant testing.
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http://dx.doi.org/10.1161/JAHA.120.018877DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955432PMC
February 2021

Interaction of diabetes genetic risk and successful lifestyle modification in the Diabetes Prevention Programme.

Diabetes Obes Metab 2021 04 29;23(4):1030-1040. Epub 2021 Jan 29.

Centre for Lifecourse Epidemiology of Adiposity and Diabetes, Colorado School of Public Health, Aurora, Colorado, USA.

Aim: To test whether diabetes genetic risk modifies the association of successful lifestyle changes with incident diabetes.

Materials And Methods: We studied 823 individuals randomized to the intensive lifestyle intervention (ILS) arm of the Diabetes Prevention Programme who were diabetes-free 1 year after enrolment. We tested additive and multiplicative interactions of a 67-variant diabetes genetic risk score (GRS) with achievement of three ILS goals at 1 year (≥7% weight loss, ≥150 min/wk of moderate leisure-time physical activity, and/or a goal for self-reported total fat intake) on the primary outcome of incident diabetes over 3 years of follow-up.

Results: A lower GRS and achieving each or all three ILS goals were each associated with lower incidence of diabetes (all P < 0.05). Additive interactions were significant between the GRS and achievement of the weight loss goal (P < 0.001), physical activity goal (P = 0.02), and all three ILS goals (P < 0.001) for diabetes risk. Achievement of all three ILS goals was associated with 1.8 (95% CI 0.3, 3.4), 3.1 (95% CI 1.5, 4.7), and 3.9 (95% CI 1.6, 6.2) fewer diabetes cases/100-person-years in the first, second and third GRS tertiles (P < 0.001 for trend). Multiplicative interactions between the GRS and ILS goal achievement were significant for the diet goal (P < 0.001), but not for weight loss (P = 0.18) or physical activity (P = 0.62) goals.

Conclusions: Genetic risk may identify high-risk subgroups for whom successful lifestyle modification is associated with greater absolute reduction in the risk of incident diabetes.
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http://dx.doi.org/10.1111/dom.14309DOI Listing
April 2021

Potential unrealized mortality benefit of glucagon-like peptide-1 receptor agonists and sodium-glucose co-transport-2 inhibitors: A report from the Veterans Health Administration Clinical Assessment, Reporting and Tracking program.

Diabetes Obes Metab 2021 01 3;23(1):97-105. Epub 2020 Oct 3.

Cardiology Section, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA.

Aim: To assess the unrealized potential of glucagon-like peptide-1 receptor agonist (GLP-1RA) or sodium-glucose co-transport-2 inhibitor (SGLT2i) use to reduce mortality in veterans with type 2 diabetes (T2D), coronary artery disease (CAD), and other characteristics congruent with clinical trial cohorts that established the efficacy of these agents.

Methods: Veterans with T2D and CAD on angiography in 2014 who were untreated with either a GLP-1RA or a SGLT2i were assessed for key eligibility criteria of the LEADER (GLP-1RA) and EMPA-REG OUTCOME (SGLT2i) trials. Trial hazard ratios and 95% confidence intervals for all-cause death were applied to deaths observed in veterans through 2018 to estimate the potential benefit of GLP-1RA or SGLT2i use.

Results: Median observation was 4.3 years. Of 15 987 veterans with T2D and CAD, 1186 (7.4%) were excluded for GLP-1RA or SGLT2i treatment, and 1386 lacked glycated haemoglobin measurement. Of the remaining 13 415 patients, 4103 (30.1%) and 5313 (39.6%) fulfilled the key criteria for the LEADER and EMPA-REG OUTCOME trials, respectively. Death occurred in 1009 (24.6%) of LEADER-eligible patients and 1335 (25.1%) of EMPA-REG OUTCOME-eligible patients. Under treatment with liraglutide in LEADER-eligible veterans, a 3.5% (0.7%-6.2%) potential absolute mortality reduction, corresponding to 144 (28-253) fewer deaths (0.88 [0.17-1.56] per 100 person-years), might have been expected. Similarly, under treatment with empagliflozin in EMPA-REG OUTCOME-eligible veterans, a 7.9% (4.5%-10.8%) potential absolute mortality reduction, corresponding to 418 (230-573) fewer deaths (1.98 [1.14-2.72] per 100 person-years), might have been expected.

Conclusions: This analysis indicates unrealized opportunities to reduce mortality in selected veterans with T2D and CAD via increased GLP-1RA and SGLT2i use.
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http://dx.doi.org/10.1111/dom.14193DOI Listing
January 2021

Optimizing Atherosclerotic Cardiovascular Disease Risk Estimation for Veterans With Diabetes Mellitus.

Circ Cardiovasc Qual Outcomes 2020 Aug 31:CIRCOUTCOMES120006528. Epub 2020 Aug 31.

Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.).

Background: Estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk in diabetes mellitus patients is used to guide primary prevention, but the performance of risk estimators (2013 Pooled Cohort Equations [PCE] and Risk Equations for Complications of Diabetes [RECODe]) varies across populations. Data from electronic health records could be used to improve risk estimation for a health system's patients. We aimed to evaluate risk equations for initial ASCVD events in US veterans with diabetes mellitus and improve model performance in this population.

Methods And Results: We studied 183 096 adults with diabetes mellitus and without prior ASCVD who received care in the Veterans Affairs Healthcare System (VA) from 2002 to 2016 with mean follow-up of 4.6 years. We evaluated model discrimination, using Harrell's C statistic, and calibration, using the reclassification χ test, of the PCE and RECODe equations to predict fatal or nonfatal myocardial infarction or stroke and cardiovascular mortality. We then tested whether model performance was affected by deriving VA-specific β-coefficients. Discrimination of ASCVD events by the PCE was improved by deriving VA-specific β-coefficients (C statistic increased from 0.560 to 0.597) and improved further by including measures of glycemia, renal function, and diabetes mellitus treatment (C statistic, 0.632). Discrimination by the RECODe equations was improved by substituting VA-specific coefficients (C statistic increased from 0.604 to 0.621). Absolute risk estimation by PCE and RECODe equations also improved with VA-specific coefficients; the calibration increased from <0.001 to 0.08 for PCE and from <0.001 to 0.005 for RECODe, where higher indicates better calibration. Approximately two-thirds of veterans would meet a guideline indication for high-intensity statin therapy based on the PCE versus only 10% to 15% using VA-fitted models.

Conclusions: Existing ASCVD risk equations overestimate risk in veterans with diabetes mellitus, potentially impacting guideline-indicated statin therapy. Prediction model performance can be improved for a health system's patients using readily available electronic health record data.
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http://dx.doi.org/10.1161/CIRCOUTCOMES.120.006528DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914289PMC
August 2020

Estimation of Atherosclerotic Cardiovascular Disease Risk Among Patients in the Veterans Affairs Health Care System.

JAMA Netw Open 2020 07 1;3(7):e208236. Epub 2020 Jul 1.

Atlanta Veterans Affairs Medical Center, Decatur, Georgia.

Importance: Current guidelines recommend statin therapy for millions of US residents for the primary prevention of atherosclerotic cardiovascular disease (ASCVD). It is unclear whether traditional prediction models that do not account for current widespread statin use are sufficient for risk assessment.

Objectives: To examine the performance of the Pooled Cohort Equations (PCE) for 5-year ASCVD risk estimation in a contemporary cohort and to test the hypothesis that inclusion of statin therapy improves model performance.

Design, Setting, And Participants: This cohort study included adult patients in the Veterans Affairs health care system without baseline ASCVD. Using national electronic health record data, 3 Cox proportional hazards models were developed to estimate 5-year ASCVD risk, as follows: the variables and published β coefficients from the PCE (model 1), the PCE variables with cohort-derived β coefficients (model 2), and model 2 plus baseline statin use (model 3). Data were collected from January 2002 to December 2012 and analyzed from June 2016 to March 2020.

Exposures: Traditional ASCVD risk factors from the PCE plus baseline statin use.

Main Outcomes And Measures: Incident ASCVD and ASCVD mortality.

Results: Of 1 672 336 patients in the cohort (mean [SD] baseline age 58.0 [13.8] years, 1 575 163 [94.2%] men, 1 383 993 [82.8%] white), 312 155 (18.7%) were receiving statin therapy at baseline. During 5 years of follow-up, 66 605 (4.0%) experienced an ASCVD event, and 31 878 (1.9%) experienced ASCVD death. Compared with the original PCE, the cohort-derived model did not improve model discrimination in any of the 4 age-sex strata but did improve model calibration. The PCE overestimated ASCVD risk compared with the cohort-derived model; 211 237 of 1 136 161 white men (18.6%), 29 634 of 218 463 black men (13.6%), 1741 of 44 399 white women (3.9%), and 836 of 16 034 black women (5.2%) would be potentially eligible for statin therapy under the PCE but not the cohort-derived model. When added to the cohort-derived model, baseline statin therapy was associated with a 7% (95% CI, 5%-9%) lower relative risk of ASCVD and a 25% (95% CI, 23%-28%) lower relative risk for ASCVD death.

Conclusions And Relevance: In this study, lower than expected rates of incident ASCVD events in a contemporary national cohort were observed. The PCE overestimated ASCVD risk, and more than 15% of patients would be potentially eligible for statin therapy based on the PCE but not on a cohort-derived model. In the statin era, health care professionals and systems should base ASCVD risk assessment on models calibrated to their patient populations.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.8236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361654PMC
July 2020

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

PLoS One 2020 7;15(5):e0230815. Epub 2020 May 7.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230815PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205201PMC
August 2020

Association of Glycemic Control Trajectory with Short-Term Mortality in Diabetes Patients with High Cardiovascular Risk: a Joint Latent Class Modeling Study.

J Gen Intern Med 2020 08 24;35(8):2266-2273. Epub 2020 Apr 24.

Department of Veterans Affairs, Eastern Colorado Healthcare System, Aurora, CO, USA.

Background: The relationship between risk factor or biomarker trajectories and contemporaneous short-term clinical outcomes is poorly understood. In diabetes patients, it is unknown whether hemoglobin A1c (HbA1c) trajectories are associated with clinical outcomes and can inform care in scenarios in which a single HbA1c is uninformative, for example, after a diagnosis of coronary artery disease (CAD).

Objective: To compare associations of HbA1c trajectories and single HbA1c values with short-term mortality in diabetes patients evaluated for CAD DESIGN: Retrospective observational cohort study PARTICIPANTS: Diabetes patients (n = 7780) with and without angiographically defined CAD MAIN MEASURES: We used joint latent class mixed models to simultaneously fit HbA1c trajectories and estimate association with 2-year mortality after cardiac catheterization, adjusting for clinical and demographic covariates.

Key Results: Three HBA1c trajectory classes were identified: individuals with stable glycemia (class A; n = 6934 [89%]; mean baseline HbA1c 6.9%), with declining HbA1c (class B; n = 364 [4.7%]; mean baseline HbA1c 11.6%), and with increasing HbA1c (class C; n = 482 [6.2%]; mean baseline HbA1c 8.5%). HbA1c trajectory class was associated with adjusted 2-year mortality (3.0% [95% CI 2.8, 3.2] for class A, 3.1% [2.1, 4.2] for class B, and 4.2% [3.4, 4.9] for class C; global P = 0.047, P = 0.03 comparing classes A and C, P > 0.05 for other pairwise comparisons). Baseline HbA1c was not associated with 2-year mortality (P = 0.85; hazard ratios 1.01 [0.96, 1.06] and 1.02 [0.95, 1.10] for HbA1c 7-9% and ≥ 9%, respectively, relative to HbA1c < 7%). The association between HbA1c trajectories and mortality did not differ between those with and without CAD (interaction P = 0.1).

Conclusions: In clinical settings where single HbA1c measurements provide limited information, HbA1c trajectories may help stratify risk of complications in diabetes patients. Joint latent class modeling provides a generalizable approach to examining relationships between biomarker trajectories and clinical outcomes in the era of near-universal adoption of electronic health records.
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http://dx.doi.org/10.1007/s11606-020-05848-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403288PMC
August 2020

Early-phase study of a telephone-based intervention to reduce weight regain among bariatric surgery patients.

Health Psychol 2020 May 30;39(5):391-402. Epub 2020 Jan 30.

William S. Middleton Memorial Veterans Hospital.

Objective: This study describes early-phase development of a behavioral intervention to reduce weight regain following bariatric surgery. We utilized the Obesity-Related Behavioral Intervention Trials model to guide intervention development and evaluation. We sought to establish recruitment, retention, and fidelity monitoring procedures; evaluate feasibility of utilizing weight from the electronic medical record (EMR) as an outcome; observe improvement in behavioral risk factors; and evaluate treatment acceptability.

Method: The intervention comprised 4 weekly telephone calls addressing behavior change strategies for diet, physical activity, and nutrition supplement adherence and 5 biweekly calls addressing weight loss maintenance constructs. Veterans ( = 33) who received bariatric surgery 9-15 months prior consented to a 16-week, pre-post study. Self-reported outcomes were obtained by telephone at baseline and 16 weeks. Clinic weights were obtained from the EMR 6 months pre- and postconsent. Qualitative interviews were conducted at 16 weeks to evaluate treatment acceptability. We aimed to achieve a recruitment rate of ≥ 25% and retention rate of ≥ 80%, and have ≥ 50% of participants regain < 3% of their baseline weight.

Results: Results supported the feasibility of recruiting (48%) and retaining participants (93% provided survey data; 100% had EMR weight). Pre-post changes in weight (73% with < 3% weight regain) and physical activity (Cohen's ds 0.38 to 0.52) supported the potential for the intervention to yield clinically significant results. Intervention adherence (mean 7.8 calls of 9 received) and positive feedback from interviews supported treatment acceptability.

Conclusions: The intervention should be evaluated in an adequately powered randomized controlled trial. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/hea0000835DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219473PMC
May 2020

Association Between Early Hypertension Control and Cardiovascular Disease Incidence in Veterans With Diabetes.

Diabetes Care 2019 10;42(10):1995-2003

Atlanta Veterans Affairs Medical Center, Decatur, GA.

Objective: Guidelines for hypertension treatment in patients with diabetes diverge regarding the systolic blood pressure (SBP) threshold at which treatment should be initiated and treatment goal. We examined associations of early SBP treatment with atherosclerotic cardiovascular disease (ASCVD) events in U.S. adults with diabetes.

Research Design And Methods: We studied 43,986 patients with diabetes who newly initiated antihypertensive therapy between 2002 and 2007. Patients were classified into categories based on SBP at treatment initiation (130-139 or ≥140 mmHg) and after 2 years of treatment (100-119, 120-129, 130-139, 140-159, and ≥160 mmHg). The primary outcome was composite ASCVD events (fatal and nonfatal myocardial infarction and stroke), estimated using inverse probability of treatment-weighted Poisson regression and multivariable Cox proportional hazards regression.

Results: Relative to individuals who initiated treatment when SBP was 130-139 mmHg, those with pretreatment SBP ≥140 mmHg had higher ASCVD risk (hazard ratio 1.10 [95% CI 1.02, 1.19]). Relative to those with pretreatment SBP of 130-139 mmHg and on-treatment SBP of 120-129 mmHg (reference group), ASCVD incidence was higher in those with pretreatment SBP ≥140 mmHg and on-treatment SBP 120-129 mmHg (adjusted incidence rate difference [IRD] 1.0 [-0.2 to 2.1] events/1,000 person-years) and in those who achieved on-treatment SBP 130-139 mmHg (IRD 1.9 [0.6, 3.2] and 1.1 [0.04, 2.2] events/1,000 person-years for those with pretreatment SBP 130-139 mmHg and ≥140 mmHg, respectively).

Conclusions: In this observational study, patients with diabetes initiating antihypertensive therapy when SBP was 130-139 mmHg and those achieving on-treatment SBP <130 mmHg had better outcomes than those with higher SBP levels when initiating or after 2 years on treatment.
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http://dx.doi.org/10.2337/dc19-0686DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754236PMC
October 2019

Random plasma glucose predicts the diagnosis of diabetes.

PLoS One 2019 19;14(7):e0219964. Epub 2019 Jul 19.

Atlanta VA Health Care System, Decatur, Georgia, United States of America.

Aims/hypothesis: Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes.

Methods: Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug).

Results: Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively).

Conclusions: RPG levels below the diabetes "diagnostic" range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels-obtained opportunistically, during outpatient visits-could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219964PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641200PMC
March 2020

Associations of Diabetes Genetic Risk Counseling with Incident Diabetes and Weight: 5-Year Follow-up of a Randomized Controlled Trial.

J Gen Intern Med 2020 03 16;35(3):944-946. Epub 2019 Jul 16.

Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.

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http://dx.doi.org/10.1007/s11606-019-05126-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080941PMC
March 2020

Diabetes Mellitus-Related All-Cause and Cardiovascular Mortality in a National Cohort of Adults.

J Am Heart Assoc 2019 02;8(4):e011295

7 Department of Veterans Affairs Atlanta Medical Center Atlanta GA.

Background Diabetes mellitus is a risk factor for cardiovascular disease ( CVD ) and has been associated with 2- to 4-fold higher mortality. Diabetes mellitus-related mortality has not been reassessed in individuals receiving routine care in the United States in the contemporary era of CVD risk reduction. Methods and Results We retrospectively studied 963 648 adults receiving care in the US Veterans Affairs Healthcare System from 2002 to 2014; mean follow-up was 8 years. We estimated associations of diabetes mellitus status and hemoglobin A1c (HbA1c) with all-cause and CVD mortality using covariate-adjusted incidence rates and multivariable Cox proportional hazards regression. Of participants, 34% had diabetes mellitus. Compared with nondiabetic individuals, patients with diabetes mellitus had 7.0 (95% CI , 6.7-7.4) and 3.5 (95% CI, 3.3-3.7) deaths/1000-person-years higher all-cause and CVD mortality, respectively. The age-, sex-, race-, and ethnicity-adjusted hazard ratio for diabetes mellitus-related mortality was 1.29 (95% CI, 1.28-1.31), and declined with adjustment for CVD risk factors (hazard ratio, 1.18 [95% CI, 1.16-1.19]) and glycemia (hazard ratio, 1.03 [95% CI, 1.02-1.05]). Among individuals with diabetes mellitus, CVD mortality increased as HbA1c exceeded 7% (hazard ratios, 1.11 [95% CI, 1.08-1.14], 1.25 [95% CI, 1.22-1.29], and 1.52 [95% CI, 1.48-1.56] for HbA1c 7%-7.9%, 8%-8.9%, and ≥9%, respectively, relative to HbA1c 6%-6.9%). HbA1c 6% to 6.9% was associated with the lowest mortality risk irrespective of CVD history or age. Conclusions Diabetes mellitus remains significantly associated with all-cause and CVD mortality, although diabetes mellitus-related excess mortality is lower in the contemporary era than previously. We observed a gradient of mortality risk with increasing HbA1c >6% to 6.9%, suggesting HbA1c remains an informative predictor of outcomes even if causality cannot be inferred.
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http://dx.doi.org/10.1161/JAHA.118.011295DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405678PMC
February 2019

Association of Diabetes Mellitus Status and Glycemic Control With Secondary Prevention Medication Adherence After Acute Myocardial Infarction.

J Am Heart Assoc 2019 02;8(3):e011448

1 Department of Medicine University of Colorado School of Medicine Aurora CO.

Background Cardioprotective medication adherence can mitigate the risk of recurrent cardiovascular events and mortality after acute myocardial infarction ( AMI ). We examined the associations of diabetes mellitus status and glycemic control with cardioprotective medication adherence after AMI . Methods and Results We performed a retrospective observational cohort study of 14 517 US veterans who were hospitalized for their first AMI between 2011 and 2014 and prescribed a beta-blocker, 3-hydroxy-3-methyl-glutaryl-CoA-reductase inhibitor, and angiotensin-converting enzyme inhibitor or angiotensin receptor blocker. The primary exposure was a diagnosis of type 2 diabetes mellitus; in diabetes mellitus patients, hemoglobin A1c (HbA1c) was a secondary exposure. The primary outcome was 1-year adherence to all 3 medication classes, defined as proportion of days covered ≥0.8, assessed using adjusted risk differences and multivariable Poisson regression. Of 14 517 patients (mean age, 66.3 years; 98% male), 52% had diabetes mellitus; 9%, 31%, 24%, 15%, and 21% had HbA1c <6%, 6% to 6.9%, 7% to 7.9%, 8% to 8.9%, and ≥9%, respectively. Diabetes mellitus patients were more likely to be adherent to all 3 drug classes than those without diabetes mellitus (adjusted difference in adherence, 2.1% [0.5, 3.7]). Relative to those with HbA1c 6% to 6.9%, medication adherence declined with increasing HbA1c (risk ratio of achieving proportion of days covered ≥0.8, 0.99 [0.94, 1.04], 0.93 [0.87, 0.99], 0.82 [0.77, 0.88] for HbA1c 7-7.9%, 8-8.9%, and ≥9%, respectively). Conclusions Although diabetes mellitus status had a minor positive impact on cardioprotective medication adherence after AMI , glycemic control at the time of AMI may help identify diabetes mellitus patients at risk of medication nonadherence who may benefit from adherence interventions after AMI .
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http://dx.doi.org/10.1161/JAHA.118.011448DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405589PMC
February 2019

Device-measured physical activity data for classification of patients with ventricular arrhythmia events: A pilot investigation.

PLoS One 2018 29;13(10):e0206153. Epub 2018 Oct 29.

Individualized Data Analysis Organization, Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States of America.

Low levels of physical activity are associated with increased mortality risk, especially in cardiac patients, but most studies are based on self-report. Cardiac implantable electronic devices (CIEDs) offer an opportunity to collect data for longer periods of time. However, there is limited agreement on the best approaches for quantification of activity measures due to the time series nature of the data. We examined physical activity time series data from 235 subjects with CIEDs and at least 365 days of uninterrupted measures. Summary statistics for raw daily physical activity (minutes/day), including statistical moments (e.g., mean, standard deviation, skewness, kurtosis), time series regression coefficients, frequency domain components, and forecasted predicted values, were calculated for each individual, and used to predict occurrence of ventricular tachycardia (VT) events as recorded by the device. In unsupervised analyses using principal component analysis, we found that while certain features tended to cluster near each other, most provided a reasonable spread across activity space without a large degree of redundancy. In supervised analyses, we found several features that were associated with the outcome (P < 0.05) in univariable and multivariable approaches, but few were consistent across models. Using a machine-learning approach in which the data was split into training and testing sets, and models ranging in complexity from simple univariable logistic regression to ensemble decision trees were fit, there was no improvement in classification of risk over naïve methods for any approach. Although standard approaches identified summary features of physical activity data that were correlated with risk of VT, machine-learning approaches found that none of these features provided an improvement in classification. Future studies are needed to explore and validate methods for feature extraction and machine learning in classification of VT risk based on device-measured activity.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0206153PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6205644PMC
March 2019

Oral diabetes medication monotherapy and short-term mortality in individuals with type 2 diabetes and coronary artery disease.

BMJ Open Diabetes Res Care 2018 15;6(1):e000516. Epub 2018 Jun 15.

Section of Hospital Medicine, Veterans Affairs Eastern Colorado Healthcare System, Denver, Colorado, USA.

Objective: To determine whether sulfonylurea use, compared with non-sulfonylurea oral diabetes medication use, was associated with 2-year mortality in individuals with well-controlled diabetes and coronary artery disease (CAD).

Research Design And Methods: We studied 5352 US veterans with type 2 diabetes, obstructive CAD on coronary angiography, hemoglobin A1c ≤7.5% at the time of catheterization, and taking zero or one oral diabetes medication (categorized as no medications, non-sulfonylurea medication, or sulfonylurea). We estimated the association between medication category and 2-year mortality using inverse probability of treatment-weighted (IPW) standardized mortality differences and IPW multivariable Cox proportional hazards regression.

Results: 49%, 35%, and 16% of the participants were on no diabetes medications, non-sulfonylurea medications, and sulfonylureas, respectively. In individuals on no medications, non-sulfonylurea medications, and sulfonylureas, the unadjusted mortality rates were 6.6%, 5.2%, and 11.9%, respectively, and the IPW-standardized mortality rates were 5.9%, 6.5%, and 9.7%, respectively. The standardized absolute 2-year mortality difference between non-sulfonylurea and sulfonylurea groups was 3.2% (95% CI 0.7 to 5.7) (p=0.01). In Cox proportional hazards models, the point estimate suggested that sulfonylurea use might be associated with greater hazard of mortality than non-sulfonylurea medication use, but this finding was not statistically significant (HR 1.38 (95% CI 1.00 to 1.93), p=0.05). We did not observe significant mortality differences between individuals on no diabetes medications and non-sulfonylurea users.

Conclusions: Sulfonylurea use was common (nearly one-third of those taking medications) and was associated with increased 2-year mortality in individuals with obstructive CAD. The significance of the association between sulfonylurea use and mortality was attenuated in fully adjusted survival models. Caution with sulfonylurea use may be warranted for patients with well-controlled diabetes and CAD, and metformin or newer diabetes medications with cardiovascular safety data could be considered as alternatives when individualizing therapy.
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http://dx.doi.org/10.1136/bmjdrc-2018-000516DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014184PMC
June 2018

Coronary artery disease severity modifies associations between glycemic control and both mortality and myocardial infarction.

J Diabetes Complications 2018 05 31;32(5):480-487. Epub 2018 Jan 31.

Veterans Affairs Eastern Colorado Healthcare System, Denver, CO, United States; Division of Cardiology, Washington University School of Medicine, St. Louis, MO, United States.

Aims: This study examined whether the association between hemoglobin A1c (HbA1c) and short-term clinical outcomes is moderated by CAD severity.

Methods: We studied 17,394 US Veterans with type 2 diabetes who underwent elective cardiac catheterization between 2005 and 2013. CAD severity was categorized as obstructive, non-obstructive, or no CAD. Using multivariable Cox proportional hazards regression, we assessed associations between time-varying HbA1c and two-year all-cause mortality and non-fatal MI, with an interaction term between HbA1c and CAD severity.

Results: 61%, 22%, and 17% of participants had obstructive, non-obstructive, and no CAD, respectively. CAD severity modified the relationship between HbA1c and each outcome (interaction p-value 0.0005 for mortality and <0.0001 for MI). Low HbA1c (<42 mmol/mol) was associated with increased mortality, relative to HbA1c of 48-52 mmol/mol, in individuals with obstructive CAD (HR 1.52 [1.17, 1.97]) and non-obstructive CAD (HR 2.61 [1.61, 4.23]), but not in those with no CAD (HR 0.91 [0.46, 1.79]). In contrast, higher HbA1c levels (≥53 mmol/mol) were associated with increased MI risk only in individuals with obstructive CAD.

Conclusions: The associations between HbA1c and mortality and MI were moderated by CAD severity. Measures of cardiovascular disease severity may inform optimal individualized diabetes management.
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http://dx.doi.org/10.1016/j.jdiacomp.2018.01.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920719PMC
May 2018

Characteristics Associated With Decreased or Increased Mortality Risk From Glycemic Therapy Among Patients With Type 2 Diabetes and High Cardiovascular Risk: Machine Learning Analysis of the ACCORD Trial.

Diabetes Care 2018 03 26;41(3):604-612. Epub 2017 Dec 26.

Harvard Medical School, Boston, MA.

Objective: Identifying patients who may experience decreased or increased mortality risk from intensive glycemic therapy for type 2 diabetes remains an important clinical challenge. We sought to identify characteristics of patients at high cardiovascular risk with decreased or increased mortality risk from glycemic therapy for type 2 diabetes using new methods to identify complex combinations of treatment effect modifiers.

Research Design And Methods: The machine learning method of gradient forest analysis was applied to understand the variation in all-cause mortality within the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial ( = 10,251), whose participants were 40-79 years old with type 2 diabetes, hemoglobin A (HbA) ≥7.5% (58 mmol/mol), cardiovascular disease (CVD) or multiple CVD risk factors, and randomized to target HbA <6.0% (42 mmol/mol; intensive) or 7.0-7.9% (53-63 mmol/mol; standard). Covariates included demographics, BMI, hemoglobin glycosylation index (HGI; observed minus expected HbA derived from prerandomization fasting plasma glucose), other biomarkers, history, and medications.

Results: The analysis identified four groups defined by age, BMI, and HGI with varied risk for mortality under intensive glycemic therapy. The lowest risk group (HGI <0.44, BMI <30 kg/m, age <61 years) had an absolute mortality risk decrease of 2.3% attributable to intensive therapy (95% CI 0.2 to 4.5, = 0.038; number needed to treat: 43), whereas the highest risk group (HGI ≥0.44) had an absolute mortality risk increase of 3.7% attributable to intensive therapy (95% CI 1.5 to 6.0; < 0.001; number needed to harm: 27).

Conclusions: Age, BMI, and HGI may help individualize prediction of the benefit and harm from intensive glycemic therapy.
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http://dx.doi.org/10.2337/dc17-2252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829969PMC
March 2018

Diabetes Mellitus Treatment Deintensification: When Well-Controlled Diabetes Mellitus Becomes Overcontrolled.

Circ Cardiovasc Qual Outcomes 2017 04;10(4)

From the Department of Veterans Affairs, Eastern Colorado Healthcare System, Denver (S.R.); Division of General Internal Medicine (S.R.) and Division of Geriatric Medicine (D.M.), Department of Medicine, University of Colorado School of Medicine, Aurora; Colorado Cardiovascular Outcomes Research Consortium, Denver (S.R., D.M.); and VA Eastern Colorado Geriatric Research Education and Clinical Center, Denver (D.M.).

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http://dx.doi.org/10.1161/CIRCOUTCOMES.117.003706DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477665PMC
April 2017

Risk of Developing Diabetes Among Refugees and Immigrants: A Longitudinal Analysis.

J Community Health 2016 Dec;41(6):1274-1281

Division of General Internal Medicine, Massachusetts General Hospital, 50 Staniford St, 9th Floor, Boston, MA, 02114, USA.

To determine the difference in risk of developing diabetes for refugees, immigrants, and American-born participants living in the same communities, and to explore potential mediators of that difference. Retrospective longitudinal cohort from January 1, 2003 and December 31, 2013. Refugees aged ≥18 years were matched in a 1:3 ratio by age, gender, and date of care initiation to (1) Spanish-speaking non-refugee immigrants, and (2) English-speaking controls receiving care in the same community health center. We used proportional hazards regression to estimate the risk of incident diabetes. We tested whether differences in education or baseline obesity mediated diabetes risk using counterfactual mediation analysis. We included 3174 participants. Among refugee participants, the most common countries of origin were Somalia (17.8 %), Iraq (16.7 %) and Bhutan (8.8 %). Diabetes incidence rate was 1.94, 1.91, and 1.22 cases per 100 person-years follow-up for refugees, immigrants, and controls, respectively. In adjusted models, both refugee (HR 2.08 95 % CI 1.32-3.30) and immigrant (HR 1.51 95 % CI 1.01-2.24) statuses were associated with increased diabetes risk compared with controls. Risk between refugees and immigrants did not differ (adjusted HR for refugees 1.37 95 % CI 0.91-2.06). In mediation analyses, educational attainment mediated 36 % (p = 0.007) of the difference in diabetes risk between refugees/immigrants and controls. Baseline obesity did not mediate difference in diabetes risk (proportion mediated 1 %, p = 0.84). Refugees and immigrants had significantly increased risk for diabetes, partially mediated by education. Education-based lifestyle interventions may be a promising strategy to prevent diabetes for these vulnerable patients.
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http://dx.doi.org/10.1007/s10900-016-0216-4DOI Listing
December 2016

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin.

Am J Hum Genet 2016 Jul 16;99(1):56-75. Epub 2016 Jun 16.

Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.
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http://dx.doi.org/10.1016/j.ajhg.2016.05.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005440PMC
July 2016

Incident Type 2 Diabetes Risk is Influenced by Obesity and Diabetes in Social Contacts: a Social Network Analysis.

J Gen Intern Med 2016 10 4;31(10):1127-33. Epub 2016 May 4.

Division of General Internal Medicine, Department of Medicine, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.

Background: Obesity and diabetes family history are the two strongest risk factors for type 2 diabetes (T2D). Prior work shows that an individual's obesity risk is associated with obesity in social contacts, but whether T2D risk follows similar patterns is unknown.

Objective: We aimed to estimate the relationship between obesity or diabetes in an individual's social contacts and his/her T2D risk. We hypothesized that obesity and diabetes in social contacts would increase an individual's T2D risk.

Design: This was a retrospective analysis of the community-based Framingham Offspring Study (FOS).

Participants: FOS participants with T2D status, height and weight, and at least one social contact were eligible for this study (n = 4797 at Exam 1). Participants' interpersonal ties, cardiometabolic and demographic variables were available at eight exams from 1971 to 2008, and a T2D additive polygenic risk score was measured at the fifth exam.

Main Measures: Primary exposures were T2D (fasting glucose ≥ 7 mmol/L or taking diabetes medications) and obesity status (BMI ≥ 30 kg/m(2)) of social contacts at a prior exam. Primary outcome was incident T2D in participants.

Key Results: Incident T2D was associated with having a social contact with diabetes (OR 1.32, p = 0.004) or with obesity (OR 1.21, p = 0.004). In stratified analyses, incident T2D was associated with diabetes in siblings (OR 1.64, p = 0.001) and obesity in spouses (OR 1.54, p = 0.0004). The associations between diabetes and obesity in social contacts and an individual's incident diabetes risk were stronger in individuals with a high diabetes genetic risk score.

Conclusions: T2D and obesity in social contacts, particularly siblings and spouses, were associated with an individual's risk of incident diabetes even after accounting for parental T2D history. Assessing risk factors in an individual's siblings and spouses can inform T2D risk; furthermore, social network based lifestyle interventions involving spouses and siblings might be a novel T2D prevention approach.
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http://dx.doi.org/10.1007/s11606-016-3723-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023597PMC
October 2016

'Someday it will be the norm': physician perspectives on the utility of genome sequencing for patient care in the MedSeq Project.

Per Med 2015;12(1):23-32

Center for Medical Ethics & Health Policy, Baylor College of Medicine, Houston, TX 77030, USA.

Aim: To describe practicing physicians' perceived clinical utility of genome sequencing.

Materials & Methods: We conducted a mixed-methods analysis of data from 18 primary care physicians and cardiologists in a study of the clinical integration of whole-genome sequencing. Physicians underwent brief genomics continuing medical education before completing surveys and semi-structured interviews.

Results: Physicians described sequencing as currently lacking clinical utility because of its uncertain interpretation and limited impact on clinical decision-making, but they expressed the idea that its clinical integration was inevitable. Potential clinical uses for sequencing included complementing other clinical information, risk stratification, motivating patient behavior change and pharmacogenetics.

Conclusion: Physicians given genomics continuing medical education use the language of both evidence-based and personalized medicine in describing the utility of genome-wide testing in patient care.
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http://dx.doi.org/10.2217/pme.14.68DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4306284PMC
January 2015

Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.

Nat Commun 2015 Jan 29;6:5897. Epub 2015 Jan 29.

1] The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA [2] The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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http://dx.doi.org/10.1038/ncomms6897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311266PMC
January 2015

Metabolic factors and genetic risk mediate familial type 2 diabetes risk in the Framingham Heart Study.

Diabetologia 2015 May 27;58(5):988-96. Epub 2015 Jan 27.

Division of General Internal Medicine, Department of Medicine, Harvard Medical School and Massachusetts General Hospital, 50 Staniford Street, 9th Floor, Boston, MA, 02114, USA.

Aims/hypothesis: Type 2 diabetes mellitus in parents is a strong determinant of diabetes risk in their offspring. We hypothesise that offspring diabetes risk associated with parental diabetes is mediated by metabolic risk factors.

Methods: We studied initially non-diabetic participants of the Framingham Offspring Study. Metabolic risk was estimated using beta cell corrected insulin response (CIR), HOMA-IR or a count of metabolic syndrome components (metabolic syndrome score [MSS]). Dietary risk and physical activity were estimated using questionnaire responses. Genetic risk score (GRS) was estimated as the count of 62 type 2 diabetes risk alleles. The outcome of incident diabetes in offspring was examined across levels of parental diabetes exposure, accounting for sibling correlation and adjusting for age, sex and putative mediators. The proportion mediated was estimated by comparing regression coefficients for parental diabetes with (β adj) and without (β unadj) adjustments for CIR, HOMA-IR, MSS and GRS (percentage mediated = 1 - β adj / β unadj).

Results: Metabolic factors mediated 11% of offspring diabetes risk associated with parental diabetes, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.96. GRS mediated 9% of risk, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.99.

Conclusions/interpretation: Metabolic risk factors partially mediated offspring type 2 diabetes risk conferred by parental diabetes to a similar magnitude as genetic risk. However, a substantial proportion of offspring diabetes risk associated with parental diabetes remains unexplained by metabolic factors, genetic risk, diet and physical activity, suggesting that important familial influences on diabetes risk remain undiscovered.
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http://dx.doi.org/10.1007/s00125-015-3498-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4393775PMC
May 2015

Do physicians think genomic medicine will be useful for patient care?

Per Med 2014;11(4):424-433

Section of General Internal Medicine, VA Boston Healthcare System, 150 South Huntington Avenue, 152-G, Boston, MA 02130, USA ; Division of General Medicine & Primary Care, Department of Medicine, Brigham & Women's Hospital, Boston, MA, USA ; Department of Medicine, Harvard Medical School, Boston, MA, USA.

Significant technological improvements over the last decade have led to a vast expansion in the understanding of the genomic architecture of human disease. However, the use of genomic information, so-called genomic medicine, in routine clinical care, has been slow in comparison to the growth in genomic discovery. The uptake of genomic technology into clinical practice will depend on physicians' perspectives of its utility in patient care. We review recent literature addressing physician attitudes regarding the usefulness and limitations of genomic testing. We conclude by proposing research areas to better understand the role physicians will play in the uptake of genomic information into clinical medicine.
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http://dx.doi.org/10.2217/pme.14.25DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4494677PMC
January 2014

Secreted transcription factor controls Mycobacterium tuberculosis virulence.

Nature 2008 Aug;454(7205):717-21

Department of Microbiology and Immunology, Program in Microbial Pathogenesis and Host Defense, University of California, San Francisco, 600 16th Street, Campus Box 2200, San Francisco, California 94143-2200, USA.

Bacterial pathogens trigger specialized virulence factor secretion systems on encountering host cells. The ESX-1 protein secretion system of Mycobacterium tuberculosis-the causative agent of the human disease tuberculosis-delivers bacterial proteins into host cells during infection and is critical for virulence, but how it is regulated is unknown. Here we show that EspR (also known as Rv3849) is a key regulator of ESX-1 that is required for secretion and virulence in mice. EspR activates transcription of an operon that includes three ESX-1 components, Rv3616c-Rv3614c, whose expression in turn promotes secretion of ESX-1 substrates. EspR directly binds to and activates the Rv3616c-Rv3614c promoter and, unexpectedly, is itself secreted from the bacterial cell by the ESX-1 system that it regulates. Efflux of the DNA-binding regulator results in reduced Rv3616c-Rv3614c transcription, and thus reduced ESX-1 secretion. Our results reveal a direct negative feedback loop that regulates the activity of a secretion system essential for virulence. As the virulence factors secreted by the ESX-1 system are highly antigenic, fine control of secretion may be critical to successful infection.
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http://dx.doi.org/10.1038/nature07219DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2862998PMC
August 2008
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