bluuebunny/crossref_metadata_2025_split huggingface dataset:
1636-P: Incidence and Predictors of Diabetes and Prediabetes among South Asians in the United States: The MASALA Study
Authors: UNJALI GUJRAL , VENKAT NARAYAN K.M. , KANDULA NAMRATHA R. , LIU KIANG , KANAYA ALKA M. 
Published: June 2019

South Asians are at high risk for type 2 diabetes (T2DM). There is a paucity of data on prediabetes and T2DM incidence and related predictors in U.S. South Asians. We estimated prediabetes and T2DM incidence after five years of follow-up in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study (n=758) and examined the associated correlates. We defined T2DM and prediabetes using the ADA criteria. Prediabetes included isolated impaired fasting glucose (iIFG), isolated impaired fasting glucose (iIGT), and combined IFG+IGT. Overall, 482 (64%) individuals progressed, either from normal glucose tolerance (NGT) to prediabetes/T2DM, or from prediabetes to T2DM (Table 1). In standardized logistic regression models controlled for age and sex, only hepatic fat attenuation (OR: 0.69 (95% CI: 0.55, 0.87), visceral fat mass area (OR: 1.34 (95% CI: 1.05, 1.71), and hypertension (OR: 2.28 (95% CI: 1.49, 3.49) were associated with any glycemic progression. Hepatic fat attenuation was associated with progression from prediabetes to T2DM (OR: 0.56 (95% CI: 0.38, 0.82), and visceral fat mass area was associated with progression from NGT to prediabetes/T2DM (OR: 1.72 (95% CI: 1.23, 2.41). South Asians in the U.S. have a high incidence of dysglycemia. Hepatic fat attenuation may be a factor in the conversion from prediabetes to T2DM, and prevention efforts should target ectopic fat reduction.

Disclosure
U. Gujral: None. K. Narayan: None. N.R. Kandula: None. K. Liu: None. A.M. Kanaya: None.

Funding
National Institutes of Health (R01HL093009, K24HL112827, UL1RR024131)
1638-P: Urinary Polycyclic Aromatic Hydrocarbon Concentrations and Risk of Diabetes Mellitus in Korean Adults
Authors: NAM YON JU , KIM SHIN-HYE 
Published: June 2019

Background: Polycyclic aromatic hydrocarbons (PAHs) are a group of environmental chemicals with aromatic rings and are generated by the incomplete combustion of organic materials. A few animal and occupational studies suggested a possible association between PAHs exposure and increased risk of diabetes mellitus.
Objectives: We aimed to investigate the associations of urine levels of PAHs with diabetes mellitus in Korean adults.
Methods: We examined cross-sectional data from the Korean National Environmental Health Survey (KoNEHS) 2012-2014. The study population consisted of 6478 adult subjects (≥20 years of age) from 400 sampling districts in South Korea. The urinary levels of 1-hydroxypyrene, 2-naphthol, 1-hydroxyphenathrene, and 2-hydroxyfluorene were measured in the study subjects. Analyses were adjusted for gender, age, BMI, household income, alcohol consumption, physical activity, urinary creatinine, and urinary cotinine.
Results: We observed a positive association between urinary PAHs and cotinine after adjusting for all covariates. A higher geometric mean value of urinary 2-naphthol was observed in subjects with diabetes mellitus compared with controls (2.67 vs. 2.24 μg/L). There was no significant difference in other urinary PAHs according to the presence of diabetes mellitus. According to the elevation of urinary 2-naphthol quartile, the multivariate-adjusted odds ratio (OR) of diabetes mellitus significantly increased in both male and female adults (P-for-trend &lt;0.05). Compared with subjects with urinary 2-naphthol in the lowest quartile, the OR (95% confidence interval) of diabetes mellitus in those in the highest quartile was 1.8 (1.24-2.63).
Conclusions: Urinary 2-naphthol levels were positively associated with diabetes mellitus in Korean general populations. Prospective studies are needed to determine a potential causal relationship between PAHs exposure and diabetes mellitus in human.

Disclosure
Y. Nam: None. S. Kim: None.
1644-P: Novel Subgroups of Prediabetes and Their Clinical Outcomes: A Data-Driven Analysis
Authors: ZOU XIANTONG , ZHU ZHANXING , LUO YINGYING , LI YUFENG , ZHOU XIANGHAI , JI LINONG 
Published: June 2019

The progression of prediabetes to diabetes and the reversion of them to NGT are highly heterogeneous. To develop a refined classification of prediabetes, we used data-driven K-means clustering in patients diagnosed with IGT and IFG according to WHO 1999 criteria in Pinggu Study (a prospective population-based survey for diabetes in suburban Beijing, n=628), NHANES III study (a cross-sectional population-based survey in the U.S., n=1532) and Beijing Prediabetes Reversion Program (BPRP, a RCT to evaluate the efficacy of lifestyle and/or pioglitazone on prediabetes reversion, n=1905). Based on five variables including HbA1c, BMI, age, HOMAIR and HOMAB, we identified four replicable clusters across all three datasets including high glucose group (HGG), lean group (LG), early-onset group (EOG) and insulin resistant group (IRG) (Figure). HRG had significant higher 1-year diabetes progression rate (15.4% in BPRP and 25.6% in Pinggu study) and the LG had the lowest diabetes progression rate (7.1% in BPRP and 11.1% in Pinggu Study). In BPRP, HGG treated with Intensive lifestyle plus pioglitazone had significant higher reversion rate to NGT and EOG treated with intensive life style plus placebo had least reversion rate compared to other treatment. Our study provides risk stratification for prediabetes and can potentially facilitate clinical decision, representing a first step towards precision management.

Disclosure
X. Zou: None. Z. Zhu: None. Y. Luo: None. Y. Li: None. X. Zhou: None. L. Ji: Advisory Panel; Self; AstraZeneca. Consultant; Self; AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb Company, Eli Lilly and Company, Merck KGaA, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi, Takeda Pharmaceutical Company Limited. Research Support; Self; AstraZeneca, Bristol-Myers Squibb Company, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Roche Pharma, Sanofi.

Funding
The Major Chronic Non-Communicable Disease Prevention and Control Research of China; Beijing Science and Technology Committee; National Natural Science Foundation of China
1648-P: The Association between Uric Acid Level and Mortality Risks in Diabetes Population in U.S.
Authors: CHEN PO-HSUN , LEE CHIA LIN , CHEN CHING-HSIEN 
Published: June 2019

Objective: Elevated serum uric acid (UA) level has been associated with increased coronary heart disease mortality. The optimal UA level in patients with diabetes remains uncertain. We compared the mortality risk across UA levels among adults with and without diabetes.
Methods: We analyzed data from adults aged &gt;18 years without coronary heart disease and chronic renal disease (n= 29,226) from the National Health and Nutrition Examination Survey (1999-2010) and the associated mortality data (up to December 2011). We used the Cox proportional hazards models to examine the risk of all-cause and cause-specific (cardiovascular disease [CVD] and cancer) mortality at different UA levels between adults with diabetes and without diabetes.
Results: Over a median follow-up of 6.6 years, 2,069 participants died (495 from CVD and 520 from cancers). Compared with nondiabetes adults with UA level of 5-7mg/dL (reference), the hazard ratios (HR) for all-cause mortality were significantly greater for adults without diabetes at UA levels of 7-9mg/dL (HR=1.39) and ≥9mg/dL (HR=2.31). In diabetes patients, HRs were 2.10 (95% CI 1.61, 2.73), 1.28 (95% CI 0.93, 1.77), 2.88 (95% CI 2.13, 3.89), and 2.65 (95% CI 1.18, 5.96) for UA &lt;5mg/dL, 5-7mg/dL, 7-9mg/dL, and ≥9mg/dL, respectively. Compared to reference, CVD mortality risk in diabetes participants were significantly higher at every UA category (HR=2.33, 2.24, 5.03, and 1.70 for UA &lt;5mg/dL, 5-7mg/dL, 7-9mg/dL, and ≥9mg/dL, respectively). In diabetes adults, the participants with UA 7-9mg/dL had higher risk than those with UA 5-7mg/dL (p=0.038). Regarding cancer mortality risk, no significant difference was found at different UA levels no matter with or without diabetes.
Conclusions: At UA level of &gt;7mg/dL, increased risk of all-cause and CVD mortality occurred in both diabetes and nondiabetes participants. Without accounting for the effect of glycemic control, our results support all-cause mortality risk in diabetes adults was lowest at UA level of 5-7mg/dL.

Disclosure
P. Chen: None. C. Lee: None. C. Chen: None.
165-OR: The Mechanisms by Which Adiponectin Reverses Insulin Resistance in High-Fat Diet Fed Mice
Authors: LI XIRUO , ZHANG DONGYAN , PERRY RACHEL J. , VATNER DANIEL F. , GOEDEKE LEIGH , ZHANG YE , SHULMAN GERALD I. 
Published: June 2019

Adiponectin has emerged as an antidiabetic adipokine, and a potential therapy to treat type 2 diabetes. However, the mechanism by which adiponectin improves insulin sensitivity remains unclear. To address this question, we examined the effects of a 2-week continuous infusion of globular adiponectin (gAcrp30) or saline (CON) on glucose and lipid metabolism in a high fat diet fed (HFD) mouse model. Whole-body and tissue-specific insulin action was assessed by a hyperinsulinemic-euglycemic clamp (HEC). gAcrp30-treated mice displayed reduced fasting plasma glucose and insulin concentrations (both P&lt;0.05 vs. CON) and increased glucose infusion rate (14 vs. 22 mg/(kg-min), P&lt;0.001) during the HEC reflecting increased whole-body insulin-sensitivity. Increased insulin sensitivity could be attributed to reduced endogenous glucose production (16.7 vs.14.2 mg/(kg-min), P&lt;0.05), increased glucose uptake in muscle (191 vs. 285 nmol/(kg-min), p=0.006) and adipose tissues (BAT: 112 vs. 217, WAT: 11 vs. 22 nmol/(kg-min), both P&lt;0.05) during the HEC. These improvements in liver and muscle insulin sensitivity were associated with ∼50% reductions in liver and muscle triglyceride (TAG) and ∼40% diacylglycerol (DAG) (both P&lt;0.01 vs. CON) content but no changes in hepatic ceramide content. Reduced tissue TAG/DAG content occurred independent of changes in WAT lipolysis, hepatic AMPK activation, ACC phosphorylation or mitochondrial oxidation. Reduced tissue DAG content was associated with decreased PKCε activation in liver and PKCθ activation in muscle and increased insulin signaling in liver, muscle and white adipose tissue.
Conclusion: Taken together these data support the hypothesis that adiponectin improves insulin sensitivity in liver and muscle of HFD fed mice by reducing ectopic lipid (DAG) content in these tissues leading to decreased nPKC activity and increased insulin signaling, and contrary to prior studies, is independent of changes in hepatic ceramide content.

Disclosure
X. Li: None. D. Zhang: None. R.J. Perry: Research Support; Self; AstraZeneca. D.F. Vatner: None. L. Goedeke: None. Y. Zhang: None. G.I. Shulman: Advisory Panel; Self; AstraZeneca, Janssen Research & Development, Merck & Co., Inc. Advisory Panel; Spouse/Partner; Merck & Co., Inc. Board Member; Self; Novo Nordisk A/S. Consultant; Self; Aegerion Pharmaceuticals, IMetabolic BioPharma Corporation, Longitude Capital, Nimbus Discovery, Inc., Staten Biotechnology B.V.

Funding
American Heart Association (19PRE34380268); National Institutes of Health (R01DK116774)
166-LB: Canagliflozin but Not Empagliflozin Activates AMPK and Suppresses Colon Cancer Cell Growth
Authors: YAGI TAKASHI , TANAKA TOMOHIRO , KUBOTA EIJI , KOYAMA HIROYUKI , GUO TINGTING , OGAWA KENTO , AOTANI DAISUKE , KATAOKA HIROMI 
Published: June 2019

Background: Recent increase in the relative proportion of cancer death in diabetic patients has become a major issue. A hypoglycemic agent, sodium-glucose cotransporter (SGLT) 2 inhibitor has attracted attention because of its potency in reducing cardiovascular risks. Several lines of evidence has emerged suggesting a potential anti-oncotic effect. Here we address potential effects of canagliflozin (Cana) on human colon cancer cell growth and underlying mechanisms and compared with empagliflozin (Empa).
Material and Methods: We examined the effects of Cana and Empa on 1) cell proliferation using colon cancer cell lines, SW480 and HCT116 by MTT assay, 2) DNA synthesis by flow cytometry-based analysis of bromodeoxyuridine (BrdU) uptake. We further examined 3) the expression of SGLT1 and 2 in these cells and 4) investigated molecules of signal transduction pathways with established roles in cancer cell growth such as AMPK, 4EBP1, mTOR by western blotting. Finally, we analyzed 5) time-dependent changes of metabolomic signatures after the treatment with Cana.
Results: While SGLT1 and 2 mRNA and protein expression was detected in both cell lines, Cana but not Empa significantly inhibited cell proliferation and in a dose-dependent manner. Cana suppressed BrdU positive cells and enhanced AMPK phosphorylation with a consequent suppression of 4EBP1 and mTOR activity. Metabolomic profiling revealed that, as a function of time, intermediate metabolites of glycolysis especially phosphoenolpyruvate was decreased with an acute rise in ADP and gradual decrease in ATP and GSSG.
Conclusion: We demonstrate that Cana deprives human colon cancer cells of energy and anti-oxidative capacity possibly through an inhibition of SGLT1-mediated glucose influx, and thereby activates AMPK and inhibits cancer cell growth. Our data herein suggest a potential beneficial effect of Cana in suppressing colon cancer progression especially in patients with diabetes.

Disclosure
T. Yagi: None. T. Tanaka: Research Support; Self; Japan Society for the Promotion of Science. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo Company, Limited, Kissei Pharmaceutical Co., Ltd., Kowa Pharmaceutical Europe Co. Ltd., Mitsubishi Tanabe Pharma Corporation, Novartis Pharmaceuticals Corporation, Taisho Toyama Pharmaceutical Co. Ltd., Takeda Pharmaceutical Company Limited. E. Kubota: None. H. Koyama: None. T. Guo: None. K. Ogawa: None. D. Aotani: None. H. Kataoka: None.
1668-P: The Impact of Ethnicity on Clinical Characteristics and Autoantibody Status at Clinical Onset of Type 1 Diabetes—From the ADDRESS-2 Study
Authors: WALKEY HELEN C. , KAUR AKAAL , GODSLAND IAN F. , WILLIAMS ALISTAIR J. , OLIVER NICK , JOHNSTON DESMOND G. , MISRA SHIVANI 
Published: June 2019

Introduction: The phenotype of type 1 diabetes (T1D) has been explored mainly in white populations. People of non-white ethnicity are reportedly less likely to be antibody positive, but phenotypic differences are not well characterised. We investigated ethnic group differences in the clinical characteristics and antibody (Ab) status at clinical onset of T1D.
Methods: We studied people of white European (WE), Asian (A) and black African/Caribbean (AC) ethnicity with clinically-assigned T1D, age ≥5 years, recruited ≤ 6 months after diagnosis, and with Abs (GADA, IA-2A and ZnT8A) measured by radioimmunoassay.
Results: Ethnic breakdown: WE n=1,997, A n=50, AC n=41. Median (IQR) ages were: WE 23(14-24), A 18(12-29), AC 26 (15-41) years p=0.007. Presentation with DKA was more common in AC (65%) than WE (42%) or A (53%) p=0.006; otherwise clinical presentation (polyuria/dipsia, weight loss, fatigue, symptom duration) was similar. Proportions with 0, 1 and ≥2 Abs differed by ethnicity: WE (15%, 24%, 61%); A (28%, 26%, 46%); AC (36%, 32%, 32%) p&lt;0.001. For Ab negative (0 Abs), ethnic groups differed in BMI (p=0.001) and presentation with DKA (&lt;0.001), but other characteristics, including daily insulin dose, were similar. For Ab positive (≥1 Ab), there were differences in parental history of diabetes p=0.02; otherwise ethnicity had no impact. Also, differences were seen in the frequency of IA-2A: WE (67%), A (53%), AC (50%) p=0.03 and ZnT8A: WE (60%), A (39%), AC (42%) p=0.01, but not GADA: WE (83%), A (94%) AC (92%) p=0.09.
Conclusion: Although clinical presentation of T1D was remarkably similar across ethnic groups, variations were found in the proportions with Ab positivity and frequencies of individual Abs. Antibody negativity was more common in non-white ethnic groups and the presence of &gt;1 Ab most common in white ethnicity. Practitioners should be alert to differences in phenotype according to antibody status that may impact classification in some ethnic groups.

Disclosure
H.C. Walkey: None. A. Kaur: None. I.F. Godsland: None. A.J. Williams: None. N. Oliver: Advisory Panel; Self; Roche Diabetes Care. Research Support; Self; Dexcom, Inc., Roche Diabetes Care. Speaker's Bureau; Self; Dexcom, Inc., Sanofi. D.G. Johnston: None. S. Misra: None.

Funding
Diabetes UK; JDRF
1673-P: The Neighborhood Deprivation Index and Provider Geocoding Identify Critical Catchment Areas for Diabetes Outreach Programs
Authors: WALKER ASHBY F. , HU HUI , CUTTRISS NICOLAS , HALLER MICHAEL J. , WANG C. JASON , ANEZ-ZABALA CLAUDIA , YABUT KATARINA , GURKA MATTHEW J. , MAAHS DAVID M. 
Published: June 2019

Extension for Community Health Outcomes (ECHO) programs have successfully empowered primary care providers (PCPs) to deliver advanced care to patients lacking access to subspecialists. In designing an ECHO type 1 diabetes (T1D) program in Florida and California, the Neighborhood Deprivation Index (NDI) was used in conjunction with geocoding of primary care providers (PCPs) and endocrinologists in each state to concurrently identify areas with low endocrinology provider density and high health risk/poverty areas. The NDI measures many aspects of poverty proven to be critical indicators of community health outcomes such as cardiometabolic risk, adverse birth outcome, and substance use. Data from the 2013-2017 American Community Survey (ACS) 5-year estimates were used to create census tract- and block group-level NDI maps for California and Florida. In addition, geocoding and 30-minute drive-time buffers were performed using publicly available provider directories for PCPs and endocrinologists in both states by Google Geocoding API and TravelTime Search Application Programming Interface (API). Based on these findings, we defined high need catchment areas as census tracts or census block groups with: 1) more than a 30-minute drive to the nearest endocrinologist, but within a 30-minute drive to the nearest PCP; 2) an NDI in the highest quartile; and 3) a population above the median (5,199 for census tracts, and 1,394 for census block groups). Out of the 12,181 census tracts and 34,490 census block groups in California and Florida, we identified 57 tracts and 215 block groups meeting these criteria as high need catchment area. Geospatial analysis provides an important precursory methodologic step to effectively focus outreach efforts in diabetes program development. The integration of the NDI with geocoded provider directories enables more cost-effective and targeted interventions to reach the most vulnerable populations living with T1D.

Disclosure
A.F. Walker: None. H. Hu: None. N. Cuttriss: None. M.J. Haller: Advisory Panel; Self; Pancreum, SAB Biotherapeutics. C. Wang: None. C. Anez-Zabala: None. K. Yabut: None. M.J. Gurka: None. D.M. Maahs: Advisory Panel; Self; Novo Nordisk Inc. Consultant; Self; Abbott, Sanofi. Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.

Funding
The Leona M. and Harry B. Helmsley Charitable Trust
1680-P: Impact of Diabetic Environment on Sclerostin Levels in Adult Patients with Type 1 Diabetes Mellitus
Authors: BARMPA ELEFTHERIA , BARGIOTA ALEXANDRA 
Published: June 2019

Introduction: The aim of this study is to examine sclerostin levels in uncomplicated patients T1DM and its correlation with bone metabolism.
Methods/Design: We studied 118 (M/F:53/65) uncomplicated T1DM patients (Group-D) aged &gt;20 and &lt;50 years, diabetes duration&gt;5 years and 50 healthy controls matched for age, sex and body mass index (BMI)(Group-C). In both groups Sclerostin, β-crosslaps, TP1NP and HbA1c were measured and the mean HbA1c of the last 5 years was calculated (HbA1c-5). BMD at lumbar spine (LS), femoral neck (FN) and total hip (HIP) by dual energy X-ray absorptiometry (DXA) was measured.
Results: In Group-D, mean age was 35.4±10.3years, age of diagnosis was 19.2±9.8years, disease duration was 16.6±9.5years, mean HbA1c and HbA1c-5 were 7.8±1.4%, 7.4±1.1, respectively. Z-scores were lower in the Group-D compared to controls in all the 3 regions [(LS: p=0.009), (FN: p=0.000), (HIP: p=0,000)]. Lower sclerostin levels, but not statistically significant, were observed in group-D compared to group-C (D: 19.0±11.6 vs. C: 23.3±13.6, p=0.059). No difference was found between sexes. Β-CrossLaps was significantly lower in the D-group (D: 198.9±19.6 vs. C: 262.5±53.6, p=0.001), but no significant difference was observed in TP1NP (D: 50.34±30.98 vs. C: 58.47±30.74, p=0.256) between the two groups. Regression analysis showed: a negative correlation between sclerostin and bone markers (βCrosslaps: r=-0.0288, p=0.003, TP1NP: r=-0.0255, p=0.009). No correlation was observed between sclerostin and glycemic control. A positive correlation was found between sclerostin and patients’ age (r=0.490, p=0.000) and between sclerostin and BMD in both LS and FN (LS: r=0.311, p=0.001, FN: r=0.183, p=0.049).
Conclusion: Sclerostin levels were lower, but not statistically significant, in T1DM patients compared to controls. Sclerostin was positively correlated with BMD and negative correlation was found with both bone turnover markers. No correlation was found with the metabolic control.

Disclosure
E. Barmpa: None. A. Bargiota: None.
1682-P: A Rule-Based Discovery of Gene-Environment Interactions on Risk of Islet Autoimmunity: TEDDY Study
Authors: LYNCH KRISTIAN F. , FENG TIANSHU , QIAN XIAONING , HAGOPIAN WILLIAM , LERNMARK ÅKE , ZIEGLER ANETTE , TOPPARI JORMA , REWERS MARIAN , SHE JIN-XIONG , SCHATZ DESMOND , AKOLKAR BEENA , KRISCHER JEFFREY , HUANG SHUAI , VEHIK KENDRA 
Published: June 2019

Type 1 diabetes (T1D) associated genetic factors affect risk of islet autoantibodies (IA), but non-genetic factors show conflicting associations. Mechanistic interactions may play a role. Under a sufficient-component causal framework, we used a rule-based discovery method to investigate if genetic factors, early environment and first appearing IA (IAA or GADA) act synergistically to mark different disease mechanisms.
TEDDY children (n=7512) were followed until age 6 years for IA development (n=518). Rules differentiating IAA-first (n=258) from GADA-first (n=243) were identified by a rule discovery algorithm (RuleFit) and examined in logistic regression models. Rule components were assessed for additive interaction on IAA-first and GADA-first separately using Relative Excess Risk due to Interaction (RERI) calculated from Cox regression models.
Here we show 2 of the 5 top rules, the first involving the child having CTLA4-AA (rs231775) and mother with a gestational respiratory but no skin infection (rule1, OR=5.6, 95% CI=2.6-12.0, p&lt;0.0001); the second involving child having BACH2-T (rs3757247) and sufficient weight gain by age 3 months (rule2, OR=0.47, 95% CI=0.30-0.72, p&lt;0.0001). Each differentiated IAA from GADA, and rule components showed interaction on absolute risk of IAA-first or GADA-first.
Figure 1. Gene-environmental interaction with first appearing IA may mark different mechanisms.

Disclosure
K.F. Lynch: None. T. Feng: None. X. Qian: None. W. Hagopian: Research Support; Self; Novo Nordisk A/S. Å. Lernmark: None. A. Ziegler: None. J. Toppari: None. M. Rewers: None. J. She: None. D. Schatz: None. B. Akolkar: None. J. Krischer: None. S. Huang: None. K. Vehik: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention; JDRF; University of Florida (UL1TR000064); University of Colorado (UL1TR001082)