bluuebunny/crossref_metadata_2025_split huggingface dataset:
1395-P: Characteristics of Patients with Type 2 Diabetes and MetALD—Insight into a New Entity
Authors: BRIL FERNANDO 
Published: June 2024

In 2023 nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease (MASLD). A new entity was also defined: metabolic and alcohol related/associated liver disease (MetALD), corresponding to patients with MASLD with moderate alcohol consumption. In this study, we assessed the clinical and hepatic characteristics of patients with T2D with MetALD vs. MASLD.
Adult patients from NHANES 2017-2020 with complete data on transient elastography (TE) and alcohol intake were included. Diabetes was defined based on fasting plasma glucose, A1c, or prior history. Patients with secondary causes of liver steatosis were excluded. MASLD was defined as a controlled attenuation parameter (CAP) ≥288 dB/m. MetALD was defined based on CAP and self-reported alcohol use (i.e., females: 140-350 mg weekly and males: 210-420mg weekly).
Compared to MASLD (n=760), patients with T2D and MetALD (n=19; 2.4%) were younger (53 ± 15 vs. 59 ± 13 years, p=0.04) and predominantly male (89 vs. 53%, p=0.002). However, there were no significant differences in race or metabolic parameters, such as BMI (35.3 ± 9.5 vs. 34.6 ± 7.1 kg/m2, p=0.71), A1c (7.4 ± 2.6 vs. 7.4 ± 1.6%, p=0.91), triglycerides (p=0.72), HDL (p=0.90), or mean blood pressure (p=0.26). Despite metabolically similar, patients with MetALD had higher plasma AST (27 ± 9 vs. 22 ± 13, p=0.002), ALT (38 ± 23 vs. 27 ± 19, p=0.01), and GGT (p=0.01). Liver fibrosis by TE (7.9 ± 5.1 vs. 7.6 ± 5.2 kPa, p=0.82) and fat accumulation by CAP (353 ± 35 vs. 341 ± 33 dB/m, p=0.14) were similar between MASLD and MetALD.
Conclusions: MetALD represents a small percentage of patients with hepatic steatosis and T2D. Their metabolic profile is similar to MASLD patients, and despite higher liver biochemistries (i.e., ALT, AST, GGT), liver fibrosis and fat accumulation by imaging were similar in both groups. Thus, the clinical impact of this new definition in T2D is unclear. Future research is needed to determine if patients with MetALD behave similarly to patients with MASLD.

Disclosure
F. Bril: Consultant; Novo Nordisk.
1396-P: Association between COVID-19 Infection and Incident Diabetes in Two Distinct Cohorts—A Nationwide Commercial Claims Database and a Regional Academic Medical Center
Authors: LACY MARY E. , SMITH AARON P. , HAMMERSLAG LINDSEY R. , HEIER KORY , FIELDS ALICIA B. , TALBERT JEFFERY , FOWLKES JOHN , FISHER SIMON J. , KERN PHILIP A. 
Published: June 2024

Background & Objective: The risk of new onset diabetes following infection with COVID-19 was contrasted in two distinct cohorts.
Methods: Using Merative MarketScan Commercial Claims database (MarketScan) and electronic health records from University of Kentucky HealthCare (UKHC), we created three cohorts in each database: 1) a COVID-19 infected cohort, 2) a contemporaneous cohort of individuals without COVID-19 infection, and 3) a historic pre-COVID-19 cohort (Table 1). Diabetes incidence rates and hazard ratios were contrasted between the COVID-19 cohort and two control cohorts (no-COVID & pre-COVID).
Results: Compared to the commercial database, diabetes prevalence was higher in UKHC database, reflecting an objectively sicker population (higher comorbidity index and increased hospitalizations). In both databases, diabetes incidence rates and hazard ratios were significantly higher in the COVID cohort (Table 1), compared to either pre-COVID or non-COVID cohorts.
Conclusions: Both databases demonstrate that COVID-19 was associated with 2-3-fold increased rate of incident diabetes. However, as compared to an academic medical center with a sicker patient population, relatively healthier patients in the commercial data set had lower incidence of COVID-19 associated diabetes.

Disclosure
M.E. Lacy: None. A.P. Smith: None. L.R. Hammerslag: None. K. Heier: None. A.B. Fields: None. J. Talbert: None. J. Fowlkes: None. S.J. Fisher: None. P.A. Kern: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health (R01DK124626)
1399-P: Exploring Polycystic Ovary Syndrome and Leucine—A Bidirectional Mendelian Randomization Study
Authors: CAI MEILI , LU JIAYI , DILIMULATI DILIQINGNA , ZHANG YUQIN , CHEN HAIBING , QU SHEN , ZHANG MANNA 
Published: June 2024

Background: Polycystic ovary syndrome (PCOS) has a certain genetic predisposition. Previous observational studies have reported alterations in the amino acid profile among women with PCOS, yet causality remains unclear. Our study aims to elucidate the causal relationship through bidirectional Mendelian randomization (MR).
Methods: Leveraging genome-wide association studies (GWAS) data from a European lineage, encompassing 1,400 blood metabolisms, a two-sample MR study was conducted to assess the causal association between PCOS and Leucine. Five models, including inverse variance weighted model (IVW), weighted median estimator model (WME), weighted model-based method (WM), and MR-Egger regression model (MER), estimated causal associations. The leave-one-out sensitivity test, MR-PRESSO, and Cochran’s Q test assessed IVs heterogeneity and pleiotropy.
Results: We found 12 metabolites (8 risk and 3 protective) that showed suggestive associations with PCOS risk. The protective metabolites included Leucine, Isovalerylcarnitine, and hydroxytryptophan. The primary IVW method revealed a negative association between genetically determined PCOS and Leucine levels (OR&lt;0.001, 95%CI: 0.000-0.295, P= 0.018). There was no evidence of pleiotropy by the MR-Egger regression intercept or MR-PRESSO global test (MR-Egger intercept = 0.124, Global test P= 0.637). Multiple metabolic pathways were implicated, including amino acid metabolism and androgen synthesis.
Conclusion: Our MR study underscores a negative correlation between Leucine levels and increased PCOS risk. Identified metabolic products and pathways can serve as biomarkers for clinical screening and prevention, offering insights for future mechanistic exploration and drug target selection. Further observational studies and clinical trials are imperative for comprehensive understanding and validation.
Keywords: Leucine; amino acid; Mendelian randomization; polycystic ovary syndrome; blood metabolism

Disclosure
M. Cai: None. J. Lu: None. D. Dilimulati: None. Y. Zhang: None. H. Chen: None. S. Qu: None. M. Zhang: None.

Funding
National Key R&D Program of China (No.2018YFC1314100); National Nature Science Foundation of China (No. 82170861 and No.81970677); Clinical Research Plan of SHDC (No. SHDC2020CR1017B).
14-OR: Autonomous Artificial Intelligence Diabetic Eye Exams Mitigates Disparities in Screening Completion for Youth
Authors: PATEL DHRUVA , BROMBERGER LEE A. , PARIMI NEHA , BROWN ELIZABETH A. , LIU ALVIN , LEHMANN HAROLD , ABRÀMOFF MICHAEL D. , WOLF RISA M. 
Published: June 2024

Diabetic retinal disease (DRD) is a complication of diabetes mellitus that can lead to vision loss; early detection through screening and treatment can prevent this. Few individuals with diabetes meet recommended DRD screening guidelines, and racial/ethnic minority youth are even less likely to undergo recommended screening. We sought to determine if implementing point of care (POC) autonomous artificial intelligence (AI) screening could mitigate disparities in diabetic eye exam completion. In ACCESS2, a preregistered prospective pre-post study design, youth with type 1(T1D) and type 2 diabetes (T2D) meeting American Diabetes Association criteria for needing a diabetic eye exam underwent POC autonomous AI diabetic eye exams at routine diabetes clinic visits. Completion rates of diabetic eye exams were compared prior to and after implementation of autonomous AI. A total of 380 youth with T1D (71.1%) and T2D (28.9%) were enrolled, mean age 15.2y, 46.8% Non-Hispanic (NH) White, with mean duration of diabetes of 6.0y, and median hemoglobin A1c of 8.1%. A greater percentage of NH White participants reported any prior diabetic eye exam (81.6 v 62.0%, p&lt;0.001) compared to non-white and Hispanic participants. Multivariable analysis demonstrated that the strongest predictor for prior eye exam was diabetes duration. After undergoing POC autonomous AI diabetic eye exams, completion rates were 98% among non-white and Hispanic participants, and 99% among white participants. Introducing autonomous AI at the point of care enhances the accessibility and completion rates of diabetic screening eye exams, and promotes health equity for minority youth with diabetes.

Disclosure
D. Patel: None. L.A. Bromberger: None. N. Parimi: None. E.A. Brown: None. A. Liu: None. H. Lehmann: None. M.D. Abràmoff: Board Member; Digital Diagnostics. Stock/Shareholder; Digital Diagnostics. Other Relationship; Digital Diagnostics. R.M. Wolf: Research Support; Dexcom, Inc., Boehringer-Ingelheim, Novo Nordisk.

Funding
National Eye Institute (R01EY033233-03)
1424-P: Cumulative TyG Index—A Noninvasive Measure to Assess the Risk of Hyperuricemia
Authors: WU YIWEI , CHEN YAN 
Published: June 2024

Objective: The aim of this study is to investigate the relationship between hyperuricemia risk and changes in the Triglyceride-Glucose (TyG) index among middle-aged and elderly Chinese individuals.
Methods: Baseline demographic, health, and physical examination data, along with blood samples, were collected from participants in both CHARLS Wave 1 and Wave 3. The TyG index was calculated, and participants meeting the inclusion criteria were grouped into four quartiles based on their cumulative TyG index. Independent factors influencing hyperuricemia were identified through the use of univariate and multivariate Cox regression models, with the lowest TyG quartile serving as the reference point. The correlation between hyperuricemia risk and cumulative TyG index was assessed using restricted cubic spline regression. Subgroup and interaction analyses were also carried out.
Results: A total of 5,600 participants (2,438 men and 3,162 women) with a median age of 57 years were included in this study. When the cumulative TyG index was less than 34.38, the risk of hyperuricemia was significantly decreased as the cumulative TyG index was reduced. Conversely, when the cumulative TyG index exceeded 34.38, the risk of hyperuricemia was seen to increase slowly with a higher cumulative TyG index. Subgroup analyses indicated that the cumulative TyG index increased the risk of hyperuricemia in various subgroups, including age, gender, hukou, education level, smoking, hypertension, body mass index (BMI), and WC. High cumulative TyG index was found to be more likely to raise the risk of hyperuricemia in individuals with low WC (&lt; 85 cm for males, &lt; 80 cm for females).
Conclusion: In this longitudinal study of middle-aged and elderly Chinese individuals, independent risk factors for hyperuricemia were found to include cumulative TyG index, male gender, hypertension, DBP, WC, and Cr. The cumulative TyG index, as a straightforward measure, was demonstrated to be a valuable tool for the evaluation of hyperuricemia risk.

Disclosure
Y. Wu: None. Y. Chen: None.

Funding
Natural Science Foundation of Jilin Province of China (YDZJ202301ZYTS074)
1460-P: Antibody+ (Ab+) Individuals with Marked Metabolic Heterogeneity at Screening Have Similar Evolution in the Progression to Type 1 Diabetes (T1D) with Converging Metabolic Status
Authors: SIMS EMILY K. , JACOBSEN LAURA M. , ISMAIL HEBA M. , REDONDO MARIA J. , NATHAN BRANDON M. , SOSENKO JAY 
Published: June 2024

Introduction: We asked if marked OGTT metabolic heterogeneity at screening persists at T1D diagnosis.
Methods: Multiple Ab+ TrialNet Pathway to Prevention participants (n=364) who had diagnostic OGTTs ≥1 yr after screening OGTTs were stratified by median fasting glucose x fasting C-peptide (fgxfp; basic metabolic component of C-peptide HOMA-IR). Glucose and C-peptide response curves (shapes from mean OGTT glucose and C-peptide at 30, 60, 90 and 120 min; GCRCs) were derived from OGTTs at baseline and diagnosis.
Results: The fgxfp group&gt;median (Figure: blue) had much higher baseline AUC C-peptide (p&lt;0.001), indicated by the wider shape and rightward location of their GCRC. They subsequently had upward and leftward GCRC movement from baseline to diagnosis vs. mostly upward movement for the group

Disclosure
E.K. Sims: Consultant; Sanofi. Board Member; American Diabetes Association. Other Relationship; American Diabetes Association, Medscape. Consultant; DRI. L.M. Jacobsen: Advisory Panel; Insulet Corporation. H.M. Ismail: Consultant; Sanofi, Rise Therapeutics. M.J. Redondo: None. B.M. Nathan: None. J. Sosenko: None.
1474-P: Cross-Sectional and Longitudinal Relationships between Detailed Family History (FH) of Type 2 Diabetes Mellitus (T2DM), Hypertension (HT), and Dyslipidemia (DL) and Prevalence of Each Disorder
Authors: IKEDA IZUMI , FUJIHARA KAZUYA , TAKEDA YASUNAGA , HATTA MARIKO , WU SIJIA , KODAMA SATORU , MORI YASUMICHI , KADOWAKI TAKASHI , YAMAMOTO-HONDA RITSUKO , ARASE YASUJI , SONE HIROHITO 
Published: June 2024

A FH of T2DM, HT, and DL are known risk factors; however, few studies have compared the impact of a FH of the 3 diseases in the same population. We examined the impact of a detailed FH of these conditions (i.e., in fathers, mothers, siblings and grandparents) on their prevalence and incidence in the study population. Data on 41,931 participants who underwent health checkups were examined and the results of a logistic regression and (Cox regression model in the same cohort were examined. Results of the cross-sectional study showed that odds ratios increased with the degree of a positive FH for all three diseases. Furthermore, in T2DM, the group with a three-generation positive FH was approximately 20 times larger than the control group which had no FH (Figure). In the longitudinal study, FH had a strong influence on the incidence of T2DM, HT, and DL, in that order, with a hazard ratio of 2.40 (1.93-2.98) for T2DM. A detailed FH was extremely useful for both quantitative screening for each disease and predicting the incidence of the three diseases, especially T2DM, for which a high risk was indicated in multiple generations with overlapping of positivity for a particular disease.

Disclosure
I. Ikeda: None. K. Fujihara: None. Y. Takeda: None. M. Hatta: None. S. Wu: None. S. Kodama: None. Y. Mori: None. T. Kadowaki: None. R. Yamamoto-Honda: None. Y. Arase: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.
1480-P: TOPMed Metabolomics Association Analysis of Cardiovascular Disease in Participants with Type 2 Diabetes
Authors: ZHANG YIXIN , DICORPO DANIEL A. , GOODARZI MARK O. , GUO XIUQING , HAESSLER JEFFREY , HANSON PAUL A. , KOOPERBERG CHARLES L. , NGUYEN NGOC QUYNH H. , REINER ALEX , SARNOWSKI CHLOE , SEVILLA-GONZALEZ MAGDALENA , TAYLOR KENT , YU BING , DUPUIS JOSÉE , MANNING ALISA , MEIGS JAMES B. , LIU CHING-TI 
Published: June 2024

Type 2 diabetes (T2D) is a prominent risk factor for cardiovascular diseases (CVD). People with T2D are twice as likely to develop heart disease or all-type stroke compared to people without T2D, though the reason behind this excess risk remains unclear. To better understand the molecular mechanisms underlying CVD in T2D, we compared the metabolomics profiles of T2D participants with or without CVD event. Using LC/MS-based metabolite data from the Trans-Omics for Precision Medicine (TOPMed) program, we collected 522 blood metabolite level measurements common to 1356 T2D participants across three TOPMed participating cohorts. We compared metabolite levels in CVD cases that occurred after T2D, versus T2D without CVD at the time of metabolite measurement. We performed cross-sectional pooled association analysis for each metabolite using a mixed effects linear model, with log-transformed and standardized metabolite level as the outcome and CVD event as the predictor, adjusting for age, sex, study population, and self-reported race/ethnicity, accounting for relatedness using a kinship matrix and a correlation-adjusted Bonferroni correction alpha level of 3.0x10-4 to define significant associations.
We identified 15 significant associations, where CVD is negatively associated with five lipids while positively associated with ten organic acids. We also replicated the effect size direction at a statistically significant level for nine organic acids in a separate TOPMed cohort with 1823 T2D participants. Most of the acids, such as gluconate, ADMA and cystine, have been previously reported as risk factors of CVD. 1-methyladenosine, our novel finding, could be a potential biomarker for CVD in T2D individuals.
Our results established metabolite associations with prevalent CVD in T2D in TOPMed. These associations will pave the way for future mechanistic studies exploring the potential utility of metabolites as therapeutic targets specific for T2D individuals at risk for CVD.

Disclosure
Y. Zhang: None. D.A. DiCorpo: None. M.O. Goodarzi: Advisory Panel; Nestlé Health Science, Organon. X. Guo: None. J. Haessler: None. P.A. Hanson: None. C.L. Kooperberg: None. N.H. Nguyen: None. A. Reiner: None. C. Sarnowski: None. M. Sevilla-Gonzalez: Research Support; Novo Nordisk Foundation. K. Taylor: None. B. Yu: None. J. Dupuis: None. A. Manning: None. J.B. Meigs: None. C. Liu: None.

Funding
National Institute of Health (NHLBI R01 HL151855); National Institute of Health (NHLBI UM1 DK078616)
1481-P: Type 2 Diabetes Is Causally Associated with Increased Risk of Pulmonary Tuberculosis—A Mendelian Randomization Study
Authors: LEE HYUNSUK , PARK SEHOON , CHOI JAEWON , PARK JONGSEOK , LEE JEONGEUN , KIM JONG-IL , SOO PARK KYONG , HEON KWAK SOO 
Published: June 2024

Tuberculosis (TB) ranked as the second leading cause of mortality from infectious disease after COVID-19 in 2022, resulting in the loss of 1.3 million lives worldwide. Type 2 diabetes (T2D) is one of five risk factors of TB and an estimated 370,000 new cases were attributable to T2D in 2020. However, whether T2D is causally associated with TB is largely unknown. We aimed to infer causal relationship between T2D and pulmonary TB using a two-sample Mendelian randomization (MR) framework.
We conducted a MR analysis in the East Asian population, where pulmonary TB is endemic. Eighteen independent genome-wide significant variants of T2D from the meta-analysis of the Korean Genome and Epidemiology Study and the Taiwan Biobank (N=135,387, F-statistics=70.2) were used as instrumental variables for T2D. Outcome data for genome-wide association analysis of pulmonary TB was obtained from the Biobank Japan (N=212,453).
Summary-level MR analysis showed that higher genetic risk for T2D was significantly associated with higher risk for pulmonary TB (beta=0.324, P=3.4×10-5). This association was also significant in multiple sensitivity analyses (MR-Egger P=0.046; weighted median P=8.9×10-4; weighted mode P=0.023; MR-PRESSO P=6.7×10-4; MR-RAPS; P=9.9×10-4). Absence of horizontal pleiotropy was supported via the MR-Egger intercept test (P=0.36). Multivariable MR analysis showed that T2D’s causal effect on pulmonary TB was independent of smoking, alcohol intake, body mass index and other cardiometabolic traits. Higher genetic risk for HbA1c was also significantly associated with increased risk for pulmonary TB (43 non-erythrocytic variants, beta=0.604, P=0.029). However, genetic risk for fasting glucose showed concordant directionality but did not reach statistical significance (beta=0.266, P=0.114).
Genetically predicted T2D is significantly associated with higher risk of pulmonary TB. This MR analysis supports the causal predisposition of T2D to pulmonary TB.

Disclosure
H. Lee: None. S. Park: None. J. Choi: None. J. Park: None. J. Lee: None. J. Kim: None. K. Park: None. S. Kwak: Employee; SNUH Venture.
1486-P: Role of HLA Class I Gene Alleles and Haplotypes in Type 1 Diabetes in Kuwaiti Children
Authors: DASHTI MOHAMMED H. , ZUBBAIR MALIK MD. , NIZAM RASHEEBA , JACOB SINDHU , ALKANDARI HESSA , ALOZAIRI EBAA S. , THANGAVEL ALPHONSE T. , ALMULLA FAHD 
Published: June 2024

Introduction & Objective: HLA class I genes have a role in influencing immune response and self-tolerance as they bind and present antigens to T cells. Allelic variations of these genes are associated with multifactorial autoimmune conditions including type 1 diabetes (T1D) and show variability across different ethnic groups and populations. Additionally, the amino acid variations of these genes may affect the binding and immunogenicity of insulin peptide.
Methods: We performed an association study of classical HLA class I genes between Kuwaiti T1D children (95 individuals) and adult controls (150 individuals) groups using Next-generation sequencing dataset.
Results: Significant associations were identified for alleles at HLA-A and HLA-C genes, including A*02:01 and C*07:01 were both conferred high risk for T1D. The A*24:02~B* 08:01~C*07:02 haplotype was significantly associated with the risk of developing T1D. Furthermore, we identified significant 33 amino acid positions at HLA-B and HLA-C genes that were both predisposing and protective against T1D.
Conclusion: Our results suggest that HLA class I genes and their allelic and amino acid variations play a role in modulating the risk of T1D and may have implications for disease risk management and genetic counseling in the Kuwaiti population.

Disclosure
M.H. Dashti: None. M. Malik: None. R. Nizam: None. S. Jacob: None. H. Alkandari: None. E.S. Alozairi: None. A.T. Thangavel: None. F. Almulla: None.

Funding
Kuwait Foundation for the Advancement of Sciences.
1487-P: Obesity Induces Metabolic Dysfunction in Adipose Tissue T-Cells
Authors: GUAK HANNAH , LUMENG CAREY N. 
Published: June 2024

Individuals with obesity or diabetes often have impaired immune responses to infection despite elevated systemic inflammation. T cells are essential for controlling adaptive immune responses, and during chronic obesity, adipose tissue T (ATT) cells display features of exhaustion, which are characterized by impaired activation and cytokine production. How ATT cell exhaustion is generated is not well understood. We hypothesized that mitochondrial dysfunction leads to the loss of effector function in obese ATT cells. Flow cytometry-based assays were used to evaluate the effect of long-term diet-induced obesity in mouse adipose tissue. Mitochondrial dyes in conjunction with cell surface markers revealed dramatic decreases in mitochondrial mass and membrane potential by both CD8+ and CD4+ T cell populations in white adipose tissue, but not in the spleen, as early as 2 weeks of high-fat diet feeding. In addition, we performed SCENITH, an assay that determines the bioenergetic profiles of cells based on the high energetic cost of protein translation. Results from this assay showed that obese ATT cells have reduced glycolytic and mitochondrial metabolism, suggesting they have diminished metabolic activity overall. We have previously discovered that macrophages in adipose tissue of diabetic humans have induced genes associated with glucocorticoid (GC) exposure, which is in line with literature demonstrating elevated GC levels in obese adipose tissue. Our preliminary data suggest that GC receptor signaling may contribute to mitochondrial impairment, as treatment of the white adipose stromal vascular fraction with synthetic GC reduces mitochondrial mass and membrane potential in ATT cells. Overall, we have observed ATT cells experience loss of mitochondria and metabolic activity with diet-induced obesity and GC treatment. These findings will help expand understanding of the role of ATT cells in metabolic health and immunity.

Disclosure
H. Guak: None. C.N. Lumeng: None.

Funding
American Diabetes Association (4-24-PDF-81); National Institutes of Health (R01DK090262); National Institutes of Health (T32DK101357)