bluuebunny/crossref_metadata_2025_split huggingface dataset:
1968-LB: Early Prediction of Gestational Diabetes Mellitus Using Electronic Health Records and Machine Learning
Authors: GERMAINE MARK A. , O'HIGGINS AMY C. , HEALY GRAHAM , EGAN BRENDAN 
Published: June 2024

Introduction: The objective of this study is to assess the efficacy of machine learning models in gestational diabetes mellitus (GDM) prediction using electronic health record (EHR) data collected in the first trimester.
Methods: Data were extracted from The Coombe Hospital EHRs, Dublin, spanning from 2018-2022. The year 2020 was excluded due to COVID-19-related deviations from usual screening practices. We employed four machine learning models—Random Forest, XGBoost, Logistic Regression and Explainable Boosting Machine—evaluating them using receiver operating characteristic (ROC) curve and average precision (AP). Models were trained on data within the EHRs collected during the first prenatal visit (8-14 weeks).
Results: 27,500 pregnancies and 3,100 GDM cases were analyzed post-processing. Logistic Regression consistently showed high performance (full feature set ROC AUC = 0.821, AP = 0.39; top 13 features ROC AUC = 0.818, AP = 0.39; first pregnancy only ROC AUC = 0.826, AP = 0.38). Other models demonstrated varying degrees of performance, some slightly decreasing when reducing features or considering only the first pregnancy.
Conclusion: Logistic regression appears to match or better the performance of more sophisticated machine learning models when predicting GDM using data from EHRs. This has the added benefit of easily explainable models for healthcare practitioners and stakeholders.

Disclosure
M.A. Germaine: None. A.C. O'Higgins: None. G. Healy: None. B. Egan: None.

Funding
This work has emanated from research supported in part by a grant from Science Foundation Ireland (18/CRT/6183).
1991-LB: Triglyceride–Glucose Index Is an Effective Tool for Assessing Glycemic Control in Asian Indians with Type 2 Diabetes
Authors: PRADEEPA RAJENDRA , JHA VINITAA , THYPARAMBIL ARAVINDAKSHAN PRAMODKUMAR , WAGHDHARE SWATI , MOHAN VISWANATHAN , CHAMBERS JOHN , MOHAN ANJANA RANJIT 
Published: June 2024

Introduction & Objective: Glycated hemoglobin (HbA1c) may not accurately reflect glycemic control in certain conditions like hemoglobinopathy, hemolytic anemia, or acute blood loss. There is a need for alternative tools for assessing glycemic control, particularly in India, where high costs and unavailability of standardized assays make widespread use of HbA1c challenging. We attempted to evaluate the efficacy of the Triglyceride-glucose (TyG) index, as a cost-effective alternative to HbA1c for assessment of glycemic control.
Methods: Cross-sectional data from the South Asia Biobank were analyzed. This included data of 8597 adults (aged ≥18 years) with type 2 diabetes (T2D) from Chennai and Delhi, India, surveyed during the period 2019-21. T2D was diagnosed if the fasting plasma glucose [FPG] ≥126 mg/dl and/or HbA1c ≥6.5%. TyG index was calculated using the formula Ln [fasting triglycerides (mg/dL) × FPG (mg/dL)/2]. Receiver Operating Curve (ROC) and multivariable logistic regression were used to quantify the association of TyG index with HbA1c.
Results: TyG index (Mean± SD: 5.1±0.3 vs.4.8±0.3, p&lt;0.001) was significantly higher in those with suboptimal glycemic control (HbA1c ≥7%) compared to those with good control (HbA1c &lt;7%), and showed significant correlation with HbA1c (r=0.501; p&lt;0.001). After adjusting for age and sex, regression analysis showed that Tertile 2-TyG index ≥4.9-5.6 (Odds Ratio [OR] 2.7, 95% Confidence Interval [CI]: 2.5-3.1) and Tertile 3-TyG index ≥5.7 (OR 9.1, 95% CI:8.0-10.3) were associated with HbA1c ≥7%. The area under the curve (AUC) of the ROC curve of TyG index ≥5.03 for prediction of HbA1c ≥7% was 0.75 (95% CI,0.74-0.76) with a sensitivity of 63% and specificity of 74% (p&lt;0.001).
Conclusion: The TyG index appears to be a cost-effective marker for assessing glycemic control, offering a valuable tool for monitoring diabetes in low-resource settings and situations where HbA1c cannot be reliably estimated.

Disclosure
R. Pradeepa: None. V. Jha: None. P. Thyparambil Aravindakshan: None. S. Waghdhare: None. V. Mohan: None. J. Chambers: None. R. Anjana: None.

Funding
National Institute for Health Care and Research (NIHR132960)
2003-LB: Dissecting Ancestry-Aware Molecular Causal Paths of Type 2 Diabetes
Authors: YOSHIJI SATOSHI , BOCHER OZVAN , LUIZA ARRUDA ANA , YIN XIANYONG , CAMMANN DAVIS B. , ZHAO CHI , TAYLOR HENRY J. , CHEN JINGCHUN , MANDLA RAVI , HUERTA ALICIA , YANG TA-YU , WOOD ALEXIS , LORENZ KIMBERLY , MATSUDA FUMIHIKO , FLANNICK JASON , MERCADER JOSEP M. , SPRACKLEN CASSANDRA N. , MEIGS JAMES B. , ROTTER JEROME I. , VUJKOVIC MARIJANA , VOIGHT BENJAMIN F. , MORRIS ANDREW , ZEGGINI ELEFTHERIA 
Published: June 2024

Multiple molecular mechanisms are involved in the pathogenesis of type 2 diabetes (T2D), with potentially different effects across ancestries. Recent large-scale efforts by the Type 2 Diabetes Global Genomics Initiative (T2DGGI) have broadly described the genetic architecture of T2D, data that can be subsequently used to pinpoint causal molecular mechanisms leading to T2D in an ancestry-aware manner.
In this work, we sought to explore the causal effects of gene expression and proteins on T2D across ancestries by leveraging data from the latest T2DGGI multi-ancestry genome-wide association study (GWAS). We conducted two-sample Mendelian randomization (MR) using cis-expression and protein quantitative trait loci (eQTL/pQTL) data from various datasets of four different major ancestries. To corroborate our findings, we performed statistical colocalization using PWCoCo. We then performed meta-analyses across ancestries for molecular traits showing evidence of causality in at least one ancestry (5% FDR-adjusted MR p-value and PWCoCo posterior probability ≥ 0.5).
We found causal evidence for changes in the genetically regulated expression of 267 genes and 15 proteins with T2D risk in at least one ancestry. When meta-analyzing the results across ancestries, we found, for eQTLs, evidence of causality between 148 genes and T2D, including PABPC4, a high-confidence effector gene for T2D with evidence of ancestry-correlated heterogeneity (I2 = 85%). For pQTLs, NELL1, ANXA7, PCSK1, and CTRB2 were found to be causal to T2D risk in the cross-ancestry meta-analysis, with CTRB2 showing evidence of ancestral heterogeneity (I2 = 85%).
Our findings highlight the power of large-scale GWAS and multi-omics MR to identify causal pathways involved in T2D risk. Our results also show the existence of ancestry-correlated heterogeneity, which emphasizes the need for expanding investigations into non-European ancestry populations to better understand T2D etiology.

Disclosure
S. Yoshiji: None. O. Bocher: None. X. Yin: None. C. Zhao: None. J. Chen: None. R. Mandla: None. A. Huerta: None. T. Yang: None. A. Wood: Research Support; Beef Checkoff. Consultant; The Lundquist Institute. K. Lorenz: None. F. Matsuda: None. J. Flannick: None. J.M. Mercader: None. C.N. Spracklen: None. J.B. Meigs: None. J.I. Rotter: None. M. Vujkovic: None. B.F. Voight: None. A. Morris: None. E. Zeggini: None.
2011-LB: Patterns of Genetic Risk for Type 2 Diabetes Are Specific to Ancestry
Authors: YURCHISHIN MARIAN L. , FOWLER LAUREN A. , GOWER BARBARA , FERNANDEZ JOSE R. , O'NEIL PATRICK M. 
Published: June 2024

Introduction & Objective. The heterogeneity of type 2 diabetes (T2D) risk has a genetic basis that can be reflected in genetic risk scores (GRS). It is currently unknown if the nature of genetic risk for T2D varies with ancestral backgrounds. The aim of this study was to determine if patterns of genetic risk for T2D exist, and if they differ by ancestry in a sample of 342 Non-Hispanic White (NHW), Non-Hispanic Black (NHB), and Hispanic (HIS) adults with obesity and T2D.
Methods: Participants were genotyped using the Infinium Global array with imputation. Six GRS representing distinct T2D pathophysiological pathways (beta-cell, proinsulin, obesity, lipodystrophy, liver/lipid, and insulin resistance (IR)) were calculated. Principal components analysis was performed on the GRS and genetic admixture values to identify ancestry-specific patterns for risk. Spearman correlations quantified strength and direction of associations of variables to each component. Participant self-reported ethnicity was used as a supplementary categorical variable.
Results: Two principal components (PC) were retained. PC1 was associated with greater African ancestry (r=0.92, p &lt;0.001) and the beta-cell and proinsulin GRS (r=0.442, p &lt;0.001 and r=0.453, p&lt;0.001, respectively). PC2 was associated with higher Native American ancestry (r=0.4691, p&lt;0.001) and the IR and lipodystrophy GRS (r=0.52, p &lt;0.001 and r=0.66, p&lt;0.001, respectively). NHB were distinctly different from NHW for all variables. NHB had the highest scores for PC1, suggesting that genetic susceptibility to T2D in this group arises from impaired insulin secretion and processing abilities. HIS had the highest scores for PC2, which suggests T2D risk in this group is characterized by lipodystrophy-driven IR.
Conclusion: Our results demonstrate that genetic risk for T2D manifests in patterns that are ancestry-specific. This may be useful in future research to help refine criteria for identifying at-risk individuals based on ancestral background.

Disclosure
L.A. Fowler: None. B. Gower: Advisory Panel; Cook Keto, Simply Good Foods, Abbott. J.R. Fernandez: None. P.M. O'Neil: Other Relationship; Novo Nordisk.

Funding
National Institutes of Health (T32HL105349); National Institutes of Health (T32DK062710)Clinical trial from which data were collected was sponsored by Weight Watchers International to the Medical University of South Carolina (NCT01601574)
2032-LB: In Vivo Chain Splitting of Human Insulin
Authors: STURIS JEPPE , CRAMER CHRISTIAN , BRAND CHRISTIAN L. , HELLEBERG HANS , KURTZHALS PETER , HUBALEK FRANTISEK 
Published: June 2024

Non-insulin receptor-mediated insulin degradation via insulin degrading enzyme has been proposed to play a role in insulin resistance (IR). Recently, chain-splitting (CS) via a disulfide bond exchange process has been shown to occur for insulin icodec dosed to humans. As insulin icodec contains disulfide bond stabilizing substitutions, the present aim was to estimate the degree of CS of human insulin (HI) from A-chain (Ach) levels during infusion of HI to rats combined with kinetics of Ach in rats.
Ach was injected IV into male Sprague-Dawley (SprD) rats (1, 7 and 50 nmol/kg), and Ach in plasma sampled from the carotid artery was measured by LC/MS. Ach clearance (CL) and t½ (geometric mean) were estimated by regression analysis. A euglycemic clamp during IV HI infusion (2 nmol/kg/min) into SprD rats (n=2) allowed plasma HI and Ach from in vivo CS to be measured. The rate of CS was estimated as the 180 min clamp Ach level multiplied by Ach CL.
Ach was measured in all rats. The estimated CS rate in the clamp experiment was 0.37 nmol/kg/min or 19% of the HI infusion.

We have estimated that a substantial proportion of HI was degraded by CS in rats during HI infusion. Further studies are warranted to substantiate our findings and to investigate 1) if CS of HI during transport to the interstitial fluid may limit the access of HI to target tissues and 2) to what extent increased CS and reduced access of endogenous insulin may be a mechanism for compensatory insulin secretion, hyperinsulinemia and IR.

Disclosure
J. Sturis: Employee; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S. C. Cramer: Employee; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S. C.L. Brand: Employee; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S. H. Helleberg: Stock/Shareholder; Novo Nordisk A/S. P. Kurtzhals: Employee; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S. F. Hubalek: Employee; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S.
2041-LB: The Divergent Effects of Alternate Day Fasting on Body Weight, Glucose Homeostasis, Endothelial Function, and Adipose Inflammation in Control and Type 2 Diabetic Mice
Authors: ZHANG HANRUI 
Published: June 2024

Introduction: There is growing interest in the benefits of intermittent fasting for weight loss, glucose control, vascular protection, and mitigating chronic inflammation. Nonetheless, it remains unclear whether the metabolic and endothelial protective benefits depend on weight loss or anti-inflammatory effects.
Objective: Using type 2 diabetic (db/db) mice and the respective heterozygote controls, we aimed to determine whether alternate day fasting (ADF) provides metabolic benefits and endothelial protection, partially independent of its effects on weight control and adipose inflammation.
Methods: Mice were either allowed to eat ad libitum or placed on an ADF diet regimen for 12 weeks.
Results: In control mice, ADF led to significant reductions in body weight and insulin levels. There was a modest, though not statistically significant, decrease in blood glucose and HOMA-IR. In db/db mice, ADF significantly reduced blood glucose and HOMA-IR while not affecting body weight or insulin levels. This underscores the effects of ADF on improving glucose metabolism despite the absence of weight loss in diabetic mice. ADF improved endothelium-dependent vasorelaxation in small mesenteric arteries of db/db mice without altering endothelium-independent vasorelaxation or phenylephrine-induced vasoconstriction. In control mice, ADF exhibited a trend toward enhancing the maximal relaxation at 10-7 mol/L acetylcholine while not affecting endothelium-independent vasorelaxation or vasoconstriction. Despite the significant metabolic and endothelial protective benefits, ADF did not mitigate adipose inflammation in either control or db/db mice.
Conclusions: ADF's weight control, metabolic, endothelial protective, and anti-inflammatory benefits can manifest independently in diabetic and control mice. The results also imply the potential to explore ADF benefits in non-obese, healthy individuals.

Disclosure
H. Zhang: None.
2048-LB: Activation of Connexin Hemichannels and PGE2 Release in Osteocytes Reduce Global Adiposity and Improve Metabolic Homeostasis while Preserving Lean Mass
Authors: ACOSTA FRANCISCA M. , ZHANG JINGRUO , MOTA LINDA , MAKONAHALLI AMULYA , WANG XUEWEI , HERNANDEZ ELIZABETH , RIQUELME MANUEL A. , BREY ERIC , JIANG JEAN X. 
Published: June 2024

Background: Research into signaling molecules for obesity therapies has largely overlooked the role of bone, particularly osteocytes (Ocy), which play crucial roles in biomechanical, inflammatory, & metabolic signaling. Connexin 43 (Cx43) hemichannels (HCs), abundant in Ocy, facilitate cellular communication. Research has shown these HCs, sensitive to mechanical cues, exchange molecules, such as prostaglandin E2 (PGE2), influencing bone quality and differentiation of adipose tissue (AT) & skeletal muscle (SkM).
Objective: Investigate the role of Ocy Cx43 HCs in mediating cross-organ regulation between AT & SkM in obesity.
Methods: In vivo we used transgenic mice with overexpression of Cx43 dominant negative mutants in Ocy: R76W (inhibited gap junctions (GJs), enhanced HCs) & Δ130-136 (inhibited HCs & GJs), or a monoclonal Cx43(M2) antibody that opens Cx43 HCs, ±high-fat diet, and in vitro, conditioned media (CM) collected from fluid flow-stimulated Ocy.
Results: Impaired HCs (Δ130-136) contributed to increased AT, while enhanced HC activity (R76W/M2) reduced it, resulting in improved energy expenditure and preservation of SkM/lean mass. This association was linked to Cx43 HC-mediated elevation in global PGE2 levels. Specifically, Δ130-136 mice exhibited up to an 8% increase in %fat and decrease in lean mass. Conversely, augmentation of HCs (R76W/M2) increased activity, food intake, & calorie expenditure, while mitigating up to a 4-fold increase in %fat & reducing weight (p=0.01), glucose, triglycerides, AT hypertrophy/whitening, & liver AT. Treatment with Ocy CM inhibited adipogenic differentiation of AT-derived stem cells, which was undone by CM from Ocy treated with a HC-blocking antibody.
Conclusion: These studies provide new insight into the role of Ocy Cx43 HC in metabolic health, through the regulation of AT/lean mass, and present it as a unique target for combatting obesity, with PGE2 being a major regulator.

Disclosure
J. Zhang: None. L. Mota: None. A. Makonahalli: None. X. Wang: None. E. Hernandez: None. E. Brey: None.

Funding
National Institutes of Health (F32DK134051), National Institutes of Health (AR072020), Welch Foundation (AQ-1507), and Clinical & Translational Research Pilot Grant Award from the Institute for Integration of Medicine & Science (IIMS) at UT Health San Antonio
2055-LB: Temporal Resolution of Single-Cell Transcriptomics and Epigenomics of Murine Pancreatic Islet in Diet-Induced Obesity
Authors: SINGH SIMRAN , PAVAN MUSALE KRUSHNA , BARELLA LUIZ F. , SHREE AJITA , ZAFAR HAMIM , WESS JÜRGEN , PRASAD PYDI SAI 
Published: June 2024

Introduction: The escalating global prevalence of obesity has contributed significantly to the burgeoning incidence of type 2 diabetes (T2D). Despite major advancements in modern medicine, more effective therapies for treating obesity and T2D are needed. Pancreatic islets are the most dynamic endocrine organ with remarkable abilities to adapt to the dietary status. However, the transcriptional, epigenetic, metabolic, and cellular events that occur in pancreatic islets during the progression from a healthy state to insulin resistance and T2D are poorly characterized.
Objective: To address this issue, we took the advantage of single-cell omics and challenged mice with either regular and/or high-fat diet for different time intervals, to decipher the different molecular events associated with the progression of insulin resistance and diabetes. Method: To assess changes in gene expression in murine pancreatic islet cells, we used single-cell RNA and ATAC seq techniques during different degrees of obesity and insulin resistance.
Result: We identified subpopulations of alpha, beta, delta, gamma, endothelial, and immune cells and demonstrated commonalities and differences across murine and human species and dietary conditions. We found that different stages of obesity are associated with the trans-differentiation of endocrine cell types. Obesity led to dysregulated gene expression networks, including several metabolic and inflammatory pathways in a cell subtype-specific manner. Our findings also highlight the underappreciated role of endothelial islet cell in obesity across human and mouse population.
Conclusion: Our study provides a powerful resource for identification of heterogeneity across islet endocrine and non-endocrine populations during different states of obesity.

Disclosure
S. Singh: None. L.F. Barella: Employee; Kallyope. A. Shree: None. H. Zafar: None. J. Wess: None. S. Pydi: None.
2061-LB: Secreted EMC10 (scEMC10) Suppresses Thermogenesis in Brown Adipose Tissue via the Inhibition of PKA-CREB/p42 MAPK Signaling
Authors: WANG XUANCHUN , WANG YAHAO , LIU SHAN , ZHAN CHONGWEN , MIAO QING 
Published: June 2024

Brown adipose tissue (BAT) plays a significant role in regulating energy metabolism, contributing to improved glucose homeostasis and reduced weight gain. We have shown Emc10 gene knockout or antibody neutralization of circulating scEMC10 prevent diet-induced obesity and its associated metabolic disorders in mouse via activation of BAT thermogenesis. In this study, we observed serum scEMC10 levels were significantly elevated by thermoneutrality, concomitant with suppression of active BAT in BAT-positive humans. Overexpression of scEMC10 promoted mouse diet-induced obesity via suppression of BAT thermogenesis, evidenced by reduced expression of UCP1 and PGC1α in BAT. scEMC10 overexpression also resulted in cold intolerance of HFD-fed mouse due to decreased levels of UCP1 and PGC1α in both epididymal adipose tissue and BAT, suggesting the involvement of scEMC10 in the sympathetic nervous system/norepinephrine-modulated BAT thermogenesis. Recombinant scEMC10 protein significantly suppressed CL 316243, a β3-adrenoceptor agonist, -induced expression of thermogenic (Ucp1, Pgc 1 ɑ, and Dio2) and lipolytic (Hsl and Atgl) genes via inhibiting PKA-CREB/p42 MAPK signaling in both cultured brown adipocyte in vitro and BAT in vivo. In conclusion, this work identifies scEMC10 exerts an inhibitory role in BAT thermogenesis via suppression of PKA-CREB/p42 MAPK signaling, and also suggests the inhibition of circulating scEMC10 will be a promising way to treat obesity and its related cardiometabolic diseases.

Disclosure
X. Wang: None. Y. Wang: None. S. Liu: None. C. Zhan: None. Q. Miao: None.

Funding
National Natural Science Foundation of China (81800691), Science and Technology Commission of Shanghai Municipality (22140902700).
2065-LB: Slug Regulates Adipogenesis and Adipose Tissue Growth
Authors: JU LIPING , KANG QIANQIAN , ZHOU RUOYU , ZHENG QIANTAO , RUI LIANGYOU 
Published: June 2024

Adipose stem cell commitment, proliferation, and differentiation critically regulate adipose tissue development and homeostasis. Transcription factor Slug, also known as Snai2, is well known to promote epithelial-mesenchymal transition and cell motility. Slug also emerges as an important regulator of body weight and metabolism. In the hypothalamus, Slug promotes leptin resistance, leading to obesity. In the liver, hepatic Slug promotes de novo lipogenesis and fatty liver disease. In this study, we observed that Slug is expressed in adipose stromal vascular fraction cells (SVFs). SVFs contains adipose stem cells/preadipocytes. To determine the fate of Slug-expressing SVFs, we generated Slug-Cre and Slug-CreERT (tamoxifen-dependent) drivers. The drivers were crossed with Rosa26-mTmG or Rosa26-tdTomato reporter mice to generate Slug-expressing cell lineage-tracing models. The Slug-Cre based tracing paradigm revealed that Slug-expressing stem cells generate the majority of white adipocytes and brown adipocytes in mice. The Slug-CreERT models demonstrated that in adult mice, Slug-expressing SVFs play an important role in regulating adipose tissue regeneration and maintenance. To examine Slug function, we generated adipose stem cell-specific Slug knockout mice by crossing Slugf/f mice with PDGFRα-Cre drivers. Body weight was lower in Slug mutant mice relative to Slugf/f mice on a high fat diet (HFD). Likewise, whole body deletion of Slug also protected against HFD-induced obesity and insulin resistance. In conclusion, our results suggest that Slug directly regulates adipose stem cell behavior, adipogenesis, adipose growth, and adipose function.

Disclosure
L. Ju: None. Q. Kang: None. R. Zhou: None. Q. Zheng: None. L. Rui: None.