bluuebunny/crossref_metadata_2025_split huggingface dataset:
1287-P: Unmasking the Risk Factors for Undiagnosed Diabetes among Adult Ghanaians Using Generalised Structural Equation Modeling—Insight from CarMeR Study
Authors: HORMENU THOMAS 
Published: June 2024

Undiagnosed diabetes mellitus poses a global health challenge, contributing to morbidity and mortality worldwide. In Ghana, the burden of diabetes is escalating, posing substantial challenges to the healthcare system, especially during COVID-19. A considerable number of cases remain undiagnosed, resulting in delayed interventions and heightened complications. Understanding the etiology of diabetes in indigenous communities is critical for implementing early interventions for diabetes prevention and remission. Our goal was to unmask risk factors of undiagnosed diabetes among adults in Ghana. We screened 1200 ostensibly healthy adults aged 25-70 years, predominantly female (63%) across 13 indigenous communities with unique characteristics. Fasting plasma glucose (FPG) assessed glucose tolerance using ADA criteria for FPG. The results revealed overall diabetes prevalence of 3.8% (n=46) [5.2% in females, 1.2% in males; 6.4% in rural, 2.1% in peri-urban, 4.6% in urban], and prediabetes at 14.4% (n=173) [15.3% in females, 12.6% in males; 22.0% in rural, 13.3% in peri-urban, 7.6% in urban]. Body Mass Index (BMI), Triglycerides (TG), Systolic Blood Pressure (SBP), gamma GT, gender and family history directly contributed significantly to diabetes risk. Age, education and Total Cholesterol (TC) indirectly influenced diabetes development through TG. High-Density Lipoprotein (HDL), TC, childhood overweight, physical activity, gender, and occupation indirectly influenced BMI. Alcohol intake, childhood overweight, family history of diabetes, gender, and socioeconomic status influenced waist circumference (WC). WC, TG, age, physical activity, and residency indirectly influenced SBP. Alcohol intake, gender and religion indirectly influenced diabetes prevalence through gamma GT. Controlling these factors may improve diabetes prognosis within indigenous communities.

Disclosure
T. Hormenu: None.

Funding
Africa Academy of Sciences (APT-18-03)
1289-P: Longitudinal Cohort Study—Type 2 Diabetes Prevention and Genetic CAD Risk Interaction on Cardiovascular Factors
Authors: SHANKAR ANAND , GUHA SHAIBAL , DAS AMIT K. , KUMAR SUBHASH , SINHA AJAY K. 
Published: June 2024

Introduction: Understanding the interaction between lifestyle interventions for Type 2 Diabetes (T2D) prevention and genetic predispositions to Coronary Artery Disease (CAD) is crucial in developing personalized strategies for reducing cardiovascular risk. This study aims to investigate how T2D prevention strategies interact with genetic determinants of CAD to influence cardiovascular risk factors over time.
Methods: A cohort of 200 high-risk individuals for T2D and CAD were followed over three years. They were categorized by genetic risk for CAD and underwent T2D prevention strategies (diet, exercise, medication). Cardiovascular risk factors were measured biannually. The study used mixed-effects models to analyze the influence of T2D prevention strategies on these factors, considering genetic CAD risk.
Results: Individuals with higher genetic CAD risk had smaller improvements in lipid profiles (mean LDL reduction of 10 vs. 20 mg/dL, p&lt;0.01) and blood pressure (5 vs. 12 mmHg reduction, p&lt;0.05) under the same T2D prevention strategies as those with lower risk. Notably, LDL changes showed a significant interaction with genetic risk (p&lt;0.05), indicating that genetic predisposition might moderate T2D prevention's effectiveness in reducing cardiovascular risk.
Conclusion: The study reveals a complex relationship between T2D prevention, CAD genetics, and cardiovascular risks, advocating for intensified, personalized T2D strategies for those with high genetic CAD risk. It emphasizes precision medicine's role in T2D and CAD management, urging further research for tailored solutions.

Disclosure
A. Shankar: None. S. Guha: None. A.K. Das: None. S. Kumar: None. A.K. Sinha: None.
1318-P: Postprandial C-Peptide (pCP) in Provider-Diagnosed Pediatric Type 1 Diabetes (T1D) and Type 2 Diabetes (T2D)
Authors: REDONDO MARIA J. , HARRALL KYLIE K. , BIRD SARAH M. , TOSUR MUSTAFA , UYSAL SERIFE , SILLER ALEJANDRO F. , VELASQUEZ HORACIO J. , MUIR ANDREW , VEHIK KENDRA , BRUSKO TODD M. , ATKINSON MARK A. , DABELEA DANA , HAGOPIAN WILLIAM , ORAM RICHARD A. 
Published: June 2024

Introduction & Objective: Classification of diabetes (DM) type (T1D vs T2D) is often challenging in adolescence, especially among non-White ethnic groups. We hypothesized that pCP differentiates between provider-diagnosed T1D and T2D in ethnically diverse youth with DM. Methods: We studied 410 youth in the Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) Study. Low C-peptide, pre-defined as pCP &lt; 1.8 ng/ml (0.6 nmol/L) was compared between youth diagnosed with T1D and T2D using Fisher’s exact tests. Differences in the distribution of log pCP were assessed visually with histograms.
Results: There were 356 youth diagnosed with T1D (age 8.4 ± 3.1 yrs; 55% female; 36% Hispanic, 19% non-Hispanic Black) and 54 (13%) with T2D (age 11.7 ±1.7 yrs; 71% female; 70% Hispanic, 21.4% non-Hispanic Black). Low pCP was observed in 97.8% of T1D vs 27.1% of T2D youth (p&lt;0.0001); 99.6% (T1D) vs 24.0% (T2D) (p&lt;0.0001) in those with DM duration &gt;4 yrs; 97.2% (T1D) vs 22.2% (T2D) (p&lt;0.0001) in those with simultaneous glucose &gt;115 mg/dl (6.4 mmol/L); and 99.5% (T1D) vs 11.1% (T2D) (&lt;0.0001) in those with DM for &gt;4 yrs and glucose &gt;115 mg/dl (Figure).
Conclusion: In ethnically diverse youth, pCP &lt;1.8 ng/ml can reliably identify those with provider-diagnosed T1D. Performance further improves in youth with DM duration &gt;4 yrs and a simultaneous glucose &gt;115 mg/dl. A sizeable subset of youth with T2D have lower pCP.

Disclosure
M.J. Redondo: None. K.K. Harrall: None. S.M. Bird: None. M. Tosur: None. S. Uysal: None. A.F. Siller: None. H.J. Velasquez: None. A. Muir: None. K. Vehik: None. T.M. Brusko: None. M.A. Atkinson: None. D. Dabelea: None. W. Hagopian: Research Support; Janssen Pharmaceuticals, Inc., Provention Bio, Inc. Consultant; Sanofi-Aventis U.S., Randox R & D. R.A. Oram: Research Support; Randox R & D. Consultant; Provention Bio, Inc., Sanofi.

Funding
National Institutes of Health (NIDDK R01DK124395)
1328-P: Exploring DNA Methylation-Based EpiMetabolic Index via Direct-to-Consumer Testing for Type 2 Diabetes Risk Assessment
Authors: ARCH ROULA , HU NICOLAS , LIU ZHENFENG , YANG XIAOJING 
Published: June 2024

Introduction: Investigating new biomarkers for type 2 diabetes (T2D) risk screening, especially for non-typical high-risk groups, is essential for prevention. Direct-to-consumer (DTC) tests bypass traditional lab visits for convenience and encourage screening. This study evaluates the association between a DNA methylation-based EpiMetabolic index (eMI) DTC testing and T2D.
Methods: The EpiMetabolic indexz (eMI) was estimated through linear regression of DNA methylation at 15 regions associated with diabetes and metabolic traits (e.g., ABCG1, CPT1A, PHGDH, SREBF1). Blood samples, mainly collected at home, were sent to the CLIA facility (Pangea laboratory) for targeted next-gen sequencing. Customer medical data was self-reported online. Only adults with specific metabolic statuses and valid epi-metabolic indices were included. Independent variables: birth-assigned sex, diabetes, and medication (e.g., statins). The dependent variable was the epi-metabolic index. We studied each factor's individual effects using one-way ANOVA and combined them with sex for interaction effects using two-way ANOVA.
Results: Significant associations were found between an accelerated eMI and prediabetes/diabetes (p=0.001). Some lifestyle associations (e.g., exercise) lacked statistical significance, potentially due to self-report biases. Notably, a significant association existed between statin usage and an elevated eMI.
Conclusions: This study on the DTC cohort identifies an association between eMI and diabetes/prediabetes status, emphasizing the potential use of DNA methylation-based DTC as a practical tool for monitoring individuals at diabetes risk. This approach can benefit those lacking consistent access to care due to financial, social, cultural, or geographical barriers.

Disclosure
R. Arch: None. N. Hu: Employee; Zymo Research. Z. Liu: None. X. Yang: None.
1352-P: Cardiometabolic Risk Factors Superior to FIB4 in Identifying Adults at Risk for NAFLD with Fibrosis
Authors: GODINEZ LEIVA EDDISON , SHARMA ANU , KALAVALAPALLI SRILAXMI , ORTIZ ROCHA ANDREA , VALDEZ SAENZ ENRIQUE , MOHSENI YASMINE , CUERVO PARDO NATHALY , ROSENBERG JENS T. , GRAJO JOSEPH R. , BARB DIANA , CUSI KENNETH 
Published: June 2024

Introduction & Objective: A single effective screening tool for hepatic fibrosis across all age groups is currently lacking. The fibrosis-4 score (FIB-4) is the most commonly used screening tool but is less reliable in younger and older ages. The goal was to identify the best combination of cardiometabolic risk factors in all adults to guide clinical screening for hepatic fibrosis.
Methods: A total of 1420 adults with (63%) and without (37%) type 2 diabetes (T2D) without a prior history of NAFLD were recruited. A complete history, physical examination, and screening for NAFLD with laboratory tests and assessment of insulin sensitivity by HOMA-IR and Adipo-IR were performed. Clinically significant hepatic fibrosis (≥F2) was defined as a liver stiffness measurement ≥8.0 kPa by elastography, or ≥3.0 kPa by MRE, or on liver biopsy.
Results: Of those with hepatic fibrosis (n=135), 34% (n=46) were &lt;35 or &gt;65 years old. The presence of T2D had a sensitivity of 87% and a specificity of 39% for hepatic fibrosis. Adding obesity to T2D, lowered the sensitivity (76%) but increased specificity to 61%. The presence of T2D, obesity, and hypertension (HTN) together did not change test characteristics. Adding atherogenic dyslipidemia (non-HDL ≥130 mg/dL), however, significantly lowered sensitivity (20%). HOMA-IR and Adipo-IR were sensitive but not specific for hepatic fibrosis. The presence of any combination of ≥3 cardiometabolic risk factors (T2D, obesity, HTN, atherogenic dyslipidemia) had a sensitivity of 86% and specificity of 54% for hepatic fibrosis. The addition of FIB-4 ≥1.3 increased the sensitivity to 97% but decreased specificity to 41%. In comparison, FIB-4 ≥1.3 in those 35-65 years old had a sensitivity of 84% and specificity of 25% for hepatic fibrosis.
Conclusion: The presence of ≥3 common cardiometabolic risk factors (T2D, obesity, HTN, atherogenic dyslipidemia) is a simple yet effective clinical screening strategy for NAFLD in all adults with superior specificity compared to FIB-4.

Disclosure
E. Godinez Leiva: None. A. Sharma: None. S. Kalavalapalli: None. A. Ortiz Rocha: None. E. Valdez Saenz: None. Y. Mohseni: None. N. Cuervo Pardo: None. J.T. Rosenberg: None. J.R. Grajo: None. D. Barb: Speaker's Bureau; Novo Nordisk. Other Relationship; Inventiva Pharma. K. Cusi: Research Support; Echosens, Boehringer-Ingelheim, Quest Diagnostics, Inventiva Pharma, LabCorp, Nordic Bioscience A/S. Consultant; Arrowhead Pharmaceuticals, Inc., AstraZeneca, Boehringer-Ingelheim, Lilly Diabetes, 89bio, Inc., GlaxoSmithKline plc, Novo Nordisk, Siemens Healthcare Diagnostics, Sagimet Biosciences, Terns Pharmaceuticals.

Funding
National Institutes of Health (R01DK120331)
1361-P: Development and Validation of a Scoring System for Predicting the Need for Hypoglycemic Agents during Glucocorticoid Treatments
Authors: KATO AYAKA , FUWA MASAYUKI , ASANO MOTOCHIKA , MORI ICHIRO , MORITA HIROYUKI 
Published: June 2024

Introduction & Objective: Glucocorticoid (GC) treatments have widely contributed to induction and maintenance therapies. However, GC-induced hyperglycemia cannot be predicted by fasting plasma glucose and HbA1c alone. The aim of the study was to identify the risk factors for GC-induced hyperglycemia and have developed and validated a novel scoring system for predicting the need for hypoglycemic agents during GC treatment.
Methods: In a developing set, 508 adults receiving prednisolone (PSL) for the first time were divided into two groups based on their treatment with or without hypoglycemic agents. Their clinical and laboratory parameters were compared, and risk factors were identified using logistic regression analysis after performing univariate analyses between the two groups. A point-addition scoring system with several categories and their coefficients in each risk factor was constructed to predict the need for hypoglycemic agents. The scoring system was then applied and validated on two validation sets, A and B.
Results: Older age and higher HbA1c percentages, body mass index, and initial PSL dosage were identified as risk factors. The sensitivity, specificity, and accuracy of the scoring system were 70.6%, 81.9%, and 77.1% in the developing set, 75.8%, 78.4%, and 77.4% in the validation set A, 79.4%, 73.9%, and 75.3% in the validation set B, respectively.
Conclusion: The scoring system is a valid and reliable tool for predicting the need for hypoglycemic agents in advance during GC treatment.

Disclosure
A. Kato: None. M. Fuwa: None. M. Asano: None. I. Mori: None. H. Morita: None.

Funding
JSPS KAKENHI (23K06864)
1367-P: Cognitive Assessment in Type 2 Diabetes—A Pilot Study in an Outpatient Clinic
Authors: LUDINGTON JANE , CHEN ROGER , GNJIDIC DANIJELA 
Published: June 2024

Aim: Type 2 diabetes (T2D) is associated with an increased risk of cognitive decline which may impact diabetes self-care and outcomes. Assessment of cognitive function is not routine practice. The primary objective was to assess cognitive function in outpatients &gt;55 years with T2D.
Method: People with T2D (&gt; 55 years) attending a tertiary hospital diabetes outpatient clinic with no known cognitive impairment and sufficient English language skills were recruited. The Montreal Cognitive Assessment and Problem Areas in Diabetes questionnaires were completed with a trained investigator. Routine demographic and clinical data were obtained from healthcare records. Analysis was descriptive and results expressed as mean ± standard deviation. Institutional ethics approval was obtained.
Results: Forty patients were enrolled, age 71.3 ± 8.7 years, 75% male, diabetes duration was 15.4 ±8.7 years and current HbA1c 7.7% ± 1.2%. The number of medications prescribed was 8.2 ± 3.7. The PAID score was 14.2 ± 13.3. In 27/40 (67.5%) patients the MOCA score was &lt;26/30 (23.6 ± 2.8) indicating cognitive impairment. The number of medications prescribed to this group was 8.4 ± 3.7. High risk medicines were prescribed to 23/27 (85%) of this cohort of patients.
Conclusion: Cognitive screening highlighted the prevalence of impairment in this outpatient clinic population (67.5%). Inclusion of routine cognitive screening can identify people who may benefit from additional diabetes management support and appropriate modifications to treatment regimens. This data will inform plans to implement routine screening in accordance with professional guidelines and screening principles.

Disclosure
J. Ludington: None. R. Chen: Speaker's Bureau; Abbott Diagnostics, AstraZeneca, Boehringer-Ingelheim. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. D. Gnjidic: None.
139-OR: Empagliflozin Enhances Hepatic Glucose Production and Reduces Total-Body Norepinephrine Turnover Rate—A Randomized Trial
Authors: ABDELGANI SIHAM , BASKOY GOZDE , ADAMS JOHN M. , KHATTAB AHMED , DEFRONZO RALPH A. , ABDUL-GHANI MUHAMMAD 
Published: June 2024

Background/Aims: SGLT2 inhibitors cause an increase in hepatic glucose production (HGP) which returns glucose to the systemic circulation and offsets the amount of glucose excreted in the urine by ~50%. The signal which is activated by SGLT2 inhibition and causes the increase in HGP is unknown. We previously have shown that the acute administration of SGLT2 inhibitor is associated with an increase (within 4 hours) in norepinephrine (NE) turnover. The aim of the present study is to examine the long-term effect of SGLT2 inhibition on total body NE turnover.
Methods: 36 T2D and 36 nondiabetic subjects were randomized to receive empagliflozin or matching placebo (2:1 ratio) for 12 weeks. HGP and total-body NE turnover were measured with 3-3H-glucose and 3H-NE infusion before and after therapy with empagliflozin.
Results: Empagliflozin administration (day 1), caused an increase in HGP by 22% and 19% within 4 hours in T2D and nondiabetic individuals, respectively, and the increase in HGP persisted at week 12. Total-body NE turnover significantly decreased in both groups. The placebo-subtracted decrease in NE turnover was -139±35 and -165±71 ng/min (both p&lt;0.05) in T2DM and nondiabetic individuals, respectively, at 24 hours after empagliflozin administration (day 2), and the decrease in NE turnover persisted at week 12 (p&lt;0.01). The decrease in NE turnover strongly and inversely correlated with the increase in HGP at week 12 (r=0.64, p&lt;0.001). However, the decrease in NE turnover at day 2 did not correlate with the increase in HGP on day 1 of empagliflozin administration (r=0.09, p=ns).
Interpretation: The long-term empagliflozin-induced stimulation of HGP cannot be explained by activation of the SNS. However, the inhibition of sympathetic activity by SGLT2i may explain the lack of increase in heart rate consistently observed in cardiovascular outcome trials with SGLT2 inhibitors.

Disclosure
S. Abdelgani: None. G. Baskoy: None. J.M. Adams: None. A. Khattab: None. R.A. DeFronzo: Advisory Panel; AstraZeneca, Novo Nordisk, Boehringer-Ingelheim, Intarcia Therapeutics, Inc., Aardvark, Renalytix, Corcept Therapeutics, Alnylam Pharmaceuticals, Inc. Research Support; Boehringer-Ingelheim, AstraZeneca, 89bio, Inc., Amgen Inc., Medality, Corcept Therapeutics. Speaker's Bureau; AstraZeneca, Corcept Therapeutics, Renalytix. M. Abdul-Ghani: None.

Funding
National Institutes of Health (2R01DK097554-06 grant to MAG)
1392-P: Morning Chronotype Reduces the Risk of PCOS—A Mendelian Randomization
Authors: ZHANG MANNA , LU JIAYI , DILIMULATI DILIQINGNA , CAI MEILI , ZHANG YUQIN 
Published: June 2024

Objective: Previous observational studies have suggested a potential connection between PCOS and chronotype, and we aimed to assess the causal relationship between PCOS and chronotype.
Methods: A two-sample Mendelian randomization (MR) study was used to evaluate the causal association between PCOS and chronotype. The GWAS summary statistics for chronotype were obtained from the UK Biobank, and the GWAS summary statistics for PCOS were obtained from the FinnGen cohort on the IEU Open GWAS Project database. Inverse-variance weighted (IVW) fixed-effect method, the MR-Egger method, and a weighted median method were used for MR estimates.
Results: The primary IVW method showed a genetically determined morning chronotype had a significant negative causal relationship with the risk of PCOS. In the main IVW analysis, one unit morning chronotype decreased the incidence of PCOS by 0.86 (OR: 0.14, 95% CI: 0.02 ~ 0.86, P = 0.033). The main IVW estimate was generally consistent with the results of weighted median, weighted mode, and MR-Egger. The MR-PRESSO results showed no outlier SNPs, and the leave-one-out analysis showed that no single SNP has an influence on the overall estimates. Cochran’s Q statistics showed little evidence of heterogeneity between SNPs. There was no evidence of pleiotropy by MR-Egger regression intercept or MR-PRESSO global test (MR-Egger intercept = 0.020, P = 0.835), and symmetry of funnel plots supported the validity of our MR analysis.
Conclusion: Our findings indicate that genetically predicted morning chronotype had a significant negative prevalence in PCOS.

Disclosure
M. Zhang: None. J. Lu: None. D. Dilimulati: None. M. Cai: None. Y. Zhang: None.
1394-P: One-Year Effectiveness of Carbohydrate-Restricted Nutrition Therapy in Individuals with Prediabetes in Rural vs. Urban Areas
Authors: ATHINARAYANAN SHAMINIE J. , ADAMS REBECCA N. , VOLK BRITTANIE M. , ROBERTS CAROLINE G.P. , ZOLLER ALISON , MCKENZIE AMY L. 
Published: June 2024

Availability of diabetes prevention programs is largely limited to urban (U) areas, posing a challenge to diabetes prevention in rural (R) areas. Virta Health provides carbohydrate-restricted nutrition therapy (CRNT) through continuous remote care (CRC) and has been implemented nationwide to prevent progression of prediabetes (preD). In this retrospective analysis, we aim to assess the 1-year effect of the program on cardiometabolic markers in individuals with preD from both R and U counties. A random sample of individuals with preD who remained in the program at least 1y was selected (250 from R areas and 250 from U areas). Changes in metabolic markers from enrollment (E) to 1y were assessed in a linear mixed effect model. Characteristics at E were consistent between the R and U cohorts (age=50.9 (9.4)y, BMI= 36.7 (7.7)kg/m2, HbA1c=5.8(0.3)%). HbA1c [-0.2% from E:5.7±0.0 (R), -0.2% from E: 5.8±0.0 (U); ps&lt;0.001], weight [-9.2% from E:231.3±1.3 (R), -9.2% from E: 231.4±1.3 (U); ps&lt;0.001], HDL-C [13.3% from E:49.5±0.6 (R), 13.1% from E:50.2±0.6 (U); ps&lt;0.001], TG [-24.3% from E:152.2±4.2 (R), -26.9% from E:137.4±4.2 (U); ps&lt;0.001] improved, with no differences between R and U areas. Liver enzymes [ALT at E: 28.4±0.9(R), 27.6±0.9(U) U/L; ALP at E: 79.4±1.3(R), 76.5±1.3(U) U/L ] were within normal limits and significantly decreased [ALT:-11.2% (R), -11.5%(U); ALP: -5.7% (R), -5.8% (U); ps&lt;0.001]. Total cholesterol, LDL-cholesterol, and AST were unchanged. Individuals with preD in both R and U settings showed similar improvements in weight, HbA1c, and cardiometabolic markers. These findings demonstrate the effectiveness of this care model in improving cardiometabolic risk markers in people with preD living in both R and U areas.

Disclosure
S.J. Athinarayanan: Employee; Virta Health Corp. R.N. Adams: Employee; Virta Health Corp. Stock/Shareholder; Virta Health Corp. B.M. Volk: Employee; Virta Health Corp. Stock/Shareholder; Virta Health Corp. C.G.P. Roberts: Other Relationship; Virta Health Corp. A. Zoller: Employee; Virta Health Corp. Stock/Shareholder; Virta Health Corp. A.L. McKenzie: Employee; Virta Health Corp. Stock/Shareholder; Virta Health Corp. Employee; Abbott.