bluuebunny/crossref_metadata_2025_split huggingface dataset:
124-OR: Intervention of Select Lipid Signaling Reduces Type 1 Diabetes Incidence
Authors: WHITE TAYLEUR , ALMUTAIRI ABDULAZIZ , TUSING YING , HAMMOCK BRUCE , MCREYNOLDS CINDY , STEPHENSON DANIEL , CHALFANT CHARLES E. , RAMANADHAM SASANKA 
Published: June 2024

Activation of Ca2+-independent phospholipase A2β (iPLA2β) leads to production of proinflammatory prostaglandins E2 (PGE2) and diols generated by cyclooxygenase (COX) and soluble epoxide hydrolase (sEH), respectively, and we reported that decreasing iPLA2β reduces T1D incidence. Importantly, we find that inhibiting PGE2 signaling with an EP4r antagonist or sEH inhibitor mitigates immune cell inflammatory phenotype. We therefore tested if inhibiting PGE2 signaling (with grapiprant, GP) or sEH (with &lt;u&gt;EC&lt;/u&gt;5026) can prevent T1D onset. Starting at 4-weeks of age, NOD mice were treated with vehicle (PEG), GP, or EC and TID onset (≥275 mg/dl glucose) was monitored over 32 weeks of age. Further, as we noted that the production of proinflammatory PGs increases early and higher DHETs/EETs ratios occur closer to predicted T1D onset age, a 4th group was treated with GP starting at 4 weeks and EC added at 8 weeks of age. As expected, T1D incidence was 85% in PEG-treated NOD. Alone, GP reduced incidence modestly and EC5026 was without effect. However, the combination of both significantly reduced incidence. Intriguingly, near T1D onset age there was evidence of higher resolvins (Rvs), which are generated in response to inflammation to affect resolution. We therefore tested the effects of RvD2 and RvE1 supplementation and found that RvD2 was without effect. In contrast, RvE1 produced a significant decrease in incidence, compared with vehicle-treated NOD. In contrast to vehicle-treated diabetic NOD, circulating insulin levels were measured in nondiabetic NOD from both treatment regimens and there was no discernible drug cytotoxicity, as reflected by pathological assessments of pancreas, liver, kidney, and heart. These findings suggest consideration of targeting early inflammation and subsequent resolution phases to counter T1D development. Further, they provide a strong rationale for employing novel combination regimens to modulate select inflammatory and resolving lipid signaling to delay or prevent or T1D onset.

Disclosure
T. White: None. A. Almutairi: None. Y. Tusing: None. B. Hammock: Board Member; Eicosis. C. McReynolds: Employee; EicOsis. Consultant; Inipharm. D. Stephenson: None. C.E. Chalfant: None. S. Ramanadham: None.

Funding
NIH/NIAID 1R21AI169214-01JDRF 2-SRA-2022-1210-S-B3-SRA-2023-1362-S-B1-INO-2023-1344-A-NNIH/NIAID 1 R21 AI 146743UAB Department of CDIBUAB Comprehensive Diabetes Center
1249-P: Flash Glucose Monitoring in Gestational Diabetes—A Pilot Randomized Study
Authors: ZORKO KLARA , MUNDA ANA , SMID TANJA , ZAJEC ANASTAZIJA , JANEŽ ANDREJ , PONGRAC BARLOVIC DRAZENKA 
Published: June 2024

Introduction & Objective: Despite the increasing use of systems for subcutaneous glucose measurement very limited data exists on its use and glycemic targets in women with gestational diabetes (GDM). Therefore, the aim of our study was to analyze the impact of flash glucose monitoring system (FGM) on glycemic and perinatal outcomes in GDM.
Methods: In an ongoing single-center pilot randomized controlled trial, 37 women with GDM were randomly assigned to either the self-monitoring of blood glucose (SMBG) group or the SMBG + FGM group. The primary outcome was glycemic control, measured by mean glucose levels and the percentage of measurements within the target range by using SMBG data. Secondary outcomes included FGM glycemic control and perinatal data. Statistical comparison between the two groups was performed using the Mann-Whitney U test.
Results: The SMBG group (n=21,(age: 32.4 ± 4.9)) and the SMBG+FGM group (n=16, (age: 30.3 ± 4.9)) exhibited a significant difference solely in the percentage of measurements in target range postprandially (92.6% [84.0-1.0] vs. 80.1% [59.5-91.4], p=0.047). FGM data revealed minimal variations among participants, with an average time-in-range (TIR) of 95.5 ± 4.0%. Notably, 93.8% of participants achieved a TIR above 90%. The coefficient of variation (CV) was 4.2. In the SMBG cohort, two newborns were classified as large for gestational age (LGA), while none were reported in the FGM group.
Conclusion: Our data suggest better glycemic control 1-hour postprandially in the SMBG group, despite a vast majority within the SMBG+FGM group achieved TIR levels above 90%. Possibly stricter glycemic targets will be needed in this population of women, where even slight variations in glucose levels imply more significant therapeutic interventions. Given the limited sample size, definitive conclusions cannot be drawn; further research is warranted.

Disclosure
K. Zorko: None. A. Munda: None. T. Smid: None. A. Zajec: None. A. Janež: Advisory Panel; Novo Nordisk A/S. Speaker's Bureau; Abbott, Eli Lilly and Company, Boehringer-Ingelheim, Ascensia Diabetes Care, Medtronic, AstraZeneca. D. Pongrac Barlovic: None.

Funding
University Medical Centre Ljubljana 20230134 and 20220126
1252-P: Markers of Alzheimer's Disease (AD) in Young Adults with Type 1 Diabetes, With and Without Diabetic Retinopathy (DR)
Authors: PAULEY MEGHAN E. , COUGHLAN CHRISTINA , BELLATORRE ANNA , SNELL-BERGEON JANET K. , DABELEA DANA , SHAPIRO ALLISON 
Published: June 2024

Introduction & Objective: Diabetes increases risk of dementia, yet underlying neuropathology is unclear. While DR is associated with AD in adults with type 2 diabetes, less is known in young people with T1D. This study assessed plasma phosphorylated tau-181 (pTau181), a preclinical biomarker of AD, in young adults with T1D, by DR status.
Methods: Plasma pTau181 (pg/mL) was quantified in participants with T1D using samples from the SEARCH for Diabetes in Youth study Colorado site. Samples were taken from the baseline visit, at which time no DR was present (≤2 years of T1D duration; mean age 11 [4.2] years), and a follow-up (F/U) visit in young adulthood (mean age 21 [4.6] years). DR was assessed via fundus photography at F/U and defined as any DR present. Changes in levels of pTau181 over time were assessed with paired Wilcoxon signed-rank test and compared by DR status via Mann-Whitney U test.
Results: 45 participants were included (DR at F/U, n=18; No DR at F/U, n=27). pTau181 significantly increased over time in all participants (median [IQR]; 16.64 [12.60-23.67] to 109.60 [91.25-128.90], p&lt;0.001) but there were no significant differences by DR status.
Conclusion: Young adults with T1D show increasing burden of preclinical markers of AD neuropathology over time, unrelated to DR. Studies are underway to investigate the implications of these findings on cognitive function and future risk of AD in T1D.

Disclosure
M.E. Pauley: None. C. Coughlan: None. A. Bellatorre: None. J.K. Snell-Bergeon: None. D. Dabelea: None. A. Shapiro: None.

Funding
NIH NIDDK and CDC (1R01DK127208-01, 1UC4DK108173); NIH NIDDK (T325T32DK063687); DiabDocs Physician-Scientist Career Development Award: NIH NIDDK (K12DK133995) & The Leona M. and Harry B. Helmsley Charitable Trust to Stanford University (2305-06041)
1255-P: Sulfonylurea Prescription in Elderly Patients with Diabetes Survey Using Real-World Data in Japan
Authors: SAKAMOTO MASAYA , YAMAZAKI MICHIKO , TAKEBE TOHRU , HOSOKAWA MASAYA , SAIKA TOMOYA , NAKAO YUTAKA , IKEDA SHUNYA 
Published: June 2024

Introduction: Similar to the US, Japan has seen a decline in sulfonylureas (SUs) use in the elderly patients (pts) with diabetes, but the detailed usage status of SU is unknown.
Methods: To investigate real-world SU prescribing patterns, we conducted a retrospective cross-sectional survey using pharmacy data in Japan, targeting pts prescribed SUs, aged 20-100 years. From November 2022 to October 2023, we extracted data for 91,230 pts from the electronic prescription system Musubi (KAKEHASHI Inc., adopted in over 7,000 pharmacies, accounting for 10% market share, as of 2023 in Japan). The most commonly prescribed SUs were glimepiride (73,061 pts, 80.1%), gliclazide (14,841 pts, 16.3%), and glibenclamide (3,327 pts, 3.6%). Our analysis focused on adherence to Japanese guidelines in prescribing these SUs in elderly pts (adhering to limits of 1 mg/day for glimepiride and 40 mg/day for gliclazide, and avoiding glibenclamide).
Results: Of 91,230 pts showed 55,947 were male (61.3%) and a mean age of 68.8 years; 66,319 (72.7%) were aged ≥65 years. Elderly pts on average used 2.7 antidiabetic medications concurrently. The most common additional medications with SUs were DPP-4 inhibitor (49,963 pts, 75.3%), biguanide (34,266 pts, 61.2%), and SGLT-2 inhibitor (25,878 pts, 46.3%). Insulin was used concomitantly in 3,682 elderly pts (6.6%). Among elderly pts, 25.0% and 7.8% exceeded the recommended dosages for glimepiride (&gt;1 mg/day) and gliclazide (&gt;40 mg/day), respectively. Glibenclamide was prescribed to 2,578 elderly pts (77.5%). However, elderly pts used fewer diabetes medications on average: 3.3 for those &lt;65 years, 3.0 for 65-&lt;75 years, and 2.7 for ≥75 years.
Conclusion: We identified high-dose prescription of glimepiride and gliclazide, and glibenclamide use in elderly pts, indicating potential non-adherence to guidelines. Our findings highlight the need for enhanced education and appropriate SU usage to prevent hypoglycemia and diabetic complications.

Disclosure
M. Sakamoto: None. M. Yamazaki: None. T. Takebe: None. M. Hosokawa: None. T. Saika: None. Y. Nakao: None. S. Ikeda: None.
1264-P: Impacts of Diabetes (DM) on Severe Functional Disability (FD) and Care-Need Level Deterioration in Japanese
Authors: IKEDA IZUMI , FUJIHARA KAZUYA , SHIOZAKI HARUKA , MORIKAWA SAKIKO Y. , TSURUOKA KAHORI , YUKO YAMASHITA , MON KHIN LAY , WU SIJIA , YAGYUDA NORIKO , HORIKAWA CHIKA , SONE HIROHITO 
Published: June 2024

Avoidance of FD and the deterioration of care level needs leading to a decline in ADL and increased medical costs is urgent. We aimed to clarify the association between lifestyle habits, non-communicable diseases (i.e., DM, HT, and dyslipidemia) and their combinations and the incidence of severe FD and deterioration of the care-level. Followed for a median of 3.7 years were 9673 people who underwent health checkups. Care-level ≥2 (total assistance needed) indicates severe FD and worsening from the initial examination indicates deterioration. During the study period, 111 cases of severe FD occurred. Multivariate analysis showed that aging (per 5y) (OR 2.24 [1.95-2.56]), male (1.76 [1.16-2.66]), BMI&lt;18.5 (2.46 [1.40-4.35]), DM (1.81 [1.06-3.08]), HT (1.58 [1.05-2.38]), and lack of physical activity (PA) (2.17 [1.37-3.45]) were associated with severe FD. Prevalence of DM additively associated with severe FD. DM and ≥2 risk factors had a 10 times greater association than non-DM and no risk factor. Of 85 cases with worsening care needs, only DM was significantly associated with deterioration (2.88 [1.08-7.65]). DM is a significant risk factor for with double the increased risk of severe FD and triple care-need deterioration compared with those without DM. Also, in DM patients, low BMI, HT, and lack of PA greatly increased the risk of severe FD, suggesting the need for comprehensive treatment strategies.

Disclosure
I. Ikeda: None. K. Fujihara: None. H. Shiozaki: None. S.Y. Morikawa: None. K. Tsuruoka: None. Y. Yuko: None. L. Khin: None. S. Wu: None. N. Yagyuda: None. C. Horikawa: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.
1278-P: Changes in Cardiovascular Disease (CVD) Incidence Due to Remission of Diabetes and Metabolic Dysfunction–Associated Steatotic Liver Disease (MASLD)
Authors: MATSUBAYASHI YASUHIRO , FUJIHARA KAZUYA , SATO TAKAAKI , YAMAMOTO MASAHIKO , ISHIGURO HAJIME , OSAWA TAEKO , KITAZAWA MASARU , SUZUKI HIROSHI , KODAMA SATORU , YAMADA TAKAHO , SONE HIROHITO 
Published: June 2024

The leading cause of death in patients with steatotic liver disease (SLD) is CVD. As SLD is frequently associated with metabolic disorders such as type 2 diabetes (DM), the concept of MASLD has been proposed. MASLD can be classified according to the type of associated metabolic dysfunction. Among MASLD subtypes, MASLD with DM (DM-MASLD) was shown to have a major impact on the development of CVD. However, the presence of SLD and status of concomitant metabolic abnormalities change over time. Since it is unclear how the incidence of CVD changes when DM-MASLD transitions, this study aimed to clarify this issue. Included were 11592 participants selected from a nationwide claims database from 2008 to 2019 who underwent health screening 2 years before baseline (B-2) and who had DM-MASLD at B-2 but without CVD at baseline. Participants were classified by whether DM and MASLD remained or were in remission, respectively, from B-2 to baseline. Incidence of new onset of CVD in each category was analyzed by a multivariate Cox proportional hazard model. During a median follow up of 4.9 y, 446 CVD events occurred. Changes in incidence of CVD due to changes in DM and MASLD status are shown in Figure 1. Remission in DM and MASLD each significantly reduced the incidence of CVD. Remission of hepatic steatosis in DM-MASLD patients was comparable to remission of DM in preventing new onset of CVD.

Disclosure
Y. Matsubayashi: None. K. Fujihara: None. T. Sato: None. M. Yamamoto: None. H. Ishiguro: None. T. Osawa: None. M. Kitazawa: None. H. Suzuki: None. S. Kodama: None. T. Yamada: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.

Funding
Japan Society for Promotion of Science (JSPS) KAKENHI(JP 23K16814)
1281-P: Impact of Estimated Glomerular Filtration Rate (eGFR) on New-Onset Heart failure (HF) according to Glucose Tolerance Status
Authors: UEGAMI YOHEI , FUJIHARA KAZUYA , TAKIZAWA HIROKI , KITAZAWA MASARU , SUZUKI HIROSHI , OSAWA TAEKO , MATSUBAYASHI YASUHIRO , YAMADA TAKAHO , KODAMA SATORU , SONE HIROHITO , SHIMAYAMA CHIHIRO 
Published: June 2024

Chronic kidney disease, HF, and type 2 diabetes mellitus (DM) are common and interrelated. Although both low eGFR and high eGFR have been associated with an increased risk of cardiovascular disease in patients with DM, it is unclear whether this association differs according to glucose tolerance. Thus, we aimed to clarify the association between eGFR and the incidence of new-onset HF according glucose tolerance status in the same cohort. Study participants underwent medical checkups between 2008 and 2019. Based on glucose tolerance status they were divided into three groups (normoglycemia [n=510,300], prediabetes [n=222,327] or DM [n=42,903]). Participants were also classified by eGFR level. Risk for HF was analyzed by a multivariate Cox regression model. During a median follow-up period of 4.4 y, 362 cases of HF occurred. Compared with 60≤ eGFR &lt;90, the risk of HF significantly increased in those with eGFR ≥105 in people with prediabetes and DM. However, this association was not observed in those with normoglycemia (Table). In addition, both participants with DM and eGFR ≥105 and with DM with eGFR &lt;60 had an approximately 6-fold higher risk for HF than persons with normoglycemia and 60≤ eGFR &lt;90. Results suggested HF risk may be increased by hyperfiltration accompanied with glucose abnormality. Further studies are required to clarify the mechanisms underlying this relationship.

Disclosure
Y. Uegami: None. K. Fujihara: None. H. Takizawa: None. M. Kitazawa: None. H. Suzuki: None. T. Osawa: None. Y. Matsubayashi: None. T. Yamada: None. S. Kodama: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd. C. Shimayama: Employee; Kowa Company, Ltd.
1290-P: Developing Machine Learning Model for Predicting Acute Coronary Syndrome in Type 2 Diabetes Mellitus Patients through Substitution of Propensity Scores for Binary Variables
Authors: LEE DAVID S.U. , WON JUNG-HYUN , LEE HOWARD 
Published: June 2024

Introduction & Objective: T2DM patients have a high risk for acute coronary syndrome (ACS), requiring early and accurate risk stratification. However, traditional risk models lack generalizability for this patient population, while machine learning (ML)-based models have been plagued by inaccuracies in the training data, particularly those of binary information. Our study aims to develop an ML model for ACS prediction in T2DM patients by applying a novel data representation approach.
Methods: We used the EMRs of T2DM patients treated with basal insulin. The study unit was treatment period, during which the subjects were continuously treated with basal insulin. The primary outcome was ACS occurrence during this period. We addressed EMR inaccuracies by replacing binary information with their respective propensity scores (PS), re-defined as the probability of having a record given covariates. We used various ML algorithms to develop ACS prediction models and evaluated their performance. Additionally, the Shapley Additive Explanation (SHAP) method identified important clinical predictors of ACS.
Results: The study included 9,338 patients (mean age 60.2 years and 56.6% male) over 10,184 treatment periods. The most prevalent comorbidities were hypertension and dyslipidemia. Notably, 6.9% experienced ACS. Our best performing model achieved a 0.969 in all performance metrics. Compared with models developed via traditional methodologies, our approach improved prediction performance by over 6 percentage points. SHAP analysis showed that older age, higher baseline glucose, history of antithrombotic therapy, history of chest pain, and indicators of T2DM progression (e.g., senile cataract) were important ACS risk factors.
Conclusion: Our model showed a high generalizability for T2DM patients, improved prediction accuracy, and higher reliance on clinical predictors that align with current medical understanding.

Disclosure
D.S.U. Lee: None. J. Won: None. H. Lee: None.

Funding
the Seokchunnanum Foundation (SCY2205P); the BK21FOUR Program of the National Research Foundation of Korea (NRF) in the Ministry of Education (5120200513755)
131-OR: A Multiomics Study of Individual Responses to Long-Term Mediterranean Diet Interventions in the DIRECT-PLUS Trial
Authors: DONG DANYUE , LIU YUXI , STAMPFER MEIR , SHAI IRIS , HUTTENHOWER CURTIS , WANG DONG 
Published: June 2024

Introduction: We applied multi-omics to study individual responses to dietary interventions and their effects on the gut microbiome in a long-term randomized controlled trial of Mediterranean Diet (MedDiet).
Methods: We profiled host genetics (Global Screening Array), the gut microbiome (shotgun metagenomics), and fecal and plasma metabolomics (LC-MS) at baseline and endpoint in the 18-month DIRECT-PLUS Trial with 294 participants randomized into three groups: healthy dietary guidelines, MedDiet and MedDiet + polyphenols (Fig. 1A).
Results: We observed large variability in individuals' responses to dietary interventions: mean coefficients of variation of post-intervention changes: BMI at 92 (Fig. 1B), hs-CRP at 103, and LDL/HDL at 96. Age, sex, baseline factors, and multi-omics collectively explained the variability in post-intervention changes: BMI (4%) and fasting glucose (11%; Fig 1C). Furthermore, the integration of baseline multi-omics significantly enhanced predicting individual diet responsiveness. (AUC from 0.55 to 0.78; Fig. 1D). Our longitudinal analysis revealed MedDiet-induced alterations in metabolites and the gut microbial taxonomy (Fig. 1E, F)
Conclusion: Our study demonstrates the application of multi-omics in predicting personalized responses to dietary intervention, laying the foundation for precision nutrition in metabolic disease prevention.

Disclosure
D. Dong: None. Y. Liu: None. M. Stampfer: Advisory Panel; Elysium Health. I. Shai: None. C. Huttenhower: Advisory Panel; Seres Therapeutics, Empress Therapeutics, ZOE Nutrition. D. Wang: None.

Funding
National Institutes of Health (R01NR01999, R00DK119412, P30DK046200); Deutsche Forschungsgemeinschaft (209933838); The Israel Ministry of Health (87472511); The Israel Ministry of Science and Technology (3-13604)
1319-P: Assessment of a Comprehensive Physical Fitness Index to Predict Various Metabolic Diseases
Authors: SATO TAKAAKI , FUJIHARA KAZUYA , YAGUCHI YUTA , YAMAMOTO MASAHIKO , KITAZAWA MASARU , SUZUKI HIROSHI , MATSUBAYASHI YASUHIRO , ISHIGURO HAJIME , OSAWA TAEKO , YAMADA TAKAHO , KATO KIMINORI , SONE HIROHITO 
Published: June 2024

Although associations of the risk of developing type 2 diabetes or cardiovascular disease with muscle strength, balance, or flexibility were established separately, a comprehensive evaluation of physical fitness is required. We previously developed a composite measure of these fitness components designated as the Physical ScoreTM and reported its significant associations with the prevalence of diabetes, hypertension, dyslipidemia, fatty liver, and metabolic syndrome (MetS). We now examined longitudinal associations between the PS and incidence of these diseases.To calculate the PS data on 103,348 individuals (64,834 men) aged 30 to 69 y who underwent physical fitness assessments, principal component analysis was applied to the correlation matrix of fitness test results adjusted for age and sex. PS is close to the deviation for physical fitness, with a change in PS of 1 corresponding to a change of 10 deviations. Cox hazard regression analysis evaluated the relationship between PS at the initial assessment and subsequent development of each disease, with a minimum follow-up of 3 y. For every decrease of 1 in the PS from the initial evaluation, the hazard ratios for incident disease ranged from 1.04 to 1.22. PS was weakly associated with diabetes and most strongly associated with MetS. Findings suggest that the PS, which is convenient and non-invasive, could predict various metabolic diseases.

Disclosure
T. Sato: None. K. Fujihara: None. Y. Yaguchi: None. M. Yamamoto: None. M. Kitazawa: None. H. Suzuki: None. Y. Matsubayashi: None. H. Ishiguro: None. T. Osawa: None. T. Yamada: None. K. Kato: None. H. Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kowa Company, Ltd., Kyowa Kirin Co., Ltd., Eisai Inc., Sumitomo Dainippon Pharma Co., Ltd.