Diabetes最新文献

{"title":"229-OR: Orforglipron Improves Markers of Beta-Cell Function and Insulin Sensitivity in Type 2 Diabetes","authors":"JULIO ROSENSTOCK, DEBORAH A. ROBINS, KEVIN L. DUFFIN, JONATHAN M. WILSON, KIEREN J. MATHER, HIYA BANERJEE, YANZHU LIN, SARAH EYDE, CHRISTOF M. KAZDA, MANIGE KONIG","doi":"10.2337/db24-229-or","DOIUrl":"https://doi.org/10.2337/db24-229-or","url":null,"abstract":"Orforglipron (OFG), an oral, non-peptide GLP-1 receptor agonist, demonstrated significantly greater glycemic control and weight loss at doses ≥12 mg vs placebo (PBO) or dulaglutide (DU) 1.5 mg in a 26-week phase 2 study of adults with type 2 diabetes (T2D) (Table). These exploratory analyses investigated mechanisms by which OFG improved glycemic control in T2D by analyzing exploratory biomarkers. Participants with T2D (mean age, 58.9 years; baseline HbA1c, 8.1%; weight, 100.3 kg) treated with diet and exercise, with/without metformin, were randomized to PBO, DU 1.5 mg, or once-daily OFG 3, 12, 24, 36, or 45 mg. Biomarkers of β-cell function and insulin sensitivity were analyzed by mixed model repeated measures, excluding data after study drug discontinuation or rescue drug initiation. Biomarkers of β-cell function were improved by OFG at 26 weeks from baseline (Table). HOMA-B significantly increased with OFG at doses ≥12 mg vs PBO or DU. HOMA-IR (computed with insulin) significantly decreased from baseline with OFG at doses ≥24 mg but was not significantly different vs PBO and DU. Fasting glucose-adjusted glucagon significantly decreased with OFG at doses ≥12 mg vs PBO and with OFG 12, 24, and 45 mg vs DU. These analyses suggest improved glycemic control with OFG vs DU may be partly explained by improved β-cell function and insulin sensitivity. Additional studies are ongoing to understand these mechanisms. Disclosure J. Rosenstock: Research Support; Biomea Fusion, Inc. Other Relationship; Lilly Diabetes. Research Support; Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Corcept Therapeutics. Other Relationship; Novo Nordisk. Research Support; Pfizer Inc. Other Relationship; Sanofi, Boehringer-Ingelheim. Research Support; Shionogi & Co., Ltd. Other Relationship; Structure Therapeutics, Inc. Advisory Panel; Terns Pharmaceuticals, Zealand Pharma A/S. Other Relationship; Applied Therapeutics, Hanmi Pharm. Co., Ltd., Oramed Pharmaceuticals. Advisory Panel; Scholar Rock. D.A. Robins: None. K.L. Duffin: Employee; Eli Lilly and Company. J.M. Wilson: Employee; Eli Lilly and Company. K.J. Mather: Employee; Eli Lilly and Company. H. Banerjee: None. Y. Lin: Stock/Shareholder; Eli Lilly and Company, Pfizer Inc., AstraZeneca. S. Eyde: None. C.M. Kazda: Employee; Eli Lilly and Company. M. Konig: None. Funding Eli Lilly and Company","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"35 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"1308-P: A Voice-Based AI Algorithm Can Predict Type 2 Diabetes Status—Findings from the Colive Voice Study on U.S. Adult Participants","authors":"ABIR ELBEJI, MÉGANE PIZZIMENTI, GLORIA A. AGUAYO, AURELIE FISCHER, HANIN AYADI, FRANCK MAUVAIS-JARVIS, JEAN-PIERRE RIVELINE, VLADIMIR DESPOTOVIC, GUY FAGHERAZZI","doi":"10.2337/db24-1308-p","DOIUrl":"https://doi.org/10.2337/db24-1308-p","url":null,"abstract":"Introduction: Reducing undiagnosed type 2 diabetes (T2D) cases worldwide is an urgent public health challenge. Most current screening methods are invasive, lab-based, and costly. Meanwhile, there is a growing focus on noninvasive T2D detection through advanced artificial intelligence (AI) and digital technology. This study explores the feasibility of using a voice-based AI algorithm to predict T2D status in adults, a preliminary step toward innovative screening tools. Objective: To develop and assess the performance of a voice-based AI algorithm for T2D status detection in the adult population in the US. Methods: We analyzed text reading voice recordings from 607 US participants from the Colive Voice study, adhering to the CONSORT AI standards. We trained and cross-validated algorithms with BYOL-S/CvT embeddings for each gender, evaluating them on accuracy, precision, recall, and AUC. Performance of the best models was stratified by age, BMI, and hypertension, and compared to the American Diabetes Association (ADA) score for T2D risk assessment using a Bland-Altman analysis. Results: We analyzed 323 females and 284 males; Females with T2D (age: 49.5 years, BMI: 35.8 kg/m²) vs without (40.0 years, 28.0 kg/m²). Males with T2D (47.6 years, 32.8 kg/m²) vs without (41.6 years, 26.6 kg/m²). The voice-based algorithm achieved good overall predictive capacity (AUC=75% for males, 71% for females) and correctly predicted 71% of male and 66% of female T2D cases. It is enhanced in females aged 60 years (AUC=74%) or older but also with the presence of hypertension for both genders (AUC=75%). We observed an overall agreement above 93% with the ADA risk score. Conclusion: This study demonstrates the feasibility of detecting T2D using exclusively voice features. It is the first step toward using voice analysis as a first-line T2D screening strategy. While the findings are promising, further research and validation are necessary to specifically target early-stage T2D cases. Disclosure A. Elbeji: None. M. Pizzimenti: None. G.A. Aguayo: None. A. Fischer: None. H. Ayadi: None. F. Mauvais-Jarvis: None. J. Riveline: Board Member; Abbott, Novo Nordisk A/S, Sanofi, Eli Lilly and Company, Medtronic, Dexcom, Inc., Insulet Corporation, Air Liquide, AstraZeneca. V. Despotovic: None. G. Fagherazzi: Speaker's Bureau; Sanofi. Advisory Panel; Timkl, SAB Biotherapeutics, Inc., Vitalaire, Roche Diabetes Care.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"43 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"1928-LB: Feasibility of Calibration-Free Intradermal Glucose Monitoring Using a Sensor Microarray","authors":"MARK P. CHRISTIANSEN, NARESH C. BHAVARAJU, REBECCA GOTTLIEB, ALAN CAMPBELL, SIRILAK SATTAYASAMITSATHIT, MARK C. BRISTER, KEITH NOGUEIRA, AMY L. VANDENBERG, RICH YANG, JARED R. TANGNEY","doi":"10.2337/db24-1928-lb","DOIUrl":"https://doi.org/10.2337/db24-1928-lb","url":null,"abstract":"Introduction: Subcutaneous glucose sensors using introducer needles have been well characterized. Robust microsensors are required for a less invasive approach, accessing interstitial glucose in the dermis. Advancements in semiconductor manufacturing have facilitated new sensing technologies using arrays of silicon microsensors on a wearable patch without introducer needles. Several independent electrodes on the microarray chip support redundancy and reliability. The objective of this study was to evaluate the performance of a calibration-free, intradermal glucose sensor, compared to a gold standard. Methods: A 5-day study was conducted at two US sites evaluating the device in persons with Diabetes. Intradermal glucose sensors were placed on the volar forearm or upper arm. All subjects participated in one clinic day on Day 1, 3, or 5 of wear. Venous blood was obtained every 15 minutes for 8 hours and analyzed with the YSI (YSI Inc, Yellow Springs, Ohio) 2300 Stat Plus. A prospective, calibration-free algorithm was used. Results: 19 subjects with Type 1 diabetes ages 19 to 70 were studied. Mean Absolute Relative Difference (MARD) was 10.1% compared to YSI (n=388). 83.2% of paired points were within 20% of YSI and 100% were within Clark Error Grid A+B regions. Conclusion: The intradermal glucose sensor demonstrated accurate tracking and trending of glucose levels compared to the gold standard laboratory analyzer. Disclosure M.P. Christiansen: Research Support; Abbott Diagnostics, Amgen Inc., Biolinq, Boehringer-Ingelheim, Dexcom, Inc., Eli Lilly and Company, Google, Lilly Diabetes, MannKind Corporation, Medtronic, Novo Nordisk, Pfizer Inc., Roche Diabetes Care, REMD Biotherapeutics, ViaCyte, Inc. N.C. Bhavaraju: Employee; Biolinq. R. Gottlieb: Employee; Biolinq. A. Campbell: Employee; Biolinq. S. Sattayasamitsathit: Employee; Biolinq. M.C. Brister: Employee; Biolinq. K. Nogueira: Employee; Biolinq. A.L. VandenBerg: Employee; Biolinq. J.R. Tangney: Employee; Biolinq.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"47-48 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"1229-P: Blood Glycated Albumin or Fructosamine (GA/Fruc) Rather Than Hemoglobin A1c (A1C) Is Useful for Specifying Individuals Having a Macrosomic Baby—Meta-analysis","authors":"SATORU KODAMA, TAKAHO YAMADA, NORIKO YAGYUDA, KAZUYA FUJIHARA, LAY MON KHIN, MASARU KITAZAWA, MASAHIKO YAMAMOTO, YASUHIRO MATSUBAYASHI, KIMINORI KATO, HIROHITO SONE","doi":"10.2337/db24-1229-p","DOIUrl":"https://doi.org/10.2337/db24-1229-p","url":null,"abstract":"Introduction & Objective: Poor glycemic control (GC) increases the risk of various pregnancy complications. Both A1C and GA/Fruc are convenient as they require only one measurement and do not impose fasting. However, GA/Fruc is possibly a better predictor of complications than A1C during pregnancy when GC quickly changes. This meta-analysis compared the predictive ability of pregnancy complications between A1C and GA/Fruc. Methods: We comprehensively searched for studies of prediction of maternal or neonatal adverse outcomes using both A1C and GA/Fruc and for their best cut-off values in each study presenting 2 x 2 data (i.e., true-positive, false-negative, true-negative, and false-positive cases). Results: Of 9 eligible studies, 7 predicted macrosomia and could be meta-analyzed using a hierarchical summary receiver-operating characteristic (HSROC) model. Other complications were impossible to be analyzed because of an insufficient number of data. Pooled specificity (95% confidence interval [CI]) was significantly higher (P=0.02) for GA/Fruc (0.83 [0.70-0.91]) compared with A1C (0.57 [0.35-0.77]) while pooled sensitivity (95% CI) was 0.44 (0.26-0.63) for GA/Fruc and 0.67 (0.50-0.81) for A1C (P for difference, 0.17). Conclusion: Compared with A1C, GA/Fruc is useful for specifying individuals having a macrosomic baby. Disclosure S. Kodama: None. T. Yamada: None. N. Yagyuda: None. K. Fujihara: None. L. Khin: None. M. Kitazawa: None. M. Yamamoto: None. Y. Matsubayashi: 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.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"48 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"240-OR: Longitudinal Assessment of Glycemia and Severe Hypoglycemia among Adults with Type 1 Diabetes—An Online Survey","authors":"JENNIFER L. SHERR, KAITLIN HAGAN, RACHEL BHAK, MEGAN PETER, HUYEN NGUYEN, CHENKUN WANG, TATHABBAI PAKALAPATI, JORDAN SHERWOOD, TINA GUPTA, JASON L. GAGLIA, EMILEE M. CORNELIUS, KATHERINE S.M. CHAPMAN, WENDY WOLF, JEREMY PETTUS","doi":"10.2337/db24-240-or","DOIUrl":"https://doi.org/10.2337/db24-240-or","url":null,"abstract":"Introduction & Objective: Longitudinal trends of glycemia and severe hypoglycemic events (SHE) among individuals with T1D are not well described, particularly in those using diabetes technologies (i.e., continuous glucose monitors [CGM], automated insulin delivery [AID]). Methods: An online survey recruited adults with T1D through the T1D Exchange Registry or online communities from February-April 2021. Overall, 2,044 individuals completed the survey and eligible participants were invited to complete follow-up survey from April-May 2023. Participants self-reported CGM use, insulin delivery method, HbA1c, impaired awareness of hypoglycemia (IAH), and SHE. Results: Of 1,999 eligible individuals, 1,056 completed the follow-up survey and were eligible for analysis (53% response rate; mean age: 46 y; mean T1D duration: 29 y; 71% female; 97% White). Most reported using CGMs at baseline (91.8%) and follow-up (94.4%), and use of AID increased (baseline: 53.5%; follow-up: 69.0%; Table). At baseline, 61.7% reported HbA1c <7% vs. 67.4% at follow-up. Rates of IAH and SHE in the prior year were similar at both time points. Conclusion: Despite nearly universal CGM usage and increased adoption of AID, one-third of respondents did not achieve HbA1c targets and the proportion of respondents with IAH and SHE did not decline. These results highlight the need for innovative approaches to improve T1D care. Disclosure J.L. Sherr: Consultant; Medtronic. Advisory Panel; Medtronic, Insulet Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Vertex Pharmaceuticals Incorporated, MannKind Corporation, StartUp Health T1D Moonshot, Bigfoot Biomedical, Inc., Cecelia Health. Speaker's Bureau; Zealand Pharma A/S. K. Hagan: Employee; Vertex Pharmaceuticals Incorporated. R. Bhak: Employee; Vertex Pharmaceuticals Incorporated, Novartis Pharmaceuticals Corporation. M. Peter: None. H. Nguyen: None. C. Wang: Employee; Vertex Pharmaceuticals Incorporated. T. Pakalapati: None. J. Sherwood: Employee; Vertex Pharmaceuticals Incorporated. T. Gupta: Employee; Vertex Pharmaceuticals Incorporated. J.L. Gaglia: Consultant; Vertex Pharmaceuticals Incorporated. Stock/Shareholder; Vertex Pharmaceuticals Incorporated. Consultant; Avotres Inc., Imcyse, Diamyd Medical. E.M. Cornelius: None. K.S.M. Chapman: None. W. Wolf: None. J. Pettus: Consultant; Sanofi, Novo Nordisk, Diasome, Carmot Therapeutics, Inc., Kriya Therapeutics, Lilly Diabetes, Provention Bio, Inc. Funding Vertex Pharmaceuticals Incorporated","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"26 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"155-OR: Genetic Variation and Time to Progression in TN10 (Teplizumab)","authors":"DOMINIKA A. MICHALEK, SUNA ONENGUT-GUMUSCU, WEI-MIN CHEN, TODD M. BRUSKO, ANDREA STECK, PETER GOTTLIEB, RICHARD A. ORAM, JEFFREY KRISCHER, HEMANG M. PARIKH, MARIA J. REDONDO, KEVAN C. HEROLD, STEPHEN S. RICH","doi":"10.2337/db24-155-or","DOIUrl":"https://doi.org/10.2337/db24-155-or","url":null,"abstract":"Introduction & Objective: TN10 Anti-CD3 Prevention (TN10) was a randomized phase 2 clinical trial that showed teplizumab delayed progression to type 1 diabetes (T1D) in high-risk participants. Both HLA and non-HLA variants could influence time to progression. Here, genome-wide analysis identified variants and pathways that influence time to progression in TN10 participants. Methods: In TN10, relatives with stage 2 T1D (i.e., multiple autoantibodies and dysglycemia) received either teplizumab (N = 44) or placebo (N = 32). Samples were genotyped with a genome-wide array followed by imputation. Cox proportional hazards regression models were used to determine the effect of teplizumab, SNPs, and their interaction on time to progression to stage 3 T1D. Thousands of Polygenic Scores (PGSs) from the PGS catalogue were inferred for each of the TN10 samples, and we identified PGS traits that shared common genetic modifiers with time to progression with teplizumab. Results: A genome-wide analysis identified three loci associated with time to progression (p < 5 x 10-6). Two loci contain genes implicated in the inflammatory response (NFKBIZ) and drug metabolism effect (FMO3). SNP-drug interaction analysis identified four known T1D regions that account for progression differences in teplizumab vs placebo: CCR9 (rs34549672), SH2B3 (rs3184504), UBASH3A (rs9984852), and INS (rs3842761). Within the teplizumab group, novel loci (p < 5 x 10-6) were associated with time to progression, including ZNF385D, CCDC38, SHH, ZNF366, ITPKB and RABGAP1L. Traits with similar genetic contribution to teplizumab time to progression were vitamin B12 (AUC = 0.76) and vitamin D (AUC = 0.72). Conclusions: In individuals with stage 2 T1D, variants in inflammatory, immune-relevant, and drug-responsive genes are associated with teplizumab time to progression. Similarity of the teplizumab-responsive polygenic score with other traits implicate novel pathways that could influence teplizumab treatment. Disclosure D.A. Michalek: None. S. Onengut-Gumuscu: None. W. Chen: None. T.M. Brusko: None. A. Steck: None. P. Gottlieb: Other Relationship; IM Therapeutics. Research Support; Imcyse. Advisory Panel; Imcyse. Consultant; Juvenile Diabetes Research Foundation (JDRF). Research Support; Hemsley Charitable Trust, Novartis AG, Provention Bio, Inc., Precigen, Inc. Advisory Panel; ViaCyte, Inc. Research Support; Nova Pharmaceuticals. R.A. Oram: Research Support; Randox R & D. Consultant; Provention Bio, Inc., Sanofi. J. Krischer: None. H.M. Parikh: None. M.J. Redondo: None. K.C. Herold: Consultant; Sanofi. S.S. Rich: None. Funding National Institutes of Health (1R01DK121843-01)","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"92 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"348-OR: Multiancestry Whole Genome Sequencing (WGS) Meta-analysis to Identify Loci Associated with Imaging-Measured Hepatic Steatosis","authors":"NICHOLETTE ALLRED, CHINMAY RAUT, YANHUA CHEN, ANTONINO OLIVERI, JEFFREY O'CONNELL, KATHLEEN RYAN, JEROME I. ROTTER, STEPHEN S. RICH, AARON HAKIM, PATRICIA PEYSER, LAWRENCE F. BIELAK, CHING-TI LIU, JAMES G. TERRY, MYRIAM FORNAGE, LYNNE E. WAGENKNECHT, ELIZABETH K. SPELIOTES, NHLBI TRANS-OMICS FOR PRECISION MEDICINE (TOPMED)PROGRAM, GOLD CONSORTIUM","doi":"10.2337/db24-348-or","DOIUrl":"https://doi.org/10.2337/db24-348-or","url":null,"abstract":"Introduction and Objective: Steatotic liver disease, formerly called non-alcoholic fatty liver disease (NAFLD), is the most common cause of chronic liver disease worldwide; yet, few effective methods for prevention/treatment exist making it one of the biggest unmet public health needs of our time. To date, genetic studies have been limited to identifying common variants in predominantly European-ancestry populations or focused on surrogate phenotypes, e.g. liver enzymes, identifying association with comorbidities. Here we present a multi-ancestry whole genome sequencing (WGS) association study to discover rare variants associated with imaging-measured hepatic steatosis. Methods: Study-, ancestry- and sex-stratified association analyses were conducted using SAIGEgds in nine studies with imaging-measured hepatic steatosis adjusted for age, sex, alcoholic drinks per week and principal component estimates of admixture. Stratified results were meta-analyzed using a fixed-effects model. Cochran’s Q-test and the I2 metric were used to estimate heterogeneity. Results: Meta-analyses included 23,156 European, African, Hispanic and Chinese ancestry individuals and identified five significant loci (P<5x10-08): PNPLA3, PPP1R3B, HAPLN4, intergenic region on chr14 and F11-AS1. Nine additional variants trended toward association (P<5x10-07). Sex-stratified meta-analyses revealed additional associations in an intergenic region on chr10, RP11-115J16.1 and UBE3B. Variants in RP11-115J16.1 remained significant in European ancestry samples. Significantly associated variants in SLC2A1-AS1 and LINC01684 were novel loci in African Americans. Conclusion: Taken together, multi-ancestry analysis of imaging-measured hepatic steatosis using WGS replicated previously associated loci and identified novel sex- and ancestry-specific loci. Functional studies are underway to determine the biological impact of these findings. Disclosure N. Allred: None. C. Raut: None. Y. Chen: None. A. Oliveri: None. J. O'Connell: None. K. Ryan: None. J.I. Rotter: None. S.S. Rich: None. A. Hakim: None. P. Peyser: None. L.F. Bielak: None. C. Liu: None. J.G. Terry: None. M. Fornage: None. L.E. Wagenknecht: None. E.K. Speliotes: Other Relationship; University of Michigan. Funding National Institute of Diabetes and Digestive Kidney Disease (R01 DK128871)","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"79 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"1301-P: Frequency of Single Autoantibody Positivity (SAB+) Varies by Race/Ethnicity and Area Deprivation Index in Individuals at Risk for Type 1 Diabetes (T1D)","authors":"ANANTA ADDALA, SUSANNE M. CABRERA, DAVID D. CUTHBERTSON, INGRID LIBMAN, MUSTAFA TOSUR, ALEJANDRO F. SILLER, LINDA A. DIMEGLIO, KEVAN C. HEROLD, MARIA J. REDONDO, HEBA M. ISMAIL","doi":"10.2337/db24-1301-p","DOIUrl":"https://doi.org/10.2337/db24-1301-p","url":null,"abstract":"Introduction & Objective: The diversity of individuals living with T1D has increased, driven by Hispanic (H) and non-Hispanic Black (NHB) populations. Yet, whether H and NHB populations have different rates of SAB+ than other groups, which can impact clinical care and research opportunities, has not been well characterized. Area deprivation and race/ethnicity are strongly associated with each other and have compounding and adverse effects on diabetes-related health outcomes. We examined TrialNet data from relatives of persons with T1D screened for pancreatic autoantibodies and evaluated the frequency of SAB+ by race/ethnicity and area deprivation. Methods: Persons (n=28330) screened between 4/9/19-12/31/22 were included. Race/ethnicity was categorized as non-Hispanic white (NHW), H, NHB, and non-Hispanic other (NHO). Home address zip codes were used to assign an Area Deprivation Index, a Health and Human Services Administration index incorporating neighborhood income, education, employment, and housing that ranges from 1 (least deprived) to 100 (most deprived). Deprivation was analyzed in quintiles. Results: A majority (80.7%) self-identified as NHW; fewer as H (9.8%), NHB (2.5%), and NHO (7.0%). Deprivation differed by race/ethnicity (NHW 46±23, H: 45±24, NHB: 53±23, and NHO: 39±25, p<0.001). SAB+ was more common in NHB and H than NHO and NHW individuals (Overall: 3.0%, NHB: 4.7%, H: 3.8%, NHO: 3.1%, NWH: 3.0%; χ2 p=0.02). Logistic regression identified a linear relationship between SAB+ and deprivation (Deprivation quintiles 1 to 5: 2.9%, 2.7%, 3.1%, 3.1%, 3.5%; p=0.04). Conclusion: These data suggest SAB+ status varies by both race/ethnicity and deprivation which warrants further investigation. Understanding patterns of autoantibody positivity that occur in diverse populations at risk for T1D is foundational to identifying persons who are SAB+ or in early stages of T1D who may now be eligible for preventive therapies. Disclosure A. Addala: None. S.M. Cabrera: Research Support; Abbott. D.D. Cuthbertson: None. I. Libman: None. M. Tosur: None. A.F. Siller: None. L.A. DiMeglio: Research Support; Dompé, Lilly Diabetes, MannKind Corporation, Medtronic, Provention Bio, Inc., Sanofi, Zealand Pharma A/S, Amgen Inc. Advisory Panel; Vertex Pharmaceuticals Incorporated, Abata Therapeutics. K.C. Herold: Consultant; Sanofi. M.J. Redondo: None. H.M. Ismail: Consultant; Sanofi, Rise Therapeutics.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"340 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"235-OR: Quality of Life and Health Utility 12 Years after Randomization to Bariatric Surgery vs. Medical Therapy in Patients with Type 2 Diabetes and Obesity—The ARMMS-T2D Study","authors":"DONALD C. SIMONSON, WILLIAM F. GOURASH, DAVID ARTERBURN, BO HU, SANGEETA R. KASHYAP, MARY-ELIZABETH PATTI, PHILIP SCHAUER, DAVID E. CUMMINGS, ANITA COURCOULAS, ALI AMINIAN, JOHN M. JAKICIC, ASHLEY H. VERNON, JOHN P. KIRWAN","doi":"10.2337/db24-235-or","DOIUrl":"https://doi.org/10.2337/db24-235-or","url":null,"abstract":"Introduction & Objective: T2D and obesity are associated with reduced quality of life (QoL) and health utility (HU), but long-term effects of metabolic/bariatric surgery (MBS) vs. a medical/lifestyle intervention (MLI) on these outcomes are not known. Methods: We studied 228 patients with T2D and obesity who were randomized to MBS (RYGB, gastric band, or sleeve gastrectomy; n = 152) vs. MLI (n = 76) in the ARMMS-T2D study. QoL (SF-36; including Physical Component Score [PCS], Mental Component Score [MCS], and 8 scale scores) and HU (SF-6D) were measured annually for 12 yrs. Results: At baseline, age = 49.2 ± 8.0 yrs., 68% were female, 68% White, BMI = 36.3 ± 3.4 kg/m², HbA1c = 8.7 ± 1.6%. PCS improved significantly in MBS at year 1, remained higher vs. MLI over 12 yrs. (p < 0.001), and was associated with better general health (p < 0.001), physical function (p = 0.001), energy (p = 0.003), and reduced pain (p = 0.03). Change in BMI was greater after MBS vs. MLI (-18.6 ± 12.4% vs. -11.4 ± 10.9%, p < 0.001), and significantly correlated with change in PCS (r = -0.43, p < 0.001). In contrast, MCS (p = 0.14), emotional well-being (p = 0.53), role emotional (p = 0.43), and social functioning (p = 0.11) did not change from baseline and were similar between groups over 12 yrs. Changes in PCS and MCS were not associated with change in HbA1c. Among patients taking insulin at baseline, those who discontinued insulin had higher PCS (p < 0.001) over time. HU was moderately low at baseline (0.69 ± 0.08) and did not change significantly in either group during 12 yrs. Conclusions: MBS produced sustained weight loss that correlated with improved PCS, including better general health, physical function, energy, and less pain. PCS improved more in patients who discontinued insulin. There were no significant differences between groups over time in MCS or in HU. These differences may help patients with T2D and obesity make informed decisions about their best treatment options. Disclosure D.C. Simonson: Stock/Shareholder; Phase V Technologies, Inc. Advisory Panel; GI Windows. W.F. Gourash: None. D. Arterburn: None. B. Hu: None. S.R. Kashyap: Research Support; Fractyl Health, Inc. Advisory Panel; GI Dynamics. Research Support; Janssen Pharmaceuticals, Inc. M. Patti: Research Support; Dexcom, Inc. Consultant; Hanmi Pharm. Co., Ltd., MBX Biosciences. Other Relationship; Fractyl Health, Inc. Consultant; AstraZeneca, Spruce Biosciences. P. Schauer: Research Support; Ethicon, Inc. Other Relationship; Ethicon, Inc. Research Support; Medtronic. Other Relationship; Medtronic, Novo Nordisk. Advisory Panel; Lilly Diabetes, GI Dynamics, Heron. Stock/Shareholder; Mediflix, SE Healthcare. Other Relationship; Klens. Advisory Panel; Persona, Keyron. Stock/Shareholder; Metabolic Health International LTD. D.E. Cummings: None. A. Courcoulas: Research Support; Allurion, Eli Lilly and Company. A. Aminian: Research Support; Medtronic. Consultant; Medt","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"9 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"349-OR: Reduction of RNA-Editing Enzyme ADAR1 in Human Islets Triggers an Interferon Response and Impairs Beta-Cell Function","authors":"CHUNHUA DAI, AJAY K. SINGH, REBEKAH BRANTLEY, AMBER BRADLEY, REGINA JENKINS, DIANE C. SAUNDERS, MARCELA BRISSOVA, EREZ LEVANON, AGNES KLOCHENDLER, YUVAL DOR, ALVIN C. POWERS","doi":"10.2337/db24-349-or","DOIUrl":"https://doi.org/10.2337/db24-349-or","url":null,"abstract":"Introduction & Objective: It is thought that viral infection triggers islet inflammation, an interferon signature, and autoimmunity resulting in type 1 diabetes. Despite extensive research, an inciting virus has not been identified. We hypothesized that impaired RNA editing and accumulation of double-stranded RNA in beta cells triggers an interferon response, causing islet inflammation, autoimmunity, and beta cell destruction. While RNA editing regulated by adenosine deaminases acting on RNA (ADAR) has been studied in some organs and in cancer, little is known about the role of ADAR in human islets. Method: To elucidate the role of ADAR1 in human islets, we first studied ADAR expression and distribution in human pancreas across postnatal developmental timeline (1 day, 4 months, 2, 6, 10, 35 years). Then we transduced human pseudoislets with a shRNA for ADAR and examined their function and gene expression. The transduced pseudoislets were also transplanted into NSG mice. Insulin secretion was measured and grafts were studied. Results: We found that ADAR1 expression at all ages was greater in endocrine cells than acinar cells. Using the shRNA approach, ADAR mRNA levels were reduced by 70% (n=11 donors). After 7-day culture, expression of dsRNA sensors, IFNB1, IRF7, IRF9, and interferon-stimulated genes was increased while INS and MAFA expression was reduced in ADAR knockdown islets without changes in insulin secretion. However, 3 weeks post transplantation, glucose/arginine-stimulated human insulin secretion was significantly decreased in mice with the ADAR shRNA graft compared with scrambled shRNA control graft (0.117 vs 0.300 ng/mL, p=0.0001, n=3 donors). Analysis of pseudoislet grafts 4 weeks after transplantation showed marked accumulation of mouse CD45+ cells around ADAR-knockdown islet grafts. Conclusion: Interruption of RNA editing in human islets activates the interferon signaling pathway leading to islet inflammation and beta cell dysfunction. Disclosure C. Dai: None. A.K. Singh: None. R. Brantley: None. A. Bradley: None. R. Jenkins: None. D.C. Saunders: None. M. Brissova: None. E. Levanon: Advisory Panel; ADARX, Exsilio. A. Klochendler: None. Y. Dor: None. A.C. Powers: None.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"19 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}