RAJAMANNAR THENNATI, VINOD S. BURADE, MUTHUKUMARAN NATARAJAN, PRADEEP SHAHI, RAVISHANKARA NAGARAJA, SUDEEP K. AGRAWAL, THIERRY DUVAUCHELLE, ADOLFO GARCIA-OCANA, GUY A. RUTTER, RICHARD E. PRATLEY, BERNARD THORENS, TINA VILSBØLL
Introduction & Objective: GL0034 (GL), a once weekly glucagon-like peptide 1 receptor agonist, previously demonstrated significant reductions in body weight (BW) up to Day 22 in a single ascending dose study in individuals with obesity. This phase 1 study assessed the safety, tolerability and metabolic effects of GL after multiple ascending doses. Methods: Individuals with BMI ≥28 kg/m2 (N=24) were randomized (9:3) to subcutaneous GL, fixed doses (4 × 680 µg; cohort 1); or increasing doses (680, 900, 1520, 2000 µg; cohort 2) or placebo, once weekly for four weeks. Safety, tolerability and key metabolic parameters were assessed. Results: Most common adverse events (AE) were gastrointestinal (GI) with dose-dependent nausea, decreased appetite and vomiting. One individual with a GI related serious AE rapidly recovered upon treatment with intravenous rehydration. On Day 23, reduction was observed in all parameters from baseline (BL) with significant reductions in glucose area under the curve and HbA1c in both groups. In cohorts 1 & 2, BW reduction versus BL was 2.9 kg and 4.6 kg respectively on Day 29 (Table). Conclusions: In individuals with obesity, once weekly GL dosing for four weeks, demonstrated clinically relevant reductions in glucose, insulin, HbA1c, lipids and BW with an overall good tolerability. Disclosure R. Thennati: None. V.S. Burade: None. M. Natarajan: None. P. Shahi: None. R. Nagaraja: None. S.K. Agrawal: None. T. Duvauchelle: Consultant; Sun Pharmaceutical Industries Ltd. A. Garcia-Ocana: Consultant; Sun Pharmaceutical Industries Ltd. G.A. Rutter: Advisory Panel; Sun Pharmaceutical Industries Ltd. R.E. Pratley: Other Relationship; Bayer AG, Dompé, Endogenex, Inc., Gasherbrum Bio, Inc., Hengrui (USA) Ltd., Intas Pharmaceuticals Ltd., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk, Novo Nordisk, Pfizer Inc., Rivus Pharmaceuticals Inc., Sun Pharmaceutical Industries Ltd. Consultant; AbbVie Inc., AstraZeneca. Other Relationship; Bayer HealthCare Pharmaceuticals, Inc., Biomea Fusion, Carmot Therapeutics, Inc., Corcept Therapeutics, Fractyl Health, Inc., Genprex. Consultant; Getz Pharma. Other Relationship; Lilly USA LLC, Sanofi. Consultant; Scholar Rock, Inc. B. Thorens: Advisory Panel; Sun Pharmaceutical Industries Ltd. T. Vilsbøll: Consultant; AstraZeneca. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Mundipharma. Advisory Panel; Novo Nordisk, Lilly Diabetes, Sanofi. Speaker's Bureau; Bayer Inc., Gilead Sciences, Inc. Advisory Panel; Sun Pharmaceutical Industries Ltd. Research Support; Lilly Diabetes.
{"title":"121-OR: Safety, Tolerability, and Metabolic Effects of Once-Weekly GL0034 (Utreglutide) in Individuals with Obesity—A Multiple Ascending Dose Study","authors":"RAJAMANNAR THENNATI, VINOD S. BURADE, MUTHUKUMARAN NATARAJAN, PRADEEP SHAHI, RAVISHANKARA NAGARAJA, SUDEEP K. AGRAWAL, THIERRY DUVAUCHELLE, ADOLFO GARCIA-OCANA, GUY A. RUTTER, RICHARD E. PRATLEY, BERNARD THORENS, TINA VILSBØLL","doi":"10.2337/db24-121-or","DOIUrl":"https://doi.org/10.2337/db24-121-or","url":null,"abstract":"Introduction & Objective: GL0034 (GL), a once weekly glucagon-like peptide 1 receptor agonist, previously demonstrated significant reductions in body weight (BW) up to Day 22 in a single ascending dose study in individuals with obesity. This phase 1 study assessed the safety, tolerability and metabolic effects of GL after multiple ascending doses. Methods: Individuals with BMI ≥28 kg/m2 (N=24) were randomized (9:3) to subcutaneous GL, fixed doses (4 × 680 µg; cohort 1); or increasing doses (680, 900, 1520, 2000 µg; cohort 2) or placebo, once weekly for four weeks. Safety, tolerability and key metabolic parameters were assessed. Results: Most common adverse events (AE) were gastrointestinal (GI) with dose-dependent nausea, decreased appetite and vomiting. One individual with a GI related serious AE rapidly recovered upon treatment with intravenous rehydration. On Day 23, reduction was observed in all parameters from baseline (BL) with significant reductions in glucose area under the curve and HbA1c in both groups. In cohorts 1 & 2, BW reduction versus BL was 2.9 kg and 4.6 kg respectively on Day 29 (Table). Conclusions: In individuals with obesity, once weekly GL dosing for four weeks, demonstrated clinically relevant reductions in glucose, insulin, HbA1c, lipids and BW with an overall good tolerability. Disclosure R. Thennati: None. V.S. Burade: None. M. Natarajan: None. P. Shahi: None. R. Nagaraja: None. S.K. Agrawal: None. T. Duvauchelle: Consultant; Sun Pharmaceutical Industries Ltd. A. Garcia-Ocana: Consultant; Sun Pharmaceutical Industries Ltd. G.A. Rutter: Advisory Panel; Sun Pharmaceutical Industries Ltd. R.E. Pratley: Other Relationship; Bayer AG, Dompé, Endogenex, Inc., Gasherbrum Bio, Inc., Hengrui (USA) Ltd., Intas Pharmaceuticals Ltd., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk, Novo Nordisk, Pfizer Inc., Rivus Pharmaceuticals Inc., Sun Pharmaceutical Industries Ltd. Consultant; AbbVie Inc., AstraZeneca. Other Relationship; Bayer HealthCare Pharmaceuticals, Inc., Biomea Fusion, Carmot Therapeutics, Inc., Corcept Therapeutics, Fractyl Health, Inc., Genprex. Consultant; Getz Pharma. Other Relationship; Lilly USA LLC, Sanofi. Consultant; Scholar Rock, Inc. B. Thorens: Advisory Panel; Sun Pharmaceutical Industries Ltd. T. Vilsbøll: Consultant; AstraZeneca. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Mundipharma. Advisory Panel; Novo Nordisk, Lilly Diabetes, Sanofi. Speaker's Bureau; Bayer Inc., Gilead Sciences, Inc. Advisory Panel; Sun Pharmaceutical Industries Ltd. Research Support; Lilly Diabetes.","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"60 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730496","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}
FIORELLA SOTOMAYOR, CHIKARA GOTHONG, REYNIER HERNANDEZ, MONICA Y. CHOE, GARRETT I. ASH, WILLIAM H. SCOTT, LILLIAN PINAULT, FERNANDO GOMEZ-PERALTA, LAKSHMI G. SINGH, JOHN D. SORKIN, ILIAS (ELIAS) SPANAKIS
Introduction & Objective: RCT aimed to assess if a Diabetes Advanced Telemedicine (DAT) clinic leads to improvement in glycemic control compared to standard of care (SoC). Methods: Patients with type 2 diabetes (T2D) randomized to DAT or SoC. DAT used continuous glucose monitoring devices, smart insulin pens, telecommunication (i.e. video visits) with physical activity (PA) counseling by an exercise physiologist. SoC used glucometers, traditional insulin pens, in-person visits and PA counseling by providers. Primary outcome was change in HbA1c. Secondary outcomes were time in range (TIR) 70-180 mg/dl, time above range (TAR)>180 mg/dl, TAR>250 mg/dl and time below range (TBR)<70 mg/dl. ANCOVA was used, adjusted for baseline value to determine the relation between group and outcome, and report p-values of the interaction term, group*time. Exercise was evaluated by senior fitness test and assessed by Hedge’s g effect size. Results: Twenty-four patients with T2D completed the trial. Non-statistically significant reductions in glucose metrics were seen. HbA1c decreased by 2.2% (DAT) vs 1.1% (SoC) (-1.1%, [-0.2, -1.8], p=0.076). TIR 70-180 mg/dL increased 17.3% vs 15.4% (+1.9%, [-16.1,15.5], p=0.984), TAR>180 mg/dL decreased 20.5% vs 17.9% (-2.6%, [-21.5,10.5], p=0.756), TAR>250 mg/dL decreased 17.1% vs 6.0% (-11.1%. [-20.3,2.7], p=0.375), TBR changed 0.41% vs -0.88% (+0.47, [-0.16,1.37], p=0.054), DAT vs. SoC, respectively. Fitness tests, completed by 60% of participants, showed improvements in medium strength (bicep curls g=0.90 /p=0.06, chair stands g=0.63/p=0.18), daily physical function (g=0.56/p=0.20), aerobic performance (6min walk test g=0.24/p=0.61), agility/flexibility (timed up and go g=-0.30/p=0.49, back stretch g=-0.51/p=0.26). Conclusions: T2D patients managed by DAT had non-significant improvement in glucose control driven by decreased hyperglycemia > 250 mg/dl. Non-significant modest increase in PA observed. Disclosure F. Sotomayor: None. C. Gothong: None. R. Hernandez: None. M.Y. Choe: None. G.I. Ash: None. W.H. Scott: None. L. Pinault: None. F. Gomez-Peralta: Advisory Panel; Abbott. Speaker's Bureau; Abbott. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Insulcloud S.L. Speaker's Bureau; Medtronic. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. Advisory Panel; Sanofi. L.G. Singh: None. J.D. Sorkin: None. I. Spanakis: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc.
简介& 目标：研究旨在评估与标准护理（SoC）相比，糖尿病高级远程医疗（DAT）诊所是否能改善血糖控制。研究方法2型糖尿病（T2D）患者随机接受DAT或SoC治疗。DAT使用连续血糖监测设备、智能胰岛素笔、远程通信（即视频访问）以及运动生理学家提供的体育锻炼（PA）咨询。SoC 使用血糖仪、传统胰岛素笔、上门访问和由医疗服务提供者提供的体育锻炼咨询。主要结果是 HbA1c 的变化。次要结果是在范围内的时间（TIR）70-180 mg/dl、高于范围的时间（TAR）>180 mg/dl、TAR>250 mg/dl和低于范围的时间（TBR）<70 mg/dl。采用方差分析，并对基线值进行调整，以确定组别与结果之间的关系，并报告交互项（组别*时间）的 p 值。运动量通过高级体能测试进行评估，并通过 Hedge's g效应大小进行评估。结果24 名糖尿病患者完成了试验。血糖指标的下降无统计学意义。HbA1c 下降了 2.2%（DAT）与 1.1%（SoC）（-1.1%，[-0.2, -1.8], p=0.076）。TIR 70-180 mg/dL 上升 17.3% vs 15.4% (+1.9%, [-16.1,15.5], p=0.984)，TAR>180 mg/dL 下降 20.5% vs 17.9% (-2.6%, [-21.5,10.5], p=0.756)，TAR>180 mg/dL 下降 20.5% vs 17.9% (-2.6%, [-21.5,10.5], p=0.756)。756），TAR>250 mg/dL 下降了 17.1% vs 6.0% (-11.1%. [-20.3,2.7], p=0.375)，TBR 变化了 0.41% vs -0.88% (+0.47, [-0.16,1.37], p=0.054)，DAT vs. SoC 分别如此。60%的参与者完成了体能测试，结果显示，他们在中等力量（二头肌卷曲 g=0.90 /p=0.06, 椅子站立 g=0.63/p=0.18）、日常身体功能（g=0.56/p=0.20）、有氧运动能力（6分钟步行测试 g=0.24/p=0.61）、敏捷性/灵活性（定时起立 g=-0.30/p=0.49, 背部伸展 g=-0.51/p=0.26）方面均有所改善。结论通过DAT治疗的T2D患者的血糖控制得到了非显著性改善，这主要归功于高血糖的减少> 250 mg/dl。观察到 PA 略有增加，但不明显。披露 F. Sotomayor：无。C. Gothong：无：C. Gothong: None.R. Hernandez：无。M.Y. Choe：无。G.I. Ash: None.W.H. Scott: None.L. Pinault：无。F. Gomez-Peralta：Advisory Panel; Abbott.Speaker's Bureau; Abbott.顾问团；礼来公司。Speaker's Bureau; Eli Lilly and Company.顾问团；Insulcloud S.L.演讲事务处；美敦力。顾问团；诺和诺德。诺和诺德公司演讲事务处。顾问团；赛诺菲。L.G. Singh：无。J.D. Sorkin：无。I. Spanakis：研究支持；Dexcom, Inc.
{"title":"1113-P: Utilizing a Novel Telemedicine Clinic for Managing Type 2 Diabetes—A Six-Month Pilot Study","authors":"FIORELLA SOTOMAYOR, CHIKARA GOTHONG, REYNIER HERNANDEZ, MONICA Y. CHOE, GARRETT I. ASH, WILLIAM H. SCOTT, LILLIAN PINAULT, FERNANDO GOMEZ-PERALTA, LAKSHMI G. SINGH, JOHN D. SORKIN, ILIAS (ELIAS) SPANAKIS","doi":"10.2337/db24-1113-p","DOIUrl":"https://doi.org/10.2337/db24-1113-p","url":null,"abstract":"Introduction & Objective: RCT aimed to assess if a Diabetes Advanced Telemedicine (DAT) clinic leads to improvement in glycemic control compared to standard of care (SoC). Methods: Patients with type 2 diabetes (T2D) randomized to DAT or SoC. DAT used continuous glucose monitoring devices, smart insulin pens, telecommunication (i.e. video visits) with physical activity (PA) counseling by an exercise physiologist. SoC used glucometers, traditional insulin pens, in-person visits and PA counseling by providers. Primary outcome was change in HbA1c. Secondary outcomes were time in range (TIR) 70-180 mg/dl, time above range (TAR)&gt;180 mg/dl, TAR&gt;250 mg/dl and time below range (TBR)&lt;70 mg/dl. ANCOVA was used, adjusted for baseline value to determine the relation between group and outcome, and report p-values of the interaction term, group*time. Exercise was evaluated by senior fitness test and assessed by Hedge’s g effect size. Results: Twenty-four patients with T2D completed the trial. Non-statistically significant reductions in glucose metrics were seen. HbA1c decreased by 2.2% (DAT) vs 1.1% (SoC) (-1.1%, [-0.2, -1.8], p=0.076). TIR 70-180 mg/dL increased 17.3% vs 15.4% (+1.9%, [-16.1,15.5], p=0.984), TAR&gt;180 mg/dL decreased 20.5% vs 17.9% (-2.6%, [-21.5,10.5], p=0.756), TAR&gt;250 mg/dL decreased 17.1% vs 6.0% (-11.1%. [-20.3,2.7], p=0.375), TBR changed 0.41% vs -0.88% (+0.47, [-0.16,1.37], p=0.054), DAT vs. SoC, respectively. Fitness tests, completed by 60% of participants, showed improvements in medium strength (bicep curls g=0.90 /p=0.06, chair stands g=0.63/p=0.18), daily physical function (g=0.56/p=0.20), aerobic performance (6min walk test g=0.24/p=0.61), agility/flexibility (timed up and go g=-0.30/p=0.49, back stretch g=-0.51/p=0.26). Conclusions: T2D patients managed by DAT had non-significant improvement in glucose control driven by decreased hyperglycemia &gt; 250 mg/dl. Non-significant modest increase in PA observed. Disclosure F. Sotomayor: None. C. Gothong: None. R. Hernandez: None. M.Y. Choe: None. G.I. Ash: None. W.H. Scott: None. L. Pinault: None. F. Gomez-Peralta: Advisory Panel; Abbott. Speaker's Bureau; Abbott. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Insulcloud S.L. Speaker's Bureau; Medtronic. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. Advisory Panel; Sanofi. L.G. Singh: None. J.D. Sorkin: None. I. Spanakis: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc.","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":"141730546","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}
HAJIME YAMAZAKI, SHIN-ICHI TAUCHI, MITSURU DOHKE, NAGISA HANAWA, YOSHIHISA KODAMA, AKIO KATANUMA, SHUNICHI FUKUHARA, KATSIARYNA PRYSTUPA, JULIA HUMMEL, ROBERT WAGNER, MARTIN HENI
Introduction & Objective: Individuals with type 2 diabetes (T2D) are thought to have a smaller pancreas; however, whether this is cause or consequence of T2D is unclear. We investigated the association between pancreas volume and T2D risk and whether this association was modified by pancreatic fat. Methods: Using magnetic resonance imaging from the UK Biobank, 25,389 individuals were classified into four groups based on the median values of pancreas volume (60 cm3) and pancreatic fat (8%). Odds ratios (ORs) for prevalent T2D were estimated using logistic regression. Additionally, we conducted a 6-year case-cohort study in an independent Japanese cohort using computed tomography during health examinations. Hazard ratios (HRs) for incident T2D were estimated using weighted-Cox regression in 658 randomly-selected individuals and 146 incident T2D cases among 2,168 individuals without diabetes. The regression models in both studies were adjusted for age, sex, body mass index, daily alcohol intake, current smoking, liver fat, and visceral fat. Results: In the UK Biobank, individuals who had fat accumulation in a smaller pancreas exhibited the highest likelihood of T2D. Compared with large/low-fat pancreas, the adjusted ORs (95%CI) of T2D were 1.63 (1.36-1.97) in small/high-fat pancreas, 1.09 (0.89-1.33) in large/high-fat pancreas, and 1.08 (0.85-1.37) in small/low-fat pancreas. This finding was prospectively validated in the Japanese cohort with 6.27-year median follow-up. The adjusted HRs (95%CI) of incident T2D were 3.12 (1.40-6.96) in small/high-fat pancreas, 1.00 (0.59-1.69) in large/high-fat pancreas, and 0.74 (0.26-2.14) in small/low-fat pancreas. Conclusion: Fat accumulation in an already smaller pancreas appears to be a key determinant of elevated T2D risk and might therefore be a novel target for preventive interventions. Disclosure H. Yamazaki: Other Relationship; AstraZeneca, Janssen Pharmaceuticals, Inc., Mitsubishi Tanabe Pharma Corporation, Kowa Company, Ltd., Kyorin Pharmaceutical Co. Ltd, Takeda Pharmaceutical Company Limited, Takeda Pharmaceutical Company Limited, Magmitt Pharmaceutical Co. S. Tauchi: None. M. Dohke: None. N. Hanawa: None. Y. Kodama: None. A. Katanuma: None. S. Fukuhara: None. K. Prystupa: None. J. Hummel: None. R. Wagner: Speaker's Bureau; Sanofi. Advisory Panel; Lilly Diabetes. Speaker's Bureau; Boehringer-Ingelheim, Novo Nordisk. M. Heni: Research Support; Boehringer-Ingelheim. Advisory Panel; Amryt Pharma Plc. Speaker's Bureau; Amryt Pharma Plc. Advisory Panel; Boehringer-Ingelheim, Boehringer-Ingelheim. Speaker's Bureau; Lilly Diabetes, Novartis AG, Novo Nordisk, Sanofi. Funding Japan Society for the Promotion of Science KAKENHI grants (JP22K15685); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation: 518749683)
{"title":"345-OR: Beyond Size Matters—The Impact of Pancreatic Volume and Pancreatic Fat on Type 2 Diabetes","authors":"HAJIME YAMAZAKI, SHIN-ICHI TAUCHI, MITSURU DOHKE, NAGISA HANAWA, YOSHIHISA KODAMA, AKIO KATANUMA, SHUNICHI FUKUHARA, KATSIARYNA PRYSTUPA, JULIA HUMMEL, ROBERT WAGNER, MARTIN HENI","doi":"10.2337/db24-345-or","DOIUrl":"https://doi.org/10.2337/db24-345-or","url":null,"abstract":"Introduction & Objective: Individuals with type 2 diabetes (T2D) are thought to have a smaller pancreas; however, whether this is cause or consequence of T2D is unclear. We investigated the association between pancreas volume and T2D risk and whether this association was modified by pancreatic fat. Methods: Using magnetic resonance imaging from the UK Biobank, 25,389 individuals were classified into four groups based on the median values of pancreas volume (60 cm3) and pancreatic fat (8%). Odds ratios (ORs) for prevalent T2D were estimated using logistic regression. Additionally, we conducted a 6-year case-cohort study in an independent Japanese cohort using computed tomography during health examinations. Hazard ratios (HRs) for incident T2D were estimated using weighted-Cox regression in 658 randomly-selected individuals and 146 incident T2D cases among 2,168 individuals without diabetes. The regression models in both studies were adjusted for age, sex, body mass index, daily alcohol intake, current smoking, liver fat, and visceral fat. Results: In the UK Biobank, individuals who had fat accumulation in a smaller pancreas exhibited the highest likelihood of T2D. Compared with large/low-fat pancreas, the adjusted ORs (95%CI) of T2D were 1.63 (1.36-1.97) in small/high-fat pancreas, 1.09 (0.89-1.33) in large/high-fat pancreas, and 1.08 (0.85-1.37) in small/low-fat pancreas. This finding was prospectively validated in the Japanese cohort with 6.27-year median follow-up. The adjusted HRs (95%CI) of incident T2D were 3.12 (1.40-6.96) in small/high-fat pancreas, 1.00 (0.59-1.69) in large/high-fat pancreas, and 0.74 (0.26-2.14) in small/low-fat pancreas. Conclusion: Fat accumulation in an already smaller pancreas appears to be a key determinant of elevated T2D risk and might therefore be a novel target for preventive interventions. Disclosure H. Yamazaki: Other Relationship; AstraZeneca, Janssen Pharmaceuticals, Inc., Mitsubishi Tanabe Pharma Corporation, Kowa Company, Ltd., Kyorin Pharmaceutical Co. Ltd, Takeda Pharmaceutical Company Limited, Takeda Pharmaceutical Company Limited, Magmitt Pharmaceutical Co. S. Tauchi: None. M. Dohke: None. N. Hanawa: None. Y. Kodama: None. A. Katanuma: None. S. Fukuhara: None. K. Prystupa: None. J. Hummel: None. R. Wagner: Speaker's Bureau; Sanofi. Advisory Panel; Lilly Diabetes. Speaker's Bureau; Boehringer-Ingelheim, Novo Nordisk. M. Heni: Research Support; Boehringer-Ingelheim. Advisory Panel; Amryt Pharma Plc. Speaker's Bureau; Amryt Pharma Plc. Advisory Panel; Boehringer-Ingelheim, Boehringer-Ingelheim. Speaker's Bureau; Lilly Diabetes, Novartis AG, Novo Nordisk, Sanofi. Funding Japan Society for the Promotion of Science KAKENHI grants (JP22K15685); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation: 518749683)","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":"141730548","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}
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
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
{"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}
ABIR ELBEJI, MÉGANE PIZZIMENTI, GLORIA A. AGUAYO, AURELIE FISCHER, HANIN AYADI, FRANCK MAUVAIS-JARVIS, JEAN-PIERRE RIVELINE, VLADIMIR DESPOTOVIC, GUY FAGHERAZZI
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.
{"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}
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
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.
{"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}
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.
{"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}
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
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
{"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 &lt;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}
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
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)
{"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 &lt; 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 &lt; 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}
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
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)
{"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&lt;5x10-08): PNPLA3, PPP1R3B, HAPLN4, intergenic region on chr14 and F11-AS1. Nine additional variants trended toward association (P&lt;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}
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