bluuebunny/crossref_metadata_2025 huggingface dataset:
1024-P: Identification of Sex-Specific Cytokine and Viral Infection Profiles in Type 1 Diabetes Patients
Authors: GIRDHAR KHYATI , PINA ALEJANDRA , MOMIROV JELENA , ATKINSON MARK A. , LADNER JASON , ALTINDIS EMRAH
Published: May 2022

Type 1 Diabetes (T1D) is an autoimmune disease caused by the destruction of beta cells. Because both viral infections and cytokines are suggested to play a role in T1D pathogenesis, we analyzed the viral infection and cytokine profiles of T1D patients compared to age and sex-matched healthy controls. The median age in years of T1D patients was 16.9 ± 1.14 (mean ± SEM) and 17.88 ± 0.78 for the healthy subjects. The disease duration in years was 8 ± 1.1 (n=25, 13 females, 12 males) . We first assessed the viral infection history using a PepSeq-based highly multiplexed serological assay. This assay covers the full proteomes of human viruses and determines serum immunoglobulin-G (IgG) reactivity to 30mer viral peptides. We showed that enterovirus (EV) seropositivity were distinct between the two groups, with more EV-C and EV-D positives in the T1D samples and more EV-A and EV-B positives in the controls. The trends for the viruses showing higher seropositivity were primarily driven by the female patients. To determine the cytokine profiles, we measured the serum levels of 48 cytokines, chemokines and growth factors. Interestingly, we only observed significant sex-specific differences. For example, anti-inflammatory cytokines interleukin-4 (IL-4) , IL-13, IL-22, and pro-inflammatory cytokines IL-17E and tumor necrosis factor-β were significantly lower in female patients as compared to female controls. Male patients had increased levels of epidermal growth factor and platelet-derived growth factor compared to healthy males. IL-22 was unique, unlike the decrease in female patients, it increased in the male patients compared to healthy males. Altogether, we identified sex-dependent alterations in the cytokine profiles and observed a difference in EV exposure profiles between T1D patients and healthy subjects. Determining sex-specific cytokine profiles and the potential role of viral infections in T1D pathogenesis will help us to gain deeper insight into the pathogenesis of the disease.

Disclosure

K.Girdhar: n/a. A.Pina: None. J.Momirov: None. M.A.Atkinson: None. J.Ladner: None. E.Altindis: None.

Funding

NIH NIDDK 1K01DK117967-G. Harold & Leila Y. Mathers Foundation grants to EA
1032-P: Improving CGM Uptake in Minority Youth and Youth with Poorly Controlled T1D
Authors: LIN TYGER L. , MANFREDO JACQUELYN A. , ILLESCA NICOLE , ABIOLA KAI , HWANG NEARRY , SEEL MAUREEN , BROWN ELIZABETH A. , WOLF RISA M.
Published: May 2022

Background: Continuous glucose monitoring (CGM) improves glycemic control for youth with type 1 diabetes (T1D) . Despite these benefits, less than half of youth with T1D use CGM.

Objective: To determine if trial CGM use (10-days) increases CGM uptake and is associated with improved glycemic control among minority youth and youth with poorly controlled T1D. We also examined barriers to CGM use.

Methods: This prospective study was conducted at an academic Pediatric Diabetes Center. Youth with T1D for more than 3 months, with no previous CGM usage, or no CGM usage in the last year were enrolled. Diabetes staff placed CGM at the point of care (POC) and provided CGM education. Barriers to prior CGM use, hemoglobin A1c (HbA1c) , and demographic information were recorded. Participants received 5 and 10-day follow up calls from the diabetes team to review glycemic trends. At 3 months, participants' use of CGM and HbA1c were recorded.

Results: Youth with T1D (n=22) were enrolled (13 first time CGM users, 9 past users) , mean age 14.1years (SD 3.1) , 41% non-Hispanic black, 68% female, mean diabetes duration 6.3 ± 4.4years, and baseline mean HbA1c of 10.8%. Patient-cited barriers to prior CGM use included technical difficulties (n=5) , unawareness of CGM (n=4) , difficulty obtaining CGM (n=4) , general apprehension (n=3) , not wanting devices (n=3) , and pain, fear of needles, and new diabetes diagnosis (n=1 each) . Of participants, 20 completed some follow-up, and 18/20 (90%) cited wanting to use CGM long-term. Of 13 participants who completed 3 and/or 6-month follow-up visits, only 9 were actively using CGM. Further barriers to use included insurance issues (n=2) and CGM falling off (n=1) . There was no change in mean HbA1c from baseline to follow-up (10.8 ±2.4% vs. 10.3 ±2.3%, p=0.46) .

Conclusion: There are many barriers to CGM uptake in youth. Providing a trial use of CGM at the POC may increase uptake of CGM use in at-risk diabetes populations, but further investigation of additional barriers that impact long-term adherence to CGM is needed.

Disclosure

T.L.Lin: None. J.A.Manfredo: None. N.Illesca: None. K.Abiola: None. N.Hwang: None. M.Seel: None. E.A.Brown: None. R.M.Wolf: Consultant; NEMA Research, Research Support; Dexcom, Inc.

Funding

Johns Hopkins Children's Center Innovation Award, and Dexcom
1039-P: Association of GDM Risk Factors with Glucose at Diagnosis and Treatment in Sweden
Authors: FADL HELENA E. , PATIL SNEHAL , WIKSTRÖM ANNA-KARIN , JANSSON STEFAN P. , SENGPIEL VERENA , BERNTORP KERSTIN , RYEN LINDA , AHLSSON FREDRIK , LINDHOLM ELISABETH S. , STREVENS HELENA , WENNERHOLM ULLA-BRITT , PERSSON MARTINA , DE BRUN MARYAM , MONTGOMERY SCOTT , SIMMONS DAVID
Published: May 2022

Background: The screening strategy in Sweden for GDM is mainly based on random plasma glucose measurements combined with presence of risk factors (previous GDM or LGA (large for gestational age) /macrosomia, obesity, heredity, accelerated growth or polyhydramnios) . The association of risk factors with mean levels of glucose in the diagnostic OGTT in different populations is unclear.

Method/Material: Data from Changing Diagnostic Criteria for GDM in Sweden (CDC4G) - a stepped wedge randomised RCT (ISRCTN41918550) where centers during 2018 were randomized to switch to new IADPSG criteria for GDM every month. All pregnant women underwent a venous OGTT during 2018. Mean glucose values by risk factor are presented with 95% CI, significant p value <0. (marked bold in the table) .

Results: Of 53 124 pregnancies 69 (13.0%) underwent venous OGTT. Either metformin or Insulin was used in 11% before the diagnostic criteria switch and 18.8% after the switch. Metformin only was used in 9.7% before and in 16.4% after randomization to new criteria.

Conclusions: BMI≥35 or Previous LGA/macrosomia were associated with a higher fasting glucose value in OGTT, but previous GDM, accelerated growth and high random blood glucose were statistically significantly associated with higher glucose values in all measurements in the diagnostic OGTT. Women with previous GDM had the highest proportion treated with either insulin and/or metformin

Disclosure

H.E.Fadl: None. H.Strevens: None. U.Wennerholm: None. M.Persson: None. M.De brun: None. S.Montgomery: None. D.Simmons: Other Relationship; Elsevier, Research Support; Abbott, Hitachi, Ltd., Novo Nordisk, Speaker's Bureau; Sanofi. S.Patil: None. A.Wikström: None. S.P.Jansson: None. V.Sengpiel: None. K.Berntorp: None. L.Ryen: None. F.Ahlsson: None. E.S.Lindholm: None.

Funding

Swedish Research Council (2018-00470)
1061-P: Need for Insulin Therapy in Gestational Diabetes Mellitus: A Predictive Model Assessment
Authors: CAPORUSSO MARIANGELA , GIOIA LUDOVICO DI , SORICE GIAN PIO , CIGNARELLI ANGELO , NATALICCHIO ANNALISA , GIORGINO FRANCESCO , LAVIOLA LUIGI
Published: May 2022

A significant portion of pregnant women with Gestational Diabetes Mellitus (GDM) eventually requires insulin therapy, thus necessitating closer monitoring. In this study, we assessed a predictive model for the need of insulin therapy in women with GDM. In a retrospective cohort study, baseline data from 246 women with GDM (43% on subsequent insulin therapy, 57% on nutritional therapy alone) were analyzed using logistic regression. Diagnosis of GDM in previous pregnancies, previous GDM managed with insulin therapy, previous maternal impaired fasting glucose, fasting serum glucose diagnostic for GDM, and 0h and 2h diagnostic values at 75-g oral glucose tolerance test were independent qualitative significant predictors for subsequent insulin therapy. Pre-conceptional maternal body mass index, fasting serum glucose, HbA1c and gestational age at GDM diagnosis were independent quantitative significant predictors for subsequent insulin therapy. According to the odds ratios produced by the logistic regression, a risk score was developed, with identification of low (score <10, p <0.001) , moderate (score ≥and <14, p = 0.052) and high (score ≥14, p < 0.001) risk categories for need of insulin therapy during pregnancy. The area under the ROC curve (AUC) for the internal validation of the predictive model was 0.724. The risk assessment tool was then validated with an independent cohort of 22 GDM women, resulting in a similar predictive power (AUC = 0.744) . Thus, a simple risk score based on easily available clinical and biochemical data at the first visit can predict the need for insulin therapy in GDM women, leading to closer monitoring and timely initiation of therapy in pregnancies at higher risk.

Disclosure

M.Caporusso: Other Relationship; Eli Lilly and Company. L.Di gioia: Other Relationship; Eli Lilly and Company, Menarini Group. G.Sorice: None. A.Cignarelli: None. A.Natalicchio: Consultant; Novo Nordisk, Other Relationship; AstraZeneca, Lilly Diabetes, Sanofi. F.Giorgino: Advisory Panel; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk, Consultant; Lilly Diabetes, Sanofi, Research Support; Lilly Diabetes, Roche Diabetes Care, Takeda Pharmaceutical Company Limited. L.Laviola: Advisory Panel; Lilly Diabetes, Novo Nordisk, Roche Diabetes Care, Sanofi, Speaker's Bureau; A. Menarini Diagnostics, Abbott Diabetes, Medtronic, Terumo Corporation.
1070-P: Association between Social Determinants of Health and Risk of Type 2 Diabetes in Young Adults Aged 18–45
Authors: ZHANG YAHAN , ZHANG PING , PAVKOV MEDA E. , WANG YU , GUO JINGCHUAN , ZHANG YONGKANG , SHAO HUI
Published: May 2022

Objective: The prevalence of diagnosed diabetes among adults aged 18-45 years old continues to increase. Since type 2 diabetes (T2D) is preventable through lifestyle modification, implementing lifestyle intervention in those at high risk for T2D may help to reduce the overall diabetes burden. A better understanding of how social determinants of health (SDOH) are related to T2D risk can help to better identify those who are at high risk of T2D for intervention. This study aims to examine the association between a wide array of SDOH factors and risk of T2D in young adults aged 18-45.

Methods: We included data on 14,325 individuals with and without T2D in the 2007-2016 National Health and Nutrition Examination Survey. Forty-four factors covering three SDOH domains (education access and quality, economic stability, and healthcare access and quality) in the databases were selected. Stepwise logistic regression was used to identify statistically significant SDOH risk factors for T2D and estimate the corresponding odds ratios (OR) and 95% confidence intervals (CI) , controlling for age, sex and race/ethnicity.

Results: Among 14,325 sampled individuals, 394 (2.75%) had T2D. SDOH risk factors that were associated with a higher risk of T2D included educational level below high school (OR: 1.89, 95% CI: 1.22-2.86, ref: education above high school) , receiving social security/railroad retirement income (1.89 [1.38-2.56], ref: not receiving social security income) , receiving food stamp benefit (1.45 [1.11- 1.89], ref: not receiving food stamp benefit) , unstable housing (1.50 [1.16-1.93], ref: owning a house) , unstable employment (1.34 [1.04-1.73], ref: stable employment) , and having a higher number of meals not prepared at home in a week (1-10: 1.36 [1.00-1.86]; ≥11: 2.23 [1.35-3.68], ref: 0) . SDOH factors play an important role in the risk of T2D in young adults.

Conclusions: Our findings may help improve tools for screening or prevention of T2D in clinical and community settings.

Disclosure

Y.Zhang: None. P.Zhang: None. M.E.Pavkov: None. Y.Wang: None. J.Guo: None. Y.Zhang: None. H.Shao: Board Member; BRAVO4HEALTH, LLC.
1071-P: A Scoping Review on Diabetes Management in People with Mild Cognitive Impairment (MCI) : Glycemic Control, Medications, and Onset of Alzheimer's and Related Dementias (ADRD)
Authors: ABULOHA SUMAYA , ALSHEHRI ALAA A. , OSPINA NAYKKY SINGH , JAFFEE MICHAEL , SHAO HUI
Published: May 2022

Controversy exists in diabetes management after the onset of MCI, and the ideal treatment goals and medication use in this population remain inconclusive. This review aimed to comprehensively summarize the existing literature on diabetes management after MCI onset, focusing on the change of A1c goals, medication choices, and the risk of ADRD onset. We conducted a systematic literature search in PubMed (2000.1.1-2021.9.30) to identify studies related to mild cognitive impairment, glycemic goal, and medication use after MCI onset. Study types include guidelines, clinical trials, and observational studies. A standard literature searching process including title/abstracts screening, duplication removal, eligibility assessment, and data extraction was conducted by two reviewers independently. We have identified 30 studies addressing the management of diabetes in patients with MCI. The study contents were categorized into two main focuses; glycemic control (moderate vs. intensive) and the role of medications in delaying ADRD onset. Most guidelines recommend individualized goal setting to a relaxed glycemic target to avoid hypoglycemia after MCI onset. On the other hand, existing evidence linked improved glycemic control with a lower risk of ADRD onset. Observational studies and small-sized trials found the use of metformin, TZD, DPP4, and GLP-1 receptor agonists may be able to slow down the cognitive function decline. However, whether such effects were attributable to improved glycemic control or other mechanisms such as neutral protective effect is inconclusive. The risk-benefit tradeoff in glycemic control is vital in diabetes population with MCI. A large gap exists in understanding the underlying mechanism for the potential protective effect of cognitive function from glucose-lowering medications.

Disclosure

S.Abuloha: None. A.A.Alshehri: None. N.Singh ospina: None. M.Jaffee: Advisory Panel; Novo Nordisk. H.Shao: Board Member; BRAVO4HEALTH, LLC.
1075-P: Racial/Ethnic Differences in the Association between Frailty and Depression among Adults with Diabetes
Authors: EGEDE LEONARD E. , DAWSON APRILL Z. , CAMPBELL JENNIFER A. , WALKER REBEKAH J.
Published: May 2022

Individuals with diabetes are at increased risk of developing depression. The prevalence of depression in non-Hispanic Blacks (NHB) with diabetes is about 25%, higher than the prevalence among non-Hispanic Whites (NHWs) . Frailty, a measure of biological age and one’s increased susceptibility to negative health outcomes and has been found to be associated with disability and dependency. The aim of this study was to examine the association between depression and frailty and to understand whether this association differs by race/ethnicity among adults with diabetes. Data on 3792 adults with diabetes from NHANES (2003-2005) were analyzed. Depression was assessed using scores from the 9-item Patient Health Questionnaire (PHQ-9) . Frailty index composed of 46 variables (comorbidities, disability, symptoms, labs, general health) was created ranging from 0 - 1 (frail>=0.21; not frail<0.21) . Unadjusted and adjusted linear regression models were used to assess the association between depression and frailty. Covariates included age, sex, education, income-to-poverty ratio, marry, insurance, employment, smoke, physical activity, and body mass index. All models were stratified by race/ethnicity. Unadjusted models showed an association depression and frailty across all racial/ethnic groups with those who were frail having significantly higher PHQ9 scores (NHW: b 2.63; 95%CI:1.36, 3.89; NHB: b 3.26; 95%CI:2.23, 4.23; Hispanic/Other (H/O) : b 1.33; 95%CI:0.52, 2.14) . The association remained significant across all groups in adjusted models (NHW: b 4.5; 95%CI:1.9, 7.1; NHB: b 6.3; 95%CI:4.2, 8.4; H/O: b 2.1; 95%CI:0.5, 3.7) .While depression was associated with frailty across all racial/ethnic groups, NHBs who were frail had the highest mean PHQ9 score. Additional research is needed to identify the key drivers of this relationship and potential targets for home-based lifestyle intervention to improve care provided to and outcomes for frail patients with diabetes.

Disclosure

L.E.Egede: None. A.Z.Dawson: None. J.A.Campbell: None. R.J.Walker: None.

Funding

American Diabetes Association (1-19-JDF-075) ; National Institute of Diabetes and Digestive and Kidney Diseases (grant K24DK093699, R01DK118038, R01DK120861, Principal Investigator (PI) : Leonard Egede, MD) National Institute on Minority Health and Health Disparities (R01MD013826, PI: Egede/Walker)
1076-P: Racial/Ethnic Differences in the Association between Frailty and Clinical Outcomes among Adults with Diabetes
Authors: DAWSON APRILL Z. , WALKER REBEKAH J. , CAMPBELL JENNIFER A. , EGEDE LEONARD E.
Published: May 2022

Racial/ethnic minorities with diabetes have increased risk of complications. Frailty, an indicator of increased vulnerability to adverse health outcomes is associated with dependency and disability. The aim of this study was to examine the association between frailty and clinical outcomes (blood pressure (BP) , hemoglobinA1C (HbA1C) , low-density lipoprotein (LDL)) and whether associations differ by race/ethnicity among adults with diabetes. Data on 3792 adults with diabetes from NHANES (2003-2005) were analyzed. Frailty index composed of 46 variables (comorbidities, disability, symptoms, labs, general health) was created ranging from 0 - 1 (frail>=0.21; not frail<0.21) . Linear regression models were used to assess the association between clinical outcomes and frailty. Models were adjusted for age, sex, education, income-to-poverty ratio, marry, insurance, employment, smoke, physical activity, and body mass index; and were stratified by race/ethnicity. Unadjusted models showed an association between systolic BP (SBP) and frailty with those who were frail having significantly higher SBP (NHW: b 19.6; 95%CI:2.5,26.2; non-Hispanic Black (NHB) : b 6.22; 95%CI:0.95,11.5; Hispanic/Other (H/O) : b 13.5;95%CI:7.7, 19.3) ; significantly lower diastolic BP (DBP) for H/O (b -5.5;95%CI:-8.9,-2.1) , and significantly lower HbA1c for NHW (b -0.60;95%CI:-0.99,-0.20) compared to not frail. In adjusted models, frailty was associated with lower DBP for H/O (b -9.8; 95%CI:-17.8,-1.8) , higher LDL for H/O (b 154;95%CI:97.5,210.6) , and higher HbA1C for NHWs (b 0.91;95%CI:0.004,1.8) and NHBs (b 2.5;95%CI:0.97,4.0) . Associations between frailty and clinical outcomes differed by race/ethnicity among adults with diabetes. Frailty should be assessed as part of routine care for patients with diabetes and interventions accounting for limitations and cultural differences of diverse groups of frail adults with diabetes should be developed to improve clinical outcomes.

Disclosure

A.Z.Dawson: None. R.J.Walker: None. J.A.Campbell: None. L.E.Egede: None.

Funding

American Diabetes Association (1-19-JDF-075) ; National Institute of Diabetes and Digestive and Kidney Diseases (grant K24DK093699, R01DK118038, R01DK120861, Principal Investigator (PI) : Leonard Egede, MD) National Institute on Minority Health and Health Disparities (R01MD013826, PI: Egede/Walker)
108-LB: Ultrarapid Lispro (URLi) Improved Postprandial Glucose (PPG) Excursion vs. Humalog (HL) in Predominantly Chinese Adult Patients with Type 2 Diabetes (T2D)
Authors: ZHOU JIAN , CHEN SI , CHENG JIE , SHEN LI , ZHU JIANKUN , LOU YING , BAO YUQIAN , JIA WEIPING
Published: May 2022

URLi is a novel formulation of insulin lispro developed to better match physiological insulin response to a meal that demonstrates faster absorption and onset of action than HL. This study aimed to evaluate the efficacy and safety of URLi vs. HL in predominantly Chinese adult patients with T2D. It was a Phase 3, randomized, double-blind study, in which patients with T2D randomly received URLi (395 patients) or HL (200 patients) plus glargine or degludec for 26 weeks. The primary endpoint was the treatment difference in the change in HbA1c from baseline to Week 26 (noninferiority margin 0.4%) . The treatment differences in the 1- and 2-hour PPG excursions at Week 26 were assessed as the multiplicity-adjusted endpoints. URLi achieved noninferiority to HL on change in HbA1c with least squares mean difference (95% confidence interval) of 0.07% (-0.07, 0.21) . URLi was superior to HL in controlling 1-hour (4.8 mmol/L vs. 5.6 mmol/L, P <0.001) and 2-hour PPG excursions (6.2 mmol/L vs. 7.4 mmol/L, P <0.001) at Week 26. A greater decrease in daily mean 1- and 2-hour PPG excursions with URLi than HL from baseline to Week 26 was observed in the 10-point self-monitored blood glucose profile. Increase in the dose of bolus insulin from baseline to Week 26 was slightly higher with URLi than HL (0.21 U/kg/day vs. 0.18 U/kg/day, P=0.045) . During the 26-week treatment period, both groups showed similar and low rate and incidence of severe hypoglycemia and documented symptomatic hypoglycemia. The incidences of serious adverse events and treatment-emergent adverse events were comparable between both groups. URLi vs. HL in a basal-bolus regimen demonstrated noninferior glycemic control as assessed by HbA1c and superior control on PPG excursions in predominantly Chinese adult patients with T2D with a similar safety profile.

Disclosure

J. Zhou: n/a. S. Chen: None. J. Cheng: Employee; Eli Lilly and Company. L. Shen: Employee; Eli Lilly and Company. J. Zhu: Employee; Eli Lilly and Company. Y. Lou: None. Y. Bao: None. W. Jia: None.

Funding

Eli Lilly and Company
1084-P: Trends in Cardiovascular Risk Factors (CRF) for Youth with Incident Diabetes: The SEARCH for Diabetes in Youth Study
Authors: BELL RONNY A. , RIGDON JOSEPH , BELLATORRE ANNA , DABELEA DANA , DAGOSTINO RALPH , DIVERS JASMIN , DOLAN LAWRENCE M. , IMPERATORE GIUSEPPINA , JENSEN ELIZABETH T. , LIESE ANGELA D. , LUSTIGOVA EVA , MARCOVINA SANTICA M. , MERJANEH LINA , PETTITT DAVID J. , PIHOKER CATHERINE , SHAH AMY S. , SOUTH ANDREW M. , WAGENKNECHT LYNNE E.
Published: May 2022

To examine CRF trends that may impact future CVD risk, the SEARCH study assessed CRF for diabetes-related complications in incident cohorts established from 2002 - 2016. Linear regression was used to assess trends over each incident year for non-HDL-c, LDL-c, VLDL-c, TG, BMI z-score, systolic and diastolic blood pressure (BP) z-scores, albumin/creatinine ratio (ACR) and eGFR. Models were stratified by diabetes type (Type 1, N=4600; Type 2, N=932) , adjusted for age at diagnosis, sex, DM duration and race/ethnicity. An interaction analysis was conducted to assess differential time trends by type. For youth with type 1, non-HDL-c, BP, BMI and ACR >30 decreased while HDL-c increased over time. For youth with type 2, non-HDL-c, and eGFR decreased, and BMI increased over time (table) . Significant time change interactions by type were seen for HDL-c and for BMI z-score and BP measures (table) .We observed small but significant changes in several CRFs over time in youth with incident DM, especially lipids, with greater improvements seen in youth with type 1. Youth with type 2 had worsening trends over time in BMI, BP, and kidney function. Further research is needed to better understand these trends and their implications for long term CVD risk.

Disclosure

R.A.Bell: None. A.D.Liese: None. E.Lustigova: None. S.M.Marcovina: None. L.Merjaneh: None. D.J.Pettitt: n/a. C.Pihoker: None. A.S.Shah: None. A.M.South: None. L.E.Wagenknecht: None. J.Rigdon: None. A.Bellatorre: None. D.Dabelea: None. R.Dagostino: Consultant; Aetion, Inc., AstraZeneca, Biogen, Bristol-Myers Squibb Company, Daiichi Sankyo, Merck & Co., Inc. J.Divers: None. L.M.Dolan: None. G.Imperatore: None. E.T.Jensen: Consultant; Regeneron Pharmaceuticals Inc.

Funding

Centers for Disease Control and Prevention U18DP006131
109-LB: An Investigation into Local Infusion Site Pain after Infusion of URLi Excipients across Sites and Depths
Authors: IGNAUT DEBRA A. , FUKUDA TSUYOSHI , RAMANJINEYULU BANDI , ERMER MARCEL , STOFFEL MARC S. , ZIJLSTRA ERIC , PAAVOLA D
Published: May 2022

A Phase 1, randomized, 1-day 5-period crossover study in adults with type 1 diabetes on CSII investigated whether pain is dependent on the site and/or depth of infusion of ultra rapid lispro (URLi) excipients.

Forty participants (mean age 40.5 years; BMI 27.5) were randomized to 1 of 5 infusion site sequences consisting of the abdomen, arm, thigh, and buttock (6 mm cannula depth) , and abdomen (9 mm depth) . Basal infusion of sodium citrate, treprostinil, and magnesium chloride in diluent was initiated (1 U/h) and 15 unit-equivalent boluses were given at 3, 6, and 9 h after basal initiation. Participants rated local infusion site pain perception by the 0-100 mm validated visual analog scale (VAS) at 5 min before bolus and 1 and 15 min post bolus.

An increased VAS score was occasionally reported at 1 min post bolus, more frequently for the arm. Most scores were ≤10 mm (little to no discomfort) while 7 of 577 were >45 mm (generally considered clinically meaningful pain) . VAS score distributions were similar between cannula depths (Figure) . After 15 min, scores were similar to pre bolus. No participants discontinued the study.

Local infusion site discomfort after infusion of URLi excipients was reported by a subset of participants; it was transient, tolerable, and dependent on infusion site. Given differences among sites within individuals, patients may consider changing infusion site if they experience discomfort.

Disclosure

D. A. Ignaut: None. T. Fukuda: Employee; Eli Lilly and Company. B. Ramanjineyulu: None. M. Ermer: None. M. S. Stoffel: None. E. Zijlstra: Speaker’s Bureau; Gan & Lee Pharmaceuticals, Novo Nordisk. D. Paavola: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company.

Funding

Eli Lilly and Company
109-OR: Physiologic Subtypes of Gestational Glucose Intolerance and Risk of Future Prediabetes
Authors: SELEN DARYL J. , THAWEETHAI TANAYOTT , YU CHU , HSU SARAH , JAMES KAITLYN , ECKER JEFFREY L. , MEIGS JAMES B. , POWE CAMILLE E.
Published: May 2022

Background: Gestational glucose intolerance (GGI, abnormal initial gestational diabetes [GDM] screen) conveys an increased risk of future diabetes (DM) , even when GDM criteria is not met. We previously defined subtypes of GGI/GDM according to the underlying mechanism leading to hyperglycemia (insulin resistance vs. deficiency) . We aimed to determine if GGI subtypes are at differential risk for future prediabetes/DM; we hypothesized increased risk with insulin deficient subtypes.

Methods: We defined GGI as glucose loading test 1-hr glucose ≥ 140 mg/dL at > 22 weeks’ gestation. We applied homeostasis model assessment (HOMA) to fasting glucose and insulin at 16-20 weeks’ gestation and classified pregnancies with GGI without GDM into subtypes according to the presence of insulin resistance and/or deficiency. We used Cox proportional-hazards models with time-varying exposures to assess risk of preDM/DM (HbA1c ≥ 5.7% at ≥ 3 months after delivery) in each GGI subtype compared to pregnancies with normal glucose tolerance after adjustment for age, race/ethnicity, health insurance, and first trimester BMI. Women were censored at the time of last HbA1c or GDM diagnosis.

Results: Of 671 women with a median 9.9 years of follow-up, 29% (n=196) developed preDM/DM. Among pregnancies in 113 women with GGI, 54% had the insulin resistant subtype (IR) , 25% had the insulin deficient subtype (ID) , and 16% had the mixed pathophysiology subtype (MP) . Subtypes with insulin deficiency (ID + MP) and insulin resistance (IR) were both associated with increased risk of preDM/DM (ID + MP hazard ratio [HR]=1.8 [1.1-2.9], p=0.02 and IR HR=1.7 [1.1-2.6], p=0.01) . Each insulin deficient subtype also appeared to carry increased risk: ID HR=1.7 (0.9-3.1, p=0.12) and MP HR=2.1 (1.0-4.2, p=0.048) .

Conclusions: GGI confers an increased risk of future prediabetes/DM, regardless of the mechanism leading to glucose intolerance. A combination of insulin resistance and deficiency may convey the highest risk of future prediabetes/DM.

Disclosure

D.J. Selen: None. T. Thaweethai: None. K. James: None. J.L. Ecker: None. J.B. Meigs: Consultant; Quest Diagnostics. C.E. Powe: None.

Funding

National Institutes of Health (T32DK007028) , Massachusetts General Hospital (Physician Scientist Development Award and Claflin Distinguished Scholar’s Award)
11-OR: Transcriptome Heterogeneity in Insulin-Positive Insulitic vs. Noninsulitic Human Islets in Type 1 Diabetes (T1D)
Authors: DYE ALYSSA M. , ASHBERY GRACE , LENCHIK NATALIYA I. , ATKINSON MARK A. , MATHEWS CLAYTON E. , CAMPBELL-THOMPSON MARTHA , GERLING IVAN C.
Published: May 2022

Insulitis involves the infiltration of predominantly CD3+ T cells in islets in a patchy distribution between lobes in a pancreas. We hypothesized that gene expression profiling of insulin containing islets (INS+CD3-) vs. insulin containing insulitic islets (INS+CD3+) would show heterogeneity in autoimmune and ßcell dysfunction pathways within the same donor. Pancreatic islets were obtained by laser-capture microdissection from nPOD donors (5 autoantibody positive nondiabetic (AAb+) and 6 T1D) . Transcriptome data was collected and compared in 83 individual islets. INS+CD3+ islets were compared to the average of all INS+CD3- islets in each donor. For each INS+CD3+ islet we created two registries of genes >2-fold up or >2-fold downregulated that were analyzed to detect differences in pathways and ontologies. Islets were analyzed based on five categories: immunity, mitochondrial, metabolism, secretion, and cell signaling. A majority of donors (64%) had all 5 categories represented in either up or downregulated pathways. The most upregulated category in T1D donor islets was immunity (39%) and most downregulated was secretion (33%) . These islets were distinguished by extreme heterogeneity in signaling pathways. In AAb+ donor islets, the most upregulated category was immunity (32%) , with the most downregulated noted as metabolism (21%) . Similarly, AAb+ donor islets had heterogeneity in signaling pathways. In contrast, we observed great intra-donor heterogeneity; each individual islet had 65% unique genes upregulated and 58% downregulated compared to other INS+CD3+ islets within the same donor.

In summary, similar themes of up or downregulated categories were noted in INS+CD3+ compared to averaged INS+CD3- islets. Most strikingly, significant heterogeneity between INS+CD3+ islets within donors at the individual gene levels was observed. These findings indicate substantial complexity of pancreatic islet destruction leading to T1D.

Disclosure

A.M.Dye: None. G.Ashbery: None. N.I.Lenchik: n/a. M.A.Atkinson: None. C.E.Mathews: None. M.Campbell-thompson: Consultant; TRex Bio. I.C.Gerling: None.

Funding

NIH-NIDDK (HIRN-CBDS) UC4 DK104155-01LeBonheur Children’s Foundation Research Institute (CFRI) Fellows Research Grant
1102-P: Identifying Blood Biomarkers for Type 2 Diabetes Subtyping: A Report from the ORIGIN Trial
Authors: PIGEYRE MARIE , GERSTEIN HERTZEL C. , GROOP LEIF , HESS SIBYLLE , PARE GUILLAUME
Published: May 2022

Diabetes (DM) can be classified into 5 subtypes characterized by distinct progression in dysglycaemia and complications. Using 5 clinical variables, we categorized 7017 participants from the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial into 1/auto-immune DM (n=241) , 2/insulin-deficient DM (n=1594) , 3/insulin-resistant DM (n=914) , 4/obesity-related DM (n=1595) , 5/age-related DM (n=2673) .Yet, whether blood biomarkers are associated with these subtypes is unknown. Forward-selection logistic regression models were used to identify biomarkers that were each independent determinant of one cluster versus the others, among 233 selected cardiometabolic proteins measured at baseline. Models were adjusted for age, sex, ethnicity, C-peptide level, diabetes duration. A total of 13, 2, 7 and biomarkers were independent determinants of DM subtypes 2 to 5 respectively (all P<4.3x10-5) . A combination of 5 biomarkers that were distinctively associated with clusters (fig) , showed a diagnosis performance, through AUC-ROC curves, of 0.71, 0.86, 0.88, 0.82 to respectively distinguish cluster 2 to 5 from the others. No biomarkers other than GAD antibodies were determinants of cluster 1. We identified 5 serum biomarkers, as independent determinants of DM subtypes, that could be used as a diagnosis test for DM subtyping. Although this requires further validation in an independent population.

Disclosure

M.Pigeyre: n/a. H.C.Gerstein: Advisory Panel; Abbott, Eli Lilly and Company, Hanmi Pharm. Co., Ltd., Novo Nordisk, Pfizer Inc., Sanofi, Viatris Inc., Consultant; Kowa Company, Ltd., Other Relationship; DKSH, Eli Lilly and Company, Sanofi, Zuellig Pharma Holdings Pte. Ltd., Research Support; AstraZeneca, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk, Sanofi. L.Groop: None. S.Hess: Employee; Sanofi. G.Pare: Advisory Panel; Amgen Inc., Bayer AG, Sanofi, Research Support; Bayer AG.

Funding

NCT00069784 Canadian Institute of Health Research Sanofi
1104-P: Prevalence and Clinical Determinants of Nonalcoholic Fatty Liver Disease by Liver Scores in Adults with T1DM
Authors: LUNDHOLM MICHELLE D. , BENA JAMES F. , ZHOU KEREN , TSUSHIMA YUMIKO , KASHYAP SANGEETA
Published: May 2022

NAFLD is common in diabetes, however the prevalence and clinical features of NAFLD in T1DM are not well defined.

A retrospective, unicenter, cross-sectional analysis was performed of adults with T1DM at our institution from 2015-2018. The hepatic steatosis index (HSI) , Framingham steatosis index (FSI) , FIB-4 index, and AST-to-platelet ratio index (APRI) were calculated and associated with clinical parameters.

We identified 447 patients, 38.6 ± 14.5 yrs, 54% (N=241) female, HgA1c 8.4 ± 1.8 %, BMI 28 ± 5.9 kg/m2. The prevalence of NAFLD by HSI ≥36 was 61% (N=271) and by FSI ≥23 was 52% (N=230) . The presence of advanced fibrosis by APRI >0.7 was 4% (N=18) and FIB-4 >2.67 was 4% (N=8 of 221 included) . Patients with metabolic syndrome (N=103, 23%) were significantly more likely to have NAFLD by HSI (86% vs. 53%, p<0.001) and FSI (93% vs. 39%, p<0.001) . Compared to BMI <30, nearly all patients with BMI ≥30 (N=125, 28%) had NAFLD by HSI (100% vs. 45%, p<0.001) and FSI (98% vs. 34%, p<0.001) . Older age (44 vs. 33 yrs) , HTN, HLD, cardiovascular disease, and higher TG/HDL ratio (median 1.8 vs. 1.1) were associated with FSI ≥23. Older age (41 vs. 30 years) , HTN, HLD, and lower HDL (58 vs. 66 mg/dL) were associated with HSI ≥36. On multivariable analysis, older age, metabolic syndrome features, and BMI were associated with higher HSI and FSI. HgA1c was inversely related to HSI. Twenty of 94 patients (21%) with abdominal imaging reported hepatic steatosis; 8 (2%) had hepatology referral and 6 (1%) had a liver biopsy. Of 447 patients, GLP-1 agonist was prescribed in 5% (N=24) and thiazolidinedione in 4% (N=16) .

Liver scores indicating liver steatosis but not fibrosis is common in adults with T1DM with obesity and/or metabolic syndrome, and is associated with older age, HTN, HLD, and high TG/HDL. NAFLD is overlooked; only 21% of patients had any liver imaging and only 1% had a liver biopsy. Thiazolidinedione and GLP-1 agents are effective at preventing and reversing NAFLD damage but appear underutilized in the T1DM population.

Disclosure

M.D.Lundholm: None. J.F.Bena: None. K.Zhou: None. Y.Tsushima: None. S.Kashyap: Advisory Panel; Fractyl Health, Inc., GI Dynamics, Research Support; Janssen Pharmaceuticals, Inc.
1107-P: Is There a Discrepancy between Interstitial Glucose and Laboratory HbA1c in People Living with HIV?
Authors: DAULTREY HARRIET , LEVETT TOM , WRIGHT JULIET , OLIVER NICK , CHAKERA ALI
Published: May 2022

Background: Diabetes is reported to be more common in people living with HIV (PLWH) . There is no internationally agreed screening method for diabetes in PLWH due to reports that HbA1c is falsely low in this group. The ADA recommend a fasting glucose to screen for diabetes in PLWH whilst the British HIV Association recommend measuring HbA1c.

Aims: To explore the relationship between HbA1c and interstitial glucose in PLWH. Methods Each participant wore a Dexcom G6 for days and had HbA1c measured. Exclusion criteria included factors affecting HbA1c. HbA1c values were compared to GMI values. Bland-Altman plot method was used to assess the agreement between the measurements.

Results: We included 57 PLWH (27 with T2DM, 6 female) , median HbA1c 44mmol/mol (IQR 38-55) , average sensor glucose 7.3mmol/l (IQR 6.4-9.1) . Median completed CGM readings per participant 99% (IQR 92-99) . Bland-Altman plot method (see figure) demonstrates the bias between the two methods is -3.2mmol/mol (95% CI: -1.0 to -5.6) with 95% limits of agreement -14.2 to 20.6. Six participants had an HbA1c 10mmol/mol lower than GMI and 2 had an HbA1c 10mmol/mol higher.

Conclusion: This is the first study using CGM to explore HbA1c discrepancy in PLWH. It shows the bias between interstitial glucose and HbA1c is small with moderate agreement between the two methods. Our data support a potential role for using HbA1c to assess glycaemia in PLWH.

Disclosure

H. Daultrey: None. N. Oliver: Advisory Panel; Dexcom, Inc., Medtronic, Roche Diabetes Care. Research Support; Dexcom, Inc., Medtronic. A. Chakera: None.

Funding

Dexcom - providing the glucose monitors for the study.
1111-P: Prevalence of Preexisting and Newly Detected Diabetes in Young Indians: Retrospective Analysis of Data from RSSDI Countrywide Defeat Diabetes Community Screening Program
Authors: GUPTA AMIT , SABOO BANSHI D. , PARIKH RAKESH M. , CH VASANTH K. , AGARWAL SANJAY , MAKKAR BRIJ M. , KOVIL RAJIV R. , CHAWLA SR., PURVI M. , NANDITHA ARUN , BHATTACHARYYA SUPRATIK , CHITTAWAR SACHIN
Published: May 2022

Background: The ADA 2022 standard of care recommends routine screening for T2DM beginning from the age of 35 years, while Indian Council of Medical Research recommends to begin screening above the age of 30 years. Current study was aimed at assessing prevalence of diabetes among Indians below 35 and 30 years of age

Methodology: Data collected from One Nation, One Day, One Million Tests campaign by RSSDI was retrospectively analyzed. A total data of 225955 adults was included in the analysis. 466 subjects (28026 males & 18561 females) were below the age of 35 years while 27924 (16460 males and 11446 females) were below the age of 30 years. Prevalence of preexisting (self-reported) diabetes and newly detected diabetes was calculated in this subgroup

Result: 225955 people screened, 44.3% (100074) were having diabetes. 34.8% (78694) were aware that they have diabetes while 9.4% (21380) were detected with diabetes for the first time during screening. Overall 55.3% (55338) of subjects had family history of diabetes.

Subgroup analysis below 35 years of age showed- 12% (5612) had preexisting diabetes while 5.8% (2713) were newly detected with an overall prevalence 17.8% (8325) .

Among subjects below 30 years of age 8.7% (2433) had preexisting diabetes while 4.6% (1642) were newly detected with diabetes with an overall prevalence of 13.3% (3713) .

Conclusion: The prevalence of T2DM among the young population is on rise. Our study supports the ICMR guidelines for screening of diabetes in the Indian population to begin at the age of 30 years. Higher screening age is likely to miss out a significant number of people. The study has important implications as ADA may also consider screening people of Indian origin at a younger age.Thought should be given to begin screening In Indian population even below the age of 30 years especially in those with a family history of diabetes.

Disclosure

A.Gupta: Speaker's Bureau; Lupin Pharmaceuticals, Inc., Medtronic, Novartis AG, Novo Nordisk, Sanofi. S.Bhattacharyya: None. S.Chittawar: None. B.D.Saboo: None. R.M.Parikh: None. V.K.Ch: None. S.Agarwal: Speaker's Bureau; Novo Nordisk, Roche Diabetes Care, Sanofi, USV Private Limited. B.M.Makkar: None. R.R.Kovil: None. P.M.Chawla: Speaker's Bureau; Biocon, Boehringer Ingelheim International GmbH, Eris Lifesciences Ltd., Novo Nordisk, Sanofi. A.Nanditha: None.
1118-P: Prediction of Clamp-Derived Insulin Sensitivity in African Americans from Clinical Risk Factors
Authors: FOWLER LAUREN A. , PARCHA VIBHU , COUCH CATHARINE , GARVEY W. TIMOTHY , GOWER BARBARA
Published: May 2022

Surrogate indices of insulin sensitivity based on fasting glucose and insulin values fail to adequately predict insulin sensitivity in African-Americans (AA) , a group with high risk for type 2 diabetes. The objective of this study was to evaluate the individual and combined utility of clinically accessible risk factors (demographic, anthropometric, and metabolic traits) to predict clamp-derived insulin sensitivity in 53 AA adults without diabetes. Insulin sensitivity was measured with the euglycemic clamp (SI-clamp) at an insulin dose of 120 µU/m2/min/kg lean body mass to assess primarily skeletal muscle glucose disposal. Concentrations of lipid/lipoproteins, adipokines, glucose, insulin, C-peptide, proinsulin, and inflammatory markers were obtained from fasting sera. Individual associations between SI-clamp and predictors were evaluated with linear regression, adjusting for age and sex. Multiple regression analyses with backward stepwise selection of all candidate predictors were used to derive prediction models. Body mass, triglycerides (TAG) , glucose, insulin, C-peptide, proinsulin, and TNF-α were inversely associated with SI-clamp, whereas female sex, HDL-cholesterol, adiponectin, and IFN-γ were positively associated (P< 0.05) . For the prediction models, HDL-cholesterol, TAG, C-peptide, adiponectin, leptin, and IL-6 explained the highest proportion of variance in SI-clamp (AIC = 15.8 and adjusted R2 = 54.27%) . A second, more clinically applicable model was also derived using HDL-cholesterol, TAG, C-peptide, and adiponectin (AIC = 18.136 and adjusted R2 = 50.63%) . These results suggest that in AA, fasting levels of lipid/lipoproteins, C-peptide, and adiponectin are stronger predictors of insulin sensitivity than fasting glucose and insulin. Development of a surrogate index for insulin sensitivity with these predictors may aid in accurately identifying AA at increased risk for type 2 diabetes in clinical settings and epidemiological studies.

Disclosure

L.A.Fowler: None. V.Parcha: None. C.Couch: None. W.Garvey: Other Relationship; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Epitomee, JAZZ Pharmaceuticals, Novo Nordisk, Novo Nordisk, Pfizer Inc., Pfizer Inc. B.Gower: None.

Funding

NIH/NIDDK (R01DK096288) NIH/NIDDK (P30DK056336) NIH/NIDDK (P60DK079626) NIH/NIDDK (T32DK062710) NIH/NCATS CTSA (U54TR001368-01)
1122-P: Subgroup Analysis to Evaluate Individuals at Risk for Incident Diabetes
Authors: ITO RYOMA , DAIMON MAKOTO , MIZUSHIRI SATORU , ONO SHOMA , NISHIYA YUKI , TAMURA AYUMI , MURABAYASHI MASAYA , KAMBA AYA
Published: May 2022

Since type 2 diabetes (T2D) is a heterogenous disease, treatment of T2D appears to be better personalized depending on their underlining conditions. A recent attempt to classify adult-onset DM based on only 6 DM related variables (GAD antibodies, age at diagnosis, BMI, HbA1c, and HOMA2 indices) , showed that DM can be classified into 5 clusters, among them 4 represent T2D (Lancet Diabetes Endocrinol. 2018;6:361) . We here classified non-diabetic population to find risk cluster for incident DM, or to extend strategies for prevention of T2D. The participants were recruited from Iwaki study, a health promotion study of Japanese people. Among 1167 participants in 2014 (baseline) , 868 non-diabetic individuals who attended at least one time in 2015 to 20were included in this prospective study. A hierarchical cluster analysis was performed based on 5 variables (age, BMI, HbA1c, HOMA2-β, and HOMA2-IR) . The hazard ratios (HRs) for incident T2D of clusters observed were examined using Cox proportional hazards model. Traits (mean) of 5 clusters observed were as follows: age (clusters; 1: 60.1, 2: 58.7, 3: 63.6, 4: 36.1, 5: 48.3) , BMI (1: 20.8, 2: 24.2, 3: 22.9, 4: 20.7, 5: 27.7) , HbA1c (1: 5.54, 2: 5.67, 3: 6.01, 4: 5.41, 5: 5.73) , HOMA2-β (1: 82.8, 2: 101.8, 3: 78.5, 4: 101.4, 5: 143.1) , and HOMA2-IR (1: 0.53, 2: 0.79, 3: 0.73, 4: 0.57, 5: 1.16) . The HR for incident T2D was significantly higher in cluster 3 than in clusters 1, 2, and 4, even after adjustment for age and sex (HR (p) : 5.00 (0.005) , 4.90 (0.005) , and 10.4 (0.048) , respectively) . Accordingly, cluster 3 had significantly higher age and HbA1c than other clusters, lower HOMA2-β than clusters 2, 4, and 5, and lower HOMA2-IR and BMI than clusters 2 and 5.

In summary, cluster analysis of a general non-diabetic population revealed a risk cluster for incident T2D, and, thus, individuals with characteristics representing the cluster (less insulin resistant but decreased insulin secretion, older age, and poor metabolic control) should be a target for prevention of incident T2D.

Disclosure

R.Ito: None. M.Daimon: None. S.Mizushiri: None. S.Ono: None. Y.Nishiya: None. A.Tamura: None. M.Murabayashi: None. A.Kamba: None.
1125-P: Obstructive Sleep Apnea and Insomnia Are Highly Prevalent in Monogenic Diabetes
Authors: AROSEMENA MARILYN A. , WROBLEWSKI KRISTEN , TASALI ESRA , PHILIPSON LOUIS H.
Published: May 2022

Background: Sleep disorders are highly common in type 1 and type 2 diabetes with important cardiometabolic implications. Maturity Onset Diabetes of the Young (MODY) has unique features compared to type 1 or type 2 diabetes, such that patients are generally lean and not using insulin.

Objective: To evaluate primary sleep disorders in patients with MODY. Methods: Participants were recruited from the Monogenic Diabetes Registry at the University of Chicago. The presence and severity of obstructive sleep apnea (OSA) was objectively assessed by a validated home OSA screening device (WatchPAT) . Insomnia was assessed by a validated survey, the Insomnia Severity Index.

Results: Demographic characteristics are shown in Table 1. The majority of the patients were white lean women, not using insulin with no diabetic complications. Among all patients (n=24) , OSA was found in 58% (64% had mild OSA, 22% had moderate OSA, 14% had severe OSA) . Among lean patients (n=15) , 53% had mild-to-moderate OSA and 47% had no OSA. Based on the Insomnia Severity Index score, 71% of patients had some degree of insomnia (17% clinical insomnia, 54% subthreshold insomnia) and 29% no insomnia.

Conclusion: OSA and insomnia were highly prevalent in MODY patients despite their lack of most traditional risk factors for sleep disorders. Given their unique characteristics, further research should investigate the pathophysiology of sleep disorders in this population.

Disclosure

M.A.Arosemena: None. K.Wroblewski: None. E.Tasali: None. L.H.Philipson: Advisory Panel; Nevro Corp., Research Support; Dompé, Novo Nordisk, provention BIo.