bluuebunny/crossref_metadata_2025_split huggingface dataset:
144-OR: Norepinephrine Mediates Severe Hypoglycemia–Induced Fatal Heart Block in Rats
Authors: NUIBE EMILY H. , CHAMBERS MATT , RENO-BERNSTEIN CANDACE M. 
Published: June 2023

Severe hypoglycemia can lead to fatal cardiac arrhythmias, specifically 3rd degree heart block. During hypoglycemia, the brain senses low glucose and activates the sympathetic nervous system leading to epinephrine and norepinephrine secretion. It is hypothesized that norepinephrine increases severe hypoglycemia induced fatal cardiac arrhythmias. To test this hypothesis, nondiabetic Sprague Dawley rats underwent hyperinsulinemic/severe hypoglycemic (10-15 mg/dl) clamps for 3 hours with continuous electrocardiogram recording. Rats were continuously infused with either 1) brain norepinephrine (ICV; n =15), 2) brain control (ICV aCSF; n = 11), 3) IV norepinephrine nerve terminal blocker (reserpine; n = 7), or 4) IV control (DMSO/saline; n = 6). Severe hypoglycemia induced mortality was increased to 40% with brain norepinephrine infusion compared to 27% in aCSF. Similarly, heart block was increased to 40% with brain norepinephrine infusion compared to 25% in aCSF (p &lt; 0.05). Blockade of norepinephrine completely prevented mortality and heart block during severe hypoglycemia compared to 17% and 25% (p &lt; 0.05), respectively, in controls.
In summary, norepinephrine increases while blockade of norepinephrine prevents fatal heart block during severe hypoglycemia. Drugs that target norepinephrine action may have therapeutic potential in people with diabetes at risk for severe hypoglycemia.

Disclosure
E.H. Nuibe: None. M. Chambers: None. C.M. Reno-Bernstein: None.

Funding
National Institutes of Health (1R56HL160835-01); University of Utah
1440-P: Single Islet Antigen 2 Antibody–Positive (IA2A Ab+) Children Exhibit Significant Metabolic Abnormalities and 5-Year Type 1 Diabetes (T1D) Risk
Authors: SIMS EMILY K. , CUTHBERTSON DAVID D. , BOSI EMANUELE , EVANS-MOLINA CARMELLA , REDONDO MARIA J. , NATHAN BRANDON M. , ISMAIL HEBA M. , JACOBSEN LAURA M. , SOSENKO JAY 
Published: June 2023

Current T1D staging defines multiple Ab+ as the start of T1D (Stage 1 or 2 depending on presence of dysglycemia). However, single Ab+ individuals are considered low-risk and are typically not considered for inclusion in prevention trials. We hypothesized that single IA2A+ children exhibit metabolic compromise with appreciable Stage 3 (clinical diabetes) risk. To test this, we evaluated 2163 confirmed single Ab+ children (IA2A, glutamic acid decarboxylase [GADA], or insulin [IAA]) with available OGTT data in the TrialNet natural history study. With and without age and BMI adjustment (Table), IA2A+ children had higher area under the curve (AUC) glucose, lower AUC C-peptide, and higher diabetes risk indices (Diabetes Prevention Trial Type 1 Risk Score [DPTRS] and Index60). Cox regression demonstrated that IA2A+ children were most likely to have progressed to Stage 3 (50.9% vs. 12.0% or 9.6% over 5 years). Of single Ab+ children who did not progress to Stage 3, GADA+ most frequently progressed to multiple Ab+ (34.0% over 5 years). In conclusion, amongst single Ab+ children, IA2A+ children have greater metabolic dysfunction and rates of progression to Stage 3. These findings suggest that single IA2A+ children exhibit substantial T1D risk, should also be considered as having Stage 1 T1D, and be considered for eligibility in prevention studies.

Disclosure
E.K.Sims: Speaker's Bureau; Medscape, American Diabetes Association. D.D.Cuthbertson: None. E.Bosi: None. C.Evans-molina: Advisory Panel; Provention Bio, Inc., DiogenX, Avotres Inc., Neurodon, MaiCell Therapeutics, Other Relationship; Isla Technology, Bristol-Myers Squibb Company, Nimbus Therapeutics, Research Support; Lilly, Astellas Pharma Inc. M.J.Redondo: None. B.M.Nathan: None. H.M.Ismail: Consultant; Rise Therapeutics. L.M.Jacobsen: None. J.Sosenko: None.
1449-P: Machine Learning Reveals Metabolic Signatures in Patients with Type 1 Diabetes
Authors: ZHU JIANGYU , ZHAO MINZHE , ZHENG XUEYING , LUO SIHUI , DING YU , WENG JIANPING 
Published: June 2023

Background: Metabolic dysbiosis has been linked to the development of type 1 diabetes. However, there are few studies reflecting the metabolic signatures in patients with type 1 diabetes based on machine learning. Therefore, we aim to investigate the serum metabolic alterations and signatures in patients with type 1 diabetes.
Methods: We recruited 29 type 1 diabetes patients and 29 healthy controls with matching age, sex and ethnicity. Serum metabolites were analyzed using liquid chromatograph-mass spectrometry (LC-MS). Four machine-learning approaches (Logistic Regression, Support Vector Machine, Gaussian Naive Bayes, and Random Forest) were used to screen potential T1D-related biomarkers.
Results: Between the T1D group and the control group, 150 different metabolites were identified. These metabolites were significantly enriched in three metabolic pathways (P&lt;0.05), purine metabolism, ketone body synthesis and degradation, and methyl butyrate metabolism. We combined comprehensive analysis and four machine-learning algorithmsto screen for biomarkers associated with type 1 diabetes. The top 20 metabolites coincided with 150 metabolites identified by LC-MS. In addition, three metabolites were identified as T1D diagnostic biomarkers, including docosahexaenoic acid, estrane and inosine. The combination of these metabolites also accurately diagnosis type 1 diabetes.
Conclusions: In this study, purine metabolism, synthesis and degradation of ketone bodies, and impaired methyl butyrate metabolism were identified as metabolic disturbance associated with type 1 diabetes. These biomarkers by using machine-learning approaches may have important clinical significance in the diagnosis of type 1 diabetes and in the follow of responses to therapeutic interventions.

Disclosure
J.Zhu: None. M.Zhao: None. X.Zheng: None. S.Luo: None. Y.Ding: None. J.Weng: None.
1455-P: Developing Computable Phenotypes (CPs) for Identifying Children, Adolescents, and Young Adults with Diabetes Using Electronic Health Records in the DiCAYA Network
Authors: SHAO HUI , GUO YI , BIAN JIANG , LI PIAOPIAO , DABELEA DANA , CONWAY REBECCA B. , CRUME TESSA L. , SCHWARTZ BRIAN S. , HIRSCH ANNEMARIE G. , DIXON BRIAN E. , LUSTIGOVA EVA , ROSENMAN MARC , ZHONG VICTOR W. , CONDERINO SARAH , DIVERS JASMIN , THORPE LORNA , LIESE ANGELA D. , RUDISILL CAROLINE , OBEID JIHAD S. , PAVKOV MEDA E. , IMPERATORE GIUSEPPINA , EWING JOSEPH A. 
Published: June 2023

The DiCAYA Network, which is funded by the CDC and NIDDK, is working to create a nationwide electronic health record-based diabetes surveillance system. The feasibility and performance of existing diabetes computable phenotypes in this system were unknown, as they had only been tested in individual health systems. This study aimed to develop a DiCAYA-wide EHR-based computable phenotype (CP) to identify prevalent cases of diabetes by type. We conducted network-wide chart reviews for 1830 youth (age &lt; 18y) and 1830 young adults (age 18 - &lt;45y) among individuals with possible diabetes, identified as those with any potential indication of diabetes in the EHR (any diabetes-related diagnosis, medication, or abnormal lab test). We assessed the performance of the DiCAYA CP (two outpatient diagnoses or one inpatient diagnosis by type) for identifying diabetes and diabetes type in children and young adults in the reviewed sample, using chart review as the gold standard. (Table 1). We developed a highly accurate EHR-based CP for diabetes in children and young adults based on EHR data from the DiCAYA network. Our results support the feasibility of deploying a unified CP across a nationwide EHR network for diabetes surveillance, with consistently high accuracy across the participating sites.

Disclosure
H.Shao: Consultant; Lilly Diabetes. B.E.Dixon: Consultant; Merck & Co., Inc. E.Lustigova: None. M.Rosenman: None. V.W.Zhong: None. S.Conderino: None. J.Divers: None. L.Thorpe: None. A.D.Liese: None. C.Rudisill: Stock/Shareholder; Pfizer Inc., Viatris Inc., Teladoc Health, Catalent. J.S.Obeid: None. Y.Guo: None. M.E.Pavkov: None. G.Imperatore: None. J.A.Ewing: None. J.Bian: None. P.Li: None. D.Dabelea: None. R.B.Conway: None. T.L.Crume: None. B.S.Schwartz: None. A.G.Hirsch: None.

Funding
Centers for Disease Control and Prevention (U18DP006512)
146-OR: Causative Role of Hypothalamic Ventromedial Glucose-Inhibited Neurons in Impaired Counterregulatory Responses to Hypoglycemia
Authors: COPPERI FRANCESCA , SHEN XIAOTIAN , DIANO SABRINA 
Published: June 2023

The development of impaired counterregulatory responses (CRR) after recurrent hypoglycemia (RH) is one of the most life-threatening and debilitating aspects of Type 1 Diabetes (T1D). Numerous scientific evidence points to the ventromedial nucleus of the hypothalamus (VMH) glucose-inhibited (GI) neurons as major players in the development of impaired CRR. However, there is no current evidence of a causative role of VMH GI neurons in impaired CRR. In this study, we used a protocol in which mice were injected with insulin (2.5 U/kg, i.p.) for 4 consecutive days. These mice displayed impaired CRR after 2-deoxy-D-glucose (2-DG) administration (200 mg/kg, i.p. injected on the 5th day) with blunted levels of circulating glucose, corticosterone, and epinephrine in comparison to mice with intact CRR after 2-DG administration. Using a TRAP2:tdTomato mouse model, we labeled (tdTomato) GI neurons by injecting 4-hydroxytamoxifen after 2-DG administration. Four weeks later, the mice were injected with either insulin or vehicle for 4 days followed by 2-DG administration, of which the brains were then immunostained and analyzed for cFos in the VMH. We observed a significant decrease in double-labeled tdTomato/cFos cells in mice with impaired CRR compared to the controls, thus suggesting an altered VMH GI neuronal activation following insulin-induced RH. In support of this, chemogenetic activation of VMH GI neurons in mice with impaired CRR significantly increased blood glucose levels following 2-DG administration compared to mice with impaired CRR. Overall, our data provide evidence for a direct and causal involvement of VMH GI neurons in the development of impaired CRR following RH.

Disclosure
F.Copperi: None. X.Shen: None. S.Diano: None.

Funding
Naomi Berrie Diabetes Center; National Institute of Diabetes and Digestive and Kidney Diseases (DK107293)
1466-P: Genome-Wide Association Studies in the GRADE Study Identify Genetic Variation Influencing the Response to Pharmacotherapy for Type 2 Diabetes
Authors: LI JOSEPHINE H. , SZCZERBINSKI LUKASZ , LIU HAIYIN , TRIPPUTI MARK , KRETOWSKI ADAM , KAHN STEVEN E. , LACHIN JOHN M. , YOUNES NAJI , MERCADER JOSEP M. , FLOREZ JOSE C. 
Published: June 2023

Treatment selection for type 2 diabetes (T2D) is largely driven by guidelines based on population-level clinical data and does not incorporate genetics into decision making. To address this gap, we conducted genome-wide association studies in GRADE, a randomized trial comparing the metabolic effects of glargine, glimepiride, liraglutide, or sitagliptin, when added to metformin over a mean follow-up of 5 years. 4,689 participants with T2D from diverse ancestries underwent genome-wide genotyping with the Illumina Infinium GSA 3.0 array, and high-quality imputation was performed with the TOPMed reference panel. We defined cases as meeting the two outcome criteria (primary: HbA1c ≥7%; secondary: HbA1c ≥7.5%) after 1 or 4 years of treatment. Whole-genome logistic regression using an additive model tested for case-control associations for each treatment. Results were filtered to minor allele frequency &gt;0.005 and imputation R2 ≥0.80. We identified four loci associated with glargine response and one with sitagliptin response at standard genome-wide significance (p&lt;5.0×10−8). For glargine, rs116991960 proximal to the RPSAP52 pseudogene region was associated with increased risk of the primary outcome at year 1 (p=2.6×10−8). Interestingly, RPSAP52 interacts with the RNA binding protein IGF2BP2, and genetic variation in IGF2BP2 has been associated with increased T2D risk. Moreover, rs142895019, located in ITPK1, was associated with the secondary outcome for sitagliptin at year 1 (p=9.4×10−9). In a separate Cox proportional hazards survival analysis, C-allele carriers of rs142895019 had an increased risk of treatment failure on sitagliptin (HR 3.6, p=1.0×10−7). In summary, we identified new genetic loci that may be associated with glycemic response in a multi-ancestry clinical trial of common glucose-lowering medications for T2D. These findings require independent validation but have potential utility in guiding therapy selection.

Disclosure
J.H. Li: None. L. Szczerbinski: None. H. Liu: None. M. Tripputi: None. A. Kretowski: None. S.E. Kahn: Advisory Panel; Anji Pharmaceuticals, Bayer Inc., Boehringer Ingelheim Inc., Eli Lilly and Company, Merck & Co., Inc. Other Relationship; Novo Nordisk. J.M. Lachin: None. N. Younes: None. J.M. Mercader: None. J.C. Florez: Consultant; AstraZeneca. Other Relationship; AstraZeneca, Merck & Co., Inc. Consultant; Novo Nordisk.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (U01DK098246, U34DK088043, R01DK123019)
1467-P: Type 2 Diabetes Polygenic Score Predicts the Risk of Glucocorticoid-Induced Hyperglycemia in Patients without Diabetes
Authors: DEUTSCH AARON J. , SCHROEDER PHILIP H. , MANDLA RAVI , ERENLER FEYZA , MERCADER JOSEP M. , UDLER MIRIAM , FLOREZ JOSE C. , BRENNER LAURA 
Published: June 2023

Introduction: Glucocorticoids are commonly prescribed medications with a known side effect of hyperglycemia due to their effect on glucose metabolism. However, only 10-50% of patients receiving glucocorticoids develop overt hyperglycemia. It is unknown whether patients with increased genetic risk for type 2 diabetes (T2D) are predisposed to develop hyperglycemia after glucocorticoid treatment.
Methods: We accessed electronic health records and genetic data in the Mass General Brigham Biobank. We examined patients with no diagnosis of diabetes or prediabetes who received a glucocorticoid dose equivalent to 10 mg of prednisone or more, and who had glucose levels checked within 7 days of glucocorticoid administration. Hyperglycemia was defined as fasting blood glucose ≥126 mg/dL or random blood glucose ≥200 mg/dL. A T2D global extended polygenic score was constructed through a meta-analysis of T2D genome-wide association studies in the Million Veteran Program, DIAMANTE, and FinnGen. We performed logistic regression to analyze the association between the polygenic score and hyperglycemia, controlling for age, gender, BMI, baseline creatinine, glucocorticoid dose and duration, and the first 10 principal components of genetic ancestry.
Results: Out of 552 patients who received glucocorticoids, 216 developed hyperglycemia and 336 did not. The T2D polygenic score was significantly associated with glucocorticoid-induced hyperglycemia (p = 0.032, OR = 1.5 per standard deviation of the polygenic score). Other significant covariates included baseline creatinine (p = 8.0 × 10−4, OR = 2.2 per mg/dL of creatinine) and glucocorticoid dose (p = 9.5 × 10−5, OR = 1.01 per 10 mg of prednisone).
Conclusions: Patients carrying a higher burden of genetic variants that confer risk for T2D have an increased risk of hyperglycemia after receiving glucocorticoids. This finding offers a mechanism for risk stratification as part of a precision approach to medical treatment.

Disclosure
A.J.Deutsch: None. P.H.Schroeder: None. R.Mandla: None. F.Erenler: None. J.M.Mercader: None. M.Udler: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. L.Brenner: None.

Funding
National Institutes of Health (T32DK007028)
1474-P: Identification and Management of MODY2 Pregnancy Patients
Authors: LIU LIMEI , JIANG YANYAN , CHEN YATING , LIU CHANWEI , LI TIANTIAN 
Published: June 2023

Precise differentiation of glucokinase (GCK) monogenic diabetes, MODY2, from gestational diabetes mellitus (GDM) is critical for accurate management of the pregnancy outcome. We screened MODY2 complicating pregnancies in Chinese GDM patients, explored the pathogenesis of novel GCK mutations, and evaluated the patients’ pregnancy outcome and management. The GCK gene from 411 GDM patients was screened with PCR-direct sequencing and multiplex ligation-dependent probe amplification (MLPA) and 15 GCK mutations were identified. We also retrospectively analyzed a total of 65 pregnancies from 21 MODY2 families, wherein 41 were from 15 maternal families and 24 were from six paternal families. Bioinformatic analysis and biochemical functional study were conducted to identify novel GCK mutations. In total, we identified 21 GCK mutations: 15 from the 411 GDM patients and six from 24 fathers. Of the Asp78Asn (GAC → AAC), Met87Arg (ATG → AGG), Leu451Val (CTT → GTT), Leu451Pro (CTG → CCG) and 1019 + 20G &gt; A mutations, five, i.e., were novel and deleterious, with markedly decreased enzyme activity and thermal stability. The unaffected offspring of GCK mutation affected mothers were heavier than affected offspring (p&lt;0.001). Of 21 insulin-treated affected mothers, 10 had maternal hypoglycemia (47.6%) and seven had perinatal complications (33.3%), and the affected offspring of the insulin-treated affected mothers had significantly lower birth weights than that of the 20 diet-control affected mothers (p=0.031). In this study, the prevalence of MODY2 complicating pregnancy in Chinese GDM patients was 3.6% (15/411). The defective GCK may contribute to the hyperglycemia in MODY2. Insulin therapy is not beneficial for MODY2 complicating pregnancy and therefore should not be recommended.

Disclosure
L.Liu: None. Y.Jiang: None. Y.Chen: None. C.Liu: None. T.Li: None.

Funding
National Natural Science Foundation of China (81970686, 81770791, 81471012, 82070823, 81270876); Interdisciplinary Program of Shanghai Jiao Tong University (YG2019ZDA08); Shanghai Leading Talent (SLJ15055); National Institutes of Health (SC1DK104821); Tobacco-Related Disease Research Program (T31IR1603)
1477-P: Improved Diabetes Risk Prediction Using Ancestry-Specific Polygenic Score—Results from the Asian Indian Diabetic Heart Study/Sikh Diabetes Study
Authors: TUNG GURLEEN K. , ROUT MADHUSMITA , SANGHERA DHARAMBIR K. 
Published: June 2023

Background: Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, PRS-driven information on other ethnic groups is sparse, including Asian Indians (AI), who have a heightened risk for T2D. We examined the predictive efficacy of ancestry-derived (PRSAI) and European-derived (PRSEU) with a clinical risk score (CRS) of T2D.
Methods: Weighted PRSs were computed using 2921 variants (common and rare) from (Punjabi/Sikh) genome-wide association studies and 432 variants from European meta-analyses studies in 4,602 individuals (2,574 cases and 2,028 controls) of the Asian Indian Diabetes Heart Study/Sikh Diabetes Study. Both Ancestry-specific PRSAI and European PRSEU were validated on 9372 UK Biobank South Asian individuals (1943 cases/7429 controls).
Results: Ancestry-specific PRSAI showed 36.2% improved efficacy than PRSEU in Punjabi Asian Indians. Similarly, Ancestry-specific PRSAI was 18.6% superior to PRSEU in Asian Indians from UKBB based on Nagelkerke’s R2. Sensitivity analysis explained enhanced sensitivity (area under the curve-AUC) of ancestry-specific PRS over PRSEU in predicting T2D risk.
Conclusions: Our data suggest expanding genetic studies in diverse ethnic groups to exploit the full potential of PRS to improve health outcomes. More genetic evaluations, specifically in understudied/underrepresented populations, would help increase the transferability of genome-wide polygenic scores across racial and ethnic groups to make their integration into clinical practice easier.

Disclosure
G.K.Tung: None. M.Rout: None. D.K.Sanghera: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK082766, R01DK118427); Presbyterian Health Foundation
148-LB: Glycemic Outcomes of Telemedicine Endocrinology Care for Adults with T2D
Authors: ZUPA MARGARET , ROTHENBERGER SCOTT D. , LIN JONATHAN Y. , ROSLAND ANN-MARIE 
Published: June 2023

Current specialty care for T2D via telemedicine may not be as effective for patients with clinical complexity given barriers to delivery of key care elements, such blood glucose data sharing and involvement of multidisciplinary teams. In this retrospective cohort study, adults who had a telemedicine endocrinology visit for T2D in a large health system from May-October 2020 were followed through May 2022 to assess follow-up care modality and HbA1c change. Patients were assigned to telemedicine (n=1,182, baseline HbA1c 7.6%) and in-person (n=1,049, baseline HbA1c 7.4%) cohorts based on follow-up care modality. Multivariable regression models estimated the association of baseline insulin regimen and key comorbidities (macrovascular disease and psychological conditions) with HbA1c change over 12 months in each cohort. Patients who used multiple daily injections (MDI) had less HbA1c improvement at 12 months vs those not on insulin in both cohorts, and HbA1c change was significantly worse for patients on MDI who used only telemedicine (HbA1c change telemedicine-only 0.77% higher, 95% CI 0.59-0.94; HbA1c change in-person 0.52% higher, 0.34-0.70, p&lt;0.001 for both; see figure). Key comorbidities were not associated with HbA1c change in either cohort. These results indicate that patients in endocrinology care who use complex insulin regimens may need additional support to achieve HbA1c improvement, especially with telemedicine.

Disclosure
M. Zupa: None. S. D. Rothenberger: None. J. Y. Lin: None. A. Rosland: None.

Funding
National Center for Advancing Translational Sciences (KL2TR001856)