Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care

Established and emerging biomarkers for the prediction of type 1 diabetes: a systematic review

Type 1 diabetes (T1D) is an autoimmune disease with a prolonged and variable latent period that culminates in the destruction of pancreatic β-cells and the development of hyperglycemia. There is a need for diagnostic biomarkers to detect more accurately detect individuals with prediabetes to expedite targeting for prevention and intervention strategies. To assess the current ability to predict the insidious development of T1D, we conducted a comprehensive systematic review for established and prospective predictive markers of T1D using the Medline, OVID, and EMBASE databases. Resulting citations were screened for relevance to subject. Our research generated five major categories of markers that are either currently used or forthcoming: genetic, autoantibodies, risk score quantification, cellular immunity, and β-cell function. The current standard used to assess T1D onset or predisposition focuses on autoimmune pathology and disease-associated autoantibodies. Research studies in general go beyond autoantibody screening and assess genetic predisposition, and quantitate risk of developing disease based on additional factors. However, there are few currently used techniques that assess the root of T1D: β-cell destruction. Thus, novel techniques are discussed with the potential to gauge degrees of β-cell stress and failure via protein, RNA, and DNA analyses

QoL in Child LQTS Patients Compared to Cardiac Patients

Introduction: • Long QT Syndrome (LQTS) is a life threatening geneticallyinherited cardiac arrhythmia disorder affecting approximately 1:2500 persons1, often diagnosed in childhood. • Management of LQTS changes patients’ lifestyles which can affect quality of life (QoL). Patients have restrictions in physical activity, diet, treatment of noncardiac conditions; take daily doses of medicine and/or have implantable cardiac devices (pacemaker/defibrillator). • General pediatirc cardiac patients show significantly worse QoL in comparison to healthy controls2,3. • Nearly 1 in 5 with other cardiac disorders reported impaired psychosocial functioning3. • The effects of implanted cardiac rhythm devices in cardiac patients demonstrated a significant effect on QoL in pediatric patient scores4. • LQTS patients are typically not assessed for psychological symptoms. • Little research on QoL in pediatric LQTS patients has been conducted to determine if psychosocial interventions are warranted

The influence of body mass index and age on C-peptide at the diagnosis of type 1 diabetes in children who participated in the diabetes prevention trial-type 1

BACKGROUND/OBJECTIVE: The extent of influence of BMI and age on C-peptide at the diagnosis of type 1 diabetes (T1D) is unknown. We thus studied the impact of body mass index Z-scores (BMIZ) and age on C-peptide measures at and soon after the diagnosis of T1D. METHODS: Data from Diabetes Prevention Trial-Type 1 (DPT-1) participants <18.0 years at diagnosis was analyzed. Analyses examined associations of C-peptide measures with BMIZ and age in 2 cohorts: oral glucose tolerance tests (OGTTs) at diagnosis (n = 99) and mixed meal tolerance tests (MMTTs) <6 months after diagnosis (n = 80). Multivariable linear regression was utilized. RESULTS: Fasting and area under the curve (AUC) C-peptide from OGTTs (n = 99) at diagnosis and MMTTs (n = 80) after diagnosis were positively associated with BMIZ and age (P < .001 for all). Associations persisted when BMIZ and age were included as independent variables in regression models (P < .001 for all). BMIZ and age explained 31%-47% of the variance of C-peptide measures. In an example, 2 individuals with identical AUC C-peptide values had an approximate 5-fold difference in values after adjustments for BMIZ and age. The association between fasting glucose and C-peptide decreased markedly when fasting C-peptide values were adjusted (r = 0.30, P < .01 to r = 0.07, n.s.). CONCLUSIONS: C-peptide measures are strongly and independently related to BMIZ and age at and soon after the diagnosis of T1D. Adjustments for BMIZ and age cause substantial changes in C-peptide values, and impact the association between glycemia and C-peptide. Such adjustments can improve assessments of β-cell impairment at diagnosis

Neighborhood Social Resources and Depressive Symptoms: Longitudinal Results from the Multi-Ethnic Study of Atherosclerosis

The ways in which a neighborhood environment may affect depression and depressive symptoms have not been thoroughly explored. This study used longitudinal data from 5475 adults in the Multi-Ethnic Study of Atherosclerosis to investigate associations of time-varying depressive symptoms between 2000 and 2012 (measured using the 20-item Center for Epidemiologic Studies Depression Scale (CES-D)) with survey-based measures of neighborhood safety and social cohesion (both individual-level perceptions and neighborhood-level aggregates) and densities of social engagement destinations. Linear mixed models were used to examine associations of baseline cross-sectional associations and cumulative exposures with changes over time in CES-D. Econometric fixed effects models were utilized to investigate associations of within-person changes in neighborhood exposures with within-person changes in CES-D. Adjusting for relevant covariates, higher safety and social cohesion and greater density of social engagement destinations were associated with lower CES-D at baseline. Greater cumulative exposure to these features was not associated with progression of CES-D over 10 years. Within-person increases in safety and in social cohesion were associated with decreases in CES-D, although associations with cohesion were not statistically significant. Social elements of neighborhoods should be considered by community planners and public health practitioners to achieve optimal mental health

Biomarkers of islet beta cell stress and death in type 1 diabetes

Recent work on the pathogenesis of type 1 diabetes has led to an evolving recognition of the heterogeneity of this disease, both with regards to clinical phenotype and responses to therapies to prevent or revert diabetes. This heterogeneity not only limits efforts to accurately predict clinical disease but also is reflected in differing responses to immunomodulatory therapeutics. Thus, there is a need for robust biomarkers of beta cell health, which could provide insight into pathophysiological differences in disease course, improve disease prediction, increase the understanding of therapeutic responses to immunomodulatory interventions and identify individuals most likely to benefit from these therapies. In this review, we outline current literature, limitations and future directions for promising circulating markers of beta cell stress and death in type 1 diabetes, including markers indicating abnormal prohormone processing, circulating RNAs and circulating DNAs

A parallax view of type 1 diabetes

The year 2021 marks the 100th anniversary of the discovery of insulin, a therapy that transformed type 1 diabetes (T1D) from a once fatal diagnosis into a chronic condition that can be successfully managed with exogenous insulin administration. In this article, we celebrate the remarkable journey that led to the discovery of insulin and our subsequent understanding of T1D as a disease of immune-mediated β-cell destruction. Further, we discuss an alternative and parallax view of disease development, highlighting maladaptive β-cell responses that act to amplify immune responses and have been implicated in diabetes development

CRISPR Knockout of the HuR Gene Causes a Xenograft Lethal Phenotype.

Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related deaths in the United States, whereas colorectal cancer is the third most common cancer. The RNA-binding protein HuR (ELAVL1) supports a pro-oncogenic network in gastrointestinal (GI) cancer cells through enhanced HuR expression. Using a publically available database, HuR expression levels were determined to be increased in primary PDA and colorectal cancer tumor cohorts as compared with normal pancreas and colon tissues, respectively. CRISPR/Cas9 technology was successfully used to delete the HuR gene in both PDA (MIA PaCa-2 and Hs 766T) and colorectal cancer (HCT116) cell lines. HuR deficiency has a mild phenotype

Proinsulin and heat shock protein 90 as biomarkers of beta-cell stress in the early period after onset of type 1 diabetes

Rapid evaluation of therapies designed to preserve β cells in persons with type 1 diabetes (T1D) is hampered by limited availability of sensitive β-cell health biomarkers. In particular, biomarkers elucidating the presence and degree of β-cell stress are needed. We characterized β-cell secretory activity and stress in 29 new-onset T1D subjects (10.6 ± 3.0 years, 55% male) at diagnosis and then 8.2 ± 1.2 weeks later at first clinic follow-up. We did comparisons with 16 matched healthy controls. We evaluated hemoglobin A1c (HbA1c), β-cell function (random C-peptide [C] and proinsulin [PI]), β-cell stress (PI:C ratio), and the β-cell stress marker heat shock protein (HSP)90 and examined these parameters' relationships with clinical and laboratory characteristics at diagnosis. Mean diagnosis HbA1c was 11.3% (100 mmol/mol) and 7.6% (60 mmol/mol) at follow-up. C-peptide was low at diagnosis (P < 0.001 vs controls) and increased at follow-up (P < 0.001) to comparable with controls. PI did not differ from controls at diagnosis but increased at follow-up (P = 0.003) signifying increased release of PI alongside improved insulin secretion. PI:C ratios and HSP90 concentrations were elevated at both time points. Younger subjects had lower C-peptide and greater PI, PI:C, and HSP90. We also examined islets isolated from prediabetic nonobese diabetic mice and found that HSP90 levels were increased ∼4-fold compared with those in islets isolated from matched CD1 controls, further substantiating HSP90 as a marker of β-cell stress in T1D. Our data indicate that β-cell stress can be assessed using PI:C and HSP90. This stress persists after T1D diagnosis. Therapeutic approaches to reduce β-cell stress in new-onset T1D should be considered