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Insulin: A 100-Year-Old Discovery With a Fascinating History
William Rostène, Pierre De Meyts
doi : 10.1210/endrev/bnab020
Endocrine Reviews, Volume 42, Issue 5, October 2021, Pages 503–527
Diabetes has been known since antiquity. We present here a historical perspective on the concepts and ideas regarding the physiopathology of the disease, on the progressive focus on the pancreas, in particular on the islets discovered by Langerhans in 1869, leading to the iconic experiment of Minkowski and von Mering in 1889 showing that pancreatectomy in a dog induced polyuria and diabetes mellitus. Subsequently, multiple investigators searched for the active substance of the pancreas and some managed to produce extracts that lowered blood glucose and decreased polyuria in pancreatectomized dogs but were too toxic to be administered to patients. The breakthrough came 100 years ago, when the team of Frederick Banting, Charles Best, and James Collip working in the Department of Physiology headed by John Macleod at the University of Toronto managed to obtain pancreatic extracts that could be used to treat patients and rescue them from the edge of death by starvation, the only treatment then available. This achievement was quickly recognized by the Nobel Prize in Physiology or Medicine to Banting and Macleod in 1923. At 32, Banting remains the youngest awardee of this prize. Here we discuss the work that led to the discovery and its main breakthroughs, the human characters involved in an increasingly dysfunctional relationship, the controversies that followed the Nobel Prize, and the debate as to who actually “discovered” insulin. We also discuss the early commercial development and progress in insulin crystallization in the decade or so following the Nobel Prize.
The ? Cell in Diabetes: Integrating Biomarkers With Functional Measures
Steven E Kahn, Yi-Chun Chen, Nathalie Esser, Austin J Taylor, Daniël H van Raalte, Sakeneh Zraika, C Bruce Verchere
doi : 10.1210/endrev/bnab021
Endocrine Reviews, Volume 42, Issue 5, October 2021, Pages 528–583
The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet ? cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the ? cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of ?-cell secretory function that themselves could be considered biomarkers.
Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies: Beyond a Simple Count
Michelle So, Cate Speake, Andrea K Steck, Markus Lundgren, Peter G Colman, Jerry P Palmer, Kevan C Herold, Carla J Greenbaum
doi : 10.1210/endrev/bnab013
Endocrine Reviews, Volume 42, Issue 5, October 2021, Pages 584–604
Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject’s age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.
The Human Islet: Mini-Organ With Mega-Impact
John T Walker, Diane C Saunders, Marcela Brissova, Alvin C Powers
doi : 10.1210/endrev/bnab010
Endocrine Reviews, Volume 42, Issue 5, October 2021, Pages 605–657
This review focuses on the human pancreatic islet—including its structure, cell composition, development, function, and dysfunction. After providing a historical timeline of key discoveries about human islets over the past century, we describe new research approaches and technologies that are being used to study human islets and how these are providing insight into human islet physiology and pathophysiology. We also describe changes or adaptations in human islets in response to physiologic challenges such as pregnancy, aging, and insulin resistance and discuss islet changes in human diabetes of many forms. We outline current and future interventions being developed to protect, restore, or replace human islets. The review also highlights unresolved questions about human islets and proposes areas where additional research on human islets is needed.
Conducting Real-world Evidence Studies on the Clinical Outcomes of Diabetes Treatments
Sebastian Schneeweiss, Elisabetta Patorno
doi : 10.1210/endrev/bnab007
Endocrine Reviews, Volume 42, Issue 5, October 2021, Pages 658–690
Real-world evidence (RWE), the understanding of treatment effectiveness in clinical practice generated from longitudinal patient-level data from the routine operation of the healthcare system, is thought to complement evidence on the efficacy of medications from randomized controlled trials (RCTs). RWE studies follow a structured approach. (1) A design layer decides on the study design, which is driven by the study question and refined by a medically informed target population, patient-informed outcomes, and biologically informed effect windows. Imagining the randomized trial we would ideally perform before designing an RWE study in its likeness reduces bias; the new-user active comparator cohort design has proven useful in many RWE studies of diabetes treatments. (2) A measurement layer transforms the longitudinal patient-level data stream into variables that identify the study population, the pre-exposure patient characteristics, the treatment, and the treatment-emergent outcomes. Working with secondary data increases the measurement complexity compared to primary data collection that we find in most RCTs. (3) An analysis layer focuses on the causal treatment effect estimation. Propensity score analyses have gained in popularity to minimize confounding in healthcare database analyses. Well-understood investigator errors, like immortal time bias, adjustment for causal intermediates, or reverse causation, should be avoided. To increase reproducibility of RWE findings, studies require full implementation transparency. This article integrates state-of-the-art knowledge on how to conduct and review RWE studies on diabetes treatments to maximize study validity and ultimately increased confidence in RWE-based decision making.
