Jakub Mesinovic, Jackson J. Fyfe, Jason Talevski, Michael J. Wheeler, Gloria K.W. Leung, Elena S. George, Melkamu T. Hunegnaw, Costas Glavas, Paul Jansons, Robin M. Daly, David Scott
Received April 14, 2023 Accepted August 12, 2023 Published online September 14, 2023
Type 2 diabetes mellitus (T2DM) and sarcopenia (low skeletal muscle mass and function) share a bidirectional relationship. The prevalence of these diseases increases with age and they share common risk factors. Skeletal muscle fat infiltration, commonly referred to as myosteatosis, may be a major contributor to both T2DM and sarcopenia in older adults via independent effects on insulin resistance and muscle health. Many strategies to manage T2DM result in energy restriction and subsequent weight loss, and this can lead to significant declines in muscle mass in the absence of resistance exercise, which is also a first-line treatment for sarcopenia. In this review, we highlight recent evidence on established treatments and emerging therapies targeting weight loss and muscle mass and function improvements in older adults with, or at risk of, T2DM and/or sarcopenia. This includes dietary, physical activity and exercise interventions, new generation incretin-based agonists and myostatin-based antagonists, and endoscopic bariatric therapies. We also highlight how digital health technologies and health literacy interventions can increase uptake of, and adherence to, established and emerging treatments and therapies in older adults with T2DM and/or sarcopenia.
Diabetic peripheral neuropathy (DPN) is one of the most prevalent chronic complications of diabetes. The lifetime prevalence of DPN is thought to be >50%, and 15%–25% of patients with diabetes experience neuropathic pain, referred to as “painful DPN.” Appropriate treatment of painful DPN is important because this pain contributes to a poor quality of life by causing sleep disturbance, anxiety, and depression. The basic principle for the management of painful DPN is to control hyperglycemia and other modifiable risk factors, but these may be insufficient for preventing or improving DPN. Because there is no promising diseasemodifying medication for DPN, the pain itself needs to be managed when treating painful DPN. Drugs for neuropathic pain, such as gabapentinoids, serotonin–norepinephrine reuptake inhibitors, tricyclic antidepressants, alpha-lipoic acid, sodium channel blockers, and topical capsaicin, are used for the management of painful DPN. The U.S. Food and Drug Administration (FDA) has approved pregabalin, duloxetine, tapentadol, and the 8% capsaicin patch as drugs for the treatment of painful DPN. Recently, spinal cord stimulation using electrical stimulation is approved by the FDA for the treatment for painful DPN. This review describes the currently available pharmacological and nonpharmacological treatments for painful DPN.
Patients with diabetes mellitus are highly susceptible to cardiovascular complications, which are directly correlated with cardiovascular morbidity and mortality. In addition to coronary artery disease, there is growing awareness of the risk and prevalence of heart failure (HF) in patients with diabetes. Echocardiography is an essential diagnostic modality commonly performed in patients with symptoms suggestive of cardiovascular diseases (CVD), such as dyspnea or chest pain, to establish or rule out the cause of symptoms. Conventional echocardiographic parameters, such as left ventricular ejection fraction, are helpful not only for diagnosing CVD but also for determining severity, treatment strategy, prognosis, and response to treatment. Echocardiographic myocardial strain, a novel echocardiographic technique, enables the detection of early changes in ventricular dysfunction before HF symptoms develop. This article aims to review the role of echocardiography in evaluating CVD in patients with diabetes mellitus and how to use it in patients with suspected cardiac diseases.
With the increasing use of immune-checkpoint inhibitors (ICIs), such as anti-cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) and anti-programmed cell death-1 (PD-1), for the treatment of malignancies, cases of ICI-induced type 1 diabetes mellitus (ICI-T1DM) have been reported globally. This review focuses on the features and pathogenesis of this disease. T1DM is an immune-related adverse event that occurs following the administration of anti-PD-1 or anti-programmed death ligand-1 (PDL1) alone or in combination with anti-CTLA-4. More than half of the reported cases presented as abrupt-onset diabetic ketoacidosis. The primary mechanism of ICI-T1DM is T-cell stimulation, which results from the loss of interaction between PD-1 and PD-L1 in pancreatic islet. The similarities and differences between ICI-T1DM and classical T1DM may provide insights into this disease entity. ICI-T1DM is a rare but often life-threatening medical emergency that healthcare professionals and patients need to be aware of. Early detection of and screening for this disease is imperative. At present, the only known treatment for ICI-T1DM is insulin injection. Further research into the mechanisms and risk factors associated with ICI-T1DM development may contribute to a better understanding of this disease entity and the identification of possible preventive strategies.
Dyslipidemia is a potentially modifiable cardiovascular risk factor. Whereas the recommendations for the treatment target of dyslipidemia in the general population are being more and more rigorous, the 2013 Kidney Disease: Improving Global Outcomes clinical practice guideline for lipid management in chronic kidney disease (CKD) presented a relatively conservative approach with respect to the indication of lipid lowering therapy and therapeutic monitoring among the patients with CKD. This may be largely attributed to the lack of high-quality evidence derived from CKD population, among whom the overall feature of dyslipidemia is considerably distinctive to that of general population. In this review article, we cover the characteristic features of dyslipidemia and impact of dyslipidemia on cardiovascular outcomes in patients with CKD. We also review the current evidence on lipid lowering therapy to modify the risk of cardiovascular events in this population. We finally discuss the association between dyslipidemia and CKD progression and the potential strategy to delay the progression of CKD in relation to lipid lowering therapy.
In this review, we provide a brief synopsis of the connections between adipose tissue and metabolic health and highlight some recent developments in understanding and exploiting adipocyte biology. Adipose tissue plays critical roles in the regulation of systemic glucose and lipid metabolism and secretes bioactive molecules possessing endocrine, paracrine, and autocrine functions. Dysfunctional adipose tissue has a detrimental impact on metabolic health and is intimately involved in key aspects of metabolic diseases such as insulin resistance, lipid overload, inflammation, and organelle stress. Differences in the distribution of fat depots and adipose characteristics relate to divergent degrees of metabolic dysfunction found in metabolically healthy and unhealthy obese individuals. Thermogenic adipocytes increase energy expenditure via mitochondrial uncoupling or adenosine triphosphate-consuming futile substrate cycles, while functioning as a metabolic sink and participating in crosstalk with other metabolic organs. Manipulation of adipose tissue provides a wealth of opportunities to intervene and combat the progression of associated metabolic diseases. We discuss current treatment modalities for obesity including incretin hormone analogs and touch upon emerging strategies with therapeutic potential including exosome-based therapy, pharmacological activation of brown and beige adipocyte thermogenesis, and administration or inhibition of adipocyte-derived factors.
Primary cilia are microtubule-based sensory and signaling organelles on the surfaces of most eukaryotic cells. Despite their early description by microscopy studies, islet cilia had not been examined in the functional context until recent decades. In pancreatic islets as in other tissues, primary cilia facilitate crucial developmental and signaling pathways in response to extracellular stimuli. Many human developmental and genetic disorders are associated with ciliary dysfunction, some manifesting as obesity and diabetes. Understanding the basis for metabolic diseases in human ciliopathies has been aided by close examination of cilia action in pancreatic islets at cellular and molecular levels. In this article, we review the evidence for ciliary expression on islet cells, known roles of cilia in pancreas development and islet hormone secretion, and summarize metabolic manifestations of human ciliopathy syndromes. We discuss emerging data on primary cilia regulation of islet cell signaling and the structural basis of cilia-mediated cell crosstalk, and offer our interpretation on the role of cilia in glucose homeostasis and human diseases.
Cellular senescence is accelerated by hyperglycemia through multiple pathways. Therefore, senescence is an important cellular mechanism to consider in the pathophysiology of type 2 diabetes mellitus (T2DM) and an additional therapeutic target. The use of drugs that remove senescent cells has led to improvements in blood glucose levels and diabetic complications in animal studies. Although the removal of senescent cells is a promising approach for the treatment of T2DM, two main challenges limit its clinical application: the molecular basis of cellular senescence in each organ is yet to be understood, and the specific effect of removing senescent cells in each organ has to be determined. This review aims to discuss future applications of targeting senescence as a therapeutic option in T2DM and elucidate the characteristics of cellular senescence and senescence-associated secretory phenotype in the tissues important for regulating glucose levels: pancreas, liver, adipocytes, and skeletal muscle.
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Gestational diabetes mellitus (GDM) has historically been perceived as a medical complication of pregnancy that also serves as a harbinger of maternal risk of developing type 2 diabetes mellitus (T2DM) in the future. In recent decades, a growing body of evidence has detailed additional lifelong implications that extend beyond T2DM, including an elevated risk of ultimately developing cardiovascular disease. Furthermore, the risk factors that mediate this lifetime cardiovascular risk are evident not only after delivery but are present even before the pregnancy in which GDM is first diagnosed. The concept thus emerging from these data is that the diagnosis of GDM enables the identification of women who are already on an enhanced track of cardiometabolic risk that starts early in life. Studies of the offspring of pregnancies complicated by diabetes now suggest that the earliest underpinnings of this cardiometabolic risk profile may be determined in utero and may first manifest clinically in childhood. Accordingly, from this perspective, GDM is now seen as a chronic metabolic disorder that holds implications across the life span of both mother and child.
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Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and approximately one in 11 adults worldwide have diabetes mellitus. Since both microvascular and macrovascular diseases in patients with diabetes predispose them to a lower quality of life as well as higher rates of mortality, managing blood glucose levels is of clinical relevance in diabetes care. Many classes of antihyperglycemic drugs are currently approved to treat hyperglycemia in patients with type 2 diabetes mellitus, with several new drugs having been developed during the last decade. Diabetes-related complications have been reduced substantially worldwide. Prioritization of therapeutic agents varies according to national guidelines. However, since the characteristics of participants in clinical trials differ from patients in actual clinical practice, it is difficult to apply the results of such trials to clinical practice. Machine learning approaches became highly topical issues in medicine along with rapid technological innovations in the fields of information and communication in the 1990s. However, adopting these technologies to support decision-making regarding drug treatment strategies for diabetes care has been slow. This review summarizes data from recent studies on the choice of drugs for type 2 diabetes mellitus focusing on machine learning approaches.
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