Journal of Diabetes Investigation最新文献

A recent study by Warncke et al. suggested that islet autoimmunity is associated with or preceded by insults or changes to the pancreatic islets that impair glucose homeostasis, raising the possibility that β-cell insult occurs first, followed by autoimmunity to islets.

To the Editor

The Pemafibrate to Reduce Cardiovascular Outcomes by Reducing Triglycerides in Patients with Diabetes (PROMINENT) trial was recently published in the New England of Journal of Medicine,¹ and failed to show a preventive effect of pemafibrate on atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes and dyslipidemia. This study was designed to determine whether pemafibrate, a triglyceride (TG)-lowering drug, can reduce the incidence of ASCVD in hypertriglyceridemic and low high-density lipoprotein cholesterol patients, whose low-density lipoprotein cholesterol (LDL-C) is controlled <70 mg/dL with statins. As TG-rich lipoproteins (TRLs), especially its remnants, are considered to be atherogenic, like LDL, it was of interest to see if selective suppression of TRLs with pemafibrate would reduce CV events. The results showed that lowering TRL with pemafibrate did not lead to a reduction in CV events, suggesting that TRL does not play an important role in the development of atherosclerosis when LDL-C is tightly controlled. The results of this study will further solidify LDL's status as an unrivaled atherogenic lipoprotein.

LDL includes both large buoyant LDL and small density (sd) LDL particles, the latter of which are more atherogenic than the former. Recent large cohort studies showed that sdLDL-C is a powerful biomarker for ASCVD beyond LDL-C. It is well documented that sdLDL-C levels are substantially elevated in hypertriglyceridemic diabetes. As sdLDL-C is positively correlated with TG, pemafibrate treatment should reduce sdLDL-C by its TG-lowering effect. If so, why did the favorable change in LDL composition not lead to a reduction in CV events? Sampson et al.² proposed a formula for calculating sdLDL-C using LDL-C and TG as variables, based on our established direct sdLDL-C measurement.³ They also showed that calculated sdLDL-C is a strong predictor of ASCVD.³ As the PROMINENT study showed actual values of TG, total-C and high-density lipoprotein cholesterol at baseline, and 4 and 12 months,¹ sdLDL-C can be calculated. Table 1 shows calculated sdLDL-C in the PROMINENT study. Surprisingly, sdLDL-C levels were almost identical in the pemafibrate and placebo groups. This is supported by the fact that levels of non-high-density lipoprotein cholesterol and apolipoprotein B, known as surrogate markers for sdLDL-C, were not reduced by pemafibrate.¹ In the phase III study, pemafibrate alone or in combination with pemafibrate and a statin reduced the sdLDL fraction, but in the PROMINENT study, pemafibrate did not reduce the calculated value of sdLDL-C. A possible reason for this is that most participants in the phase III study had higher baseline LDL-C concentrations than in the PROMINENT trial, in which most participants received intensive st

In 2000, the world's age-adjusted prevalence of type 1 diabetes with onset under 15 years was reported using data from 1990 to 1994¹. The lowest incidence rate (/10⁵ person-years) was 0.1 in China and Venezuela, and the highest was 36.8 in Sardinia and 36.5 in Finland; revealing a difference of more than 350-fold between the lowest and highest incidence rates. Other high-incidence countries included Sweden, Norway, Canada, the United Kingdom, and New Zealand. East Asia belonged to the low incidence group, and Japan had an incidence rate of 1.1–2.2. In Asia and Africa, with an overall low incidence rate, the incidence rate is high in girls, while in Europe and the United States, with an overall high incidence rate, it is the same or higher in boys². Different reasons have been proposed for this discrepancy including genetics, racial differences, epidemiological sampling problems, autoimmunity, and pregnancy; however, the mechanism of this discrepancy is not completely understood.

The 2021 International Diabetes Federation (IDF) Atlas 10th edition³ published an estimate of 108,300 (149,500) annual new-onset type 1 diabetes cases under 15 years of age (under 20 years of age). The estimated prevalence was 651,700 (1,211,900), and compared with previous IDF Atlas estimates, there has been an increase in the incidence in many IDF regions. The reasons for this increase in incidence have been not clear, but in addition to the presence of susceptible genomic background in type 1 diabetes, environmental factors including changes milk intake, exposure to heterologous proteins from early birth, and rapid postnatal growth have been proposed to be associated with an increased incidence of type 1 diabetes. Furthermore, lifestyle changes, including a decrease in the morbidity of infectious diseases, have been proposed to affect the incidence of type 1 diabetes. Furthermore, lifestyle changes, including a decrease in the morbidity of infectious diseases, have been proposed to affect the incidence of type 1 diabetes. The male-to-female ratio of incidence in the countries and regions, described in the previous paragraph, has not changed significantly from the previous state.

From the end of 2019, it was reported that Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-Cov-2) infection spread worldwide and caused various symptoms. It has been reported that the incidence of childhood-onset type 1 diabetes increased after SARS-Cov-2 infection^{4, 5}. Additionally, there are some reports of type 1 diabetes developing after vaccination against Coronavirus disease (COVID)-19^6-8. However, currently it is impossible to clarify the causal relationship between the COVID-19 ribonucleic acid (RNA)-based vaccine and the onset of type 1 diabetes. As the relationship between the Coxsackie virus and the onset of type 1 diabetes has been r

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.

Type 2 diabetes is no longer seen as being an irreversible natural course, accompanied by progressive beta cell failure and various chronic diabetes related complications. In contrast, remission can be achieved through a personalized approach. It is a paradigm shift in our understanding of type 2 diabetes and it may be necessary to change the concept of type 2 diabetes as an urgent condition requiring rapid intervention rather than a chronic progressive disease.

Possible mechanisms of Alzheimer's disease-related cognitive impairment in patients with diabetes mellitus are shown in this figure. DPP-4i may modulate Aβ accumulation in the process of AD-related cognitive impairment.