Leveraging the future of diagnosis and management of diabetes: From old indexes to new technologies.

BACKGROUND: Diabetes is a heterogeneous and multifactorial disease. However, glycemia and glycated hemoglobin have been the focus of diabetes diagnosis and management for the last decades. As diabetes management goes far beyond glucose control, it has become clear that assessment of other biochemical parameters gives a much wider view of the metabolic state of each individual, enabling a precision medicine approach. METHODS: In this review, we summarize and discuss indexes that have been used in epidemiological studies and in the clinical practice. RESULTS: Indexes of insulin secretion, sensitivity/resistance and metabolism have been developed and validated over the years to account also with insulin, C-peptide, triglycerides or even anthropometric measures. Nevertheless, each one has their own objective and consequently, advantages and disadvantages for specific cases. Thus, we discuss how new technologies, namely new sensors but also new softwares/applications, can improve the diagnosis and management of diabetes, both for healthcare professionals but also for caretakers and, importantly, to promote the empowerment of people living with diabetes. CONCLUSIONS: In long-term, the solution for a better diabetes management would be a platform that allows to integrate all sorts of relevant information for the person with diabetes and for the healthcare practitioners, namely glucose, insulin and C-peptide or, in case of need, other parameters/indexes at home, sometimes more than once a day. This solution would allow a better and simpler disease management, more adequate therapeutics thereby improving patients' quality of life and reducing associated costs.

Big data and machine learning to tackle diabetes management.

BACKGROUND: Type 2 Diabetes (T2D) diagnosis is based solely on glycaemia, even though it is an endpoint of numerous dysmetabolic pathways. Type 2 Diabetes complexity is challenging in a real-world scenario; thus, dissecting T2D heterogeneity is a priority. Cluster analysis, which identifies natural clusters within multidimensional data based on similarity measures, poses a promising tool to unravel Diabetes complexity. METHODS: In this review, we scrutinize and integrate the results obtained in most of the works up to date on cluster analysis and T2D. RESULTS: To correctly stratify subjects and to differentiate and individualize a preventive or therapeutic approach to Diabetes management, cluster analysis should be informed with more parameters than the traditional ones, such as etiological factors, pathophysiological mechanisms, other dysmetabolic co-morbidities, and biochemical factors, that is the millieu. Ultimately, the above-mentioned factors may impact on Diabetes and its complications. Lastly, we propose another theoretical model, which we named the Integrative Model. We differentiate three types of components: etiological factors, mechanisms and millieu. Each component encompasses several factors to be projected in separate 2D planes allowing an holistic interpretation of the individual pathology. CONCLUSION: Fully profiling the individuals, considering genomic and environmental factors, and exposure time, will allow the drive to precision medicine and prevention of complications.

Distinct impacts of fat and fructose on the liver, muscle, and adipose tissue metabolome: An integrated view.

Objective: In the last years, changes in dietary habits have contributed to the increasing prevalence of metabolic disorders, such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). The differential burden of lipids and fructose on distinct organs needs to be unveiled. Herein, we hypothesized that high-fat and high-fructose diets differentially affect the metabolome of insulin-sensitive organs such as the liver, muscle, and different adipose tissue depots. Methods: We have studied the impact of 12 weeks of a control (11.50% calories from fat, 26.93% from protein, and 61.57% from carbohydrates), high-fat/sucrose (HFat), or high-fructose (HFruct) feeding on C57Bl/6J male mice. Besides glucose homeostasis, we analyzed the hepatic levels of glucose and lipid-metabolism-related genes and the metabolome of the liver, the muscle, and white (WAT) and brown adipose tissue (BAT) depots. Results: HFat diet led to a more profound impact on hepatic glucose and lipid metabolism than HFruct, with mice presenting glucose intolerance, increased saturated fatty acids, and no glycogen pool, yet both HFat and HFruct presented hepatic insulin resistance. HFat diet promoted a decrease in glucose and lactate pools in the muscle and an increase in glutamate levels. While HFat had alterations in BAT metabolites that indicate increased thermogenesis, HFruct led to an increase in betaine, a protective metabolite against fructose-induced inflammation. Conclusions: Our data illustrate that HFat and HFruct have a negative but distinct impact on the metabolome of the liver, muscle, WAT, and BAT.

Fibrosis nonalcoholic steatohepatitis index validation and applicability considering glycaemic severity and T2D duration.

Nonalcoholic fatty liver disease (NAFLD) diagnosis without using invasive methods is extremely challenging, highlighting the need for simple indexes for this end. Recently, the fibrotic nonalcoholic steatohepatitis index (FNI) was developed and proposed as an affordable non-invasive score calculated with aspartate aminotransferase, high-density lipoprotein cholesterol and haemoglobin A1c. Herein, and given the link between NAFLD and diabetes, we aimed at validating FNI in a population with type 2 diabetes (T2D), also considering diabetes duration and glycaemic severity. The performance of FNI was higher than FIB-4 (AUROC = 0.89 vs 0.67, respectively). Additionally, using 0.1 as the rule-out cut-off of FNI, the sensitivity was 0.99 and the positive predictive value was 0.19. Both duration of diabetes and A1c did not impact FNI performance. In sum, FNI is a valuable score for predicting fibrotic nonalcoholic steatohepatitis not only for primary care units but also for diabetes specialized care.

Prediabetes blunts DPP4 genetic control of postprandial glycaemia and insulin secretion.

AIMS/HYPOTHESIS: Imbalances in glucose metabolism are hallmarks of clinically silent prediabetes (defined as impaired fasting glucose and/or impaired glucose tolerance) representing dysmetabolism trajectories leading to type 2 diabetes. CD26/dipeptidyl peptidase 4 (DPP4) is a clinically proven molecular target of diabetes-controlling drugs but the DPP4 gene control of dysglycaemia is not proven. METHODS: We dissected the genetic control of post-OGTT and insulin release responses by the DPP4 gene in a Portuguese population-based cohort of mainly European ancestry that comprised individuals with normoglycaemia and prediabetes, and in mouse experimental models of Dpp4 deficiency and hyperenergetic diet. RESULTS: In individuals with normoglycaemia, DPP4 single-nucleotide variants governed glycaemic excursions (rs4664446, p=1.63x10-7) and C-peptide release responses (rs2300757, p=6.86x10-5) upon OGTT. Association with blood glucose levels was stronger at 30 min OGTT, but a higher association with the genetic control of insulin secretion was detected in later phases of the post-OGTT response, suggesting that the DPP4 gene directly senses glucose challenges. Accordingly, in mice fed a normal chow diet but not a high-fat diet, we found that, under OGTT, expression of Dpp4 is strongly downregulated at 30 min in the mouse liver. Strikingly, no genetic association was found in prediabetic individuals, indicating that post-OGTT control by DPP4 is abrogated in prediabetes. Furthermore, Dpp4 KO mice provided concordant evidence that Dpp4 modulates post-OGTT C-peptide release in normoglycaemic but not dysmetabolic states. CONCLUSIONS/INTERPRETATION: These results showed the DPP4 gene as a strong determinant of post-OGTT levels via glucose-sensing mechanisms that are abrogated in prediabetes. We propose that impairments in DPP4 control of post-OGTT insulin responses are part of molecular mechanisms underlying early metabolic disturbances associated with type 2 diabetes.

Increased Intake of Both Caffeine and Non-Caffeine Coffee Components Is Associated with Reduced NAFLD Severity in Subjects with Type 2 Diabetes.

Coffee may protect against non-alcoholic fatty liver disease (NAFLD), but the roles of the caffeine and non-caffeine components are unclear. Coffee intake by 156 overweight subjects (87% with Type-2-Diabetes, T2D) was assessed via a questionnaire, with 98 subjects (all T2D) also providing a 24 h urine sample for quantification of coffee metabolites by LC-MS/MS. NAFLD was characterized by the fatty liver index (FLI) and by Fibroscan® assessment of fibrosis. No associations were found between self-reported coffee intake and NAFLD parameters; however, total urine caffeine metabolites, defined as Σcaffeine (caffeine + paraxanthine + theophylline), and adjusted for fat-free body mass, were significantly higher for subjects with no liver fibrosis than for those with fibrosis. Total non-caffeine metabolites, defined as Σncm (trigonelline + caffeic acid + p-coumaric acid), showed a significant negative association with the FLI. Multiple regression analyses for overweight/obese T2D subjects (n = 89) showed that both Σcaffeine and Σncm were negatively associated with the FLI, after adjusting for age, sex, HbA1c, ethanol intake and glomerular filtration rate. The theophylline fraction of Σcaffeine was significantly increased with both fibrosis and the FLI, possibly reflecting elevated CYP2E1 activity-a hallmark of NAFLD worsening. Thus, for overweight/obese T2D patients, higher intake of both caffeine and non-caffeine coffee components is associated with less severe NAFLD. Caffeine metabolites represent novel markers of NAFLD progression.

Insulin-degrading enzyme: an ally against metabolic and neurodegenerative diseases.

Insulin-degrading enzyme (IDE) function goes far beyond its known proteolytic role as a regulator of insulin levels. IDE has a wide substrate promiscuity, degrading several proteins such as amyloid-ß peptide, glucagon, islet amyloid polypeptide (IAPP), and insulin-like growth factors, which have diverse physiological and pathophysiological functions. Importantly, IDE plays other non-proteolytic functions such as: a chaperone/dead-end chaperone, an E1-ubiquitin activating enzyme, and a proteasome modulator. It also responds as a heat shock protein, regulating cellular proteostasis. Notably, amyloidogenic proteins such as IAPP, amyloid-ß, and α-synuclein have been reported as substrates for IDE chaperone activity. This is of utmost importance as failure of IDE may result in increased protein aggregation, a key hallmark in the pathogenesis of beta cells in type 2 diabetes mellitus and of neurons in neurodegenerative diseases such as Alzheimer's and Parkinson's disease. In this review, we focus on the biochemical and biophysical properties of IDE and the regulation of its physiological functions. We further raise the hypothesis that IDE plays a central role in the pathological context of dysmetabolic and neurodegenerative diseases and discuss its potential as a therapeutic target. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Insulin: Trigger and Target of Renal Functions.

Kidney function in metabolism is often underestimated. Although the word "clearance" is associated to "degradation", at nephron level, proper balance between what is truly degraded and what is redirected to de novo utilization is crucial for the maintenance of electrolytic and acid-basic balance and energy conservation. Insulin is probably one of the best examples of how diverse and heterogeneous kidney response can be. Kidney has a primary role in the degradation of insulin released in the bloodstream, but it is also incredibly susceptible to insulin action throughout the nephron. Fluctuations in insulin levels during fast and fed state add another layer of complexity in the understanding of kidney fine-tuning. This review aims at revisiting renal insulin actions and clearance and to address the association of kidney dysmetabolism with hyperinsulinemia and insulin resistance, both highly prevalent phenomena in modern society.

Paraoxonase-1 as a Regulator of Glucose and Lipid Homeostasis: Impact on the Onset and Progression of Metabolic Disorders.

Metabolic disorders are characterized by an overall state of inflammation and oxidative stress, which highlight the importance of a functional antioxidant system and normal activity of some endogenous enzymes, namely paraoxonase-1 (PON1). PON1 is an antioxidant and anti-inflammatory glycoprotein from the paraoxonases family. It is mainly expressed in the liver and secreted to the bloodstream, where it binds to HDL. Although it was first discovered due to its ability to hydrolyze paraoxon, it is now known to have an antiatherogenic role. Recent studies have shown that PON1 plays a protective role in other diseases that are associated with inflammation and oxidative stress, such as Type 1 and Type 2 Diabetes Mellitus and Non-Alcoholic Fatty Liver Disease. The aim of this review is to elucidate the physiological role of PON1, as well as the impact of altered PON1 levels in metabolic disorders.

Data on metabolic profile of insulin-degrading enzyme knockout mice.

Insulin-degrading enzyme (IDE) degrades and inactivates bioactive peptides such as insulin. As insulin is a master regulator of glucose homeostasis, lack of IDE is expected to have a profound impact on both insulin and glucose levels. This article shares data on glucose and insulin homeostasis of control, heterozygous and knockout mice for Ide after 18 weeks of a normal chow diet. This data article is related to a research article entitled "Knockout of insulin-degrading enzyme leads to mice testicular morphological changes and impaired sperm quality" (Meneses et al., 2019).

Knockout of insulin-degrading enzyme leads to mice testicular morphological changes and impaired sperm quality.

Insulin-degrading enzyme (IDE) is a zinc metalloprotease responsible for degrading and inactivating several bioactive peptides, including insulin. Individuals without this enzyme or with a loss-of-function mutation in the gene that codifies it, present hyperinsulinemia. In addition, impairment of IDE-mediated insulin clearance is associated with the development of metabolic diseases, namely prediabetes. Although insulin regulates male fertility, the role of IDE on male reproductive function remains unknown. We proposed to study the influence of IDE in the reproductive potential of males. As insulin mediates key events for the normal occurrence of spermatogenesis, we hypothesized that IDE functioning might be linked with sperm quality. We used C57BL/6N mice that were divided in three groups according to its genotype: wild type (WT), heterozygous and knockout (KO) male mice for Ide. Spermatozoa were collected from the cauda of epididymis and sperm parameters were evaluated. Testicular tissue morphology was assessed through hematoxylin and eosin stain. Mitochondrial complex protein levels and lipid peroxidation were also evaluated in the testicular tissue. Our results show that KO mice present a 50% decrease in testes weight compared to WT mice as well as a decrease in seminiferous tubules diameter. Moreover, KO mice present impaired sperm quality, namely a decrease in both sperm viability and morphology. These results provide evidence that IDE plays an important role in determining the reproductive potential of males.

New insights on hormones and factors that modulate Sertoli cell metabolism.

Sertoli cells (SCs) play a key role in spermatogenesis by providing the physical support for developing germ cells and ensuring them the appropriate nutrients, energy sources, hormones, and growth factors. The control of SCs metabolism has been in the spotlight for reproductive biologists, since it may be crucial to determine germ cells' fate. Indeed, the maintenance of spermatogenesis is highly dependent on the metabolic cooperation established between SCs and germ cells, though this event has been overlooked. It depends on the orchestration of various metabolic pathways and an intricate network of signals. Several factors and/or hormones modulate the metabolic activity of SCs, which are major targets for the hormonal signalling that regulates spermatogenesis. Any alteration in the regulation of these cells' metabolic behaviour may compromise the normal development of spermatogenesis and consequently, male fertility. In this context, SC metabolism arises as a key regulation point for spermatogenesis. Herein, we present an up-to-date overview on the impact of hormones and factors that modulate SC metabolism, with special focus on glycolytic metabolism, highlighting their relevance in determining male reproductive potential.