The lung extracellular matrix protein landscape in severe early-onset and moderate chronic obstructive pulmonary disease.

Extracellular matrix (ECM) remodeling has been implicated in the irreversible obstruction of airways and destruction of alveolar tissue in chronic obstructive pulmonary disease (COPD). Studies investigating differences in the lung ECM in COPD have mainly focused on some collagens and elastin, leaving an array of ECM components unexplored. We investigated the differences in the ECM landscape comparing severe-early onset (SEO-) COPD and moderate COPD to control lung tissue for collagen type I α chain 1 (COL1A1), COL6A1, COL6A2, COL14A1, fibulin 2 and 5 (FBLN2, FBLN5), latent transforming growth factor-beta binding protein 4 (LTBP4), lumican (LUM), versican (VCAN), decorin (DCN), and elastin (ELN) using image analysis and statistical modelling. Percentage area and/or mean intensity of expression of LUM in the parenchyma, and COL1A1, FBLN2, LTBP4, DCN, and VCAN in the airway walls, was proportionally lower in COPD compared to controls. Lowered levels of most ECM proteins were associated with decreasing FEV1 measurements, indicating a relationship with disease severity. Furthermore, we identified six unique ECM signatures where LUM and COL6A1 in parenchyma and COL1A1, FBLN5, DCN, and VCAN in airway walls appear essential in reflecting the presence and severity of COPD. These signatures emphasize the need to examine groups of proteins to represent an overall difference in the ECM landscape in COPD, that are more likely to be related to functional effects, than individual proteins. Our study revealed differences in the lung ECM landscape between control and COPD and between SEO and moderate COPD signifying distinct pathological processes in the different subgroups.

Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores.

Identifying biomarkers of functional ß-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. A limitation of these screening tools is that the presence of autoantibodies marks the initiation of ß-cell loss, and is therefore not the best biomarker of progression to early-stage type 1 diabetes. GRS, on the other hand, represents a static biomarker offering a single risk score over an individual's lifetime. In this Personal View, we explore the challenges and opportunities of static and dynamic biomarkers in the prediction of progression to type 1 diabetes. We discuss future directions wherein newer dynamic risk scores could be used to predict type 1 diabetes risk, assess the efficacy of new and emerging drugs to retard, or prevent type 1 diabetes, and possibly replace or further enhance the predictive ability offered by static biomarkers, such as GRS.

Short-chain fatty acids and insulin sensitivity: a systematic review and meta-analysis.

CONTEXT: There is substantial evidence that reduced short-chain fatty acids (SCFAs) in the gut are associated with obesity and type 2 diabetes, although findings from clinical interventions that can increase SCFAs are inconsistent. OBJECTIVE: This systematic review and meta-analysis aimed to assess the effect of SCFA interventions on fasting glucose, fasting insulin, and homeostatic model assessment of insulin resistance (HOMA-IR). DATA SOURCES: Relevant articles published up to July 28, 2022, were extracted from PubMed and Embase using the MeSH (Medical Subject Headings) terms of the defined keywords [(short-chain fatty acids) AND (obesity OR diabetes OR insulin sensitivity)] and their synonyms. Data analyses were performed independently by two researchers who used the Cochrane meta-analysis checklist and the PRISMA guidelines. DATA EXTRACTION: Clinical studies and trials that measured SCFAs and reported glucose homeostasis parameters were included in the analysis. Standardized mean differences (SMDs) with 95%CIs were calculated using a random-effects model in the data extraction tool Review Manager version 5.4 (RevMan 5.4). The risk-of-bias assessment was performed following the Cochrane checklist for randomized and crossover studies. DATA ANALYSIS: In total, 6040 nonduplicate studies were identified, 23 of which met the defined criteria, reported fasting insulin, fasting glucose, or HOMA-IR values, and reported change in SCFA concentrations post intervention. Meta-analyses of these studies indicated that fasting insulin concentrations were significantly reduced (overall effect: SMD = -0.15; 95%CI = -0.29 to -0.01, P = 0.04) in treatment groups, relative to placebo groups, at the end of the intervention. Studies with a confirmed increase in SCFAs at the end of intervention also had a significant effect on lowering fasting insulin (P = 0.008). Elevated levels of SCFAs, compared with baseline levels, were associated with beneficial effects on HOMA-IR (P < 0.00001). There was no significant change in fasting glucose concentrations. CONCLUSION: Increased postintervention levels of SCFAs are associated with lower fasting insulin concentrations, offering a beneficial effect on insulin sensitivity. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD42021257248.

MicroRNAs Signature Panel Identifies Heavy Drinkers with Alcohol-Associated Cirrhosis from Heavy Drinkers without Liver Injury.

Background: Alcohol-associated liver disease (ALD) is the most common disorder of prolonged drinking. Mechanisms underlying cirrhosis in such patients remain unclear. MicroRNAs play regulatory role in several diseases, are affected by alcohol and may be important players in alcohol use disorders, such as cirrhosis. Methods: We investigated serum samples from heavy chronic alcohol users (80 g/day (male) and 50 g/day (female) for ≥10 years) that were available from our previously reported GenomALC study. A subset of GenomALC drinkers with liver cirrhosis (cases, n = 24) and those without significant liver disease (drinking controls, n = 23) were included. Global microRNA profiling was performed using high-throughput real-time quantitative PCR to identify the microRNA signatures associated with cirrhosis. Ingenuity Pathway Analysis (IPA) software was utilized to identify target mRNAs of significantly altered microRNAs, and molecular pathways were analysed. Identified microRNAs were analysed for correlation with traditional liver disease biomarkers and risk gene variants previously reported from GenomALC genome-wide association study. Results: The expression of 21 microRNAs was significantly downregulated in cases compared to drinking controls (p < 0.05, ∆∆Ct > 1.5-fold). Seven microRNAs (miR-16, miR-19a, miR-27a, miR-29b, miR-101, miR-130a, and miR-191) had a highly significant correlation (p < 0.001) with INR, bilirubin and MELD score. Three microRNAs (miR-27a, miR-130a and miR-191) significantly predicted cases with AUC-ROC 0.8, 0.78 and 0.85, respectively (p < 0.020); however, INR performed best (0.97, p < 0.001). A different set of six microRNAs (miR-19a, miR-26a, miR-101, miR-151-3p, miR-221, and miR-301) showed positive correlation (ranging from 0.32 to 0.51, p < 0.05) with rs10433937:HSD17B13 gene variant, associated with the risk of cirrhosis. IPA analysis revealed mRNA targets of the significantly altered microRNAs associated with cell death/necrosis, fibrosis and increased steatosis, particularly triglyceride metabolism. Conclusions: MicroRNA signatures in drinkers distinguished those with liver cirrhosis from drinkers without liver disease. We identified mRNA targets in liver functions that were enriched for disease pathogenesis pathways.

Innovative three-dimensional models for understanding mechanisms underlying lung diseases: powerful tools for translational research.

Chronic lung diseases result from alteration and/or destruction of lung tissue, inevitably causing decreased breathing capacity and quality of life for patients. While animal models have paved the way for our understanding of pathobiology and the development of therapeutic strategies for disease management, their translational capacity is limited. There is, therefore, a well-recognised need for innovative in vitro models to reflect chronic lung diseases, which will facilitate mechanism investigation and the advancement of new treatment strategies. In the last decades, lungs have been modelled in healthy and diseased conditions using precision-cut lung slices, organoids, extracellular matrix-derived hydrogels and lung-on-chip systems. These three-dimensional models together provide a wide spectrum of applicability and mimicry of the lung microenvironment. While each system has its own limitations, their advantages over traditional two-dimensional culture systems, or even over animal models, increases the value of in vitro models. Generating new and advanced models with increased translational capacity will not only benefit our understanding of the pathobiology of lung diseases but should also shorten the timelines required for discovery and generation of new therapeutics. This article summarises and provides an outline of the European Respiratory Society research seminar "Innovative 3D models for understanding mechanisms underlying lung diseases: powerful tools for translational research", held in Lisbon, Portugal, in April 2022. Current in vitro models developed for recapitulating healthy and diseased lungs are outlined and discussed with respect to the challenges associated with them, efforts to develop best practices for model generation, characterisation and utilisation of models and state-of-the-art translational potential.

MicroRNA Profiling from Tears as a Potential Non-invasive Method for Early Detection of Diabetic Retinopathy.

Diabetic retinopathy (DR) is a vascular complication of diabetes that can lead to partial or complete loss of vision. Early detection and treatment of DR can prevent blindness. Regular clinical examination is recommended for DR diagnosis; however, it is not always possible or feasible due to limited resources, expertise, time, and infrastructure. Several clinical and molecular biomarkers are proposed for the prediction of DR including microRNAs. MicroRNAs are a class of small non-coding RNAs that are found in biofluids and can be measured using reliable and sensitive methods. The most commonly used biofluid for microRNA profiling is plasma or serum; however, tear fluid (tears) is also demonstrated to contain microRNAs. MicroRNAs isolated from tears present a non-invasive source for DR detection. Different methods of microRNA profiling are available including digital PCR-based methods that can detect up to a single copy of microRNA in the biofluids. Here, we describe microRNA isolation from tears using manual method as well as using a high-throughput automated platform followed by microRNA profiling using digital PCR system.

The link between glycemic control measures and eye microvascular complications in a clinical cohort of type 2 diabetes with microRNA-223-3p signature.

BACKGROUND: Type 2 diabetes (T2D) is a critical healthcare challenge and priority in Qatar which is listed amongst the top 10 countries in the world, with its prevalence presently at 17% double the global average. MicroRNAs (miRNAs) are implicated in the pathogenesis of (T2D) and long-term microvascular complications including diabetic retinopathy (DR). METHODS: In this study, a T2D cohort that accurately matches the characteristics of the general population was employed to find microRNA (miRNA) signatures that are correlated with glycemic and ß cell function measurements. Targeted miRNA profiling was performed in (471) T2D individuals with or without DR and (491) (non-diabetic) healthy controls from the Qatar Biobank. Discovery analysis identified 20 differentially expressed miRNAs in T2D compared to controls, of which miR-223-3p was significantly upregulated (fold change:5.16, p = 3.6e-02) and positively correlated with glucose and hemoglobin A1c (HbA1c) levels (p-value = 9.88e-04 and 1.64e-05, respectively), but did not show any significant associations with insulin or C-peptide. Accordingly, we performed functional validation using a miR-223-3p mimic (overexpression) under control and hyperglycemia-induced conditions in a zebrafish model. RESULTS: Over-expression of miR-223-3p alone was associated with significantly higher glucose (42.7 mg/dL, n = 75 vs 38.7 mg/dL, n = 75, p = 0.02) and degenerated retinal vasculature, and altered retinal morphology involving changes in the ganglion cell layer and inner and outer nuclear layers. Assessment of retinal angiogenesis revealed significant upregulation in the expression of vascular endothelial growth factor and its receptors, including kinase insert domain receptor. Further, the pancreatic markers, pancreatic and duodenal homeobox 1, and the insulin gene expressions were upregulated in the miR-223-3p group. CONCLUSION: Our zebrafish model validates a novel correlation between miR-223-3p and DR development. Targeting miR-223-3p in T2D patients may serve as a promising therapeutic strategy to control DR in at-risk individuals.

Optimised plasma sample preparation and LC-MS analysis to support large-scale proteomic analysis of clinical trial specimens: Application to the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial.

PURPOSE: Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis of more than 1500 samples from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial of adults with type 2 diabetes. METHODS: Using LC-MS with data-independent acquisition we evaluated four variables: plasma protein depletion, EDTA or citrated anti-coagulant blood collection tubes, plasma lipid depletion strategies and plasma freeze-thaw cycles. Optimised methods were applied in a pilot study of FIELD participants. RESULTS: LC-MS of undepleted plasma conducted over a 45 min gradient yielded 172 proteins after excluding immunoglobulin isoforms. Cibachrome-blue-based depletion yielded additional proteins but with cost and time expenses, while immunodepleting albumin and IgG provided few additional identifications. Only minor variations were associated with blood collection tube type, delipidation methods and freeze-thaw cycles. From 65 batches involving over 1500 injections, the median intra-batch quantitative differences in the top 100 proteins of the plasma external standard were less than 2%. Fenofibrate altered seven plasma proteins. CONCLUSIONS AND CLINICAL RELEVANCE: A robust plasma handling and LC-MS proteomics workflow for abundant plasma proteins has been developed for large-scale biomarker studies that balance proteomic depth with time and resource costs.

Early emergence of sexual dimorphism in offspring leukocyte telomere length was associated with maternal and children's glucose metabolism-a longitudinal study.

BACKGROUND: Leukocyte telomere length (LTL) is suggested to be a biomarker of biological age and reported to be associated with metabolic diseases such as type 2 diabetes. Glucose metabolic traits including glucose and insulin levels have been reported to be associated with LTL in adulthood. However, there is relatively little research focusing on children's LTL and the association with prenatal exposures. This study investigates the relationship between maternal and offspring glucose metabolism with offspring LTL in early life. METHODS: This study included 882 mother-child pairs from the HAPO Hong Kong Field Centre, with children evaluated at age 7.0 ± 0.4 (mean ± SD) years. Glucose metabolic traits including maternal post-load glucose during pregnancy, children's glucose and insulin levels, and their derived indices at follow-up were measured or calculated. Offspring LTL was assessed using real-time polymerase chain reaction. RESULTS: Sex- and age-adjusted children's LTL was found to be associated with children's HOMA-IR (ß=-0.046 ± 0.016, p=0.005). Interestingly, both children's and maternal post-load glucose levels were positively associated with children's LTL. However, negative associations were observed between children's LTL and children's OGTT insulin levels. In addition, the LTL in females was more strongly associated with pancreatic beta-cell function whilst LTL in males was more strongly associated with OGTT glucose levels. CONCLUSIONS: Our findings suggest a close association between maternal and offspring glucose metabolic traits with early life LTL, with the offspring sex as an important modifier of the disparate relationships in insulin production and response.

Highway to heal: Influence of altered extracellular matrix on infiltrating immune cells during acute and chronic lung diseases.

Environmental insults including respiratory infections, in combination with genetic predisposition, may lead to lung diseases such as chronic obstructive pulmonary disease, lung fibrosis, asthma, and acute respiratory distress syndrome. Common characteristics of these diseases are infiltration and activation of inflammatory cells and abnormal extracellular matrix (ECM) turnover, leading to tissue damage and impairments in lung function. The ECM provides three-dimensional (3D) architectural support to the lung and crucial biochemical and biophysical cues to the cells, directing cellular processes. As immune cells travel to reach any site of injury, they encounter the composition and various mechanical features of the ECM. Emerging evidence demonstrates the crucial role played by the local environment in recruiting immune cells and their function in lung diseases. Moreover, recent developments in the field have elucidated considerable differences in responses of immune cells in two-dimensional versus 3D modeling systems. Examining the effect of individual parameters of the ECM to study their effect independently and collectively in a 3D microenvironment will help in better understanding disease pathobiology. In this article, we discuss the importance of investigating cellular migration and recent advances in this field. Moreover, we summarize changes in the ECM in lung diseases and the potential impacts on infiltrating immune cell migration in these diseases. There has been compelling progress in this field that encourages further developments, such as advanced in vitro 3D modeling using native ECM-based models, patient-derived materials, and bioprinting. We conclude with an overview of these state-of-the-art methodologies, followed by a discussion on developing novel and innovative models and the practical challenges envisaged in implementing and utilizing these systems.

Short-chain fatty acid concentrations in the incidence and risk-stratification of colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: The beneficial role of gut microbiota and bacterial metabolites, including short-chain fatty acids (SCFAs), is well recognized, although the available literature around their role in colorectal cancer (CRC) has been inconsistent. METHODS: We performed a systematic review and meta-analysis to examine the associations of fecal SCFA concentrations to the incidence and risk of CRC. Data extraction through Medline, Embase, and Web of Science was carried out from database conception to June 29, 2022. Predefined inclusion/exclusion criteria led to the selection of 17 case-control and six cross-sectional studies for quality assessment and analyses. Studies were categorized for CRC risk or incidence, and RevMan 5.4 was used to perform the meta-analyses. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated using a random-effects model. Studies lacking quantitation were included in qualitative analyses. RESULTS: Combined analysis of acetic, propionic, and butyric acid revealed significantly lower concentrations of these SCFAs in individuals with a high-risk of CRC (SMD = 2.02, 95% CI 0.31 to 3.74, P = 0.02). Additionally, CRC incidence was higher in individuals with lower levels of SCFAs (SMD = 0.45, 95% CI 0.19 to 0.72, P = 0.0009), compared to healthy individuals. Qualitative analyses identified 70.4% of studies reporting significantly lower concentrations of fecal acetic, propionic, butyric acid, or total SCFAs in those at higher risk of CRC, while 66.7% reported significantly lower concentrations of fecal acetic and butyric acid in CRC patients compared to healthy controls. CONCLUSIONS: Overall, lower fecal concentrations of the three major SCFAs are associated with higher risk of CRC and incidence of CRC.

LED based large field of view off-axis quantitative phase contrast microscopy by hologram multiplexing.

In this manuscript, we describe the development of a single shot, self-referencing wavefront division, multiplexing digital holographic microscope employing LED sources for large field of view quantitative phase imaging of biological samples. To address the difficulties arising while performing interferometry with low temporally coherent sources, an optical arrangement utilizing multiple Fresnel Biprisms is used for hologram multiplexing, enhancing the field of view and increasing the signal to noise ratio. Biprisms offers the ease of obtaining interference patterns by automatically matching the path length between the two off-axis beams. The use of low temporally coherent sources reduces the speckle noise and the cost, and the form factor of the setup. The developed technique was implemented using both visible and UV LEDs and tested on polystyrene microspheres and human erythrocytes.

The microRNA-29 family: role in metabolism and metabolic disease.

The microRNA-29 family members miR-29a-3p, miR-29b-3p, and miR-29c-3p are ubiquitously expressed and consistently increased in various tissues and cell types in conditions of metabolic disease, obesity, insulin resistance, and type 2 diabetes. In pancreatic ß cells, miR-29a is required for normal exocytosis, but increased levels are associated with impaired ß-cell function. Similarly, in liver, miR-29 species are higher in models of insulin resistance and type 2 diabetes, and either knock-out or depletion using a microRNA inhibitor improves hepatic insulin resistance. In skeletal muscle, miR-29 family upregulation is associated with insulin resistance and altered substrate oxidation, and similarly, in adipocytes, overexpression of miR-29a leads to insulin resistance. Blocking miR-29a using nucleic acid antisense therapeutics show promising results in preclinical animal models of obesity and type 2 diabetes, although the widespread expression pattern of miR-29 family members complicates the exploration of single target tissues. However, in fibrotic diseases, such as in late complications of diabetes and metabolic disease (diabetic kidney disease, nonalcoholic steatohepatitis), miR-29 species expression is suppressed by TGF-ß allowing increased extracellular matrix collagen to form. In the clinical setting, circulating levels of miR-29a and miR-29b are consistently increased in type 2 diabetes and in gestational diabetes and are also possible prognostic markers for deterioration of glucose tolerance. In conclusion, miR-29 family miRNAs play an essential role in various organs relevant to intermediary metabolism and its upregulation contributes to impaired glucose metabolism, whereas it suppresses fibrosis development. Thus, a correct balance of levels of miR-29 family miRNA seems important for cellular and organ homeostasis in metabolism.

Bimetallic nanozyme mediated urine glucose monitoring through discriminant analysis of colorimetric signal.

The ability to detect glucose concentrations in human urine offers a non-invasive approach to monitor changes in blood glucose, kidney health and vascular complications associated with diabetes. We show the potential of employing catalytically active nanoparticles directly grown on textiles to produce a dose-dependent colorimetric sensor for glucose. We use a galvanic replacement (GR) reaction for the synthesis of bimetallic nanoparticles. Here, Cu nanoparticles act as a sacrificial template that undergoes a spontaneous electroless GR reaction when exposed to metal ions of gold, silver, platinum, and palladium to form bimetallic Cu-M nanoparticles (M = Au, Ag, Pt, or Pd). The evaluation of their intrinsic peroxidase-mimicking catalytic activity ("nanozyme") in comparison to that of the Cu nanozyme revealed that the bimetallic systems show a higher catalytic rate with the Cu-Pt nanozyme showing the highest catalytic efficiency. This property of the Cu-Pt nanozyme was then utilized to detect glucose in human urine using the glucose oxidase enzyme as a molecular recognition element. A key outcome of our study is the ability to detect urine glucose without requiring sample dilution which is an advantage over the gold standard GOx-POx method and significantly more reliable performance over commercial urine glucose dipsticks. The difference in the intensity of the colorimetric response between different glucose concentrations further allowed this sensor system to be combined with digital imaging tools for multivariate analysis.

Vitamin D Levels During Pregnancy Are Associated With Offspring Telomere Length: A Longitudinal Mother-Child Study.

CONTEXT: Leukocyte telomere length (LTL) is a biomarker of biological aging and is associated with metabolic diseases such as type 2 diabetes. Insufficient maternal vitamin D was associated with increased risk for many diseases and adverse later life outcomes. OBJECTIVE: This study investigates the relationship between vitamin D levels and offspring LTL at early life. METHODS: This observational, longitudinal, hospital-based cohort study included eligible mother-child pairs from the HAPO Hong Kong Field Centre, with 853 offspring at age 6.96 ±â€…0.44 (mean ±â€…SD) years. LTL was measured using real-time polymerase chain reaction while serum vitamin D metabolites 25(OH)D2, 25(OH)D3, and 3-epi-25(OH)D3 were measured in maternal blood (at gestation 24-32 weeks) and cord blood by liquid chromatography-mass spectrometry. RESULTS: LTL at follow-up was significantly shorter in boys compared with girls (P < 0.001) at age 7. Childhood LTL was negatively associated with childhood BMI (ß ±â€…SE = -0.016 ±â€…0.007)(P = 0.02) and HOMA-IR (ß ±â€…SE = -0.065 ±â€…0.021)(P = 0.002). Multiple linear regression was used to evaluate the relationship between 25(OH)D and LTL, with covariate adjustments. Childhood LTL was positively correlated with total maternal 25(OH)D (0.048 ±â€…0.017) (P = 0.004) and maternal 3-epi-25(OH)D3 (0.05 ±â€…0.017) (P = 0.003), even after adjustment for covariates. A similar association was also noted for cord 3-epi-25(OH)D3 (0.037 ±â€…0.018) (P = 0.035) after adjustment for offspring sex and age. CONCLUSION: Our findings suggest 25(OH)D3 and 3-epi-25(OH)D3 in utero may impact on childhood LTLs, highlighting a potential link between maternal vitamin D and biological aging.

Circulating microRNAs from early childhood and adolescence are associated with pre-diabetes at 18 years of age in women from the PMNS cohort.

With type 2 diabetes presenting at younger ages, there is a growing need to identify biomarkers of future glucose intolerance. A high (20%) prevalence of glucose intolerance at 18 years was seen in women from the Pune Maternal Nutrition Study (PMNS) birth cohort. We investigated the potential of circulating microRNAs in risk stratification for future pre-diabetes in these women. Here, we provide preliminary longitudinal analyses of circulating microRNAs in normal glucose tolerant (NGT@18y, N = 10) and glucose intolerant (N = 8) women (ADA criteria) at 6, 12 and 17 years of their age using discovery analysis (OpenArray™ platform). Machine-learning workflows involving Lasso with bootstrapping/leave-one-out cross-validation identified microRNAs associated with glucose intolerance at 18 years of age. Several microRNAs, including miR-212-3p, miR-30e-3p and miR-638, stratified glucose-intolerant women from NGT at childhood. Our results suggest that circulating microRNAs, longitudinally assessed over 17 years of life, are dynamic biomarkers associated with and predictive of pre-diabetes at 18 years of age. Validation of these findings in males and remaining participants from the PMNS birth cohort will provide a unique opportunity to study novel epigenetic mechanisms in the life-course progression of glucose intolerance and enhance current clinical risk prediction of pre-diabetes and progression to type 2 diabetes.

Analysis of Half a Billion Datapoints Across Ten Machine-Learning Algorithms Identifies Key Elements Associated With Insulin Transcription in Human Pancreatic Islet Cells.

Machine learning (ML)-workflows enable unprejudiced/robust evaluation of complex datasets. Here, we analyzed over 490,000,000 data points to compare 10 different ML-workflows in a large (N=11,652) training dataset of human pancreatic single-cell (sc-)transcriptomes to identify genes associated with the presence or absence of insulin transcript(s). Prediction accuracy/sensitivity of each ML-workflow was tested in a separate validation dataset (N=2,913). Ensemble ML-workflows, in particular Random Forest ML-algorithm delivered high predictive power (AUC=0.83) and sensitivity (0.98), compared to other algorithms. The transcripts identified through these analyses also demonstrated significant correlation with insulin in bulk RNA-seq data from human islets. The top-10 features, (including IAPP, ADCYAP1, LDHA and SST) common to the three Ensemble ML-workflows were significantly dysregulated in scRNA-seq datasets from Ire-1αß-/- mice that demonstrate dedifferentiation of pancreatic ß-cells in a model of type 1 diabetes (T1D) and in pancreatic single cells from individuals with type 2 Diabetes (T2D). Our findings provide direct comparison of ML-workflows in big data analyses, identify key elements associated with insulin transcription and provide workflows for future analyses.

Decrease in Plasma miR-27a and miR-221 After Concussion in Australian Football Players.

INTRODUCTION: Sports-related concussion (SRC) is a common form of brain injury that lacks reliable methods to guide clinical decisions. MicroRNAs (miRNAs) can influence biological processes involved in SRC, and measurement of miRNAs in biological fluids may provide objective diagnostic and return to play/recovery biomarkers. Therefore, this prospective study investigated the temporal profile of circulating miRNA levels in concussed male and female athletes. METHODS: Pre-season baseline blood samples were collected from amateur Australian rules football players (82 males, 45 females). Of these, 20 males and 8 females sustained an SRC during the subsequent season and underwent blood sampling at 2-, 6- and 13-days post-injury. A miRNA discovery Open Array was conducted on plasma to assess the expression of 754 known/validated miRNAs. miRNA target identified were further investigated with quantitative real-time PCR (qRT-PCR) in a validation study. Data pertaining to SRC symptoms, demographics, sporting history, education history and concussion history were also collected. RESULTS: Discovery analysis identified 18 candidate miRNA. The consequent validation study found that plasma miR-221-3p levels were decreased at 6d and 13d, and that miR-27a-3p levels were decreased at 6d, when compared to baseline. Moreover, miR-27a and miR-221-3p levels were inversely correlated with SRC symptom severity. CONCLUSION: Circulating levels of miR-27a-3p and miR-221-3p were decreased in the sub-acute stages after SRC, and were inversely correlated with SRC symptom severity. Although further studies are required, these analyses have identified miRNA biomarker candidates of SRC severity and recovery that may one day assist in its clinical management.

A Pro-Endocrine Pancreatic Islet Transcriptional Program Established During Development Is Retained in Human Gallbladder Epithelial Cells.

BACKGROUND & AIMS: Pancreatic islet ß-cells are factories for insulin production; however, ectopic expression of insulin also is well recognized. The gallbladder is a next-door neighbor to the developing pancreas. Here, we wanted to understand if gallbladders contain functional insulin-producing cells. METHODS: We compared developing and adult mouse as well as human gallbladder epithelial cells and islets using immunohistochemistry, flow cytometry, enzyme-linked immunosorbent assays, RNA sequencing, real-time polymerase chain reaction, chromatin immunoprecipitation, and functional studies. RESULTS: We show that the epithelial lining of developing, as well as adult, mouse and human gallbladders naturally contain interspersed cells that retain the capacity to actively transcribe, translate, package, and release insulin. We show that human gallbladders also contain functional insulin-secreting cells with the potential to naturally respond to glucose in vitro and in situ. Notably, in a non-obese diabetic (NOD) mouse model of type 1 diabetes, we observed that insulin-producing cells in the gallbladder are not targeted by autoimmune cells. Interestingly, in human gallbladders, insulin splice variants are absent, although insulin splice forms are observed in human islets. CONCLUSIONS: In summary, our biochemical, transcriptomic, and functional data in mouse and human gallbladder epithelial cells collectively show the evolutionary and developmental similarities between gallbladder and the pancreas that allow gallbladder epithelial cells to continue insulin production in adult life. Understanding the mechanisms regulating insulin transcription and translation in gallbladder epithelial cells would help guide future studies in type 1 diabetes therapy.

Shortened Leukocyte Telomere Length Is Associated With Glycemic Progression in Type 2 Diabetes: A Prospective and Mendelian Randomization Analysis.

OBJECTIVE: Several studies support associations between relative leukocyte telomere length (rLTL), a biomarker of biological aging and type 2 diabetes. This study investigates the relationship between rLTL and the risk of glycemic progression in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: In this cohort study, consecutive Chinese patients with type 2 diabetes (N = 5,506) from the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data were studied. rLTL was measured using quantitative PCR. Glycemic progression was defined as the new need for exogenous insulin. RESULTS: The mean (SD) age of the 5,349 subjects was 57.0 (13.3) years, and mean (SD) follow-up was 8.8 (5.4) years. Baseline rLTL was significantly shorter in the 1,803 subjects who progressed to insulin requirement compared with the remaining subjects (4.43 ± 1.16 vs. 4.69 ± 1.20). Shorter rLTL was associated with a higher risk of glycemic progression (hazard ratio [95% CI] for each unit decrease [to ∼0.2 kilobases]: 1.10 [1.06-1.14]), which remained significant after adjusting for confounders. Baseline rLTL was independently associated with glycemic exposure during follow-up (ß = -0.05 [-0.06 to -0.04]). Each 1-kilobase decrease in absolute LTL was on average associated with a 1.69-fold higher risk of diabetes progression (95% CI 1.35-2.11). Two-sample Mendelian randomization analysis showed per 1-unit genetically decreased rLTL was associated with a 1.38-fold higher risk of diabetes progression (95% CI 1.12-1.70). CONCLUSIONS: Shorter rLTL was significantly associated with an increased risk of glycemic progression in individuals with type 2 diabetes, independent of established risk factors. Telomere length may be a useful biomarker for glycemic progression in people with type 2 diabetes.