Assessing the consistency of iPSC and animal models in cystic fibrosis modelling: A meta-analysis

INTRODUCTION

Cystic fibrosis (CF) is a hereditary autosomal recessive disorder caused by a range of mutations in the CF Transmembrane Conductance Regulator (CFTR) gene. This gene encodes the CFTR protein, which acts as a chloride channel activated by cyclic AMP (cAMP). This meta-analysis aimed to compare the responsiveness of induced pluripotent stem cells (iPSCs) to cAMP analogues to that of commonly used animal models.

METHODS

Databases searched included PubMed, Scopus, and Medline from inception to January 2020. A total of 8 and 3 studies, respectively, for animal models and iPSCs, were analyzed. Studies were extracted for investigating cAMP-stimulated anion transport by measuring the short circuit current (Isc) of chloride channels in different animal models and iPSC systems We utilized an inverse variance heterogeneity model for synthesis.

RESULTS

Our analysis showed considerable heterogeneity in the mean Isc value in both animal models and iPSCs studies (compared to their WT counterparts), and both suffer from variable responsiveness based on the nature of the underlying model. There was no clear advantage of one over the other.

CONCLUSIONS

Studies on both animal and iPSCs models generated considerable heterogeneity. Given the potential of iPSC-derived models to study different diseases, we recommend paying more attention to developing reproducible models of iPSC as it has potential if adequately developed.

Diagnostic, Prognostic, and Mechanistic Biomarkers of Diabetes Mellitus-Associated Cognitive Decline

Cognitive dysfunctions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and other forms of dementia are recognized as common comorbidities of type 2 diabetes mellitus (T2DM). Currently, there are no disease-modifying therapies or definitive clinical diagnostic and prognostic tools for dementia, and the mechanisms underpinning the link between T2DM and cognitive dysfunction remain equivocal. Some of the suggested pathophysiological mechanisms underlying cognitive decline in diabetes patients include hyperglycemia, insulin resistance and altered insulin signaling, neuroinflammation, cerebral microvascular injury, and buildup of cerebral amyloid and tau proteins. Given the skyrocketing global rates of diabetes and neurodegenerative disorders, there is an urgent need to discover novel biomarkers relevant to the co-morbidity of both conditions to guide future diagnostic approaches. This review aims to provide a comprehensive background of the potential risk factors, the identified biomarkers of diabetes-related cognitive decrements, and the underlying processes of diabetes-associated cognitive dysfunction. Aging, poor glycemic control, hypoglycemia and hyperglycemic episodes, depression, and vascular complications are associated with increased risk of dementia. Conclusive research studies that have attempted to find specific biomarkers are limited. However, the most frequent considerations in such investigations are related to C reactive protein, tau protein, brain-derived neurotrophic factor, advanced glycation end products, glycosylated hemoglobin, and adipokines.

Comparative Transcriptome Analysis Reveals That Exendin-4 Improves Steatosis in HepG2 Cells by Modulating Signaling Pathways Related to Lipid Metabolism

No therapy exists for non-alcoholic fatty liver disease (NAFLD). However, glucagon-like peptide receptor agonists (GLP-1RAs) showed a beneficial effect on NAFLD, although the underpinning mechanisms remain unclear due to their pleiotropic effects. We examined the implicated signaling pathways using comparative transcriptomics in a cell model of steatosis to overcome pleiotropy. We treated steatotic HepG2 cells with the GLP-1RA Exendin-4 (Ex-4). We compared the transcriptome profiles of untreated steatotic, and Ex-4-treated steatotic cells, and used Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and associated genes involved in the protective effect of Ex-4. Ex-4 treatment significantly reduces steatosis. RNA-seq analysis revealed 209 differentially expressed genes (DEGs) between steatotic and untreated cells, with farnesoid X receptor/retinoid X receptor (FXR/RXR) (p = 8.9 × 10−7) activation being the top regulated canonical pathway identified by IPA. Furthermore, 1644 DEGs were identified between steatotic cells and Ex-4-treated cells, with liver X receptor/retinoid X receptor (LXR/RXR) (p = 2.02 × 10−7) and FXR/RXR (p = 3.28 × 10−7) activation being the two top canonical pathways. The top molecular and cellular functions between untreated and steatotic cells were lipid metabolism, molecular transport, and small molecular biochemistry, while organismal injury and abnormalities, endocrine system disorders, and gastrointestinal disease were the top three molecular and cellular functions between Ex-4-treated and steatotic cells. Genes overlapping steatotic cells and Ex-4-treated cells were associated with several lipid metabolism processes. Unique transcriptomic differences exist between steatotic cells and Ex-4-treated steatotic cells, providing an important resource for understanding the mechanisms that underpin the protective effect of GLP-1RAs on NAFLD and for the identification of novel therapeutic targets for NAFLD.

Elevated levels of salivary α- amylase activity in saliva associated with reduced odds of obesity in adult Qatari citizens: A cross-sectional study

The relationship between salivary α-amylase activity (ssAAa) and the risk of metabolic disorders remains equivocal. We aimed to assess this relationship in adults from Qatar, where obesity and type 2 diabetes are highly prevalent. We cross-sectionally quantified ssAAa in saliva and estimated AMY1 CN from whole-genome sequencing data from 1499 participants. Linear regression was used to assess the relationship between ssAAa and adiposity and glycemic markers. Logistic regression was used to examine the association between ssAAa and occurrence of obesity or diabetes. The mean and median ssAAa were significantly lower in obese individuals. There were significant inverse associations between ssAAa and BMI, and fat mass. We detected a marked effect of ssAAa on reduced odds of obesity after adjusting for age and sex, glucose, LDL, HLD, total cholesterol, and systolic and diastolic blood pressure (OR per ssAAa unit 0.998 [95% CI 0.996–0.999], p = 0.005), with ssAAa ranging between 6.8 and 422U/mL. The obesity odds were significantly lower in the upper half of the ssAAa distributional (OR 0.58 [95% CI 0.42–0.76], p<0.001) and lower in the top versus the bottom decile of the ssAAa distribution (OR 0.46 [95% CI 0.23–0.92], p = 0.03). Our findings suggest a potential beneficial relationship between high sAAa in saliva and low odds of obesity in Qatari adults.

Identification of Novel Circulating miRNAs in Patients with Acute Ischemic Stroke

Ischemic strokes are associated with significant morbidity and mortality, but currently there are no reliable prognostic or diagnostic blood biomarkers. MicroRNAs (miRNAs) regulate various molecular pathways and may be used as biomarkers. Using RNA-Seq, we conducted comprehensive circulating miRNA profiling in patients with ischemic stroke compared with healthy controls. Samples were collected within 24 h of clinical diagnosis. Stringent analysis criteria of discovery (46 cases and 95 controls) and validation (47 cases and 96 controls) cohorts led to the identification of 10 differentially regulated miRNAs, including 5 novel miRNAs, with potential diagnostic significance. Hsa-miR-451a was the most significantly upregulated miRNA (FC; 4.8, FDR; 3.78 × 10⁻⁸⁵), while downregulated miRNAs included hsa-miR-574-5p and hsa-miR-142-3p, among others. Importantly, we computed a multivariate classifier based on the identified miRNA panel to differentiate between ischemic stroke patients and healthy controls, which showed remarkably high sensitivity (0.94) and specificity (0.99). The area under the ROC curve was 0.97 and it is superior to other current available biomarkers. Moreover, in samples collected one month following stroke, we found sustained upregulation of hsa-miR-451a and downregulation of another 5 miRNAs. Lastly, we report 3 miRNAs that were significantly associated with poor clinical outcomes of stroke, as defined by the modified Rankin scores. The clinical translation of the identified miRNA panel may be explored further.

Exendin-4 alleviates steatosis in an in vitro cell model by lowering FABP1 and FOXA1 expression via the Wnt/-catenin signaling pathway

Non-alcoholic fatty liver disease (NAFLD) is the leading chronic liver disease worldwide. Agonists of the glucagon-like peptide-1 receptor (GLP-1R), currently approved to treat type 2 diabetes, hold promise to improve steatosis and even steatohepatitis. However, due to their pleiotropic effects, the mechanisms underlying their protective effect on NAFLD remain elusive. We aimed to investigate these mechanisms using an in vitro model of steatosis treated with the GLP-1R agonist Exendin-4 (Ex-4). We established steatotic HepG2 cells by incubating the cells with 400 µM oleic acid (OA) overnight. Further treatment with 200 nM Ex-4 for 3 h significantly reduced the OA-induced lipid accumulation (p < 0.05). Concomitantly, Ex-4 substantially reduced the expression levels of Fatty Acid-Binding Protein 1 (FABP1) and its primary activator, Forkhead box protein A1 (FOXA1). Interestingly, the silencing of β-catenin with siRNA abolished the effect of Ex-4 on these genes, suggesting dependency on the Wnt/β-catenin pathway. Additionally, after β-catenin silencing, OA treatment significantly increased the expression of nuclear transcription factors SREBP-1 and TCF4, whereas Ex-4 significantly decreased this upregulation. Our findings suggest that direct activation of GLP-1R by Ex-4 reduces OA-induced steatosis in HepG2 cells by reducing fatty acid uptake and transport via FABP1 downregulation.

Association of dyslipidemia, diabetes and metabolic syndrome with serum ferritin levels: a middle eastern population-based cross-sectional study

Elevated serum ferritin (SFer) levels are implicated in many energy metabolism abnormalities. The association between SFer levels and metabolic disorders has not been studied in Middle Eastern populations. We aimed at exploring the association between SFer levels and serum lipids, diabetes determinants, and metabolic syndrome in a sample of Qatari adults. This study used biochemical parameters obtained from 1928 participants from the Qatar Biobank cohort. We utilized adjusted multivariable logistic regression analysis to estimate the odds ratios (ORs) for dyslipidemia, type 2 diabetes, the homeostasis model assessment of insulin resistance (HOMA-IR), and metabolic syndrome (MetS) according to sex-specific SFer quartiles (Q1 to Q4). Results revealed that the ORs for dyslipidemia increased progressively and significantly across the SFer quartiles, up to two folds in Q4 for women (OR 2.47 (1.68–3.62)) and men (OR 2.24 (1.41–3.55)) versus Q1 (OR:1). Exclusively in women, the ORs for IR (HOMA-IR > 3.58) increased significantly in Q4 (OR 1.79 (1.19–2.70)) versus OR 1 in Q1 as did the ORs for diabetes (OR: 2.03 (1.15–3.57) in Q4 versus OR 1 in Q1). We observed the same result when we pooled the participants with prediabetes and diabetes in one group. The OR for MetS also increased significantly across the Sfer Quartiles from OR: 1 in Q1 to 1.92 (1.06–3.02) in Q4 for women and to 2.07 (1.08–3.98) in Q4 in men. Our results suggest the elevated Sfer levels as a potential risk biomarker for dyslipidemia and MetS in adult Qatari men and women, and diabetes and IR in women only.

Accelerating the Design of Photocatalytic Surfaces for Antimicrobial Application: Machine Learning Based on a Sparse Dataset

Nowadays, most experiments to synthesize and test photocatalytic antimicrobial materials are based on trial and error. More often than not, the mechanism of action of the antimicrobial activity is unknown for a large spectrum of microorganisms. Here, we propose a scheme to speed up the design and optimization of photocatalytic antimicrobial surfaces tailored to give a balanced production of reactive oxygen species (ROS) upon illumination. Using an experiment-to-machine-learning scheme applied to a limited experimental dataset, we built a model that can predict the photocatalytic activity of materials for antimicrobial applications over a wide range of material compositions. This machine-learning-assisted strategy offers the opportunity to reduce the cost, labor, time, and precursors consumed during experiments that are based on trial and error. Our strategy may significantly accelerate the large-scale deployment of photocatalysts as a promising route to mitigate fomite transmission of pathogens (bacteria, viruses, fungi) in hospital settings and public places.

Accelerating the Design of Photocatalytic Surfaces for Antimicrobial Application: Machine Learning Based on a Sparse Dataset

Nowadays, most experiments to synthesize and test photocatalytic antimicrobial materials are based on trial and error. More often than not, the mechanism of action of the antimicrobial activity is unknown for a large spectrum of microorganisms. Here, we propose a scheme to speed up the design and optimization of photocatalytic antimicrobial surfaces tailored to give a balanced production of reactive oxygen species (ROS) upon illumination. Using an experiment-to-machine-learning scheme applied to a limited experimental dataset, we built a model that can predict the photocatalytic activity of materials for antimicrobial applications over a wide range of material compositions. This machine-learning-assisted strategy offers the opportunity to reduce the cost, labor, time, and precursors consumed during experiments that are based on trial and error. Our strategy may significantly accelerate the large-scale deployment of photocatalysts as a promising route to mitigate fomite transmission of pathogens (bacteria, viruses, fungi) in hospital settings and public places.

Comprehensive analysis of LncRNAs expression profiles in an in vitro model of steatosis treated with Exendin-4

Background and aims

The hallmark of non-alcoholic fatty liver disease (NAFLD) is the excessive hepatic lipid accumulation. Currently, no pharmacotherapy exists for NAFLD. However, the glucagon-like peptide-1 receptor agonists have recently emerged as potential therapeutics. Here, we sought to identify the long non-coding RNAs (LncRNAs) associated with the steatosis improvement induced by the GLP-1R agonist Exendin-4 (Ex-4) in vitro.

Methods

Steatosis was induced in HepG2 cells with oleic acid. The transcriptomic profiling was performed using total RNA extracted from untreated, steatotic, and Ex-4-treated steatotic cells. We validated a subset of differentially expressed LncRNAs with qRT-PCR and identified the most significantly enriched cellular functions associated with the relevant LncRNAs.

Results

We confirm that Ex-4 improves steatosis in HepG2 cells. We found 379 and 180 differentially expressed LncRNAs between untreated and steatotic cells and between steatotic and Ex-4-treated steatotic cells, respectively. Interestingly, 22 upregulated LncRNAs in steatotic cells became downregulated with Ex-4 exposure, while 50 downregulated LncRNAs in steatotic cells became upregulated in the presence of Ex-4. Although some LncRNAs, such as MALAT1, H19, and NEAT1, were previously associated with NAFLD, the association of others with steatosis and the positive effect of Ex-4 is being reported for the first time. Functional enrichment analysis identified many critical pathways, including fatty acid and pyruvate metabolism, and insulin, PPAR, Wnt, TGF-β, mTOR, VEGF, NOD-like, and Toll-like receptors signaling pathways.

Conclusion

Our results suggest that LncRNAs may play essential roles in the mechanisms underlying steatosis improvement in response to GLP-1R agonists and warrant further functional studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02885-4.

Reduced odds of diabetes associated with high plasma salivary α-amylase activity in Qatari women: a cross-sectional study

The association of salivary α-amylase activity (SAA) activity or low copy number of its coding gene AMY1 with diabetes remains controversial. We aimed to reinvestigate the association of these factors with diabetes in Qatar, where diabetes prevalence is about 16%. We obtained cross-sectional data of 929 Qataris (age > 18 years) from the Qatar Biobank. We estimated AMY1 copy number variants (CNV) from whole-genome data, and quantified the SAA activity in plasma (pSAA). We used adjusted logistic regression to examine the association between pSAA activity or AMY1 CNV and diabetes odds. We found a significant association between high pSAA activity, but not AMY1 CNV, and reduced odds of diabetes in Qatari women. The OR per pSAA activity unit was 0.95 [95% CI 0.92, 0.98] (p = 0.002) (pSAA activity range: 4.7 U/L to 65 U/L) in women. The association is driven largely by the highest levels of pSAA activity. The probability of having diabetes was significantly lower in the fifth pSAA activity quintile relative to the first (0.21 ± 0.03 (Q1) versus 0.82 ± 0.02 (Q5)), resulting in significantly reduced diabetes prevalence in Q5 in women. Our study indicates a beneficial effect of high pSAA activity, but not AMY1 CN, on diabetes odds in Qatari women, and suggests pSAA activity levels as a potential marker to predict future diabetes in Qatari women.

Simple risk score to screen for prediabetes: A cross-sectional study from the Qatar Biobank cohort

AIMS/INTRODUCTION

The progression from prediabetes to type 2 diabetes is preventable by lifestyle intervention and/or pharmacotherapy in a large fraction of individuals with prediabetes. Our objective was to develop a risk score to screen for prediabetes in the Middle East, where diabetes prevalence is one of the highest in the world.

MATERIALS AND METHODS

In this cross-sectional, case-control study, we used data of 4,895 controls and 2,373 prediabetic adults obtained from the Qatar Biobank cohort. Significant risk factors were identified by logistic regression and other machine learning methods. The receiver operating characteristic was used to calculate the area under curve, cut-off point, sensitivity, specificity, positive and negative predictive values. The prediabetes risk score was developed from data of Qatari citizens, as well as long-term (≥15 years) residents.

RESULTS

The significant risk factors for the Prediabetes Risk Score in Qatar were age, sex, body mass index, waist circumference and blood pressure. The risk score ranges from 0 to 45. The area under the curve of the score was 80% (95% confidence interval 78-83%), and the cut-off point of 16 yielded sensitivity and specificity of 86.2% (95% confidence interval 82.7-89.2%) and 57.9% (95% confidence interval 65.5-71.4%), respectively. Prediabetes Risk Score in Qatar performed equally in Qatari nationals and long-term residents.

CONCLUSIONS

Prediabetes Risk Score in Qatar is the first prediabetes screening score developed in a Middle Eastern population. It only uses risk factors measured non-invasively, is simple, cost-effective, and can be easily understood by the general public and health providers. Prediabetes Risk Score in Qatar is an important tool for early detection of prediabetes, and can help tremendously in curbing the diabetes epidemic in the region.

Using Unstated Cases to Correct for COVID-19 Pandemic Outbreak and Its Impact on Easing the Intervention for Qatar

Simple Summary

A modified SIR model was applied to provide COVID-19 pandemic analysis and predictions for Gulf Cooperation Council countries, as well as representative countries in Europe and New York City. We estimated reported, infected, and unreported cases from cumulative reported cases and simulated data. We also estimated the basic reproduction rates at different phases of the pandemic. Outputs show that the modified SIR model fits very well with the outcome of the COVID-19 pandemic for the studied countries and could be generalized to other countries. The model prediction emphasizes the value of significant interventions in public health in regulating the epidemic taking into account that a constant fraction of the infected cases remain unreported during the pandemic. We report and analyze the effectiveness of preventive/intervention measures applied to the overall community to curb the severity of the pandemic. Our model could be used to support public health authorities with respect to post-outbreak reopening decisions, highlighting effective measures that need to be maintained, eased, or implemented to support safe reopening strategies in the GCC countries.

Abstract

Epidemiological Modeling supports the evaluation of various disease management activities. The value of epidemiological models lies in their ability to study various scenarios and to provide governments with a priori knowledge of the consequence of disease incursions and the impact of preventive strategies. A prevalent method of modeling the spread of pandemics is to categorize individuals in the population as belonging to one of several distinct compartments, which represents their health status with regard to the pandemic. In this work, a modified SIR epidemic model is proposed and analyzed with respect to the identification of its parameters and initial values based on stated or recorded case data from public health sources to estimate the unreported cases and the effectiveness of public health policies such as social distancing in slowing the spread of the epidemic. The analysis aims to highlight the importance of unreported cases for correcting the underestimated basic reproduction number. In many epidemic outbreaks, the number of reported infections is likely much lower than the actual number of infections which can be calculated from the model’s parameters derived from reported case data. The analysis is applied to the COVID-19 pandemic for several countries in the Gulf region and Europe.

Greater and More Focused Measures Are Needed to Tackle Diabetes and Obesity Epidemics in the Nations of the Gulf Cooperation Council

Beyond the suffering of the affected subjects, type 2 diabetes (T2D) and obesity epidemics gripping the Gulf Cooperation Council (GCC) states are expected to seriously jeopardize these nations' economies and development due to productivity losses. Available data show that healthcare budgets in GCC nations are under tremendous pressure because of diabetes- and obesity-linked comorbidities. Furthermore, T2D, once an over-forties disease, risks becoming a whole-adult-life condition because of obesity-associated early-onset T2D and prediabetes. The incidence of T2D is set to worsen unless efficient actions are taken to fight obesity and prevent the conversion of prediabetes to T2D. There is a consensus that the concomitant increase in obesity rates drives T2D rates upward. Fighting obesity at all levels should, therefore, take center stage for the GCC nations. The battle against obesity and T2D is a long-term and complex one. Therefore, only through concerted efforts between several public and private actors, including health, economic, and urbanization agencies, food producers and retailers, schools, families, youth organizations, sports clubs, and voluntary organizations, can this battle be won. The present review tries to assess the current status of diabetes and obesity epidemics in the GCC context and take stock of some of the policies and initiatives that have been, or need to be, implemented to address their growing burden.

High plasma salivary α-amylase, but not high AMY1 copy number, associated with low obesity rate in Qatari adults: cross-sectional study

The relationship between salivary α-amylase activity (psAAa) or AMY1 copy number and the risk of obesity remains controversial. We aimed to assess this relationship in a cohort from Qatar, where obesity affects 43% of adults. The relationship was investigated cross-sectionally in 923 Qatari adults from the Qatar biobank cohort. AMY1 CN was estimated form whole genome sequencing data. The associations with obesity prevalence were assessed by linear and logistic regressions. We found no difference in AMY1 CN between obese and normal-weight individuals. However, the psAAa was significantly lower in obese individuals. Significant inverse correlations were found between adiposity markers and psAAa in both sexes, but were marginally stronger in men. A significant effect of high psAAa, but not AMY1 CN, on reduced obesity rates was identified in men (OR per psAAa unit 0.957 [95% CI 0.937–0.977], p < 0.001, with psAAa ranging between 5 to 66 U/L). A significantly higher prevalence of obesity was observed in the lowest quartile of psAAa in men (75% (Q1) vs. 36% (Q4), p < 0.001) and women (74% (Q1) vs 56% (Q4), p = 0.009). Our findings suggest that high psAAa, but not AMY1 CN, has a potential positive benefit against obesity in the Qatari population.

Noncoding RNAs in Nonalcoholic Fatty Liver Disease: Potential Diagnosis and Prognosis Biomarkers

Nonalcoholic fatty liver disease (NAFLD) is currently the most common chronic liver disease worldwide in part due to the concomitant obesity pandemic and insulin resistance (IR). It is increasingly becoming evident that NAFLD is a disease affecting numerous extrahepatic vital organs and regulatory pathways. The molecular mechanisms underlying the nonalcoholic steatosis formation are poorly understood, and little information is available on the pathways that are responsible for the progressive hepatocellular damage that follows lipid accumulation. Recently, much research has focused on the identification of the epigenetic modifications that contribute to NAFLD pathogenesis. Noncoding RNAs (ncRNAs) are one of such epigenetic factors that could be implicated in the NAFLD development and progression. In this review, we summarize the current knowledge of the genetic and epigenetic factors potentially underlying the disease. Particular emphasis will be put on the contribution of microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) to the pathophysiology of NAFLD as well as their potential use as therapeutic targets or as markers for the prediction and the progression of the disease.

DNAJB3 attenuates metabolic stress and promotes glucose uptake by eliciting Glut4 translocation

Failure of the heat shock response is a key event that leads to insulin resistance and type 2 diabetes. We recently showed that DNAJB3 co-chaperone is downregulated in obese and diabetic patients and that physical exercise restores its normal expression with a significant improvement of the clinical outcomes. In 3T3-L1 adipocytes, DNAJB3 has a role in improving the sensitivity to insulin and glucose uptake. In co-immunoprecipitation assays, DNAJB3 interacts with both JNK1 and IKKβ kinases. However, the functional impact of such interaction on their activities has not been investigated. Here, we assessed the effect of DNAJB3 on the respective activity of JNK1 and IKKβ in cell-based assays. Using JNK1- and IKKβ-dependent luciferase reporters, we show a marked decrease in luciferase activity by DNAJB3 in response to PMA and TNF-α that was consistent with a decrease in the translocation of p65/NF-κB to the nucleus in response to LPS. Furthermore, TNF-α-mediated IL-6 promoter activation and endogenous mRNA expression are significantly abrogated by DNAJB3 both in 3T3-L1 and C2C12 cells. The ability of DNAJB3 to mitigate ER stress and oxidative stress was also investigated and our data show a significant improvement of both forms of stress. Finally, we examined the effect of overexpressing and knocking down the expression of DNAJB3 on glucose uptake in C2C12 as well as the molecular determinants. Accordingly, we provide evidence for a role of DNAJB3 in promoting both basal and insulin-stimulated glucose uptake. Our finding reveals also a novel role of DNAJB3 in eliciting Glut4 translocation to the plasma membrane. These results suggest a physiological role of DNAJB3 in mitigating metabolic stress and improving glucose homeostasis and could therefore represent a novel therapeutic target for type 2 diabetes.

Evaluation of cationic channel TRPV2 as a novel biomarker and therapeutic target in Leukemia-Implications concerning the resolution of pulmonary inflammation

Patients treated during leukemia face the risk of complications including pulmonary dysfunction that may result from infiltration of leukemic blast cells (LBCs) into lung parenchyma and interstitium. In LBCs, we demonstrated that transient receptor potential vanilloid type 2 channel (TRPV2), reputed for its role in inflammatory processes, exhibited oncogenic activity associated with alteration of its molecular expression profile. TRPV2 was overexpressed in LBCs compared to normal human peripheral blood mononuclear cells (PBMCs). Additionally, functional full length isoform and nonfunctional short form pore-less variant of TRPV2 protein were up-regulated and down-regulated respectively in LBCs. However, the opposite was found in PBMCs. TRPV2 silencing or pharmacological targeting by Tranilast (TL) or SKF96365 (SKF) triggered caspace-mediated apoptosis and cell cycle arrest. TL and SKF inhibited chemotactic peptide fMLP-induced response linked to TRPV2 Ca²⁺ activity, and down-regulated expression of surface marker CD38 involved in leukemia and lung airway inflammation. Challenging lung airway epithelial cells (AECs) with LBCs decreased (by more than 50%) transepithelial resistance (TER) denoting barrier function alteration. Importantly, TL prevented such loss in TER. Therefore, TRPV2 merits further exploration as a pharmacodynamic biomarker for leukemia patients (with pulmonary inflammation) who might be suitable for a novel [adjuvant] therapeutic strategy based on TL.

Inositol 1,4,5-Trisphosphate Receptors in Hypertension

Chronic hypertension remains a major cause of global mortality and morbidity. It is a complex disease that is the clinical manifestation of multiple genetic, environmental, nutritional, hormonal, and aging-related disorders. Evidence supports a role for vascular aging in the development of hypertension involving an impairment in endothelial function together with an alteration in vascular smooth muscle cells (VSMCs) calcium homeostasis leading to increased myogenic tone. Changes in free intracellular calcium levels ([Ca²⁺] _i ) are mediated either by the influx of Ca²⁺ from the extracellular space or release of Ca²⁺ from intracellular stores, mainly the sarcoplasmic reticulum (SR). The influx of extracellular Ca²⁺ occurs primarily through voltage-gated Ca²⁺ channels (VGCCs), store-operated Ca²⁺ channels (SOC), and Ca²⁺ release-activated channels (CRAC), whereas SR-Ca²⁺ release occurs through inositol trisphosphate receptor (IP₃R) and ryanodine receptors (RyRs). IP₃R-mediated SR-Ca²⁺ release, in the form of Ca²⁺ waves, not only contributes to VSMC contraction and regulates VGCC function but is also intimately involved in structural remodeling of resistance arteries in hypertension. This involves a phenotypic switch of VSMCs as well as an alteration of cytoplasmic Ca²⁺ signaling machinery, a phenomena tightly related to the aging process. Several lines of evidence implicate changes in expression/function levels of IP₃R isoforms in the development of hypertension, VSMC phenotypic switch, and vascular aging. The present review discusses the current knowledge of these mechanisms in an integrative approach and further suggests potential new targets for hypertension management and treatment.

Relationship between salivary/pancreatic amylase and body mass index: a systems biology approach

BACKGROUND

Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach.

METHODS

We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity.

RESULTS

We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation.

CONCLUSIONS

These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.

Metabolomic Profile of Low-Copy Number Carriers at the Salivary α-Amylase Gene Suggests a Metabolic Shift Toward Lipid-Based Energy Production

Low serum salivary amylase levels have been associated with a range of metabolic abnormalities, including obesity and insulin resistance. We recently suggested that a low copy number at the AMY1 gene, associated with lower enzyme levels, also increases susceptibility to obesity. To advance our understanding of the effect of AMY1 copy number variation on metabolism, we compared the metabolomic signatures of high- and low-copy number carriers. We analyzed, using mass spectrometry and nuclear magnetic resonance (NMR), the sera of healthy normal-weight women carrying either low-AMY1 copies (LAs: four or fewer copies; n = 50) or high-AMY1 copies (HAs: eight or more copies; n = 50). Best-fitting multivariate models (empirical P < 1 × 10^-3) of mass spectrometry and NMR data were concordant in showing differences in lipid metabolism between the two groups. In particular, LA carriers showed lower levels of long- and medium-chain fatty acids, and higher levels of dicarboxylic fatty acids and 2-hydroxybutyrate (a known marker of glucose malabsorption). Taken together, these observations suggest increased metabolic reliance on fatty acids in LA carriers through β- and ω-oxidation and reduced cellular glucose uptake with consequent diversion of acetyl-CoA into ketogenesis. Our observations are in line with previously reported delayed glucose uptake in LA carriers after starch consumption. Further functional studies are needed to extrapolate from our findings to implications for biochemical pathways.

Impact of statistical models on the prediction of type 2 diabetes using non-targeted metabolomics profiling

OBJECTIVE

Characterizing specific metabolites in sub-clinical phases preceding the onset of type 2 diabetes to enable efficient preventive and personalized interventions.

RESEARCH DESIGN AND METHODS

We developed predictive models of type 2 diabetes using two strategies. One strategy focused on the probability of incidence only and was based on logistic regression (MRS1); the other strategy accounted for the age at diagnosis of diabetes and was based on Cox regression (MRS2). We assessed 293 metabolites using non-targeted metabolomics in fasting plasma samples of 1,044 participants (including 231 incident cases over 9 years) used as training population; and fasting serum samples of 128 participants (64 incident cases versus 64 controls) used as validation population. We applied a LASSO-based variable selection aiming at maximizing the out-of-sample area under the receiver operating characteristic curve (AROC) and integrated AROC.

RESULTS

Sixteen and 17 metabolites were selected for MRS1 and MRS2, respectively, with AROC = 90% and 73% in the training and validation populations, respectively for MRS1. MRS2 had a similar performance and was significantly associated with a younger age of onset of type 2 diabetes (β = -3.44 years per MRS2 SD in the training population, p = 1.56 × 10(-7); β = -4.73 years per MRS2 SD in the validation population, p = 4.04 × 10(-3)).

CONCLUSIONS

Overall, this study illustrates that metabolomics improves prediction of type 2 diabetes incidence of 4.5% on top of known clinical and biological markers, reaching 90% in total AROC, which is considered the threshold for clinical validity, suggesting it may be used in targeting interventions to prevent type 2 diabetes.