Identification of potential markers for type 2 diabetes mellitus via bioinformatics analysis

Downregulation of Glis3 in INS1 cells exposed to chronically elevated glucose contributes to glucotoxicity-associated β cell dysfunction

Chronically elevated levels of glucose are deleterious to pancreatic β cells and contribute to β cell dysfunction, which is characterized by decreased insulin production and a loss of β cell identity. The Krüppel-like transcription factor, Glis3 has previously been shown to positively regulate insulin transcription and mutations within the Glis3 locus have been associated with the development of several pathologies including type 2 diabetes mellitus. In this report, we show that Glis3 is significantly downregulated at the transcriptional level in INS1 832/13 cells within hours of being subjected to high glucose concentrations and that diminished expression of Glis3 is at least partly attributable to increased oxidative stress. CRISPR/Cas9-mediated knockdown of Glis3 indicated that the transcription factor was required to maintain normal levels of both insulin and MafA expression and reduced Glis3 expression was concomitant with an upregulation of β cell disallowed genes. We provide evidence that Glis3 acts similarly to a pioneer factor at the insulin promoter where it permissively remodels the chromatin to allow access to a transcriptional regulatory complex including Pdx1 and MafA. Finally, evidence is presented that Glis3 can positively regulate MafA transcription through its pancreas-specific promoter and that MafA reciprocally regulates Glis3 expression. Collectively, these results suggest that decreased Glis3 expression in β cells exposed to chronic hyperglycemia may contribute significantly to reduced insulin transcription and a loss of β cell identity.

Label-free quantitative proteomics analysis for type 2 diabetes mellitus early diagnostic marker discovery using data-independent acquisition mass spectrometry (DIA-MS)

Type-2 diabetes mellitus (T2DM) therapy requires early diagnosis and complication avoidance. Unfortunately, current diagnostic markers do not meet these needs. Data-independent acquisition mass spectrometry (DIA-MS) offers a solution for clinical diagnosis, providing reliable and precise sample quantification. This study utilized DIA-MS to investigate proteomic differential expression in the serum of recently diagnosed T2DM patients. The study conducted a comparative protein expression analysis between healthy and recently diagnosed T2DM groups (discovery cohort). A candidate protein was then validated using enzyme-linked immune assay (ELISA) on serum samples collected from T2DM patients (n = 87) and healthy control (n = 60) (validation cohort). A total of 1074 proteins were identified, and 90 were significantly dysregulated between the two groups, including 32 newly associated with T2DM. Among these proteins, the expression of S100 calcium-binding protein A6 (S100A6) was validated by ELISA. It showed a significant increase in T2DM samples compared to the control group. It was evaluated as a biomarker using the receiver operating characteristic (ROC) curve, consistent with the DIA-MS results. Novel proteins are reported to be involved in the development and progression of T2DM. Further studies are required to investigate the differential expression of candidate marker proteins in a larger population of T2DM patients.

LDLR and PCSK9 3´UTR variants and their putative effects on microRNA molecular interactions in familial hypercholesterolemia: a computational approach

BACKGROUND

Familial hypercholesterolemia (FH) is caused by pathogenic variants in low-density lipoprotein (LDL) receptor (LDLR) or its associated genes, including apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1). However, approximately 40% of the FH patients clinically diagnosed (based on FH phenotypes) may not carry a causal variant in a FH-related gene. Variants located at 3' untranslated region (UTR) of FH-related genes could elucidate mechanisms involved in FH pathogenesis. This study used a computational approach to assess the effects of 3'UTR variants in FH-related genes on miRNAs molecular interactions and to explore the association of these variants with molecular diagnosis of FH.

METHODS AND RESULTS

Exons and regulatory regions of FH-related genes were sequenced in 83 FH patients using an exon-target gene sequencing strategy. In silico prediction tools were used to study the effects of 3´UTR variants on interactions between miRNAs and target mRNAs. Pathogenic variants in FH-related genes (molecular diagnosis) were detected in 44.6% FH patients. Among 59 3'UTR variants identified, LDLR rs5742911 and PCSK9 rs17111557 were associated with molecular diagnosis of FH, whereas LDLR rs7258146 and rs7254521 and LDLRAP1 rs397860393 had an opposite effect (p < 0.05). 3´UTR variants in LDLR (rs5742911, rs7258146, rs7254521) and PCSK9 (rs17111557) disrupt interactions with several miRNAs, and more stable bindings were found with LDLR (miR-4435, miR-509-3 and miR-502) and PCSK9 (miR-4796).

CONCLUSION

LDLR and PCSK9 3´UTR variants disturb miRNA:mRNA interactions that could affect gene expression and are potentially associated with molecular diagnosis of FH.

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway

AIMS

Recent years have witnessed an increasing research interest in the roles of transcription factor (TF)-gene regulatory network in type 2 diabetes mellitus (T2DM). Thus, we sought to characterize the mechanistic insights based on the TF-gene regulatory network in skeletal muscle atrophy in T2DM.

METHODS

Differentially expressed TFs (DETFs) and mRNAs (DEmRNAs) were obtained in T2DM-related gene expression profiles (GSE12643, GSE55650, GSE166502, and GSE29221), followed by WGCNA, and GO and KEGG enrichment analyses. Next, the iRegulon plug-in unit of Cytoscape software was used to construct a TF-mRNA regulatory network. Besides, RT-qPCR and ChIP-seq were utilized to measure the expression of CEBPA and FGF21 in the skeletal muscle tissues or cells of T2DM rat models. At last, the effect of overexpression of FGF21 on the autophagy-lysosomal pathway was examined in skeletal muscle cells of T2DM rats.

RESULTS

Totally, 12 DETFs and 102 DEmRNAs were found in the skeletal muscle tissues of T2DM samples. The DEmRNAs were mainly enriched in the autophagy-lysosomal pathway. CEBPA affected the skeletal muscle atrophy in T2DM by regulating 5 target genes via the autophagy-lysosomal pathway. CEBPA could target FGF21. In addition, the expression of CEBPA was elevated, while the expression of FGF21 was diminished in the skeletal muscle tissues or cells of T2DM rats. The CEBPA-FGF21 regulatory network promoted skeletal muscle atrophy in T2DM by activating the autophagy-lysosomal pathway.

CONCLUSION

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway. Thus, our study provides interesting targets for prevention of skeletal muscle atrophy in T2DM.

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach

Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known as diabetes mellitus, which is a chronic condition, is brought on by a significant rise in blood glucose levels. The diagnosis of this condition is made using a variety of chemical and physical testing. Diabetes, however, can harm the organs if it goes undetected. This study develops a hybrid deep-learning technique to recognize Type 2 diabetes mellitus. The data is cleaned up at the pre-processing stage using a data transformation technique based on the Yeo-Jhonson transformation. The tanimoto similarity is used in the feature selection process to select the best features from the data. To prepare data for future processing, data augmentation is performed. The Deep Residual Network and the Rider-based Neural Network are recommended and trained separately for the T2DM identification using the Competitive Multi-Verse Rider Optimizer. The outputs generated by the RideNN and DRN classifiers are blended using correlation-based fusion. The suggested CMVRO-based NN-DRN has shown improved performance with the highest accuracy of 91.4%, sensitivity of 94.8%, and specificity of 90.1%.

Analysis, validation, and discussion of key genes in placenta of patients with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, which can have harmful health consequences for both the mother and the fetus. Given the placenta's crucial role as an endocrine organ during pregnancy, exploring and validating key genes in the placenta hold significant potential in the realm of GDM prevention and treatment. In this study, differentially expressed genes (DEGs) were identified from two databases, GSE70493 and PRJNA646212, and verified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in placenta tissues. DEGs expression was detected in normal or high-glucose-treated HTR8/SVneo cells. We also investigated the relationship between DEGs and glucose levels in GDM patients. By selecting the intersection of the two databases, we screened 20 DEGs, which were validated in GDM patients. We observed an up-regulation of SLAMF, ALDH1A2, and CHI3L2, and a down-regulation of HLA-E, MYH11, HLA-DRB5, ITGAX, GZMB, NAIP, TMEM74B, RANBP3L, PAEP, WT-1, and CEP170. We conducted further investigations into the expression of DEGs in HTR8/SVneo cells exposed to high glucose, revealing a significant upregulation in the expression of SERPINA3, while the expressions of HLA-E, BCL6, NAIP, PAEP, MUC16, WT-1, and CEP170 were decreased. Moreover, some DEGs were confirmed to have a positive or negative correlation with blood glucose levels of GDM patients through correlation analysis. The identified DEGs are anticipated to exert potential implications in the prevention and management of GDM, thereby offering potential benefits for improving pregnancy outcomes and long-term prognosis of fetuses among individuals affected by GDM.

The effect of hormones insulin and glucagon on ubiquitin modifications elucidated by proteomics in liver cells

AIMS

Insulin action is intertwined with changing levels of glucose and counter-regulatory hormone glucagon. While insulin lowers blood sugar level, glucagon raises it by promoting the breakdown of the stored glycogen in liver and releases glucose into the bloodstream. The hormones insulin and glucagon are key in the pathogenesis of type 2 diabetes (T2D). Insulin resistance is a primary predisposing factor for diabetes. Phosphorylation of insulin signaling molecules is altered in the insulin-resistant state. However, ubiquitin (Ub) modifications in insulin-resistant state are relatively understudied. To dissect the underlying mechanisms, we performed a proteomics study on hepatoma cells to study the regulation of ubiquitination by insulin and glucagon.

MATERIALS AND METHODS

We performed western blotting, immunoprecipitations, and affinity pull down using tandem Ub binding entities (TUBE) reagents on hepatoma cells treated with insulin or glucagon. Next, we performed MS/MS analysis on Ub-linkage specific affinity pull down samples. Gene ontology analysis and protein-protein interaction network analysis was performed using DAVID GO and STRING db, respectively.

KEY FINDINGS

The ubiquitination pattern of total Ub, K48-linked Ub, and K63-linked Ub was altered with the treatment of hormones insulin and glucagon. Ubiquitination in immunoprecipitated samples showed enrichment with total Ub and K48-linked Ub but not with K63-linked Ub. Ubiquitination by treatment with hormones mainly enriched key signaling pathways MAPK, Akt, oxidative stress etc. SIGNIFICANCE: Our study identified key altered proteins and signal transduction pathways which aids in understanding the mechanisms of hormonal action on ubiquitination and identify new therapeutic targets for T2D.

Human Exome Sequencing and Prospects for Predictive Medicine: Analysis of International Data and Own Experience

Today, whole-exome sequencing (WES) is used to conduct the massive screening of structural and regulatory genes in order to identify the allele frequencies of disease-associated polymorphisms in various populations and thus detect pathogenic genetic changes (mutations or polymorphisms) conducive to malfunctional protein sequences. With its extensive capabilities, exome sequencing today allows both the diagnosis of monogenic diseases (MDs) and the examination of seemingly healthy populations to reveal a wide range of potential risks prior to disease manifestation (in the future, exome sequencing may outpace costly and less informative genome sequencing to become the first-line examination technique). This review establishes the human genetic passport as a new WES-based clinical concept for the identification of new candidate genes, gene variants, and molecular mechanisms in the diagnosis, prediction, and treatment of monogenic, oligogenic, and multifactorial diseases. Various diseases are addressed to demonstrate the extensive potential of WES and consider its advantages as well as disadvantages. Thus, WES can become a general test with a broad spectrum pf applications, including opportunistic screening.

Disrupting of family with sequence similarity 105, member A (Fam105a) deteriorates pancreatic β-cell physiology and insulin secretion in INS-1 cells

The role of "Family with sequence similarity 105, member A" (FAM105A) in pancreatic β-cell function in relation to type 2 diabetes mellitus (T2D) is not fully understood. To address this issue, various molecular and functional experiments were conducted on primary human islets and INS-1 cells. RNA-seq expression analysis showed that FAM105A is highly expressed in human islets and its expression is reduced in diabetic islets compared to healthy islets. FAM105A expression correlated negatively with HbA1c levels and body mass index (BMI). Co-expression analysis showed a significant correlation between FAM105A with PDX1, GCK, GLUT1 and INSR, but not the INS gene. Silencing of Fam105a impaired insulin release, content, glucose uptake, and mitochondria ATP content but did not affect cell viability, reactive oxygen species (ROS) or apoptosis levels. Silencing of Fam105a was associated with reduced Pdx1 and Glut2 expression at mRNA and protein levels. RNA-seq analysis of dysregulated genes in Fam105a-silenced cells showed an overall downregulation of gene expression in β-cells and insulin secretion pathway. Disrupting Pdx1 did not affect Fam105a expression in INS-1 cells. Overall, the results suggest that FAM105A plays an important role in pancreatic β-cells biology and may be involved in the development of T2D.

Integrative weighted molecular network construction from transcriptomics and genome wide association data to identify shared genetic biomarkers for COPD and lung cancer

Chronic obstructive pulmonary disease (COPD) is a multifactorial progressive airflow obstruction in the lungs, accounting for high morbidity and mortality across the world. This study aims to identify potential COPD blood-based biomarkers by analyzing the dysregulated gene expression patterns in blood and lung tissues with the help of robust computational approaches. The microarray gene expression datasets from blood (136 COPD and 6 controls) and lung tissues (16 COPD and 19 controls) were analyzed to detect shared differentially expressed genes (DEGs). Then these DEGs were used to construct COPD protein network-clusters and functionally enrich them against gene ontology annotation terms. The hub genes in the COPD network clusters were then queried in GWAS catalog and in several cancer expression databases to explore their pathogenic roles in lung cancers. The comparison of blood and lung tissue datasets revealed 63 shared DEGs. Of these DEGs, 12 COPD hub gene-network clusters (SREK1, TMEM67, IRAK2, MECOM, ASB4, C1QTNF2, CDC42BPA, DPF3, DET1, CCDC74B, KHK, and DDX3Y) connected to dysregulations of protein degradation, inflammatory cytokine production, airway remodeling, and immune cell activity were prioritized with the help of protein interactome and functional enrichment analysis. Interestingly, IRAK2 and MECOM hub genes from these COPD network clusters are known for their involvement in different pulmonary diseases. Additional COPD hub genes like SREK1, TMEM67, CDC42BPA, DPF3, and ASB4 were identified as prognostic markers in lung cancer, which is reported in 1% of COPD patients. This study identified 12 gene network- clusters as potential blood based genetic biomarkers for COPD diagnosis and prognosis.

Inspiratory muscle training and functional capacity following coronary artery bypass grafting in high-risk patients: A pilot randomized and controlled trial

Background

Coronary artery bypass graft (CABG) surgery is associated with worsened functional capacity, pulmonary complications, and increased length of hospital stay. These negative effects are exacerbated in patients who are at high risk of post-operative (PO) pulmonary complications before CABG. Inspiratory muscle training (IMT) has been shown to benefit CABG patients in their recovery process. However, in high-risk patients, there is little evidence to support the post-operative implementation of IMT for purposes of faster recovery.

Aim

The aim of the study was to test the hypothesis that IMT improves the functional capacity, pulmonary complications, and length of hospital stay in patients prone to pulmonary complications who had undergone CABG.

Methods

This is a pilot clinical trial carried out with patients at high risk for pulmonary complications in the PO phase. In the pre-operative period, maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), and 6-min walk test (6MWT) were determined and administered. On the first PO day, patients were divided into two groups: A control group (CG) that received routine intervention and an IMT group that, in addition to routine care, was subjected to an IMT protocol until hospital discharge. On the day of discharge, the patients were reassessed with respect to ventilatory muscle strength, functional capacity, PO complications, and length of stay.

Results

Twenty-nine patients were evaluated, 15 in the CG and 14 in the IMT group. No significant differences were observed in relation to MIP (difference between the mean of -7 cmH₂O; 95% CI = -16.52-2.52), MEP (difference between the mean of -7cm H₂O; 95% CI = -15.39-1.39), and in the 6MWT (difference between the mean of -9 m; 95% CI = -43.71-25.71). There was a decrease in the length of stay in the IMT group compared to the CG (9 ± 3 vs. 12 ± 4 days; P = 0.04). The IMT group had a lower rate of atelectasis and pneumonia.

Conclusion

IMT does not minimize the loss of functional capacity, but it reduces pulmonary complications and the length of stay of patients undergoing CABG who are preoperatively at a high risk of pulmonary complications.

Relevance for Patients

The increase in ventilatory muscle strength, associated with IMT, can reduce PO pulmonary complications, resulting in shorter hospital stays, and improved quality of life.

Circulating extracellular vesicles exhibit a differential miRNA profile in gestational diabetes mellitus pregnancies

We undertook a prospective temporal study collecting blood samples from consenting pregnant women, to test the hypothesis that circulating extracellular vesicles (EVs) carrying specific non-coding microRNA signatures can underlie gestational diabetes mellitus (GDM). To test this hypothesis, miRNA cargo of isolated and characterized EVs revealed contributions from the placenta and differential expression at all three trimesters and at delivery between pregnant and non-pregnant states. Many miRNAs originate from the placental-specific chromosome 19 microRNA cluster (19MC) and chromosome 14 microRNA cluster (14MC). Further a positive correlation emerged between third trimester and at delivery EVs containing miRNAs and those expressed by the corresponding post-parturient placentas (R value = 0.63 to 0.69, p value = 2.2X10-16), in normal and GDM. In addition, distinct differences at all trimesters emerged between women who subsequently developed GDM. Analysis by logistic regression with leave-one-out-cross validation revealed the optimal combination of miRNAs using all the circulating miRNAs (miR-92a-3p, miR-192-5p, miR-451a, miR-122-5p), or using only the differentially expressed miRNAs (has-miR-92a-3p, hsa-miR-92b-3p, hsa-miR-100-5p and hsa-miR-125a-3p) in GDM during the first trimester. As an initial step, both sets of miRNAs demonstrated a predictive probability with an area under the curve of 0.95 to 0.96. These miRNAs targeted genes involved in cell metabolism, proliferation and immune tolerance. In particular genes of the P-I-3-Kinase, FOXO, insulin signaling and glucogenic pathways were targeted, suggestive of placental connectivity with various maternal organs/cells, altering physiology along with pathogenic mechanisms underlying the subsequent development of GDM. We conclude that circulating EVs originating from the placenta with their miRNA cargo communicate and regulate signaling pathways in maternal organs, thereby predetermining development of GDM.

Hyperbaric oxygen treatment improves pancreatic β‑cell function and hepatic gluconeogenesis in STZ‑induced type‑2 diabetes mellitus model mice

Type‑2 diabetes mellitus (T2DM) causes several complications that affect the quality of life and life span of patients. Hyperbaric oxygen therapy (HBOT) has been used to successfully treat several diseases, including carbon monoxide poisoning, ischemia, infections and diabetic foot ulcer, and increases insulin sensitivity in T2DM. The present study aimed to determine the effect of HBOT on β‑cell function and hepatic gluconeogenesis in streptozotocin (STZ)‑induced type‑2 diabetic mice. To establish a T2DM model, 7‑week‑old male C57BL/6J mice were fed a high‑fat diet (HFD) and injected once daily with low‑dose STZ for 3 days after 1‑week HFD feeding. At the 14th week, HFD+HBOT and T2DM+HBOT groups received 1‑h HBOT (2 ATA; 100% pure O2) daily from 5:00 to 6:00 p.m. for 7 days. The HFD and T2DM groups were maintained under normobaric oxygen conditions and used as controls. During HBOT, the 12‑h nocturnal food intake and body weight were measured daily. Moreover, blood glucose was measured by using a tail vein prick and a glucometer. After the final HBO treatment, all mice were sacrificed to conduct molecular biology experiments. Fasting insulin levels of blood samples of sacrificed mice were measured by an ultrasensitive ELISA kit. Pancreas and liver tissues were stained with hematoxylin and eosin, while immunohistochemistry was performed to determine the effects of HBOT on insulin resistance. TUNEL was used to determine the effects of HBOT on β‑cell apoptosis, and immunoblotting was conducted to determine the β‑cell apoptosis pathway. HBOT notably reduced fasting blood glucose and improved insulin sensitivity in T2DM mice. After HBOT, β‑cell area and β‑cell mass in T2DM mice were significantly increased. HBOT significantly decreased the β‑cell apoptotic rate in T2DM mice via the pancreatic Bcl‑2/caspase‑3/poly(ADP‑ribose) polymerase (PARP) apoptosis pathway. Moreover, HBOT improved the morphology of the liver tissue and increased hepatic glycogen storage in T2DM mice. These findings suggested that HBOT ameliorated the insulin sensitivity of T2DM mice by decreasing the β‑cell apoptotic rate via the pancreatic Bcl‑2/caspase‑3/PARP apoptosis pathway.

Integrated analysis of transcriptome profiling of lncRNAs and mRNAs in livers of type 2 diabetes mellitus

Long noncoding RNAs (lncRNAs) influence the progression of almost all human diseases, but the participation of lncRNAs in type 2 diabetes mellitus (T2DM) has not been fully elucidated. The present study aimed to systematically compare the transcriptome profiling of lncRNAs and mRNAs in livers between T2DM patients and controls, to identify key genes associated with T2DM pathogenesis, and to predict the underlying molecular mechanisms. As a result, a total of 1,512 differentially expressed (DE) lncRNAs and 1,923 DE mRNAs were identified through microarray analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that multiple metabolic processes were dysregulated such as small molecule, organic acid, lipid and branched chain amino acid metabolism. Protein-protein interaction network was constructed and 10 hub mRNAs were identified, including EHHADH, ATM, ACOX1, PIK3R1, EGFR, UQCRFS1, HMGCL, UQCRC2, NDUFS3 and F2. RT-qPCR was conducted to verify the validity of microarray results. Then, coding-noncoding co-expression network and competing endogenous RNA (ceRNA) network were analyzed to predict the lncRNA-mRNA and lncRNA-miRNA-mRNA regulatory patterns. Subsequently, 10 key intermediating miRNAs in ceRNA networks with a node degree > 80 were identified, including hsa-miR-5692a, hsa-miR-12136, hsa-miR-5680, hsa-miR-1305, hsa-miR-6833-5p, hsa-miR-7159-5p, hsa-miR-548as-3p, hsa-miR-6873-3p, hsa-miR-1290 and hsa-miR-4768-5p. In conclusion, the present study evaluated the transcriptome profiling of lncRNAs and mRNAs in livers from T2DM patients, with a value for understanding the molecular mechanism of disease pathogenesis and identifying effective biomarkers in clinical diagnosis.

The cross-talk between RAGE and DIAPH1 in neurological complications of diabetes: A review

Neuropathy, or dysfunction of peripheral nerve, is one of the most common neurological manifestation in patients with diabetes mellitus (DM). DM is typically associated with a hyperglycaemic milieu, which promotes non-enzymatic glycation of proteins. Proteins with advanced glycation are known to engage a cell-surface receptor called the receptor for advanced glycation end products (RAGE). Thus, it is reasonable to assume that RAGE and its associated molecule-mediated cellular signalling may contribute to DM-induced symmetrical axonal (length-dependent) neuropathy. Of particular interest is diaphanous related formin 1 (DIAPH1), a cytoskeletal organizing molecule, which interacts with the cytosolic domain of RAGE and whose dysfunction may precipitate axonopathy/neuropathy. Indeed, it has been demonstrated that both RAGE and DIAPH1 are expressed in the motor and sensory fibres of nerve harvested from DM animal models. Although the detailed molecular role of RAGE and DIAPH1 in diabetic neurological complications remains unclear, here we will discuss available evidence of their involvement in peripheral diabetic neuropathy. Specifically, we will discuss how a hyperglycaemic environment is not only likely to elevate advanced glycation end products (ligands of RAGE) and induce a pro-inflammatory environment but also alter signalling via RAGE and DIAPH1. Further, hyperglycaemia may regulate epigenetic mechanisms that interacts with RAGE signalling. We suggest the cumulative effect of hyperglycaemia on RAGE-DIAPH1-mediated signalling may be disruptive to axonal cytoskeletal organization and transport and is therefore likely to play a key role in pathogenesis of diabetic symmetrical axonal neuropathy.

GWAS-Top Polymorphisms Associated With Late-Onset Alzheimer Disease in Brazil: Pointing Out Possible New Culprits Among Non-Coding RNAs

Several genome-wide association studies (GWAS) have been carried out with late-onset Alzheimer's disease (LOAD), mainly in European and Asian populations. Different polymorphisms were associated, but several of them without a functional explanation. GWAS are fundamental for identifying loci associated with diseases, although they often do not point to causal polymorphisms. In this sense, functional investigations are a fundamental tool for discovering causality, although the failure of this validation does not necessarily indicate a non-causality. Furthermore, the allele frequency of associated genetic variants may vary widely between populations, requiring replication of these associations in other ethnicities. In this sense, our study sought to replicate in 150 AD patients and 114 elderly controls from the South Brazilian population 18 single-nucleotide polymorphisms (SNPs) associated with AD in European GWAS, with further functional investigation using bioinformatic tools for the associated SNPs. Of the 18 SNPs investigated, only four were associated in our population: rs769449 (APOE), rs10838725 (CELF1), rs6733839, and rs744373 (BIN1-CYP27C1). We identified 54 variants in linkage disequilibrium (LD) with the associated SNPs, most of which act as expression or splicing quantitative trait loci (eQTLs/sQTLs) in genes previously associated with AD or with a possible functional role in the disease, such as CELF1, MADD, MYBPC3, NR1H3, NUP160, SPI1, and TOMM40. Interestingly, eight of these variants are located within long non-coding RNA (lncRNA) genes that have not been previously investigated regarding AD. Some of these polymorphisms can result in changes in these lncRNAs' secondary structures, leading to either loss or gain of microRNA (miRNA)-binding sites, deregulating downstream pathways. Our pioneering work not only replicated LOAD association with polymorphisms not yet associated in the Brazilian population but also identified six possible lncRNAs that may interfere in LOAD development. The results lead us to emphasize the importance of functional exploration of associations found in large-scale association studies in different populations to base personalized and inclusive medicine in the future.

Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications

Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research.