Myocardial infarction biomarker discovery with integrated gene expression, pathways and biological networks analysis.

Myocardial infarction (MI) is the most prevalent coronary heart disease caused by the complex molecular interactions between multiple genes and environment. Here, we aim to identify potential biomarkers for the disease development and for prognosis of MI. We have used gene expression dataset (GSE66360) generated from 51 healthy controls and 49 patients experiencing acute MI and analyzed the differentially expressed genes (DEGs), protein-protein interactions (PPI), gene network-clusters to annotate the candidate pathways relevant to MI pathogenesis. Bioinformatic analysis revealed 810 DEGs. Their functional annotations have captured several MI targeting biological processes and pathways like immune response, inflammation and platelets degranulation. PPI network identify seventeen hub and bottleneck genes, whose involvement in MI was further confirmed by DisGeNET database. OpenTarget Platform reveal unique bottleneck genes as potential target for MI. Our findings identify several potential biomarkers associated with early stage MI providing a new insight into molecular mechanism underlying the disease.

Molecular insights into the coding region mutations of low-density lipoprotein receptor adaptor protein 1 (LDLRAP1) linked to familial hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is a lipid disorder caused by pathogenic mutations in LDLRAP1 gene. The present study has aimed to deepen our understanding about the pathogenicity predictions of FH causative genetic mutations, as well as their relationship to phenotype changes in LDLRAP1 protein, by utilizing multidirectional computational analysis. METHODS: FH linked LDLRAP1 mutations were mined from databases, and the prediction ability of several pathogenicity classifiers against these clinical variants, was assessed through different statistical measures. Furthermore, these mutations were 3D modelled in protein structures to assess their impact on protein phenotype changes. RESULTS: Our findings suggest that Polyphen-2, when compared with SIFT, M-CAP and CADD tools, can make better pathogenicity predictions for FH causative LDLRAP1 mutations. Through, 3D simulation and superimposition analysis of LDLRAP1 protein structures, it was found that missense mutations do not create any gross changes in the protein structure, although they could induce subtle structural changes at the level of amino acid residues. Near native molecular dynamic analysis revealed that missense mutations could induce variable degrees of fluctuation differences guiding the protein flexibility. Stability analysis showed that most missense mutations shifts the free energy equilibrium and hence they destabilize the protein. Molecular docking analysis demonstrates the molecular shifts in hydrogen and ionic bonds and Van der waals bonding properties, which further cause differences in the binding energy of LDLR-LDLRAP1 proteins. CONCLUSIONS: The diverse computational approaches used in the present study may provide a new dimension for exploring the structure-function relationship of the novel and deleterious LDLRAP1 mutations linked to FH.

Induced pluripotent stem cell modelling of HLHS underlines the contribution of dysfunctional NOTCH signalling to impaired cardiogenesis.

Hypoplastic left heart syndrome (HLHS) is among the most severe forms of congenital heart disease. Although the consensus view is that reduced flow through the left heart during development is a key factor in the development of the condition, the molecular mechanisms leading to hypoplasia of left heart structures are unknown. We have generated induced pluripotent stem cells (iPSC) from five HLHS patients and two unaffected controls, differentiated these to cardiomyocytes and identified reproducible in vitro cellular and functional correlates of the HLHS phenotype. Our data indicate that HLHS-iPSC have a reduced ability to give rise to mesodermal, cardiac progenitors and mature cardiomyocytes and an enhanced ability to differentiate to smooth muscle cells. HLHS-iPSC-derived cardiomyocytes are characterised by a lower beating rate, disorganised sarcomeres and sarcoplasmic reticulum and a blunted response to isoprenaline. Whole exome sequencing of HLHS fibroblasts identified deleterious variants in NOTCH receptors and other genes involved in the NOTCH signalling pathway. Our data indicate that the expression of NOTCH receptors was significantly downregulated in HLHS-iPSC-derived cardiomyocytes alongside NOTCH target genes confirming downregulation of NOTCH signalling activity. Activation of NOTCH signalling via addition of Jagged peptide ligand during the differentiation of HLHS-iPSC restored their cardiomyocyte differentiation capacity and beating rate and suppressed the smooth muscle cell formation. Together, our data provide firm evidence for involvement of NOTCH signalling in HLHS pathogenesis, reveal novel genetic insights important for HLHS pathology and shed new insights into the role of this pathway during human cardiac development.

Protein phenotype diagnosis of autosomal dominant calmodulin mutations causing irregular heart rhythms.

The life-threatening group of irregular cardiac rhythmic disorders also known as Cardiac Arrhythmias (CA) are caused by mutations in highly conserved Calmodulin (CALM/CaM) genes. Herein, we present a multidimensional approach to diagnose changes in phenotypic, stability, and Ca2+ ion binding properties of CA-causing mutations. Mutation pathogenicity was determined by diverse computational machine learning approaches. We further modeled the mutations in 3D protein structure and analyzed residue level phenotype plasticity. We have also examined the influence of torsion angles, number of H-bonds, and free energy dynamics on the stability, near-native simulation dynamic potential of residue fluctuations in protein structures, Ca2+ ion binding potentials, of CaM mutants. Our study recomends to use M-CAP method for measuring the pathogenicity of CA causing CaM variants. Interestingly, most CA-causing variants we analyzed, exists in either third (V/H-96, S/I-98, V-103) or fourth (G/V-130, V/E/H-132, H-134, P-136, G-141, and L-142) EF-hands located in carboxyl domains of the CaM molecule. We observed that the minor structural fluctuations caused by these variants are likely tolerable owing to the highly flexible nature of calmodulin's globular domains. However, our molecular docking results supports that these variants disturb the affinity of CaM toward Ca2+ ions and corroborate previous findings from functional studies. Taken together, these computational findings can explain the molecular reasons for subtle changes in structure, flexibility, and stability aspects of mutant CaM molecule. Our comprehensive molecular scanning approach demonstrates the utility of computational methods in quick preliminary screening of CA- CaM mutations before undertaking time consuming and complicated functional laboratory assays.

Comprehensive Computational Analysis of GWAS Loci Identifies CCR2 as a Candidate Gene for Celiac Disease Pathogenesis.

Celiac disease (CD) is a gluten intolerance disorder with known genetic contribution. The recent fine mapping and genome-wide association studies (GWAS) have identified up to 57 non-HLA CD susceptibility SNPs, majority of which are non-coding variants lacking any functional annotation. Therefore, we adopted multidimensional computational approach for uncovering the plausible mechanisms through which these GWAS SNPs are connected to CD pathogenesis. At initial phase, we identified that 25 (43.85%) out of 57 CD-SNPs lies in evolutionarily constrained genetic element regions. In follow-up phases, through computational (CADD, GWAVA, and FATHMM algorithms) deleterious intensity measurements, we have discovered that 42 (3.94%) out of 1065 variants (57 CD-lead and 1008-linked SNPs; r2 ≥ 0.8) are differentially deleterious in nature to CD. Further functional scrutinization of these CD variants by public domain eQTL mapping, gene expression, knockout mouse model, and pathway analyses revealed that deleterious SNPs of CCR2 gene influences its expression levels and may also elicit a cascade of T-cell-mediated immunological events leading to intestinal gluten intolerance in genetically susceptible individuals. This study demonstrates the utility of integrated in silico analysis of annotations, gene expression, and pathways in prioritizing the potential complex disease variants from large-scale open source genomic data. J. Cell. Biochem. 118: 2193-2207, 2017. © 2017 Wiley Periodicals, Inc.

Distribution of CYP2C8 and CYP2C9 amino acid substitution alleles in South Indian diabetes patients: A genotypic and computational protein phenotype study.

The CYP2C8 and CYP2C9 are two major isoforms of the cytochrome P450 enzyme family, which is involved in drug response, detoxification, and disease development. This study describes the differential distribution of amino acid substitution variants of CYP2C8 (*2-I269F & *3-R139K) and CYP2C9 (*2-C144R & *3-L359A) genes in 234 type 2 diabetes mellitus (T2DM) patients and 218 healthy controls from Andhra Pradesh, South India. Single locus genotype analysis has revealed that homozygous recessive genotypes of 2C8*2-TT (P ≤ .03), 2C9*2-TT (P ≤ .02), and heterozygous 2C9*3-AC (P ≤ .006) are seen to be increasingly present in the case group, indicating a significant level of their association with diabetes in Andhra population. The statistical significance of these recessive genotypes has persisted even under their corresponding allelic forms (P ≤ .01). Genotype association results were further examined by computational protein structure and stability analysis to assess the deleteriousness of the amino acid changes. The mutant CYP 2C8 and 2C9 (both *2 and *3) proteins showed structural drifts at both amino acid residue (range 0.43Å-0.77Å), and polypeptide chain levels (range 0.68Å-1.81Å) compared to their wild-type counterparts. Furthermore, the free energy value differences (range -0.915 to -1.38 Kcal/mol) between mutant and native protein structures suggests the deleterious and destabilizing potential of amino acid substitution polymorphisms of CYP genes. The present study confirms the variable distribution of CYP2C8 (*2 and *3) and CYP2C9 (*2 and *3) allelic polymorphisms among South Indian diabetic populations and further warrants the serious attention of CYP gene family, as a putative locus for disease risk assessment and therapy.

Replication of GWAS loci revealed the moderate effect of TNRC6B locus on susceptibility of Saudi women to develop uterine leiomyomas.

AIM: Uterine leiomyomas (UL) are smooth muscular nodes, whose growth is dependant up on the complex interplay of hormones with genes and uterine physiology. Global statistics indicate the role of ethnic and racial background as contributory factors for UL development. Owing to the lack of data, this study aimed to examine the association between genetic polymorphisms and susceptibility of Arab women of developing UL. METHODS: We genotyped 105 UL patients and 112 healthy controls for five genetic polymorphisms through real time PCR method. The strength of the association between genotype and allele frequencies with risk of developing UL was tested with their χ2 and odds ratio (OR) values. The synergistic cooperation between genetic polymorphisms was estimated through multifactor dimensionality reduction assay. RESULTS: We found that Saudi women with the AG genotype for the rs12484776 polymorphism are at a 2.6-fold higher risk of developing UL compared to those with other genotypes (OR, 2.69; 95% confidence interval [CI]: 1.45-5.00; P < 0.001). This significance persisted even under co-dominant models (i.e., AA vs GG + AG [OR, 2.74; 95%CI: 1.48-5.08; P = 0.001; and AG vs GG + AG [OR, 2.41; 95% CI: 1.33-4.39; P = 0.003). Genotype distribution frequencies for rs1056836, rs7913069, rs2280543, and rs4247357 were not shown to elevate the disease risk (for all tests P > 0.05). CONCLUSION: The rs12484776 significantly contributes to UL risk among Saudi women, both in single and also in synergistic cooperation with rs2280543, rs7913069, and rs1056836 markers. Our results have yielded mixed findings in replicating European- and Japanese-specific UL genetic susceptibility loci among a geographically and culturally distinct population of the Saudi Arabian Peninsula.

A Computational Protein Phenotype Prediction Approach to Analyze the Deleterious Mutations of Human MED12 Gene.

Genetic mutations in MED12, a subunit of Mediator complex are seen in a broad spectrum of human diseases. However, the underlying basis of how these pathogenic mutations elicit protein phenotype changes in terms of 3D structure, stability and protein binding sites remains unknown. Therefore, we aimed to investigate the structural and functional impacts of MED12 mutations, using computational methods as an alternate to traditional in vivo and in vitro approaches. The MED12 gene mutations details and their corresponding clinical associations were collected from different databases and by text-mining. Initially, diverse computational approaches were applied to categorize the different classes of mutations based on their deleterious impact to MED12. Then, protein structures for wild and mutant types built by integrative modeling were analyzed for structural divergence, solvent accessibility, stability, and functional interaction deformities. Finally, this study was able to identify that genetic mutations mapped to exon-2 region, highly conserved LCEWAV and Catenin domains induce biochemically severe amino acid changes which alters the protein phenotype as well as the stability of MED12-CYCC interactions. To better understand the deleterious nature of FS-IDs and Indels, this study asserts the utility of computational screening based on their propensity towards non-sense mediated decay. Current study findings may help to narrow down the number of MED12 mutations to be screened for mediator complex dysfunction associated genetic diseases. This study supports computational methods as a primary filter to verify the plausible impact of pathogenic mutations based on the perspective of evolution, expression and phenotype of proteins. J. Cell. Biochem. 117: 2023-2035, 2016. © 2016 Wiley Periodicals, Inc.

Evidence for the presence of somatic mitochondrial DNA mutations in right atrial appendage tissues of coronary artery disease patients.

Coronary artery disease (CAD) is a multifactorial disease with the underlying involvement of environment, life style and nuclear genetics. However, the role of extranuclear genetic material in terms of somatically acquired mutations in mitochondrial tRNA and protein coding genes in the initiation or progression of CAD is not well defined. Hence, in the present study, right atrial appendage tissues and matched blood samples of 150 CAD patients were screened for mutations in nucleotide regions encompassing the Cytochrome c oxidase subunit II (MT-CO2), tRNA lysine (MT-TK), ATP synthase F0 subunit 8 (MT-ATP8) and Cytochrome b (MT-CYB) genes of mitochondrial DNA. We have found 9 different somatic mutations in 6 % of the CAD patients. Out of these mutations, 4 each were localized in MT-TK gene (T8324A, A8326G, A8331G and A8344G) and MT-CYB genes (T15062C, C15238A, T15378G and C15491G) in addition to one mutation in non-coding region 7 (A8270T) of mitochondrial genome. In addition, we noticed that majority (85.3 %) of CAD patients showed double repeats of germ-line "CCCCCTCTA" intergenic sequence between MT-CO2 and MT-TK genes. Our in-silico investigations of missense mutations revealed that they may alter the free energy and stability of polypeptide chains of MT-CYB protein of complex III of mitochondrial respiratory chain. Based on our study findings, we hypothesize that the somatically acquired variations in MT-TK and MT-CYB genes may negatively impact the energy metabolism of cardiomyocytes in right atrial appendage tissues and contribute in the cardiac dysfunction among CAD patients. In conclusion, our findings may be likely to have potential implications in understanding the disease pathophysiology, diagnosis as well as for the better therapeutic management of CAD patients.

Paget's disease: a review of the epidemiology, etiology, genetics, and treatment.

Paget's disease of bone (PDB) is the second most prevalent metabolic bone disorder worldwide, with a prevalence rate of 1.5%-8.3%. It is characterized by localized areas of accelerated, disorganized, and excessive bone production and turnover. Typically, PDB develops in the later stages of life, particularly in the late 50s, and affects men more frequently than women. PDB is a complex disease influenced by both genetic and environmental factors. PDB has a complex genetic basis involving multiple genes, with SQSTM1 being the gene most frequently associated with its development. Mutations affecting the UBA domain of SQSTM1 have been detected in both familial and sporadic PDB cases, and these mutations are often associated with severe clinical expression. Germline mutations in other genes such as TNFRSF11A, ZNF687 and PFN1, have also been associated with the development of the disease. Genetic association studies have also uncovered several PDB predisposing risk genes contributing to the disease pathology and severity. Epigenetic modifications of genes involved in bone remodelling and regulation, including RANKL, OPG, HDAC2, DNMT1, and SQSTM1, have been implicated in the development and progression of Paget's disease of bone, providing insight into the molecular basis of the disease and potential targets for therapeutic intervention. Although PDB has a tendency to cluster within families, the variable severity of the disease across family members, coupled with decreasing incidence rates, indicates that environmental factors may also play a role in the pathophysiology of PDB. The precise nature of these environmental triggers and how they interact with genetic determinants remain poorly understood. Fortunately, majority of PDB patients can achieve long-term remission with an intravenous infusion of aminobisphosphonates, such as zoledronic acid. In this review, we discuss aspects like clinical characteristics, genetic foundation, and latest updates in PDB research.

The use of therapeutic drug monitoring for early identification of vedolizumab response in Saudi Arabian patients with inflammatory bowel disease.

Vedolizumab is a humanized monoclonal antibody used to treat moderate-to-severe inflammatory bowel disease (IBD). The aim of the study was to assess the effectiveness of the induction of vedolizumab trough level in predicting short-term (week 14) clinical outcomes, and covariates that affect the response in Saudi Arabian patients. This prospective, real-life study included a total of 16 patients (4 Crohn's disease (CD) and 12 ulcerative colitis (UC)) with a confirmed diagnosis of IBD and generally naïve to receiving vedolizumab therapy. Using ELISA assay, vedolizumab induction trough and peak levels were measured at weeks 0, 2, and 6. The follow-up assessment was at week 14, where clinical outcomes were measured using the partial Mayo score for UC, and the CD activity score (CDAI), and Harvey Bradshaw index (HBI) for CD. At week 14, 9 patients (52.9%) out of 16 patients demonstrated response to therapy; clinical remission was reported in 5 patients (29.4%), and in 4 cases a clinical response was noted (23.5%). Clinical remission at week 14 was linked significantly with week 6 median vedolizumab levels in responders (25.1 µg/ml 95% CI: 16.5-42.9) compared to non-responders (7.7 µg/ml, 95% CI: 4.6-10.6) (P = 0.002). Receiver operator curve analysis at week 6 identified a cut-off > 8.00 µg/mL for short-term clinical remission. Also, at week 14, BMI significantly correlated with week 6 vedolizumab trough levels (P = 0.02). No other covariates correlated with drug levels at any time point examined. Week 6 early vedolizumab trough level measurements in IBD patients predicted short-term week 14 clinical remission.

Protein structural insights into a rare PCSK9 gain-of-function variant (R496W) causing familial hypercholesterolemia in a Saudi family: whole exome sequencing and computational analysis.

Familial hypercholesterolemia (FH) is a globally underdiagnosed genetic condition associated with premature cardiovascular death. The genetic etiology data on Arab FH patients is scarce. Therefore, this study aimed to identify the genetic basis of FH in a Saudi family using whole exome sequencing (WES) and multidimensional bioinformatic analysis. Our WES findings revealed a rare heterozygous gain-of-function variant (R496W) in the exon 9 of the PCSK9 gene as a causal factor for FH in this family. This variant was absent in healthy relatives of the proband and 200 healthy normolipidemic controls from Saudi Arabia. Furthermore, this variant has not been previously reported in various regional and global population genomic variant databases. Interestingly, this variant is classified as "likely pathogenic" (PP5) based on the variant interpretation guidelines of the American College of Medical Genetics (ACMG). Computational functional characterization suggested that this variant could destabilize the native PCSK9 protein and alter its secondary and tertiary structural features. In addition, this variant was predicted to negatively influence its ligand-binding ability with LDLR and Alirocumab antibody molecules. This rare PCSK9 (R496W) variant is likely to expand our understanding of the genetic basis of FH in Saudi Arabia. This study also provides computational structural insights into the genotype-protein phenotype relationship of PCSK9 pathogenic variants and contributes to the development of personalized medicine for FH patients in the future.

Potential Biomarkers for Parkinson Disease from Functional Enrichment and Bioinformatic Analysis of Global Gene Expression Patterns of Blood and Substantia Nigra Tissues.

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Rare variant burden analysis from exomes of three consanguineous families reveals LILRB1 and PRSS3 as potential key proteins in inflammatory bowel disease pathogenesis.

Background: Inflammatory bowel disease (IBD) is a chronic autoimmune disorder characterized by severe inflammation and mucosal destruction of the intestine. The specific, complex molecular processes underlying IBD pathogenesis are not well understood. Therefore, this study is aimed at identifying and uncovering the role of key genetic factors in IBD. Method: The whole exome sequences (WESs) of three consanguineous Saudi families having many siblings with IBD were analyzed to discover the causal genetic defect. Then, we used a combination of artificial intelligence approaches, such as functional enrichment analysis using immune pathways and a set of computational functional validation tools for gene expression, immune cell expression analyses, phenotype aggregation, and the system biology of innate immunity, to highlight potential IBD genes that play an important role in its pathobiology. Results: Our findings have shown a causal group of extremely rare variants in the LILRB1 (Q53L, Y99N, W351G, D365A, and Q376H) and PRSS3 (F4L and V25I) genes in IBD-affected siblings. Findings from amino acids in conserved domains, tertiary-level structural deviations, and stability analysis have confirmed that these variants have a negative impact on structural features in the corresponding proteins. Intensive computational structural analysis shows that both genes have very high expression in the gastrointestinal tract and immune organs and are involved in a variety of innate immune system pathways. Since the innate immune system detects microbial infections, any defect in this system could lead to immune functional impairment contributing to IBD. Conclusion: The present study proposes a novel strategy for unraveling the complex genetic architecture of IBD by integrating WES data of familial cases, with computational analysis.

Bioinformatics insights into the genes and pathways on severe COVID-19 pathology in patients with comorbidities.

Background: Coronavirus disease (COVID-19) infection is known for its severe clinical pathogenesis among individuals with pre-existing comorbidities. However, the molecular basis of this observation remains elusive. Thus, this study aimed to map key genes and pathway alterations in patients with COVID-19 and comorbidities using robust systems biology approaches. Methods: The publicly available genome-wide transcriptomic datasets from 120 COVID-19 patients, 281 patients suffering from different comorbidities (like cardiovascular diseases, atherosclerosis, diabetes, and obesity), and 252 patients with different infectious diseases of the lung (respiratory syncytial virus, influenza, and MERS) were studied using a range of systems biology approaches like differential gene expression, gene ontology (GO), pathway enrichment, functional similarity, mouse phenotypic analysis and drug target identification. Results: By cross-mapping the differentially expressed genes (DEGs) across different datasets, we mapped 274 shared genes to severe symptoms of COVID-19 patients or with comorbidities alone. GO terms and functional pathway analysis highlighted genes in dysregulated pathways of immune response, interleukin signaling, FCGR activation, regulation of cytokines, chemokines secretion, and leukocyte migration. Using network topology parameters, phenotype associations, and functional similarity analysis with ACE2 and TMPRSS2-two key receptors for this virus-we identified 17 genes with high connectivity (CXCL10, IDO1, LEPR, MME, PTAFR, PTGS2, MAOB, PDE4B, PLA2G2A, COL5A1, ICAM1, SERPINE1, ABCB1, IL1R1, ITGAL, NCAM1 and PRKD1) potentially contributing to the clinical severity of COVID-19 infection in patients with comorbidities. These genes are predicted to be tractable and/or with many existing approved inhibitors, modulators, and enzymes as drugs. Conclusion: By systemic implementation of computational methods, this study identified potential candidate genes and pathways likely to confer disease severity in COVID-19 patients with pre-existing comorbidities. Our findings pave the way to develop targeted repurposed therapies in COVID-19 patients.

A comparative mRNA- and miRNA transcriptomics reveals novel molecular signatures associated with metastatic prostate cancers.

Background: Prostate cancer (PC) is a fatally aggressive urogenital cancer killing millions of men, globally. Thus, this study aims to identify key miRNAs, target genes, and drug targets associated with prostate cancer metastasis. Methods: The miRNA and mRNA expression datasets of 148 prostate tissue biopsies (39 tumours and 109 normal tissues), were analysed by differential gene expression analysis, protein interactome mapping, biological pathway analysis, miRNA-mRNA networking, drug target analysis, and survival curve analysis. Results: The dysregulated expression of 53 miRNAs and their 250 target genes involved in Hedgehog, ErbB, and cAMP signalling pathways connected to cell growth, migration, and proliferation of prostate cancer cells was detected. The subsequent miRNA-mRNA network and expression status analysis have helped us in narrowing down their number to 3 hub miRNAs (hsa-miR-455-3p, hsa-miR-548c-3p, and hsa-miR-582-5p) and 9 hub genes (NFIB, DICER1, GSK3B, DCAF7, FGFR1OP, ABHD2, NACC2, NR3C1, and FGF2). Further investigations with different systems biology methods have prioritized NR3C1, ABHD2, and GSK3B as potential genes involved in prostate cancer metastasis owing to their high mutation load and expression status. Interestingly, down regulation of NR3C1 seems to improve the prostate cancer patient survival rate beyond 150 months. The NR3C1, ABHD2, and GSK3B genes are predicted to be targeted by hsa-miR-582-5p, besides some antibodies, PROTACs and inhibitory molecules. Conclusion: This study identified key miRNAs (miR-548c-3p and miR-582-5p) and target genes (NR3C1, ABHD2, and GSK3B) as potential biomarkers for metastatic prostate cancers from large-scale gene expression data using systems biology approaches.

Identification of miRNA-mRNA-TFs regulatory network and crucial pathways involved in asthma through advanced systems biology approaches.

Asthma is a life-threatening and chronic inflammatory lung disease that is posing a true global health challenge. The genetic basis of the disease is fairly well examined. However, the molecular crosstalk between microRNAs (miRNAs), target genes, and transcription factors (TFs) networks and their contribution to disease pathogenesis and progression is not well explored. Therefore, this study was aimed at dissecting the molecular network between mRNAs, miRNAs, and TFs using robust computational biology approaches. The transcriptomic data of bronchial epithelial cells of severe asthma patients and healthy controls was studied by different systems biology approaches like differentially expressed gene detection, functional enrichment, miRNA-target gene pairing, and mRNA-miRNA-TF molecular networking. We detected the differential expression of 1703 (673 up-and 1030 down-regulated) genes and 71 (41 up-and 30 down-regulated) miRNAs in the bronchial epithelial cells of asthma patients. The DEGs were found to be enriched in key pathways like IL-17 signaling (KEGG: 04657), Th1 and Th2 cell differentiation (KEGG: 04658), and the Th17 cell differentiation (KEGG: 04659) (p-values = 0.001). The results from miRNAs-target gene pairs-transcription factors (TFs) have detected the key roles of 3 miRs (miR-181a-2-3p; miR-203a-3p; miR-335-5p), 6 TFs (TFAM, FOXO1, GFI1, IRF2, SOX9, and HLF) and 32 miRNA target genes in eliciting autoimmune reactions in bronchial epithelial cells of the respiratory tract. Through systemic implementation of comprehensive system biology tools, this study has identified key miRNAs, TFs, and miRNA target gene pairs as potential tissue-based asthma biomarkers.

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.

Genome-Wide Association Study-Guided Exome Rare Variant Burden Analysis Identifies IL1R1 and CD3E as Potential Autoimmunity Risk Genes for Celiac Disease.

Celiac disease (CeD) is a multifactorial autoimmune enteropathy characterized by the overactivation of the immune system in response to dietary gluten. The molecular etiology of CeD is still not well-understood. Therefore, this study aims to identify potential candidate genes involved in CeD pathogenesis by applying multilayered system biology approaches. Initially, we identified rare coding variants shared between the affected siblings in two rare Arab CeD families by whole-exome sequencing (WES). Then we used the STRING database to construct a protein network of rare variants and genome-wide association study (GWAS) loci to explore their molecular interactions in CeD. Furthermore, the hub genes identified based on network topology parameters were subjected to a series of computational validation analyses like pathway enrichment, gene expression, knockout mouse model, and variant pathogenicity predictions. Our findings have shown the absence of rare variants showing classical Mendelian inheritance in both families. However, interactome analysis of rare WES variants and GWAS loci has identified a total of 11 hub genes. The multidimensional computational analysis of hub genes has prioritized IL1R1 for family A and CD3E for family B as potential genes. These genes were connected to CeD pathogenesis pathways of T-cell selection, cytokine signaling, and adaptive immune response. Future multi-omics studies may uncover the roles of IL1R1 and CD3E in gluten sensitivity. The present investigation lays forth a novel approach integrating next-generation sequencing (NGS) of familial cases, GWAS, and computational analysis for solving the complex genetic architecture of CeD.

Structural characterization and conformational dynamics of alpha-1 antitrypsin pathogenic variants causing alpha-1-antitrypsin deficiency.

Background: Alpha-1 antitrypsin deficiency (A1ATD) is a progressive lung disease caused by inherited pathogenic variants in the SERPINA1 gene. However, their actual role in maintenance of structural and functional characteristics of the corresponding α-1 anti-trypsin (A1AT) protein is not well characterized. Methods: The A1ATD causative SERPINA1 missense variants were initially collected from variant databases, and they were filtered based on their pathogenicity potential. Then, the tertiary protein models were constructed and the impact of individual variants on secondary structure, stability, protein-protein interactions, and molecular dynamic (MD) features of the A1AT protein was studied using diverse computational methods. Results: We identified that A1ATD linked SERPINA1 missense variants like F76S, S77F, L278P, E288V, G216C, and H358R are highly deleterious as per the consensual prediction scores of SIFT, PolyPhen, FATHMM, M-CAP and REVEL computational methods. All these variants were predicted to alter free energy dynamics and destabilize the A1AT protein. These variants were seen to cause minor structural drifts at residue level (RMSD = <2Å) of the protein. Interestingly, S77F and L278P variants subtly alter the size of secondary structural elements like beta pleated sheets and loops. The residue level fluctuations at 100 ns simulation confirm the highly damaging structural consequences of all the six missense variants on the conformation dynamics of the A1AT protein. Moreover, these variants were also predicted to cause functional deformities by negatively impacting the binding energy of A1AT protein with NE ligand molecule. Conclusion: This study adds a new computational biology dimension to interpret the genotype-protein phenotype relationship between SERPINA1 pathogenic variants with its structural plasticity and functional behavior with NE ligand molecule contributing to the Alpha-1-antitrypsin deficiency. Our results support that A1ATD complications correlates with the conformational flexibility and its propensity of A1AT protein polymerization when misfolded.