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Background: Colorectal cancer (CRC) is the leading cancer among Saudis, and mutations in BRAF , KRAS , and NRAS genes are therapeutically significant due to their association with pathways critical for cell cycle regulation. This study evaluates the prevalence and frequency of somatic mutations in these actionable genes in Saudi CRC patients and assesses their pathogenicity with bioinformatics methods. Methodology: The study employed the TruSight Tumor 15 next-generation sequencing (NGS) panel on 86 colorectal cancer (CRC) samples to detect somatic mutations in BRAF , KRAS , and NRAS genes. Bioinformatic analyses of NGS sequences included variant annotation with ANNOVAR, pathogenicity prediction, variant reclassification with CancerVar, and extensive structural analysis. Additionally, molecular docking assessed the binding of Encorafenib to wild-type and mutant BRAF proteins, providing insights into the therapeutic relevance of pathogenic variants. Results: Out of 86 tumor samples, 40 (46.5%) harbored somatic mutations within actionable genes (BRAF : 2.3%, KRAS : 43%, NRAS : 2.3%). Fourteen missense variants were identified (BRAF : n = 1, KRAS : n = 11, NRAS : n = 2). Variants with strong clinical significance included BRAF V600E (2.32%) and KRAS G12D (18.60%). Variants with potential clinical significance included several KRAS and an NRAS mutation, while variants of unknown significance included KRAS E49K and NRAS R102Q. One variant was novel: NRAS R102Q, and two were rare: KRAS E49K and G138E. We further extended the CancerVar prediction capability by adding new pathogenicity prediction tools. Molecular docking demonstrated that Encorafenib inhibits the V600E variant BRAF protein less effectively compared to its wild-type counterpart. Conclusion: Overall, this study highlights the importance of comprehensive molecular screening and bioinformatics in understanding the mutational landscape of CRC in the Saudi population, ultimately improving targeted drug treatments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is a urogenital cancer affecting millions of post-menopausal women, globally. This study aims to identify key miRNAs, target genes, and drug targets associated with EC metastasis. The global miRNA and mRNA expression datasets of endometrial tissue biopsies (24 tumors +3 healthy tissues for mRNA and 18 tumor +4 healthy tissues for miRNAs), were extensively analyzed by mapping of DEGs, DEMi, biological pathway enrichment, miRNA-mRNA networking, drug target identification, and survival curve output for differentially expressed genes. Our results reveal the dysregulated expression of 26 miRNAs and their 66 target genes involved in focal adhesions, p53 signaling pathway, ECM-receptor interaction, Hedgehog signaling pathway, fat digestion and absorption, glioma as well as retinol metabolism involved in cell growth, migration, and proliferation of endometrial cancer cells. The subsequent miRNA-mRNA network and expression status analysis have narrowed down to 2 hub miRNAs (hsa-mir-200a, hsa-mir-429) and 6 hub genes (PTCH1, FOSB, PDGFRA, CCND2, ABL1, ALDH1A1). Further investigations with different systems biology methods have prioritized ALDH1A1, ABL1 and CCND2 as potential genes involved in endometrial cancer metastasis owing to their high mutation load and expression status. Interestingly, overexpression of PTCH1, ABL1 and FOSB genes are reported to be associated with a low survival rate among cancer patients. The upregulated hsa-mir-200a-b is associated with the decreased expression of the PTCH1, CCND2, PDGFRA, FOSB and ABL1 genes in endometrial cancer tissue while hsa-mir-429 is correlated with the decreased expression of the ALDH1A1 gene, besides some antibodies, PROTACs and inhibitory molecules. In conclusion, this study identified key miRNAs (hsa-mir-200a, hsa-mir-429) and target genes ALDH1A1, ABL1 and CCND2 as potential biomarkers for metastatic endometrial cancers from large-scale gene expression data using systems biology approaches. [ABSTRACT FROM AUTHOR]

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, hsamiR-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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Uterine smooth muscular neoplastic growths like benign leiomyomas (UL) and metastatic leiomyosarcomas (ULMS) share similar clinical symptoms, radiological and histological appearances making their clinical distinction a difficult task. Therefore, the objective of this study is to identify key genes and pathways involved in transformation of UL to ULMS through molecular differential analysis. Global gene expression profiles of 25 ULMS, 25 UL, and 29 myometrium (Myo) tissues generated on Affymetrix U133A 2.0 human genome microarrays were analyzed by deploying robust statistical, molecular interaction network, and pathway enrichment methods. The comparison of expression signals across Myo vs UL, Myo vs ULMS, and UL vs ULMS groups identified 249, 1037, and 716 significantly expressed genes, respectively (p ≤ 0.05). The analysis of 249 DEGs from Myo vs UL confirms multistage dysregulation of various key pathways in extracellular matrix, collagen, cell contact inhibition, and cytokine receptors transform normal myometrial cells to benign leiomyomas (p value ≤ 0.01). The 716 DEGs between UL vs ULMS were found to affect cell cycle, cell division related Rho GTPases and PI3K signaling pathways triggering uncontrolled growth and metastasis of tumor cells (p value ≤ 0.01). Integration of gene networking data, with additional parameters like estimation of mutation burden of tumors and cancer driver gene identification, has led to the finding of 4 hubs (JUN, VCAN, TOP2A, and COL1A1) and 8 bottleneck genes (PIK3R1, MYH11, KDR, ESR1, WT1, CCND1, EZH2, and CDKN2A), which showed a clear distinction in their distribution pattern among leiomyomas and leiomyosarcomas. This study provides vital clues for molecular distinction of UL and ULMS which could further assist in identification of specific diagnostic markers and therapeutic targets. Abbreviations UL: Uterine Leiomyomas; ULMS: Uterine Leiomyosarcoma; Myo: Myometrium; DEGs: Differential Expressed Genes; RMA: Robust Multiarray Average; DC: Degree of Centrality; BC: Betweenness of Centrality; CGC: Cancer Gene Census; FDR: False Discovery Rate; TCGA: Cancer Genome Atlas; BP: Biological Process; CC: Cellular Components; MF: Molecular Function; PPI: Protein–Protein Interaction [ABSTRACT FROM AUTHOR]

Background: Celiac disease (CD) is a genetically complex autoimmune disease which is triggered by dietary gluten. Human leukocyte antigen (HLA) class II genes are known to act as high-risk markers for CD, where >95% of CD patients carry (HLA), DQ2 and/or DQ8 alleles. Therefore, the present study was conducted to investigate the distribution of HLA haplotypes among Saudi CD patients and healthy controls by using the tag single nucleotide polymorphisms (SNP). Methods: HLA-tag SNPs showing strong linkage value (r2>0.99) were used to predict the HLA DQ2 and DQ8 genotypes in 101 Saudi CD patients and in 103 healthy controls by using real-time polymerase chain reaction technique. Genotype calls were further validated by Sanger sequencing method. Results: A total of 63.7% of CD cases and of 60.2% of controls were predicted to carry HLA-DQ2 and DQ8 heterodimers, either in the homozygous or heterozygous states. The prevalence of DQ8 in our CD patients was predicted to be higher than the patients fromother ethnic populations (35.6%). More than 32% of the CD patients were found to be non-carriers of HLA risk haplotypes as predicted by the tag SNPs. Conclusion: The present study highlights that the Caucasian specific HLA-tag SNPs would be of limited value to accurately predict CD specific HLA haplotypes in Saudi population, when compared with the Caucasian groups. Prediction of risk haplotypes by tag SNPs in ethnic groups is a good alternate approach as long as the tag SNPs were identified from the local population genetic variant databases. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Obesity is a multifactorial disease caused by complex interactions between genes and dietary factors. Salt-rich diet is related to the development and progression of several chronic diseases including obesity. However, the molecular basis of how salt sensitivity genes (SSG) contribute to adiposity in obesity patients remains unexplored. In this study, we used the microarray expression data of visceral adipose tissue samples and constructed a complex protein-interaction network of salt sensitivity genes and their co-expressed genes to trace the molecular pathways connected to obesity. The Salt Sensitivity Protein Interaction Network (SSPIN) of 2691 differentially expressed genes and their 15474 interactions has shown that adipose tissues are enriched with the expression of 23 SSGs, 16 hubs and 84 bottlenecks (p = 2.52 x 10–16) involved in diverse molecular pathways connected to adiposity. Fifteen of these 23 SSGs along with 8 other SSGs showed a co-expression with enriched obesity-related genes (r ≥ 0.8). These SSGs and their co-expression partners are involved in diverse metabolic pathways including adipogenesis, adipocytokine signaling pathway, renin-angiotensin system, etc. This study concludes that SSGs could act as molecular signatures for tracing the basis of adipogenesis among obese patients. Integrated network centered methods may accelerate the identification of new molecular targets from the complex obesity genomics data. [ABSTRACT FROM AUTHOR]

A large-scale DNA-based assay, namely SNaPshot, was developed and validated for the determination of allelic polymorphisms of genes associated with type II diabetes (T2D) mellitus disease in Saudi patients. The new approach is alternative to phenotyping and physiological diagnosis. The assay includes single nucleotide polymorphisms (SNPs) of seven most common genes namely, GNB-3, GCK, SLC30A, KNJ11, TCF7L2, CDKN2A/B and HNF4A. The study proved that the new genotyping assay is rapid, easy to perform and robust for screening of high risk T2D family members. The new assay can be applied in genetic testing as an important tool for identifying significant genetic factors that help in predicting diabetes at early stages of life to avoid subsequent complications. This assay can also be used to evaluate the gene risk variants in populations of other geographic origins. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic synovial autoinflammatory disease that destructs the cartilage and bone, leading to disability. The functional regulation of major immunity-related pathways like nuclear factor kappa B (NF-κB), which is involved in the chronic inflammatory reactions underlying the development of RA, remains to be explored. Therefore, this study has adopted statistical and knowledge-based systemic investigations (like gene correlation, semantic similarity, and topological parameters based on graph theory) to study the gene expression status of NF-κB protein family (NKPF) and its regulators in synovial tissues to trace the molecular pathways through which these regulators contribute to RA. A complex protein–protein interaction map (PPIM) of 2,742 genes and 37,032 interactions was constructed from differentially expressed genes (p ≤ 0.05). PPIM was further decomposed into a Regulator Allied Protein Interaction Network (RAPIN) based on the interaction between genes (5 NKPF, 31 seeds, 131 hubs, and 652 bottlenecks). Pathway network analysis has shown the RA-specific disturbances in the functional connectivity between seed genes (RIPK1 , ATG7 , TLR4 , TNFRSF1A , KPNA1 , CFLAR , SNW1 , FOSB , PARVA , CX3CL1 , and TRPC6) and NKPF members (RELA , RELB , NFKB2 , and REL). Interestingly, these genes are known for their involvement in inflammation and immune system (signaling by interleukins, cytokine signaling in immune system, NOD-like receptor signaling, MAPK signaling, Toll-like receptor signaling, and TNF signaling) pathways connected to RA. This study, for the first time, reports that SNW1, along with other NK regulatory genes, plays an important role in RA pathogenesis and might act as potential biomarker for RA. Additionally, these genes might play important roles in RA pathogenesis, as well as facilitate the development of effective targeted therapies. Our integrative data analysis and network-based methods could accelerate the identification of novel drug targets for RA from high-throughput genomic data. [ABSTRACT FROM AUTHOR]

Obesity is connected to the activation of chronic inflammatory pathways in both adipocytes and macrophages located in adipose tissues. The nuclear factor (NF)-κB is a central molecule involved in inflammatory pathways linked to the pathology of different complex metabolic disorders. Investigating the gene expression data in the adipose tissue would potentially unravel disease relevant gene interactions. The present study is aimed at creating a signature molecular network and at prioritizing the potential biomarkers interacting with NF-κB family of proteins in obesity using system biology approaches. The dataset GSE88837 associated with obesity was downloaded from Gene Expression Omnibus (GEO) database. Statistical analysis represented the differential expression of a total of 2650 genes in adipose tissues (p = <0.05). Using concepts like correlation, semantic similarity, and theoretical graph parameters we narrowed down genes to a network of 23 genes strongly connected with NF-κB family with higher significance. Functional enrichment analysis revealed 21 of 23 target genes of NF-κB were found to have a critical role in the pathophysiology of obesity. Interestingly, GEM and PPP1R13L were predicted as novel genes which may act as potential target or biomarkers of obesity as they occur with other 21 target genes with known obesity relationship. Our study concludes that NF-κB and prioritized target genes regulate the inflammation in adipose tissues through several molecular signaling pathways like NF-κB, PI3K-Akt, glucocorticoid receptor regulatory network, angiogenesis and cytokine pathways. This integrated system biology approaches can be applied for elucidating functional protein interaction networks of NF-κB protein family in different complex diseases. Our integrative and network-based approach for finding therapeutic targets in genomic data could accelerate the identification of novel drug targets for obesity. [ABSTRACT FROM AUTHOR]

Celiac disease (CD), a multi-factorial auto-inflammatory disease of the small intestine, is known to occur in both sporadic and familial forms. Together HLA and Non-HLA genes can explain up to 50% of CD’s heritability. In order to discover the missing heritability due to rare variants, we have exome sequenced a consanguineous Saudi family presenting CD in an autosomal recessive (AR) pattern. We have identified a rare homozygous insertion c.1683_1684insATT, in the conserved coding region of AK5 gene that showed classical AR model segregation in this family. Sequence validation of 200 chromosomes each of sporadic CD cases and controls, revealed that this extremely rare (EXac MAF 0.000008) mutation is highly penetrant among general Saudi populations (MAF is 0.62). Genotype and allelic distribution analysis have indicated that this AK5 (c.1683_1684insATT) mutation is negatively selected among patient groups and positively selected in the control group, in whom it may modify the risk against CD development [p<0.002]. Our observation gains additional support from computational analysis which predicted that Iso561 insertion shifts the existing H-bonds between 400th and 556th amino acid residues lying near the functional domain of adenylate kinase. This shuffling of amino acids and their H-bond interactions is likely to disturb the secondary structure orientation of the polypeptide and induces the gain-of-function in nucleoside phosphate kinase activity of AK5, which may eventually down-regulates the reactivity potential of CD4+ T-cells against gluten antigens. Our study underlines the need to have population-specific genome databases to avoid false leads and to identify true candidate causal genes for the familial form of celiac disease. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) for many complex diseases, including inflammatory bowel disease (IBD), produced hundreds of disease-associated loci—the majority of which are noncoding. The number of GWAS loci is increasing very rapidly, but the process of translating single nucleotide polymorphisms (SNPs) from these loci to genomic medicine is lagging. In this study, we investigated 4,734 variants from 152 IBD associated GWAS loci (IBD associated 152 lead noncoding SNPs identified from pooled GWAS results + 4,582 variants in strong linkage-disequilibrium (LD) (r2 ≥0.8) for EUR population of 1K Genomes Project) using four publicly available bioinformatics tools, e.g. dbPSHP, CADD, GWAVA, and RegulomeDB, to annotate and prioritize putative regulatory variants. Of the 152 lead noncoding SNPs, around 11% are under strong negative selection (GERP++ RS ≥2); and ~30% are under balancing selection (Tajima’s D score >2) in CEU population (1K Genomes Project)—though these regions are positively selected (GERP++ RS <0) in mammalian evolution. The analysis of 4,734 variants using three integrative annotation tools produced 929 putative functional SNPs, of which 18 SNPs (from 15 GWAS loci) are in concordance with all three classifiers. These prioritized noncoding SNPs may contribute to IBD pathogenesis by dysregulating the expression of nearby genes. This study showed the usefulness of integrative annotation for prioritizing fewer functional variants from a large number of GWAS markers. [ABSTRACT FROM AUTHOR]

Mutations in the leucine-rich repeat kinase-2 gene (LRRK2) are responsible for some forms of familial as well as sporadic Parkinson's disease (PD). The purpose of this study was to examine the frequency of a single pathogenic mutation (6055G > A) in the kinase domain of this gene in United States and Tunisian familial PD and to compare clinical characteristics between patients with and without the mutation. Standardized case report forms were used for clinical and demographic data collection. We investigated the frequency of the most common substitution of LRRK2 (G2019S, 6055G>A) and its impact on epidemiological and phenotypic features. The frequency of mutations in Tunisian families was 42% (38/91) and in U.S. families 2.6% (1/39), with the unique opportunity to compare homozygous (n = 23) and heterozygous (n = 109) Tunisian carriers of G2019S substitutions. Individuals with G2019S substitutions had an older age at onset but few other differences compared with families negative for the substitution. Patients with LRRK2 mutations had typical clinical features of PD. Comparisons between individuals with heterozygous and homozygous LRRK2 mutations suggested that gene dosage was not correlated with phenotypic differences; however, the estimated penetrance was greater in homozygotes across all age groups. [ABSTRACT FROM AUTHOR]

Celiac disease (CD), a gluten intolerance disorder, was implicated to have 57 genetic susceptibility loci for Europeans but not for culturally and geographically distinct ethnic populations like Saudi Arabian CD patients. Therefore, we genotyped Saudi CD patients and healthy controls for three polymorphisms, that is, Phe196Ser in IRAK1, Trp262Arg in SH2B3, and Met518Thr in MMEL1 genes. Single locus analysis identified that carriers of the 518 Thr/Thr (MMEL1) genotype conferred a 1.6-fold increased disease risk compared to the noncarriers (OR = 2.6; 95% CI: 1.22–5.54; P<0.01). This significance persisted even under allelic (OR = 1.55; 95% CI: 1.05–2.28; P=0.02) and additive (OR = 0.35; 95% CI: 0.17–0.71; P=0.03) genetic models. However, frequencies for Trp262Arg (SH2B3) and Phe196Ser (IRAK1) polymorphisms were not significantly different between patients and controls. The overall best MDR model included Met518Thr and Trp262Arg polymorphisms, with a maximal testing accuracy of 64.1% and a maximal cross-validation consistency of 10 out of 10 (P=0.0156). Allelic distribution of the 518 Thr/Thr polymorphism in MMEL1 primarily suggests its independent and synergistic contribution towards CD susceptibility among Saudi patients. Lack of significant association of IRAK and SH2B3 gene polymorphisms in Saudi patients but their association in European groups suggests the genetic heterogeneity of CD. [ABSTRACT FROM AUTHOR]

Background: Several genes have been implicated in the pathogenesis of Parkinson's disease (PD). The aim of this study was to define the clinical symptoms and age-associated cumulative incidence of the most frequent mutation associated with PD, LRRK2 Gly2019Ser. Methods: 238 patients with sporadic PD and 371 unrelated control participants from the Arab-Berber population were screened at the Institut National de Neurologie, Tunis. Symptoms of PD were assessed using the Hoehn and Yahr scale, the unified Parkinson's disease rating scale, and the Epworth scale. Genotyping for LRRK2 6055G-->A, which causes the Gly2019Ser mutation, was done in all participants, and the age-specific cumulative incidence of PD was calculated by Kaplan-Meier analysis. Findings: 30% of patients with PD in this case-control sample were carriers of LRRK2 Gly2019Ser. The age of onset of symptoms and the clinical presentation of patients with LRRK2 Gly2019Ser were similar to those of patients with idiopathic PD. Carriers of LRRK2 Gly2019Ser were 22.6 times (95% CI 10.2-50.1) more likely to be affected by PD than non-carriers. Tremor was the predominant symptom in LRRK2 Gly2019Ser carriers (92% [homozygotes] vs 75% [heterozygotes] vs 69% [non-carriers]; Cochran-Armitage trend test p=0.0587). Disease severity, response to treatment, and disease duration were similar among LRRK2 Gly2019Ser homozygotes, heterozygotes, and non-carriers (p=0.85). Disease penetrance in LRRK2 Gly2019Ser carriers ranged from less than 20% in those younger than 50 years to greater than 80% at 70 years. Interpretation: The LRRK2 Gly2019Ser mutation in patients with PD is a useful aid to diagnosis. LRRK2 Gly2019Ser penetrance can vary but in most carriers PD seems an inevitable consequence of ageing. LRRK2 Gly2019Ser considerably increases susceptibility to neuronal degeneration, although the process might be mediated by many triggers. By contrast, idiopathic PD is rare before 50 years and the prevalence only increases to 4% in the oldest members of the population. Funding: GlaxoSmithKline; National Institutes of Health; and Mayo Foundation. [ABSTRACT FROM AUTHOR]