The Arab population encompasses over 420 million people characterized by genetic admixture and a consequent rich genetic diversity. A number of genetic diseases have been reported for the first time from the population. Additionally a high prevalence of some genetic diseases including autosomal recessive disorders such as hemoglobinopathies and familial mediterranean fever have been found in the population and across the region. There is a paucity of databases cataloguing genetic variants of clinical relevance from the population. The availability of such a catalog could have implications in precise diagnosis, genetic epidemiology and prevention of disease. To fill in the gap, we have compiled DALIA, a comprehensive compendium of genetic variants reported in literature and implicated in genetic diseases reported from the Arab population. The database aims to act as an effective resource for population-scale and sub-population specific variant analyses, enabling a ready reference aiding clinical interpretation of genetic variants, genetic epidemiology, as well as facilitating rapid screening and a quick reference for evaluating evidence on genetic diseases.
The steady increase in global cancer burden has fuelled the development of several modes of treatment for the disease. In the presence of an actionable mutation, targeted therapies offer a method to selectively attack cancer cells, increasing overall efficacy and reducing harmful side effects. However, different drug molecules are in different stages of development, with new molecules obtaining approvals from regulatory agencies each year. To augment clinical impact, it is important that this information reaches clinicians, patients and researchers swiftly and in a structured, well-annotated manner. To this end, we have developed Mutation-Specific Therapies Resource and Database in Cancer (MUSTARD), a database that is designed to be a centralized resource with diverse information such as cancer subtype, associated mutations, therapy offered and its effect observed, along with links to external resources for a more comprehensive annotation. In its current version, MUSTARD comprises over 2105 unique entries, including associations between 418 unique drug therapies, 189 cancer subtypes and 167 genes curated and annotated from over 862 different publications. To the best of our knowledge, it is the only resource that offers comprehensive information on mutation-specific, gene fusions and overexpressed gene-targeted therapies for cancer. Database URL: http://clingen.igib.res.in/mustard/
Genetic variants in human platelet antigens (HPAs) considered allo‐ or auto antigens are associated with various disorders, including neonatal alloimmune thrombocytopenia, platelet transfusion refractoriness and post‐transfusion purpura. Although global differences in genotype frequencies were observed, the distributions of HPA variants in the Indian population are largely unknown. This study aims to explore the landscape of HPA variants in India to provide a basis for risk assessment and management of related complications. Population‐specific frequencies of genetic variants associated with the 35 classes of HPAs (HPA‐1 to HPA‐35) were estimated by systematically analysing genomic variations of 1029 healthy Indian individuals as well as from global population genome datasets. Allele frequencies of the most clinically relevant HPA systems in the Indian population were found as follows, HPA‐1a – 0.884, HPA‐1b – 0.117, HPA‐2a – 0.941, HPA‐2b – 0.059, HPA‐3a – 0.653, HPA‐3b – 0.347, HPA‐4a – 0.999, HPA‐4b – 0.0010, HPA‐5a – 0.923, HPA‐5b – 0.077, HPA‐6a – 0.998, HPA‐6b – 0.002, HPA‐15a – 0.582 and HPA‐15b – 0.418. This study provides the first comprehensive analysis of HPA allele and genotype frequencies using large scale representative whole genome sequencing data of the Indian population.
Background and Objective The rapid rate at which the current mpox virus outbreak has spread across the globe has led the World Health Organization to declare it a Public Health Emergency of International Concern. Polymerase chain reaction-based methods are one of the cornerstones for effective molecular detection of viruses including mpox virus. Genetic variants in primer binding sites are known to impact the efficiency of polymerase chain reaction and therefore diagnosis. Here we have analyzed the genetic variants and their impact on efficient binding of oligonucleotides used in diagnostics. Methods In this study, we have systematically collected primers and probes used in the detection of mpox virus from published literature and public resources, and assessed the impact of primer binding region genetic variants in the detection of mpox virus by analysing the thermodynamic parameters, Gibbs free energy and melting temperature. These were calculated using the nearest neighbour method for variants in mpox virus genomes available and the deviation in parameters was computed with respect to the reference genome sequence. Results We have identified 170 genetic variations that fall within the oligo binding region in 1176 mpox virus genomes out of which five oligos showed at least a 2 °C decrease in melting temperature, which could potentially affect the diagnostic efficacy. Conclusions Our analysis shows the importance of continuous monitoring of mpox virus detection primer efficacy and provides the list of oligos with potentially reduced detection efficiency in the current mpox virus outbreak. Supplementary Information The online version contains supplementary material available at 10.1007/s40291-022-00629-8.
Background: Colorectal cancer is a heterogeneous disease of tumors from distinct anatomical and embryological sources. According to GLOBOCAN2020, it is the second leading cause of cancer-related mortality1. Methodology: Utilising NIH-GDC2 datasets, we applied Bioinformatic algorithms to categorize LCRC and RCRC based on multi-omic variables. Mutational analysis was done using STRING v11.53. Kaplan-Meier were plotted. Transcriptome data was accessed using Bioconductor4 package TCGABiolinks5 and annotated as ‘Left’ or ‘Right’ based on tissue of origin. DE analysis was performed using DESeq6. DEGs were analyzed using Enrichr7 for signaling pathways. Further, differential methylation analysis was performed. Results: Tumors from left and right sides represent early Stage IIA non-metastatic cancers largely. Mutational analysis showed dissimilar genes in left vs right-sided tumors. CSMD1, CDH23, PCDH15, DSCAM, CDH9, and NRXN1 formed unique hubs within LCRC network while FLNC, CACNA1H, KMT2B, KMT2D, FAT4 and BRAF formed hubs in RCRC network. LCRC-specific genes were cadherins and EMT based, while RCRC-specific genes were related to lymphocytic invasion and epigenetic markers. TTN (p-value=4.61e-2) and ABCA13 (p-value=4.78e-2) significantly influenced OS in LCRC while SOX11 (p-value=4.12e-2) influenced OS in RCRC. For transcriptomic analysis, we obtained 766 DE genes at p-adjusted value <= 0.01, |log2 FC| > 1. Enrichr KEGG pathway analysis highlighted neuroactive ligand-receptor interaction (OR=3.11) and complement-coagulation cascade (OR=6.07) activity in LCRC. Platelet interaction with cancer cells have been demonstrated8 to have therapeutic potential in CRCs. NK cell mediated cytotoxicity (OR=4.33) and antigen processing-presentation (OR=6.95) were enriched in RCRC. Mean methylation analysis showed higher values in RCRC than LCRC (p-value=1.5e-05). Differential methylation gave 998 hypo- and 45 hyper-methylated genes in RCRC and LCRC respectively. RCRC evidently has an underlying hypermethylated biology when compared to LCRC. RCRCs are dependent on immune-regulated biology explaining rationale of immunotherapy. Right colon develops from midgut and is supplied by SMA. It can be hypothesized that a vast lymphatic drainage system carrying increased T-cells may play a role in creating dissimilarity. On the other hand, angiogenic factors and coagulation cascade rule left colon. This could be the reason for early metastatic potential in LCRCs. Our study unambiguously differentiates LCRC from RCRC by correlating anatomical, physiological, and multi-omic variables. Citation Format: Anu R I, Aastha Vatsyayan, Ambily Sivadas, Dileep Damodaran, Kurt van der Speeten. Multi-omic analysis classifies colorectal cancer into distinct angiogenic and immunogenic subtypes based on anatomical laterality [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1154.
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