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      Mitochondrial variants of complex I genes associated with leprosy clinical subtypes

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          Abstract

          Leprosy is a chronic bacterial infection mainly caused by Mycobacterium leprae that primarily affects skin and peripheral nerves. Due to its ability to absorb carbon from the host cell, the bacillus became dependent on energy production, mainly through oxidative phosphorylation. In fact, variations in genes of Complex I of oxidative phosphorylation encoded by mtDNA have been associated with several diseases in humans, including bacterial infections, which are possible influencers in the host response to leprosy. Here, we investigated the presence of variants in the mtDNA genes encoding Complex I regarding leprosy, as well as the analysis of their pathogenicity in the studied cohort. We found an association of 74 mitochondrial variants with either of the polar forms, Pole T (Borderline Tuberculoid) or Pole L (Borderline Lepromatous and Lepromatous) of leprosy. Notably, six variants were exclusively found in both clinical poles of leprosy, including m.4158A>G and m.4248T>C in MT-ND1, m.13650C>A, m.13674T>C, m.12705C>T and m.13263A>G in MT-ND5, of which there are no previous reports in the global literature. Our observations reveal a substantial number of mutations among different groups of leprosy, highlighting a diverse range of consequences associated with mutations in genes across these groups. Furthermore, we suggest that the six specific variants exclusively identified in the case group could potentially play a crucial role in leprosy susceptibility and its clinical differentiation. These variants are believed to contribute to the instability and dysregulation of oxidative phosphorylation during the infection, further emphasizing their significance.

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          Most cited references42

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            ClinVar: improving access to variant interpretations and supporting evidence

            Abstract ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant (‘provider interpretation’) or from groups such as patient registries that primarily provide phenotypic information from patients (‘phenotyping only’). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.
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              UpSet: Visualization of Intersecting Sets.

              Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains.
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                Author and article information

                Contributors
                giovannaccavalcante@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                16 March 2024
                16 March 2024
                2024
                : 14
                : 6365
                Affiliations
                [1 ]Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, ( https://ror.org/03q9sr818) Belém, PA 66075-110 Brazil
                [2 ]Laboratório de Dermato-Imunologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, ( https://ror.org/03q9sr818) Marituba, PA 67105-290 Brazil
                Article
                57191
                10.1038/s41598-024-57191-y
                10944465
                38493220
                75f0fe86-2f9c-4fa3-9c21-dd8311569d25
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 31 October 2023
                : 15 March 2024
                Funding
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
                Award ID: 3381/2013
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                leprosy,mitochondria,mtdna,complex i,heteroplasmy,medical genomics,infectious diseases
                Uncategorized
                leprosy, mitochondria, mtdna, complex i, heteroplasmy, medical genomics, infectious diseases

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