MtSNPscore: a combined evidence approach for assessing cumulative impact of mitochondrial variations in disease

Bhardwaj, Anshu; Mukerji, Mitali; Sharma, Shipra; Paul, Jinny; Gokhale, Chaitanya S.; Srivastava, Achal K.; Tiwari, Shrish

doi:10.1186/1471-2105-10-s8-s7

Cited by 22 publications

(19 citation statements)

References 36 publications

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“…Disease mutations caused by defects in the mitochondrial proteins also show a similar pattern ( Fig. 4C; see also Bhardwaj et al 2009;Montoya et al 2009). Somatic cell mutations implicated as having a causal role in the pathogenesis of cancer (i.e., driver mutations) exhibit a trend similar to Mendelian disease variants ( Fig.…”

Section: Evolutionary Distributions Of Disease-associated Variantsmentioning

confidence: 56%

Human genomic disease variants: A neutral evolutionary explanation

Dudley¹,

Kim²,

Liu³

et al. 2012

Genome Res.

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Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease.

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Section: Evolutionary Distributions Of Disease-associated Variantsmentioning

confidence: 56%

Human genomic disease variants: A neutral evolutionary explanation

Dudley¹,

Kim²,

Liu³

et al. 2012

Genome Res.

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“…Driver mutations contribute to cancer progression and have a tendency to be found in many independent samples as compared to passenger mutations that, as the name suggests, hitchhike causing the cells with driver mutations to increase in number by the processes of natural selection and adaptation [39, 40, 88–90]. For mitochondrial DNA (mtDNA), four different tools (including PolyPhen and SIFT) have been combined along with the biochemical features and frequency of variants to evaluate mitochondrial nSNVs [91]. This approach was adopted because only 5% of disease-associated nSNVs in mtDNA were found to be harmful by all four in silico methods, even though each of these SNVs was predicted to be damaging by at least one method [91].…”

Section: Evolutionary Diagnosis Of Function-altering Mutations In Silicomentioning

confidence: 99%

“…For mitochondrial DNA (mtDNA), four different tools (including PolyPhen and SIFT) have been combined along with the biochemical features and frequency of variants to evaluate mitochondrial nSNVs [91]. This approach was adopted because only 5% of disease-associated nSNVs in mtDNA were found to be harmful by all four in silico methods, even though each of these SNVs was predicted to be damaging by at least one method [91]. …”

Section: Evolutionary Diagnosis Of Function-altering Mutations In Silicomentioning

confidence: 99%

Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations

et al. 2011

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Modern technologies have made the sequencing of personal genomes routine. They have revealed thousands of nonsynonymous (amino-acid altering) single nucleotide variants (nSNVs) of protein coding DNA per genome. What do these variants foretell about an individual’s predisposition to diseases? The experimental technologies required to carry out such evaluations at a genomic scale are not yet available. Fortunately, the process of natural selection has lent us an almost infinite set of tests in nature. During the long-term evolution, new mutations and existing variations have been evaluated for their biological consequences in countless species, and outcomes were readily revealed by multispecies genome comparisons. We review studies that have investigated evolutionary characteristics and in silico functional diagnoses of nSNVs found in thousands of disease-associated genes. We conclude that the patterns of long-term evolutionary conservation and permissible divergence are essential and instructive modalities for functional assessment of human genetic variations.

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“…LOVD is a commonly used tool for organizing locus-centric variation data. As of now, MitoLSDB has patient and variant information from 5231 individuals from 675 different populations [24], [28] from 27 different groups including patients with Alzheimer’s disease, Asthanozoospermic, Atypical psychosis, Breast cancer, Diabetes, Angiopathy, Deafness, Glioma, Parkinson’s disease, Teratozoospermic, Thyroid cancer, etc and can be accessed at http://mitolsdb.igib.res.in. MitoLSDB is a Locus-Specific DataBase (LSDB) for human mtDNA genes and provides access to standardized and annotated data compiled from different resources which are otherwise difficult to search and comprehend.…”

Section: Introductionmentioning

confidence: 99%

MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

et al. 2013

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Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.

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MtSNPscore: a combined evidence approach for assessing cumulative impact of mitochondrial variations in disease

Cited by 22 publications

References 36 publications

Human genomic disease variants: A neutral evolutionary explanation

Human genomic disease variants: A neutral evolutionary explanation

Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations

MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

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