Specifications of the ACMG/AMP standards and guidelines for mitochondrial DNA variant interpretation.

Mitochondrial DNA (mtDNA) variant pathogenicity interpretation has special considerations given unique features of the mtDNA genome, including maternal inheritance, variant heteroplasmy, threshold effect, absence of splicing, and contextual effects of haplogroups. Currently, there are insufficient standardized criteria for mtDNA variant assessment, which leads to inconsistencies in clinical variant pathogenicity reporting. An international working group of mtDNA experts was assembled within the Mitochondrial Disease Sequence Data Resource Consortium and obtained Expert Panel status from ClinGen. This group reviewed the 2015 American College of Medical Genetics and Association of Molecular Pathology standards and guidelines that are widely used for clinical interpretation of DNA sequence variants and provided further specifications for additional and specific guidance related to mtDNA variant classification. These Expert Panel consensus specifications allow for consistent consideration of the unique aspects of the mtDNA genome that directly influence variant assessment, including addressing mtDNA genome composition and structure, haplogroups and phylogeny, maternal inheritance, heteroplasmy, and functional analyses unique to mtDNA, as well as specifications for utilization of mtDNA genomic databases and computational algorithms.

A data and text mining pipeline to annotate human mitochondrial variants with functional and clinical information.

BACKGROUND: Human mitochondrial DNA has an important role in the cellular energy production through oxidative phosphorylation. Therefore, this process may be the cause and have an effect on mitochondrial DNA mutability, functional alteration, and disease onset related to a wide range of different clinical expressions and phenotypes. Although a large part of the observed variations is fixed in a population and hence expected to be benign, the estimation of the degree of the pathogenicity of any possible human mitochondrial DNA variant is clinically pivotal. METHODS: In this scenario, the establishment of standard criteria based on functional studies is required. In this context, a "data and text mining" pipeline is proposed here, developed using the programming language R, capable of extracting information regarding mitochondrial DNA functional studies and related clinical assessments from the literature, thus improving the annotation of human mitochondrial variants reported in the HmtVar database. RESULTS: The data mining pipeline has produced a list of 1,073 Pubmed IDs (PMIDs) from which the text mining pipeline has retrieved information on 932 human mitochondrial variants regarding experimental validation and clinical features. CONCLUSIONS: The application of the pipeline will contribute to supporting the interpretation of pathogenicity of human mitochondrial variants by facilitating diagnosis to clinicians and researchers faced with this task.

HmtVar: a new resource for human mitochondrial variations and pathogenicity data.

Interest in human mitochondrial genetic data is constantly increasing among both clinicians and researchers, due to the involvement of mitochondrial DNA (mtDNA) in a number of physiological and pathological processes. Thanks to new sequencing technologies and modern databases, the large amount of information on mtDNA variability may be exploited to gain insights into the relationship between mtDNA variants, phenotypes and diseases. To facilitate this process, we have developed the HmtVar resource, a variant-focused database that allows the exploration of a dataset of over 40 000 human mitochondrial variants. Mitochondrial variation data, initially gathered from the HmtDB platform, are integrated with in-house pathogenicity assessments based on various evaluation criteria and with a set of additional annotations from third-party resources. The result is a comprehensive collection of information of crucial importance for human mitochondrial variation studies and investigation of common and rare diseases in which the mitochondrion may be involved. HmtVar is accessible at https://www.hmtvar.uniba.it and data may be retrieved using either a web interface through the Query page or a state-of-the-art API for programmatic access.