Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker

Wildeman, M.H.; Ophuizen, Ernest van; Dunnen, Johan T. den; Taschner, Peter E.M.

doi:10.1002/humu.20654

Cited by 381 publications

(322 citation statements)

References 14 publications

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“…21 First, the variants found in the literature were checked in the Leiden Open Variation Database, and the genomic positions were obtained using Mutalyzer. 20,22 Then the variants were annotated using ANNOVAR with the following databases: hg19, RefSeq with HGVS as the nomenclature type, 1000 Genomes 2012APR, NonFlagged dbSNP138, CLINVAR20140211, and COSMIC68. [23][24][25] 1000 Genomes 2012APR and NonFlagged dbSNP138, describing only single-nucleotide polymorphisms with a frequency lower than 1%, were used to determine whether the changes were reported as single-nucleotide polymorphisms.…”

Section: Review Materials and Methodsmentioning

confidence: 99%

Toward an improved definition of the genetic and tumor spectrum associated with SDH germ-line mutations

Evenepoel

Papathomas

Krol

et al. 2015

Genetics in Medicine

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The tricarboxylic acid (TCA) cycle enzyme succinate dehydrogenase (SDH) is a heterotetramer protein complex consisting of four subunits encoded by nuclear genes. These include SDHA and SDHB, which form the catalytic domain, and SDHC and SDHD, which anchor the complex to the inner mitochondrial membrane. 1 The assembly factors, SDHAF1 and SDHAF2, ensure both structural and functional integrity of the complex. 2,3 SDH, also called mitochondrial complex II, is the only enzyme involved in both the electron transport chain and the TCA cycle, where it catalyzes the oxidation of succinate to fumarate. 1 The TCA cycle is central to the metabolism of sugars, lipids, and amino acids and is a major source of adenosine triphosphate in cells. In addition, the cycle also seems to be involved in tumorigenesis; enzymes of the TCA cycle are involved in the pathogenesis of several tumor types. SDH mutations have been involved in the etiopathogeny of pheochromocytomas (PCCs), paragangliomas (PGLs), gastrointestinal stromal tumors (GISTs), renal-cell carcinomas (RCCs), and pituitary adenomas (PAs). 1,2,[4][5][6][7][8][9] In addition, mutations in fumarate hydratase (FH), another member of the TCA cycle and which catalyzes the hydration of fumarate to malate, predispose to tumor formation, including RCCs, cutaneous and uterine leiomyomas, and PCCs/PGLs. 10,11 Finally, isocitrate dehydrogenase (IDH), which catalyzes the oxidative decarboxylation of isocitrate, is frequently mutated in specific types of cartilaginous tumors, hematological malignancies, and gliomas. 12-14 The currently known mechanisms underlying tumorigenesis linked to defects in the TCA cycle are well reviewed. 15,16 Defects in the SDH, FH, and IDH genes inhibit prolyl hydroxylases, leading to decreased hydroxylation of hypoxia-inducible factor-α. This results in activation of the hypoxia pathway, which supports tumor formation by activating angiogenesis, glucose metabolism, cell motility, and cell survival. Furthermore, defects in these enzymes lead to epigenetic alterations through an accumulation of oncometabolites inhibiting α-ketoglutarate-dependent dioxygenases, which are involved in DNA and histone demethylation. In addition to SDH-associated tumorigenesis, constitutional complex II deficiencies caused by SDHA, SDHB, SDHD, and SDHAF1 mutations may also lead to Leigh syndrome, infantile leukodystrophies, and cardiomyopathy. 3,[17][18][19] In the current review, our aim is to report all currently known SDH mutations and define their nature and spectrum in SDHrelated tumors, including PCCs/PGLs, GISTs, RCCs, and PAs, as well as in other unusual tumors arising in SDH mutation carriers. We performed bioinformatics analysis using SIFT, Polyphen2, and Mutation Assessor and compared the results with those of SDHA/SDHB immunohistochemistry (IHC) to predict the functional impact of nonsynonymous mutations. Finally, we explored and report here the nature of the second hit in all tumors arising in the SDH deficiency setting. The tricarboxylic acid, or Krebs, cycle is cent...

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Section: Review Materials and Methodsmentioning

confidence: 99%

Toward an improved definition of the genetic and tumor spectrum associated with SDH germ-line mutations

Evenepoel

Papathomas

Krol

et al. 2015

Genetics in Medicine

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“…Seven variants had conflicting phenotype information and were excluded from APV analysis (see below). All variants were checked with Mutalyzer 2.0.beta-27 (https://mutalyzer.nl/check) 28 and PAH genomic sequence. 29 The reference accession number for the PAH sequence is ENSG00000171759; RefSeq NM_000277.1.…”

Section: Materials and Methods Databasesmentioning

confidence: 99%

Linking genotypes database with locus-specific database and genotype–phenotype correlation in phenylketonuria

et al. 2014

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The wide range of metabolic phenotypes in phenylketonuria is due to a large number of variants causing variable impairment in phenylalanine hydroxylase function. A total of 834 phenylalanine hydroxylase gene variants from the locus-specific database PAHvdb and genotypes of 4181 phenylketonuria patients from the BIOPKU database were characterized using FoldX, SIFT Blink, Polyphen-2 and SNPs3D algorithms. Obtained data was correlated with residual enzyme activity, patients' phenotype and tetrahydrobiopterin responsiveness. A descriptive analysis of both databases was compiled and an interactive viewer in PAHvdb database was implemented for structure visualization of missense variants. We found a quantitative relationship between phenylalanine hydroxylase protein stability and enzyme activity (r s ¼ 0.479), between protein stability and allelic phenotype (r s ¼ À0.458), as well as between enzyme activity and allelic phenotype (r s ¼ 0.799). Enzyme stability algorithms (FoldX and SNPs3D), allelic phenotype and enzyme activity were most powerful to predict patients' phenotype and tetrahydrobiopterin response. Phenotype prediction was most accurate in deleterious genotypes (E100%), followed by homozygous (92.9%), hemizygous (94.8%), and compound heterozygous genotypes (77.9%), while tetrahydrobiopterin response was correctly predicted in 71.0% of all cases. To our knowledge this is the largest study using algorithms for the prediction of patients' phenotype and tetrahydrobiopterin responsiveness in phenylketonuria patients, using data from the locus-specific and genotypes database.

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“…12 Genetic diseases registered in the database have been classified using the World Health Organization (WHO) International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) Version 2010 (http://apps.who.int/classifications/icd10/browse/2010/en).…”

Section: Methodsmentioning

confidence: 99%

The Moroccan Genetic Disease Database (MGDD): a database for DNA variations related to inherited disorders and disease susceptibility

et al. 2013

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National and ethnic mutation databases provide comprehensive information about genetic variations reported in a population or an ethnic group. In this paper, we present the Moroccan Genetic Disease Database (MGDD), a catalogue of genetic data related to diseases identified in the Moroccan population. We used the PubMed, Web of Science and Google Scholar databases to identify available articles published until April 2013. The Database is designed and implemented on a three-tier model using Mysql relational database and the PHP programming language. To date, the database contains 425 mutations and 208 polymorphisms found in 301 genes and 259 diseases. Most Mendelian diseases in the Moroccan population follow autosomal recessive mode of inheritance (74.17%) and affect endocrine, nutritional and metabolic physiology. The MGDD database provides reference information for researchers, clinicians and health professionals through a user-friendly Web interface. Its content should be useful to improve researches in human molecular genetics, disease diagnoses and design of association studies. MGDD can be publicly accessed at

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Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker

Cited by 381 publications

References 14 publications

Toward an improved definition of the genetic and tumor spectrum associated with SDH germ-line mutations

Toward an improved definition of the genetic and tumor spectrum associated with SDH germ-line mutations

Linking genotypes database with locus-specific database and genotype–phenotype correlation in phenylketonuria

The Moroccan Genetic Disease Database (MGDD): a database for DNA variations related to inherited disorders and disease susceptibility

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