title: Phylogenetic and physicochemical analyses enhance the classification of rare nonsynonymous single nucleotide variants in type 1 and 2 long-QT syndrome.
abstract: BACKGROUND
  Hundreds of nonsynonymous single nucleotide variants (nsSNVs) have been identified in the 2 most common long-QT syndrome-susceptibility genes (KCNQ1 and KCNH2). Unfortunately, an ≈3%
  
  
  BACKGROUND
  and KCNH2 nsSNVs amongst healthy individuals complicates the ability to distinguish rare pathogenic mutations from similarly rare yet presumably innocuous variants.
  
  
  RESULTS
  In this study, 4 tools [(1) conservation across species, (2) Grantham values, (3) sorting intolerant from tolerant, and (4) polymorphism phenotyping] were used to predict pathogenic or benign status for nsSNVs identified across 388 clinically definite long-QT syndrome cases and 1344 ostensibly healthy controls. From these data, estimated predictive values were determined for each tool independently, in concert with previously published protein topology-derived estimated predictive values, and synergistically when ≥3 tools were in agreement. Overall, all 4 tools displayed a statistically significant ability to distinguish between case-derived and control-derived nsSNVs in KCNQ1, whereas each tool, except Grantham values, displayed a similar ability to differentiate KCNH2 nsSNVs. Collectively, when at least 3 of the 4 tools agreed on the pathogenic status of C-terminal nsSNVs located outside the KCNH2/Kv11.1 cyclic nucleotide-binding domain, the topology-specific estimated predictive value improved from 56% to 91%.
  
  
  CONCLUSIONS
  Although in silico prediction tools should not be used to predict independently the pathogenicity of a novel, rare nSNV, our results support the potential clinical use of the synergistic utility of these tools to enhance the classification of nsSNVs, particularly for Kv11.1's difficult to interpret C-terminal region.
authors.affiliation: Department of Medicine/Division of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
authors.forename: John R
authors.initials: JR
authors.lastname: Giudicessi
authors.forename: Jamie D
authors.initials: JD
authors.lastname: Kapplinger
authors.forename: David J
authors.initials: DJ
authors.lastname: Tester
authors.forename: Marielle
authors.initials: M
authors.lastname: Alders
authors.forename: Benjamin A
authors.initials: BA
authors.lastname: Salisbury
authors.forename: Arthur A M
authors.initials: AA
authors.lastname: Wilde
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Ackerman
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D019295:Computational Biology; D000072237:ERG1 Potassium Channel; D051638:Ether-A-Go-Go Potassium Channels / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D006801:Humans; D051657:KCNQ1 Potassium Channel / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D008133:Long QT Syndrome / Q000145:classification / Q000235:genetics* / Q000473:pathology; D010641:Phenotype; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide; D017434:Protein Structure, Tertiary; D029597:Romano-Ward Syndrome / Q000145:classification / Q000235:genetics* / Q000473:pathology
chemical_list: D000072237:ERG1 Potassium Channel; D051638:Ether-A-Go-Go Potassium Channels; C000606913:KCNH2 protein, human; D051657:KCNQ1 Potassium Channel