The proportion of mutations predicted to have a deleterious effect differs between gain and loss of function genes in neurodegenerative disease.
As more studies are turning to bioinformatic prediction programs to assess the potential impact of amino acid substitutions, it is relevant to evaluate the prediction results these programs give in genes that have been well-characterized for Mendelian diseases. Eight genes responsible for neurodegenerative disease with many identified mutations were sub-grouped into those that either have a gain or loss of function disease mechanism. Three prediction programs, PolyPhen, Panther and SIFT, were queried for the reported missense mutations. The mean percent of benign mutations was significantly higher in gain of function genes using the PolyPhen program (38% versus 21%, p=0.007). The probability that a gain of function mutation was predicted to have a damaging role was also significantly less using the Panther program (p=4.86x10(-12)). In contrast, there was no difference between gain and loss of function gene when the SIFT program was used. However, the most accurate distinction between gain and loss of function genes could be obtained when considering the mutations for which all three programs predicted the same result. Further, stratification of SOD1 mutations indicated that only the PolyPhen program could distinguish mutations that impaired enzymatic activity of SOD1 from those with near wildtype activity. The profile of benign and damaging changes from these genes will aid in the interpretation of bioinformatic prediction program results from missense mutations identified in novel genes.
Valdmanis
Paul N
PN
Center of Excellence in Neuromics of Université de Montréal, CHUM Research Center and the Department of Medicine, University of Montreal.
Verlaan
Dominique J
DJ
Rouleau
Guy A
GA
D000251:Adenosine Triphosphatases / Q000235:genetics / Q000378:metabolism; D019943:Amino Acid Substitution; D016564:Amyloid beta-Protein Precursor / Q000235:genetics / Q000502:physiology; D019295:Computational Biology / Q000379:methods*; D020558:GTP Phosphohydrolases / Q000235:genetics / Q000378:metabolism; D019204:GTP-Binding Proteins; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D008565:Membrane Proteins; D009154:Mutation; D019636:Neurodegenerative Diseases / Q000235:genetics* / Q000378:metabolism / Q000503:physiopathology; D053764:Presenilin-1 / Q000235:genetics / Q000502:physiology; D012984:Software; D000074181:Spastin; D013482:Superoxide Dismutase / Q000235:genetics / Q000378:metabolism; D000072105:Superoxide Dismutase-1; D055533:Survival of Motor Neuron 1 Protein / Q000235:genetics / Q000502:physiology; D044767:Ubiquitin-Protein Ligases / Q000235:genetics / Q000378:metabolism; D016875:tau Proteins / Q000235:genetics / Q000502:physiology
D016564:Amyloid beta-Protein Precursor; C054369:MAPT protein, human; D008565:Membrane Proteins; C508853:PSEN1 protein, human; D053764:Presenilin-1; C526471:SMN1 protein, human; C000606290:SOD1 protein, human; D055533:Survival of Motor Neuron 1 Protein; D016875:tau Proteins; D013482:Superoxide Dismutase; D000072105:Superoxide Dismutase-1; D044767:Ubiquitin-Protein Ligases; C111567:parkin protein; C440006:ATL1 protein, human; D000251:Adenosine Triphosphatases; D020558:GTP Phosphohydrolases; D019204:GTP-Binding Proteins; D000074181:Spastin; C400283:SPAST protein, human