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See detailPredicting Functional Effects of Missense Variants in Voltage-Gated Sodium and Calcium Channels
Heyne, Henrike O.; Baez-Nieto, David; Iqbal, Sumaiya et al

E-print/Working paper (2019)

Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is ... [more ▼]

Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) which is not only corresponding to clinical disease manifestations, but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. Based on known gene-disease-mechanisms, we here infer LOF (518 variants) and GOF (309 variants) of likely pathogenic variants from disease phenotypes of variant carriers. We show regional clustering of inferred GOF and LOF variants, respectively, across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCN/CACNA1 genes. By training a machine learning model on sequence- and structure-based features we predict LOF- or GOF- associated disease phenotypes (ROC = 0.85) of likely pathogenic missense variants. We then successfully validate the GOF versus LOF prediction on 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and in exome-wide data from > 100.000 cases and controls. Ultimately, functional prediction of missense variants in clinically relevant genes will facilitate precision medicine in clinical practice. [less ▲]

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See detailIdentification and Characterization of Variant Intolerant Sites across Human Protein 3-Dimensional Structures
Iqbal, Sumaiya; Berg Jespersen, Jakob; Perez-Palma, Eduardo et al

in Biophysical Journal (2018, February 02), 114(3, Suppl. 1), 664

The functional interpretation of genetic variation in disease-associated genes is far outpaced by data generation. Existing algorithms for prediction of variant consequences do not adequately distinguish ... [more ▼]

The functional interpretation of genetic variation in disease-associated genes is far outpaced by data generation. Existing algorithms for prediction of variant consequences do not adequately distinguish pathogenic variants from benign rare variants. This lack of statistical and bioinformatics analyses, accompanied by an ever-increasing number of identified variants in biomedical research and clinical applications, has become a major challenge. Established methods to predict the functional effect of genetic variation use the degree of amino acid conservation across species in linear protein sequence alignment. More recent methods include the spatial distribution pattern of known patient and control variants. Here, we propose to combine the linear conservation and spatial constrained based scores to devise a novel score that incorporates 3-dimensional structural properties of amino acid residues, such as the solvent-accessible surface area, degree of flexibility, secondary structure propensity and binding tendency, to quantify the effect of amino acid substitutions. For this study, we develop a framework for large-scale mapping of established linear sequence-based paralog and ortholog conservation scores onto the tertiary structures of human proteins. This framework can be utilized to map the spatial distribution of mutations on solved protein structures as well as homology models. As a proof of concept, using a homology model of the human Nav1.2 voltage-gated sodium channel structure, we observe spatial clustering in distinct domains of mutations, associated with Autism Spectrum Disorder (>20 variants) and Epilepsy (>100 variants), that exert opposing effects on channel function. We are currently characterizing all variants (>300k individuals) found in ClinVar, the largest disease variant database, as well as variants identified in >140k individuals from general population. The variant mapping framework and our score, informed with structural information, will be useful in identifying structural motifs of proteins associated with disease risk. [less ▲]

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