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See detailIdentification of pathogenic variant enriched regions across genes and gene families
Perez-Palma, Eduardo; May, Patrick UL; Iqbal, Sumaiya et al

in Genome Research (2020), 30(1), 62-71

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to ... [more ▼]

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2,871 gene family protein sequence alignments involving 9,990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1,252 genes. As a comparison, testing the same genes individually we identified less patient variant enriched regions involving only 2,639 amino acids and 215 genes. Next, we selected de novo variants from 6,753 patients with neurodevelopmental disorders and 1,911 unaffected siblings, and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I.=3.90-Inf, p-value = 2.72x10-11). Using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, p-value < 2.2 x 10-16). All pathogenic variant enriched regions (PERs) identified are available online through the “PER viewer” a user-friendly online platform for interactive data mining, visualization and download. In summary, our gene family burden analysis approach identified novel pathogenic variant enriched regions in protein sequences. This annotation can empower variant interpretation. [less ▲]

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See detailIdentification of pathogenic variant enriched regions across genes and gene families
Pérez-Palma, Eduardo; May, Patrick UL; Iqbal, Sumaiya et al

E-print/Working paper (2019)

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to ... [more ▼]

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2,871 gene family protein sequence alignments involving 9,990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 65,034 missense variants from patients. With this gene family approach, we identified 398 regions enriched for patient variants spanning 33,887 amino acids in 1,058 genes. As a comparison, testing the same genes individually we identified less patient variant enriched regions involving only 2,167 amino acids and 180 genes. Next, we selected de novo variants from 6,753 patients with neurodevelopmental disorders and 1,911 unaffected siblings, and observed a 5.56-fold enrichment of patient variants in our identified regions (95% C.I. =2.76-Inf, p-value = 6.66×10−8). Using an independent ClinVar variant set, we found missense variants inside the identified regions are 111-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 111.48, 95% C.I = 68.09-195.58, p-value < 2.2e−16). All patient variant enriched regions identified (PERs) are available online through a user-friendly platform for interactive data mining, visualization and download at http://per.broadinstitute.org. In summary, our gene family burden analysis approach identified novel patient variant enriched regions in protein sequences. This annotation can empower variant interpretation. [less ▲]

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See detailDe novo Variants in Neurodevelopmental Disorders with Epilepsy
Heyne, Henrike O.; Singh, Tarijinder; Stamberger, Hannah et al

in Nature Genetics (2018)

Epilepsy is a frequent feature of neurodevelopmental disorders (NDD) but little is known about genetic differences between NDD with and without epilepsy. We analyzed de novo variants (DNV) in 6753 parent ... [more ▼]

Epilepsy is a frequent feature of neurodevelopmental disorders (NDD) but little is known about genetic differences between NDD with and without epilepsy. We analyzed de novo variants (DNV) in 6753 parent-offspring trios ascertained for different NDD. In the subset of 1942 individuals with NDD with epilepsy, we identified 33 genes with a significant excess of DNV, of which SNAP25 and GABRB2 had previously only limited evidence for disease association. Joint analysis of all individuals with NDD also implicated CACNA1E as a novel disease gene. Comparing NDD with and without epilepsy, we found missense DNV, DNV in specific genes, age of recruitment and severity of intellectual disability to be associated with epilepsy. We further demonstrate to what extent our results impact current genetic testing as well as treatment, emphasizing the benefit of accurate genetic diagnosis in NDD with epilepsy. [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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See detailReassessment Of Lesion-Associated Gene And Variant Pathogenicity In Focal Human Epilepsies
Neupert, Lisa Marie; Nothnagel, Michael; May, Patrick UL et al

E-print/Working paper (2017)

Purpose: Increasing availability of surgically resected brain tissue from Focal Cortical Dysplasia and low-grade epilepsy-associated tumor patients fostered large-scale genetic examination. However ... [more ▼]

Purpose: Increasing availability of surgically resected brain tissue from Focal Cortical Dysplasia and low-grade epilepsy-associated tumor patients fostered large-scale genetic examination. However, assessment of germline and somatic variant pathogenicity remains difficult. Methods: Here, we critically reevaluated the pathogenicity for all neuropathology-associated variants reported to date in the PubMed and ClinVar databases, including 12 disease-related genes and 88 neuropathology-associated missense variants. We (1) assessed evolutionary gene constraint using the pLI and missense z scores, (2) applied guidelines by the American College of Medical Genetics and Genomics (ACMG), and (3) predicted pathogenicity by using PolyPhen-2, CADD, and GERP. Results: Constraint analysis classified only seven out of 12 genes to be likely disease-associated, while 35 (40\%) of those 88 variants were classified as being variants of unknown significance (VUS) and 53 (60\%) as being likely pathogenic (LPII). Pathogenicity prediction yielded discrimination between neuropathology-associated variants (LPII and VUS) and rare variant scores obtained from individuals present in the Genome Aggregation Database (gnomAD). Conclusion: We conclude that several VUS are likely disease-associated and will be reclassified by future molecular evidence. In summary, interpretation of lesion-associated gene variants remains complex while the application of current ACMG guidelines including bioinformatic pathogenicity prediction will help improving interpretation and prediction. [less ▲]

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