Person: Pérez Palma, Eduardo
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Pérez Palma
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Eduardo
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Eduardo Esteban Pérez Palma
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Publication CNV-ClinViewer: enhancing the clinical interpretation oflarge copy-number variants online(2023) Macnee, Marie; Pérez Palma, Eduardo; Brünger, Tobias; Klöckner, Chiara; Platzer, Konrad; Stefansk, Arthur; Montanucci, Ludovica; Bayat, Allan; Radtke, Maximilian; Collins, Ryan; Talkowski, Michael; Blankenberg, Daniel; Møller, Rikke; Lemke, Johannes; Nothnagel, Michael; May, Patrick; Lal, DennisMotivation: Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts. Results: Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators' patient care and for basic scientists' translational genomic research.Publication SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis(2023) Stefanski, Arthur; Pérez Palma, Eduardo; Brünger, Tobias; Montanucci, Ludovica; Gati, Cornelius; Klöckner, Chiara; Johannesen, Katrine; Goodspeed, Kimberly; Macnee, Marie; Deng, Alexander; Aledo, Ángel; Borovikov,Artem; Kava, Maina; Bouman, Arjan; Hajianpour, M.; Pal, Deb; Engelen, Marc; Hagebeuk, Eveline; Shinawi, Marwan; Heidlebaugh, Alexis; Oetjens, Kathryn; Hoffman, Trevor; Striano, Pasquale; Freed, Amanda; Futtrup, Line; Balslev, Thomas; Abulí, Anna; Danvoye, Leslie; Lederer, Damien; Balci, Tugce; Nabavi, Maryam; Butler, Elizabeth; Drewes, Sarah; Van Engelen, Kalene; Howell, Katherine; Khoury, Jean; May, Patrick; Trinidad, Marena; Froelich, Steven; Lemke, JohannesGenetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).Publication Genomic analysis of AlphaFold2-predicted structures identifies maps of 3D essential sites in 243 neurodevelopmental disorder-associated proteins(2022) Iqbal, Sumaiya; Brunger, Tobias; Pérez Palma, Eduardo; Hoksza, David; Campbell, Arthur; Daly, Mark; May, Patrick; Lal, DennisWe propose a new methodology to identify maps of essential sites (i.e., amino acid residues) in 3D, called Essential 3D sites.Publication Conserved missense variant pathogenicity and correlated phenotypes across paralogous genes(2025) Brünger, Tobias; Ivaniuk, Alina; Pérez Palma, Eduardo; Montanucci, Ludovica; Cohen, Stacey; Smith, Lacey; Parthasarathy, Shridhar; Helbig, Ingo; Nothnagel, Michael; May, Patrick; Lal, DennisBackground: The majority of missense variants in clinical genetic tests are classified as variants of uncertain significance. Prior research shows that the deleterious effects and the subsequent molecular consequences of variants are often conserved among paralogous protein sequences within a gene family. Here, we systematically quantify on an exome-wide scale whether the existence of pathogenic variants in paralogous genes at a conserved position can serve as evidence for the pathogenicity of a new variant. For the gene family of voltage-gated sodium channels, where variants and expert-curated clinical phenotypes are available, we also assess whether phenotype patterns of multiple disorders for each gene are conserved across variant positions within the gene family. Results: Mapping 590,000 pathogenic and 1.9 million population variants onto 9928 genes grouped into 2054 paralogous families increases the number of residues with classifiable evidence 5.1-fold compared with gene-specific data alone. The presence of a pathogenic variant in a paralogous gene is associated with a positive likelihood ratio of 13.0 for variant pathogenicity. Across ten genes encoding voltage-gated sodium channels and 22 expert-curated disorders, we identify cross-paralog correlated phenotypes based on 3D structure spatial position. For example, multiple established loss-of-function related disorders across SCN1A, SCN2A, SCN5A, and SCN8A show overlapping spatial variant clusters. Finally, we show that phenotype integration in paralog variant selection improves variant classification. Conclusion: Conserved pathogenic missense variants in paralogous genes provide robust, quantifiable support for clinical variant interpretation, and phenotype-informed mapping further improves predictions.