1
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Li Q, Geng S, Luo H, Wang W, Mo YQ, Luo Q, Wang L, Song GB, Sheng JP, Xu B. Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy. Signal Transduct Target Ther 2024; 9:266. [PMID: 39370455 PMCID: PMC11456611 DOI: 10.1038/s41392-024-01953-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 07/25/2024] [Accepted: 08/16/2024] [Indexed: 10/08/2024] Open
Abstract
Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.
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Affiliation(s)
- Qing Li
- The Shapingba Hospital, Chongqing University, Chongqing, China
- Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Chongqing University Cancer Hospital and School of Medicine, Chongqing University, Chongqing, China
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, China
| | - Shan Geng
- Central Laboratory, The Affiliated Dazu Hospital of Chongqing Medical University, Chongqing, China
| | - Hao Luo
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, China
- Cancer Center, Daping Hospital, Army Medical University, Chongqing, China
| | - Wei Wang
- Chongqing Municipal Health and Health Committee, Chongqing, China
| | - Ya-Qi Mo
- Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Chongqing University Cancer Hospital and School of Medicine, Chongqing University, Chongqing, China
| | - Qing Luo
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, China
| | - Lu Wang
- Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Chongqing University Cancer Hospital and School of Medicine, Chongqing University, Chongqing, China
| | - Guan-Bin Song
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, China.
| | - Jian-Peng Sheng
- College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Bo Xu
- Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Chongqing University Cancer Hospital and School of Medicine, Chongqing University, Chongqing, China.
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2
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Young CL, Beichman AC, Mas-Ponte D, Hemker SL, Zhu L, Kitzman JO, Shirts BH, Harris K. A maternal germline mutator phenotype in a family affected by heritable colorectal cancer. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.12.08.23299304. [PMID: 38196581 PMCID: PMC10775336 DOI: 10.1101/2023.12.08.23299304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Variation in DNA repair genes can increase cancer risk by elevating the rate of oncogenic mutation. Defects in one such gene, MUTYH, are known to elevate the incidence of colorectal cancer in a recessive Mendelian manner. Recent evidence has also linked MUTYH to a mutator phenotype affecting normal somatic cells as well as the female germline. Here, we use whole genome sequencing to measure germline de novo mutation rates in a large extended family containing both mothers and fathers who are affected by pathogenic MUTYH variation. By developing novel methodology that uses siblings as "surrogate parents" to identify de novo mutations, we were able to include mutation data from several children whose parents were unavailable for sequencing. In the children of mothers affected by the pathogenic MUTYH genotype p.Y179C/V234M, we identify an elevation of the C>A mutation rate that is weaker than mutator effects previously reported to be caused by other pathogenic MUTYH genotypes, suggesting that mutation rates in normal tissues may be useful for classifying cancer-associated variation along a continuum of severity. Surprisingly, we detect no significant elevation of the C>A mutation rate in children born to a father with the same MUTYH genotype, and we similarly find that the mutator effect of the mouse homolog Mutyh appears to be localized to embryonic development, not the spermatocytes. Our results suggest that maternal MUTYH variants can cause germline mutations by attenuating the repair of oxidative DNA damage in the early embryo.
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Affiliation(s)
- Candice L. Young
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
- Department of Molecular and Cellular Biology, University of Washington, 1705 NE Pacific St, Seattle, WA 98195
| | - Annabel C. Beichman
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
| | - David Mas-Ponte
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
| | - Shelby L. Hemker
- Department of Human Genetics, University of Michigan, 1241 Catherine St, Ann Arbor, MI 48109
| | - Luke Zhu
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
- Department of Bioengineering, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
| | - Jacob O. Kitzman
- Department of Human Genetics, University of Michigan, 1241 Catherine St, Ann Arbor, MI 48109
| | - Brian H. Shirts
- Department of Laboratory Medicine and Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA 98195
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195
- Herbold Computational Biology Program, Fred Hutchinson Cancer Center, P.O. Box 19024, Seattle, WA 98109
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3
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O'Neill MJ, Yang T, Laudeman J, Calandranis ME, Harvey ML, Solus JF, Roden DM, Glazer AM. ParSE-seq: a calibrated multiplexed assay to facilitate the clinical classification of putative splice-altering variants. Nat Commun 2024; 15:8320. [PMID: 39333091 PMCID: PMC11437130 DOI: 10.1038/s41467-024-52474-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 09/10/2024] [Indexed: 09/29/2024] Open
Abstract
Interpreting the clinical significance of putative splice-altering variants outside canonical splice sites remains difficult without time-intensive experimental studies. To address this, we introduce Parallel Splice Effect Sequencing (ParSE-seq), a multiplexed assay to quantify variant effects on RNA splicing. We first apply this technique to study hundreds of variants in the arrhythmia-associated gene SCN5A. Variants are studied in 'minigene' plasmids with molecular barcodes to allow pooled variant effect quantification. We perform experiments in two cell types, including disease-relevant induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The assay strongly separates known control variants from ClinVar, enabling quantitative calibration of the ParSE-seq assay. Using these evidence strengths and experimental data, we reclassify 29 of 34 variants with conflicting interpretations and 11 of 42 variants of uncertain significance. In addition to intronic variants, we show that many synonymous and missense variants disrupted RNA splicing. Two splice-altering variants in the assay also disrupt splicing and sodium current when introduced into iPSC-CMs by CRISPR-Cas9 editing. ParSE-seq provides high-throughput experimental data for RNA-splicing to support precision medicine efforts and can be readily adopted to study other loss-of-function genotype-phenotype relationships.
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Affiliation(s)
| | - Tao Yang
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julie Laudeman
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Maria E Calandranis
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - M Lorena Harvey
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joseph F Solus
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan M Roden
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Andrew M Glazer
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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4
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Sokirniy I, Inam H, Tomaszkiewicz M, Reynolds J, McCandlish D, Pritchard J. A side-by-side comparison of variant function measurements using deep mutational scanning and base editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.30.601444. [PMID: 39005366 PMCID: PMC11244880 DOI: 10.1101/2024.06.30.601444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Variant annotation is a crucial objective in mammalian functional genomics. Deep Mutational Scanning (DMS) is a well-established method for annotating human gene variants, but CRISPR base editing (BE) is emerging as an alternative. However, questions remain about how well high-throughput base editing measurements can annotate variant function and the extent of downstream experimental validation required. This study presents the first direct comparison of DMS and BE in the same lab and cell line. Results indicate that focusing on the most likely edits and highest efficiency sgRNAs enhances the agreement between a "gold standard" DMS dataset and a BE screen. A simple filter for sgRNAs making single edits in their window could sufficiently annotate a large proportion of variants directly from sgRNA sequencing of large pools. When multi-edit guides are unavoidable, directly measuring the variants created in the pool, rather than sgRNA abundance, can recover high-quality variant annotation measurements in multiplexed pools. Taken together, our data show a surprising degree of correlation between base editor data and gold standard deep mutational scanning.
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Affiliation(s)
- Ivan Sokirniy
- Huck Institute for the Life Sciences, University Park, PA 16802
| | - Haider Inam
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - Marta Tomaszkiewicz
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - Joshua Reynolds
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - David McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Justin Pritchard
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
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5
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Fries LE, Dharma S, Chakravarti A, Chatterjee S. Variability in proliferative and migratory defects in Hirschsprung disease-associated RET pathogenic variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.24.614825. [PMID: 39372753 PMCID: PMC11451626 DOI: 10.1101/2024.09.24.614825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Despite the extensive genetic heterogeneity of Hirschsprung disease (HSCR; congenital colonic aganglionosis) 72% of patients harbor pathogenic variants in 10 genes that form a gene regulatory network (GRN) controlling the development of the enteric nervous system (ENS). Among these genes, the receptor tyrosine kinase gene RET is the most significant contributor, accounting for pathogenic variants in 12%-50% of patients depending on phenotype. RET plays a critical role in the proliferation and migration of ENS precursors, and defects in these processes lead to HSCR. However, despite the gene's importance in HSCR, the functional consequences of RET pathogenic variants and their mechanism of disease remain poorly understood. To address this, we investigated the proliferative and migratory phenotypes in a RET-dependent neural crest-derived cell line harboring one of five missense (L56M, E178Q, Y791F, S922Y, F998L) or three nonsense (Y204X, R770X, Y981X) pathogenic heterozygous variants. Using a combination of cDNA-based and CRISPR-based PRIME editing coupled with quantitative proliferation and migration assays, we detected significant losses in cell proliferation and migration in three missense (E178Q, S922Y, F998L) and all nonsense variants. Our data suggests that the Y791F variant, whose pathogenicity has been debated, is likely not pathogenic. Importantly, the severity of migration loss did not consistently correlate with proliferation defects, and the phenotypic severity of nonsense variants was independent of their position within the RET protein. This study highlights the necessity and feasibility of targeted functional assays to accurately assess the pathogenicity of HSCR-associated variants, rather than relying solely on machine learning predictions, which could themselves be refined by incorporating such functional data.
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Affiliation(s)
- Lauren E Fries
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY 10016
| | - Sree Dharma
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY 10016
| | - Aravinda Chakravarti
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY 10016
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016
| | - Sumantra Chatterjee
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY 10016
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016
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6
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Ma K, Huang S, Ng KK, Lake NJ, Joseph S, Xu J, Lek A, Ge L, Woodman KG, Koczwara KE, Cohen J, Ho V, O'Connor CL, Brindley MA, Campbell KP, Lek M. Saturation mutagenesis-reinforced functional assays for disease-related genes. Cell 2024:S0092-8674(24)00976-0. [PMID: 39326416 DOI: 10.1016/j.cell.2024.08.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 07/29/2024] [Accepted: 08/23/2024] [Indexed: 09/28/2024]
Abstract
Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods are obstacles for achieving genome-wide resolution of variants in disease-related genes. Our framework, saturation mutagenesis-reinforced functional assays (SMuRF), offers simple and cost-effective saturation mutagenesis paired with streamlined functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single-nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Overall, our approach enables variant-to-function insights for disease genes in a cost-effective manner that can be broadly implemented by standard research laboratories.
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Affiliation(s)
- Kaiyue Ma
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China.
| | - Shushu Huang
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Kenneth K Ng
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Nicole J Lake
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Soumya Joseph
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Jenny Xu
- Yale University, New Haven, CT, USA
| | - Angela Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA; Muscular Dystrophy Association, Chicago, IL, USA
| | - Lin Ge
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA; Department of Neurology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Keryn G Woodman
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Justin Cohen
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Vincent Ho
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Melinda A Brindley
- Department of Infectious Diseases, Department of Population Health, University of Georgia, Athens, GA, USA
| | - Kevin P Campbell
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
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7
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van Ravesteyn TW, Dekker M, Riele HT. Mono- and Biallelic Replication-Coupled Gene Editing Discriminates Dominant-Negative and Loss-of-Function Variants of DNA Mismatch Repair Genes. J Mol Diagn 2024; 26:805-814. [PMID: 38925454 DOI: 10.1016/j.jmoldx.2024.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/08/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
Replication-coupled gene editing using locked nucleic acid-modified single-stranded DNA oligonucleotides (LMOs) can genetically engineer mammalian cells with high precision at single nucleotide resolution. Based on this method, oligonucleotide-directed mutation screening (ODMS) was developed to determine whether variants of uncertain clinical significance of DNA mismatch repair (MMR) genes can cause Lynch syndrome. In ODMS, the appearance of 6-thioguanine-resistant colonies upon introduction of the variant is indicative for defective MMR and hence pathogenicity. Whereas mouse embryonic stem cells (mESCs) hemizygous for MMR genes were used previously, we now show that ODMS can also be applied in wild-type mESCs carrying two functional alleles of each MMR gene. 6-Thioguanine resistance can result from two possible events: first, the mutation is present in only one allele, which is indicative for dominant-negative activity of the variant; and second, both alleles contain the planned modification, which is indicative for a regular loss-of-function variant. Thus, ODMS in wild-type mESCs can discriminate fully disruptive and dominant-negative MMR variants. The feasibility of biallelic targeting suggests that the efficiency of LMO-mediated gene targeting at a nonselectable locus may be enriched in cells that had undergone a simultaneous selectable LMO targeting event. This turned out to be the case and provided a protocol to improve recovery of LMO-mediated gene modification events.
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Affiliation(s)
- Thomas W van Ravesteyn
- Division of Tumor Biology and Immunology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Marleen Dekker
- Division of Tumor Biology and Immunology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Hein Te Riele
- Division of Tumor Biology and Immunology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
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8
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Caetano da Silva C, Macias Trevino C, Mitchell J, Murali H, Tsimbal C, Dalessandro E, Carroll SH, Kochhar S, Curtis SW, Cheng CHE, Wang F, Kutschera E, Carstens RP, Xing Y, Wang K, Leslie EJ, Liao EC. Functional analysis of ESRP1/2 gene variants and CTNND1 isoforms in orofacial cleft pathogenesis. Commun Biol 2024; 7:1040. [PMID: 39179789 PMCID: PMC11344038 DOI: 10.1038/s42003-024-06715-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 08/09/2024] [Indexed: 08/26/2024] Open
Abstract
Orofacial cleft (OFC) is a common human congenital anomaly. Epithelial-specific RNA splicing regulators ESRP1 and ESRP2 regulate craniofacial morphogenesis and their disruption result in OFC in zebrafish, mouse and humans. Using esrp1/2 mutant zebrafish and murine Py2T cell line models, we functionally tested the pathogenicity of human ESRP1/2 gene variants. We found that many variants predicted by in silico methods to be pathogenic were functionally benign. Esrp1 also regulates the alternative splicing of Ctnnd1 and these genes are co-expressed in the embryonic and oral epithelium. In fact, over-expression of ctnnd1 is sufficient to rescue morphogenesis of epithelial-derived structures in esrp1/2 zebrafish mutants. Additionally, we identified 13 CTNND1 variants from genome sequencing of OFC cohorts, confirming CTNND1 as a key gene in human OFC. This work highlights the importance of functional assessment of human gene variants and demonstrates the critical requirement of Esrp-Ctnnd1 acting in the embryonic epithelium to regulate palatogenesis.
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Affiliation(s)
- Caroline Caetano da Silva
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | | | - Hemma Murali
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Casey Tsimbal
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Shriners Hospital for Children, Tampa, FL, USA
| | - Eileen Dalessandro
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Shannon H Carroll
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Shriners Hospital for Children, Tampa, FL, USA
| | - Simren Kochhar
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Sarah W Curtis
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Ching Hsun Eric Cheng
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Feng Wang
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Eric Kutschera
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Russ P Carstens
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yi Xing
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kai Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric C Liao
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Harvard Medical School, Boston, MA, USA.
- Shriners Hospital for Children, Tampa, FL, USA.
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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9
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Padigepati SR, Stafford DA, Tan CA, Silvis MR, Jamieson K, Keyser A, Nunez PAC, Nicoludis JM, Manders T, Fresard L, Kobayashi Y, Araya CL, Aradhya S, Johnson B, Nykamp K, Reuter JA. Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification. Hum Genet 2024; 143:995-1004. [PMID: 39085601 PMCID: PMC11303574 DOI: 10.1007/s00439-024-02691-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 07/12/2024] [Indexed: 08/02/2024]
Abstract
As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings. Here, we describe a framework for generating, validating and incorporating data from MAVEs into a semi-quantitative variant classification method applied to clinical genetic testing. Using single-cell gene expression measurements, cellular evidence models were built to assess the effects of DNA variation in 44 genes of clinical interest. This framework was also applied to models for an additional 22 genes with previously published MAVE datasets. In total, modeling data was incorporated from 24 genes into our variant classification method. These data contributed evidence for classifying 4043 observed variants in over 57,000 individuals. Genetic testing laboratories are uniquely positioned to generate, analyze, validate, and incorporate evidence from high-throughput functional data and ultimately enable the use of these data to provide definitive clinical variant classifications for more patients.
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Affiliation(s)
| | | | | | - Melanie R Silvis
- Invitae Corporation, San Francisco, CA, 94103, USA
- Epic Bio, South San Francisco, CA, 94080, USA
| | - Kirsty Jamieson
- Invitae Corporation, San Francisco, CA, 94103, USA
- Epic Bio, South San Francisco, CA, 94080, USA
| | - Andrew Keyser
- Invitae Corporation, San Francisco, CA, 94103, USA
- Calico Life Sciences, South San Francisco, CA, 94080, USA
| | | | - John M Nicoludis
- Invitae Corporation, San Francisco, CA, 94103, USA
- Department of Structural Biology, Genentech, South San Francisco, CA, 94080, USA
| | - Toby Manders
- Invitae Corporation, San Francisco, CA, 94103, USA
| | | | | | - Carlos L Araya
- Invitae Corporation, San Francisco, CA, 94103, USA
- Tapanti.org, Santa Barbara, CA, 93108, USA
| | | | - Britt Johnson
- Invitae Corporation, San Francisco, CA, 94103, USA
- GeneDx, Stamford, CT, 06902, USA
| | - Keith Nykamp
- Invitae Corporation, San Francisco, CA, 94103, USA.
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10
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Plowman JN, Matoy EJ, Uppala LV, Draves SB, Watson CJ, Sefranek BA, Stacey ML, Anderson SP, Belshan MA, Blue EE, Huff CD, Fu Y, Stessman HAF. Targeted sequencing for hereditary breast and ovarian cancer in BRCA1/2-negative families reveals complex genetic architecture and phenocopies. HGG ADVANCES 2024; 5:100306. [PMID: 38734904 PMCID: PMC11166883 DOI: 10.1016/j.xhgg.2024.100306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 05/07/2024] [Accepted: 05/07/2024] [Indexed: 05/13/2024] Open
Abstract
Approximately 20% of breast cancer cases are attributed to increased family risk, yet variation in BRCA1/2 can only explain 20%-25% of cases. Historically, only single gene or single variant testing were common in at-risk family members, and further sequencing studies were rarely offered after negative results. In this study, we applied an efficient and inexpensive targeted sequencing approach to provide molecular diagnoses in 245 human samples representing 134 BRCA mutation-negative (BRCAX) hereditary breast and ovarian cancer (HBOC) families recruited from 1973 to 2019 by Dr. Henry Lynch. Sequencing identified 391 variants, which were functionally annotated and ranked based on their predicted clinical impact. Known pathogenic CHEK2 breast cancer variants were identified in five BRCAX families in this study. While BRCAX was an inclusion criterion for this study, we still identified a pathogenic BRCA2 variant (p.Met192ValfsTer13) in one family. A portion of BRCAX families could be explained by other hereditary cancer syndromes that increase HBOC risk: Li-Fraumeni syndrome (gene: TP53) and Lynch syndrome (gene: MSH6). Interestingly, many families carried additional variants of undetermined significance (VOUSs) that may further modify phenotypes of syndromic family members. Ten families carried more than one potential VOUS, suggesting the presence of complex multi-variant families. Overall, nine BRCAX HBOC families in our study may be explained by known likely pathogenic/pathogenic variants, and six families carried potential VOUSs, which require further functional testing. To address this, we developed a functional assay where we successfully re-classified one family's PMS2 VOUS as benign.
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Affiliation(s)
- Jocelyn N Plowman
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE 68178, USA
| | - Evanjalina J Matoy
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE 68178, USA
| | - Lavanya V Uppala
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE 68178, USA
| | - Samantha B Draves
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE 68178, USA
| | - Cynthia J Watson
- Creighton University Core Facilities, Creighton University, Omaha, NE 68178, USA
| | - Bridget A Sefranek
- Creighton University Core Facilities, Creighton University, Omaha, NE 68178, USA
| | - Mark L Stacey
- Creighton University Core Facilities, Creighton University, Omaha, NE 68178, USA
| | - Samuel P Anderson
- Creighton University Core Facilities, Creighton University, Omaha, NE 68178, USA
| | - Michael A Belshan
- Department of Medical Microbiology and Immunology, Creighton University, Omaha, NE 68178, USA
| | - Elizabeth E Blue
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA; Institute for Public Health Genetics, University of Washington, Seattle, WA 98195, USA; Brotman Baty Institute, Seattle, WA 98195, USA
| | - Chad D Huff
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yusi Fu
- Department of Biomedical Sciences, Creighton University, Omaha, NE 68178, USA
| | - Holly A F Stessman
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE 68178, USA; Creighton University Core Facilities, Creighton University, Omaha, NE 68178, USA.
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11
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Dereli O, Kuru N, Akkoyun E, Bircan A, Tastan O, Adebali O. PHACTboost: A Phylogeny-Aware Pathogenicity Predictor for Missense Mutations via Boosting. Mol Biol Evol 2024; 41:msae136. [PMID: 38934805 PMCID: PMC11251492 DOI: 10.1093/molbev/msae136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 05/30/2024] [Accepted: 06/24/2024] [Indexed: 06/28/2024] Open
Abstract
Most algorithms that are used to predict the effects of variants rely on evolutionary conservation. However, a majority of such techniques compute evolutionary conservation by solely using the alignment of multiple sequences while overlooking the evolutionary context of substitution events. We had introduced PHACT, a scoring-based pathogenicity predictor for missense mutations that can leverage phylogenetic trees, in our previous study. By building on this foundation, we now propose PHACTboost, a gradient boosting tree-based classifier that combines PHACT scores with information from multiple sequence alignments, phylogenetic trees, and ancestral reconstruction. By learning from data, PHACTboost outperforms PHACT. Furthermore, the results of comprehensive experiments on carefully constructed sets of variants demonstrated that PHACTboost can outperform 40 prevalent pathogenicity predictors reported in the dbNSFP, including conventional tools, metapredictors, and deep learning-based approaches as well as more recent tools such as AlphaMissense, EVE, and CPT-1. The superiority of PHACTboost over these methods was particularly evident in case of hard variants for which different pathogenicity predictors offered conflicting results. We provide predictions of 215 million amino acid alterations over 20,191 proteins. PHACTboost is available at https://github.com/CompGenomeLab/PHACTboost. PHACTboost can improve our understanding of genetic diseases and facilitate more accurate diagnoses.
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Affiliation(s)
- Onur Dereli
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | - Nurdan Kuru
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | - Emrah Akkoyun
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
- Network Technologies Department, TÜBİTAK-ULAKBİM Turkish Academic Network and Information Center, Ankara 06530, Turkey
| | - Aylin Bircan
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | - Oznur Tastan
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | - Ogün Adebali
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
- Biological Sciences, TÜBİTAK Research Institute for Fundamental Sciences, Gebze 41470, Turkey
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12
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da Silva CC, Trevino CM, Mitchell J, Murali H, Tsimbal C, Dalessandro E, Carroll SH, Kochhar S, Curtis SW, Cheng CHE, Wang F, Kutschera E, Carstens RP, Xing Y, Wang K, Leslie EJ, Liao EC. Functional analysis of ESRP1/2 gene variants and CTNND1 isoforms in orofacial cleft pathogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601574. [PMID: 39005284 PMCID: PMC11245018 DOI: 10.1101/2024.07.02.601574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Orofacial cleft (OFC) is a common human congenital anomaly. Epithelial-specific RNA splicing regulators ESRP1 and ESRP2 regulate craniofacial morphogenesis and their disruption result in OFC in zebrafish, mouse and humans. Using esrp1/2 mutant zebrafish and murine Py2T cell line models, we functionally tested the pathogenicity of human ESRP1/2 gene variants. We found that many variants predicted by in silico methods to be pathogenic were functionally benign. Esrp1 also regulates the alternative splicing of Ctnnd1 and these genes are co-expressed in the embryonic and oral epithelium. In fact, over-expression of ctnnd1 is sufficient to rescue morphogenesis of epithelial-derived structures in esrp1/2 zebrafish mutants. Additionally, we identified 13 CTNND1 variants from genome sequencing of OFC cohorts, confirming CTNND1 as a key gene in human OFC. This work highlights the importance of functional assessment of human gene variants and demonstrates the critical requirement of Esrp-Ctnnd1 acting in the embryonic epithelium to regulate palatogenesis.
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Affiliation(s)
- Caroline Caetano da Silva
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
| | | | | | - Hemma Murali
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Casey Tsimbal
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
- Shriners Hospital for Children, Tampa, FL, USA
| | - Eileen Dalessandro
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
| | - Shannon H. Carroll
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
- Shriners Hospital for Children, Tampa, FL, USA
| | - Simren Kochhar
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Sarah W. Curtis
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Ching Hsun Eric Cheng
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
| | - Feng Wang
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, PA, USA
| | - Eric Kutschera
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, PA, USA
| | - Russ P. Carstens
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yi Xing
- Center for Genomic Medicine, Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Elizabeth J. Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric C. Liao
- Center for Craniofacial Innovation, Division of Plastic and Reconstructive Surgery, Department of Surgery, Children’s Hospital of Philadelphia, PA, USA
- Harvard Medical School, Boston, MA, USA
- Shriners Hospital for Children, Tampa, FL, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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13
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Ma K, Huang S, Ng KK, Lake NJ, Joseph S, Xu J, Lek A, Ge L, Woodman KG, Koczwara KE, Cohen J, Ho V, O’Connor CL, Brindley MA, Campbell KP, Lek M. Deep Mutational Scanning in Disease-related Genes with Saturation Mutagenesis-Reinforced Functional Assays (SMuRF). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.12.548370. [PMID: 37873263 PMCID: PMC10592615 DOI: 10.1101/2023.07.12.548370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods hamper crowd-sourcing approaches toward genome-wide resolution of variants in disease-related genes. Our framework, Saturation Mutagenesis-Reinforced Functional assays (SMuRF), addresses these issues by offering simple and cost-effective saturation mutagenesis, as well as streamlining functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Our approach opens new directions for enabling variant-to-function insights for disease genes in a manner that is broadly useful for crowd-sourcing implementation across standard research laboratories.
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Affiliation(s)
- Kaiyue Ma
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Shushu Huang
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Equal second authors
| | - Kenneth K. Ng
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Equal second authors
| | - Nicole J. Lake
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Soumya Joseph
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Jenny Xu
- Yale University, New Haven, CT, USA
| | - Angela Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Muscular Dystrophy Association, Chicago, IL, USA
| | - Lin Ge
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Neurology, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Keryn G. Woodman
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Justin Cohen
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Vincent Ho
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Melinda A. Brindley
- Department of Infectious Diseases, Department of Population Health, University of Georgia, Athens, GA, USA
- Senior Authors
| | - Kevin P. Campbell
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
- Senior Authors
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Senior Authors
- Lead Contact
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14
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Ma K, Gauthier LO, Cheung F, Huang S, Lek M. High-throughput assays to assess variant effects on disease. Dis Model Mech 2024; 17:dmm050573. [PMID: 38940340 PMCID: PMC11225591 DOI: 10.1242/dmm.050573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Abstract
Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.
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Affiliation(s)
- Kaiyue Ma
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Logan O. Gauthier
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Frances Cheung
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Shushu Huang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
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15
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Rao J, Xin R, Macdonald C, Howard MK, Estevam GO, Yee SW, Wang M, Fraser JS, Coyote-Maestas W, Pimentel H. Rosace: a robust deep mutational scanning analysis framework employing position and mean-variance shrinkage. Genome Biol 2024; 25:138. [PMID: 38789982 PMCID: PMC11127319 DOI: 10.1186/s13059-024-03279-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Deep mutational scanning (DMS) measures the effects of thousands of genetic variants in a protein simultaneously. The small sample size renders classical statistical methods ineffective. For example, p-values cannot be correctly calibrated when treating variants independently. We propose Rosace, a Bayesian framework for analyzing growth-based DMS data. Rosace leverages amino acid position information to increase power and control the false discovery rate by sharing information across parameters via shrinkage. We also developed Rosette for simulating the distributional properties of DMS. We show that Rosace is robust to the violation of model assumptions and is more powerful than existing tools.
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Affiliation(s)
- Jingyou Rao
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Ruiqi Xin
- Computational and Systems Biology Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Christian Macdonald
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA
| | - Matthew K Howard
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA
- Tetrad Graduate Program, UCSF, San Francisco, CA, USA
- Department of Pharmaceutical Chemistry, UCSF, San Francisco, CA, USA
| | - Gabriella O Estevam
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA
- Tetrad Graduate Program, UCSF, San Francisco, CA, USA
| | - Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA
| | - Mingsen Wang
- Department of Mathematics, Baruch College, CUNY, New York, NY, USA
| | - James S Fraser
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA
- Quantitative Biosciences Institute, UCSF, San Francisco, CA, USA
| | - Willow Coyote-Maestas
- Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA.
- Quantitative Biosciences Institute, UCSF, San Francisco, CA, USA.
| | - Harold Pimentel
- Department of Computer Science, UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
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16
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Bouras A, Lefol C, Ruano E, Grand-Masson C, Auclair-Perrossier J, Wang Q. Splicing analysis of 24 potential spliceogenic variants in MMR genes and clinical interpretation based on refined ACMG/AMP criteria. Hum Mol Genet 2024; 33:850-859. [PMID: 38311346 DOI: 10.1093/hmg/ddae016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/18/2023] [Accepted: 01/19/2024] [Indexed: 02/10/2024] Open
Abstract
Lynch syndrome (LS) is a common hereditary cancer syndrome caused by heterozygous germline pathogenic variants in DNA mismatch repair (MMR) genes. Splicing defect constitutes one of the major mechanisms for MMR gene inactivation. Using RT-PCR based RNA analysis, we investigated 24 potential spliceogenic variants in MMR genes and determined their pathogenicity based on refined splicing-related American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria. Aberrant transcripts were confirmed in 19 variants and 17 of which were classified as pathogenic including 11 located outside of canonical splice sites. Most of these variants were previously reported in LS patients without mRNA splicing assessment. Thus, our study provides crucial evidence for pathogenicity determination, allowing for appropriate clinical follow-up. We also found that computational predictions were globally well correlated with RNA analysis results and the use of both SPiP and SpliceAI software appeared more efficient for splicing defect prediction.
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Affiliation(s)
- Ahmed Bouras
- Centre Léon Bérard, Laboratory of Constitutional Genetics for Frequent Cancer HCL-CLB, 28 Laennec street, 69008 Lyon, France
- Inserm U1052, Lyon Cancer Research Center, 28 Laennec street, 69008 Lyon, France
| | - Cedrick Lefol
- Centre Léon Bérard, Laboratory of Constitutional Genetics for Frequent Cancer HCL-CLB, 28 Laennec street, 69008 Lyon, France
| | - Eric Ruano
- Centre Léon Bérard, Laboratory of Constitutional Genetics for Frequent Cancer HCL-CLB, 28 Laennec street, 69008 Lyon, France
| | - Chloé Grand-Masson
- Centre Léon Bérard, Laboratory of Constitutional Genetics for Frequent Cancer HCL-CLB, 28 Laennec street, 69008 Lyon, France
| | - Jessie Auclair-Perrossier
- Centre Léon Bérard, Lyon Cancer Research Center, Cancer Genomic Platform, 28 Laennec street, 69008 Lyon, France
| | - Qing Wang
- Centre Léon Bérard, Laboratory of Constitutional Genetics for Frequent Cancer HCL-CLB, 28 Laennec street, 69008 Lyon, France
- Centre Léon Bérard, Lyon Cancer Research Center, Cancer Genomic Platform, 28 Laennec street, 69008 Lyon, France
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17
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Grønbæk-Thygesen M, Hartmann-Petersen R. Cellular and molecular mechanisms of aspartoacylase and its role in Canavan disease. Cell Biosci 2024; 14:45. [PMID: 38582917 PMCID: PMC10998430 DOI: 10.1186/s13578-024-01224-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 03/24/2024] [Indexed: 04/08/2024] Open
Abstract
Canavan disease is an autosomal recessive and lethal neurological disorder, characterized by the spongy degeneration of the white matter in the brain. The disease is caused by a deficiency of the cytosolic aspartoacylase (ASPA) enzyme, which catalyzes the hydrolysis of N-acetyl-aspartate (NAA), an abundant brain metabolite, into aspartate and acetate. On the physiological level, the mechanism of pathogenicity remains somewhat obscure, with multiple, not mutually exclusive, suggested hypotheses. At the molecular level, recent studies have shown that most disease linked ASPA gene variants lead to a structural destabilization and subsequent proteasomal degradation of the ASPA protein variants, and accordingly Canavan disease should in general be considered a protein misfolding disorder. Here, we comprehensively summarize the molecular and cell biology of ASPA, with a particular focus on disease-linked gene variants and the pathophysiology of Canavan disease. We highlight the importance of high-throughput technologies and computational prediction tools for making genotype-phenotype predictions as we await the results of ongoing trials with gene therapy for Canavan disease.
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Affiliation(s)
- Martin Grønbæk-Thygesen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200N, Copenhagen, Denmark.
| | - Rasmus Hartmann-Petersen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200N, Copenhagen, Denmark.
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18
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Tam B, Qin Z, Zhao B, Sinha S, Lei CL, Wang SM. Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method. Int J Mol Sci 2024; 25:850. [PMID: 38255924 PMCID: PMC10815254 DOI: 10.3390/ijms25020850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/24/2024] Open
Abstract
Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.
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Affiliation(s)
- Benjamin Tam
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Zixin Qin
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Bojin Zhao
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Siddharth Sinha
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Chon Lok Lei
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - San Ming Wang
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Cancer Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
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19
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Christowitz C, Olivier DW, Schneider JW, Kotze MJ, Engelbrecht AM. Incorporating functional genomics into the pathology-supported genetic testing framework implemented in South Africa: A future view of precision medicine for breast carcinomas. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2024; 793:108492. [PMID: 38631437 DOI: 10.1016/j.mrrev.2024.108492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 02/25/2024] [Accepted: 04/11/2024] [Indexed: 04/19/2024]
Abstract
A pathology-supported genetic testing (PSGT) framework was established in South Africa to improve access to precision medicine for patients with breast carcinomas. Nevertheless, the frequent identification of variants of uncertain significance (VUSs) with the use of genome-scale next-generation sequencing has created a bottleneck in the return of results to patients. This review highlights the importance of incorporating functional genomics into the PSGT framework as a proposed initiative. Here, we explore various model systems and experimental methods available for conducting functional studies in South Africa to enhance both variant classification and clinical interpretation. We emphasize the distinct advantages of using in vitro, in vivo, and translational ex vivo models to improve the effectiveness of precision oncology. Moreover, we highlight the relevance of methodologies such as protein modelling and structural bioinformatics, multi-omics, metabolic activity assays, flow cytometry, cell migration and invasion assays, tube-formation assays, multiplex assays of variant effect, and database mining and machine learning models. The selection of the appropriate experimental approach largely depends on the molecular mechanism of the gene under investigation and the predicted functional effect of the VUS. However, before making final decisions regarding the pathogenicity of VUSs, it is essential to assess the functional evidence and clinical outcomes under current variant interpretation guidelines. The inclusion of a functional genomics infrastructure within the PSGT framework will significantly advance the reclassification of VUSs and enhance the precision medicine pipeline for patients with breast carcinomas in South Africa.
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Affiliation(s)
- Claudia Christowitz
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch 7600, South Africa.
| | - Daniel W Olivier
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch 7600, South Africa; Division of Chemical Pathology, Department of Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
| | - Johann W Schneider
- Division of Anatomical Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa; National Health Laboratory Service, Tygerberg Hospital, Cape Town 7505, South Africa
| | - Maritha J Kotze
- Division of Chemical Pathology, Department of Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa; National Health Laboratory Service, Tygerberg Hospital, Cape Town 7505, South Africa
| | - Anna-Mart Engelbrecht
- Department of Physiological Sciences, Faculty of Science, Stellenbosch University, Stellenbosch 7600, South Africa; Department of Global Health, African Cancer Institute, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
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20
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Zhao Y, Zhong G, Hagen J, Pan H, Chung WK, Shen Y. A probabilistic graphical model for estimating selection coefficient of missense variants from human population sequence data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.11.23299809. [PMID: 38168397 PMCID: PMC10760286 DOI: 10.1101/2023.12.11.23299809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Accurately predicting the effect of missense variants is a central problem in interpretation of genomic variation. Commonly used computational methods does not capture the quantitative impact on fitness in populations. We developed MisFit to estimate missense fitness effect using biobank-scale human population genome data. MisFit jointly models the effect at molecular level ( d ) and population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . MisFit is a probabilistic graphical model that integrates deep neural network components and population genetics models efficiently with inductive bias based on biological causality of variant effect. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that s is informative in predicting frequency across ancestries and consistent with the fraction of de novo mutations given s . Finally, MisFit outperforms previous methods in prioritizing missense variants in individuals with neurodevelopmental disorders.
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Affiliation(s)
- Yige Zhao
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Guojie Zhong
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Jake Hagen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032
| | - Hongbing Pan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
| | - Wendy K. Chung
- Department of Pediatrics, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
- JP Sulzberger Columbia Genome Center, Columbia University, New York, NY 10032
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21
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Fernández-Castillejo S, Roig B, Melé M, Serrano S, Salvat M, Querol M, Brunet J, Pineda M, Cisneros A, Parada D, Badia J, Borràs J, Rodríguez-Balada M, Gumà J. Opportunistic genetic screening increases the diagnostic yield and is medically valuable for care of patients and their relatives with hereditary cancer. J Med Genet 2023; 61:69-77. [PMID: 37591735 PMCID: PMC10803988 DOI: 10.1136/jmg-2023-109389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/23/2023] [Indexed: 08/19/2023]
Abstract
BACKGROUND Multigene panel testing by next-generation sequencing (MGP-NGS) enables the detection of germline pathogenic or likely pathogenic variants (PVs/LPVs) in genes beyond those associated with a certain cancer phenotype. Opportunistic genetic screening based on MGP-NGS in patients with suspicion of hereditary cancer reveals these incidental findings (IFs). METHODS MGP-NGS was performed in patients who fulfilled the clinical criteria to undergo genetic testing according to the Catalan Health Service guidelines. Variants were classified following the American College of Medical Genetics and Genomics-Association for Molecular Pathology guidelines and the Cancer Variant Interpretation Group UK guidelines. RESULTS IFs were identified in 10 (1.22%) of the 817 patients who underwent MGP-NGS. The mean age at cancer diagnosis was 49.4±9.5 years. Three IFs (30.0%) were detected in PMS2, two (20.0%) in ATM and TP53 and one (10.0%) in MSH6, NTHL1 and VHL. Seven (70.0%) IFs were single-nucleotide substitutions, two (20.0%) were deletions and one (10.0%) was a duplication. Three (30.0) IFs were located in intronic regions, three (30.3%) were nonsense, two (20.0%) were frameshift and two (20.0%) were missense variations. Six (60.0%) IFs were classified as PVs and four (40.0%) as LPVs. CONCLUSIONS Opportunistic genetic screening increased the diagnostic yield by 1.22% in our cohort. Most of the identified IFs were present in clinically actionable genes (n=7; 70.0%), providing these families with an opportunity to join cancer early detection programmes, as well as secondary cancer prevention. IFs might facilitate the diagnosis of asymptomatic individuals and the early management of cancer once it develops.
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Affiliation(s)
- Sara Fernández-Castillejo
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Bàrbara Roig
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Mireia Melé
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Sara Serrano
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Mònica Salvat
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Montserrat Querol
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL and Biomedical Research Centre Network for Oncology (CIBERONC), L'Hospitalet de Llobregat, Spain
- Hereditary Cancer Program, Catalan Institute of Oncology-IDIBGI, Girona, Spain
| | - Marta Pineda
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL and Biomedical Research Centre Network for Oncology (CIBERONC), L'Hospitalet de Llobregat, Spain
| | - Adela Cisneros
- Hematology Department, ICO and Hospital Germans Trias i Pujol, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - David Parada
- Pathology Molecular Unit, Department of Pathology, Hospital Universitari Sant Joan de Reus (HUSJR), Spain. Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Joan Badia
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Joan Borràs
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Marta Rodríguez-Balada
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
| | - Josep Gumà
- Institut d'Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. Universitat Rovira i Virgili (URV), Reus, Spain
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22
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Huang H, Hu C, Na J, Hart SN, Gnanaolivu RD, Abozaid M, Rao T, Tecleab YA, Pesaran T, Lyra PCM, Karam R, Yadav S, Domchek SM, de la Hoya M, Robson M, Mehine M, Bandlamudi C, Mandelker D, Monteiro ANA, Boddicker N, Chen W, Richardson ME, Couch FJ. Saturation genome editing-based functional evaluation and clinical classification of BRCA2 single nucleotide variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.14.571597. [PMID: 38168194 PMCID: PMC10760149 DOI: 10.1101/2023.12.14.571597] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Germline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to breast, ovarian, prostate and pancreatic cancer. However, variants of uncertain significance (VUS) (n>4000) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants. Here we report on comprehensive saturation genome editing-based functional characterization of 97% of all possible single nucleotide variants (SNVs) in the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants that is encoded by exons 15 to 26. The assay was based on deep sequence analysis of surviving endogenously targeted haploid cells. A total of 7013 SNVs were characterized as functionally abnormal (n=955), intermediate/uncertain, or functionally normal (n=5224) based on 95% agreement with ClinVar known pathogenic and benign standards. Results were validated relative to batches of nonsense and synonymous variants and variants evaluated using a homology directed repair (HDR) functional assay. Breast cancer case-control association studies showed that pooled SNVs encoding functionally abnormal missense variants were associated with increased risk of breast cancer (odds ratio (OR) 3.89, 95%CI: 2.77-5.51). In addition, 86% of tumors associated with abnormal missense SNVs displayed loss of heterozygosity (LOH), whereas 26% of tumors with normal variants had LOH. The functional data were added to other sources of information in a ClinGen/ACMG/AMP-like model and 700 functionally abnormal SNVs, including 220 missense SNVs, were classified as pathogenic or likely pathogenic, while 4862 functionally normal SNVs, including 3084 missense SNVs, were classified as benign or likely benign. These classified variants can now be used for risk assessment and clinical care of variant carriers and the remaining functional scores can be used directly for clinical classification and interpretation of many additional variants. Summary Germline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to several types of cancer. However, variants of uncertain significance (VUS) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants to facilitate current and future clinical management of individuals with these variants. Here we show the results from a saturation genome editing (SGE) and functional analysis of all possible single nucleotide variants (SNVs) from exons 15 to 26 that encode the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants. The assay was based on deep sequence analysis of surviving endogenously targeted human haploid HAP1 cells. The assay was calibrated relative to ClinVar known pathogenic and benign missense standards and 95% prevalence thresholds for functionally abnormal and normal variants were identified. Thresholds were validated based on nonsense and synonymous variants. SNVs encoding functionally abnormal missense variants were associated with increased risks of breast and ovarian cancer. The functional assay results were integrated into a ClinGen/ACMG/AMP-like model for clinical classification of the majority of BRCA2 SNVs as pathogenic/likely pathogenic or benign/likely benign. The classified variants can be used for improved clinical management of variant carriers.
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23
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Notin P, Kollasch AW, Ritter D, van Niekerk L, Paul S, Spinner H, Rollins N, Shaw A, Weitzman R, Frazer J, Dias M, Franceschi D, Orenbuch R, Gal Y, Marks DS. ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.07.570727. [PMID: 38106144 PMCID: PMC10723403 DOI: 10.1101/2023.12.07.570727] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.
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Affiliation(s)
| | | | | | | | | | | | | | - Ada Shaw
- Applied Mathematics, Harvard University
| | | | | | - Mafalda Dias
- Centre for Genomic Regulation, Universitat Pompeu Fabra
| | | | | | - Yarin Gal
- Computer Science, University of Oxford
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24
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Flagg MP, Lam B, Lam DK, Le TM, Kao A, Slaiwa YI, Hampton RY. Exploring the "misfolding problem" by systematic discovery and analysis of functional-but-degraded proteins. Mol Biol Cell 2023; 34:ar125. [PMID: 37729018 PMCID: PMC10848938 DOI: 10.1091/mbc.e23-06-0248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/08/2023] [Accepted: 09/11/2023] [Indexed: 09/22/2023] Open
Abstract
In both health and disease, the ubiquitin-proteasome system (UPS) degrades point mutants that retain partial function but have decreased stability compared with their wild-type counterparts. This class of UPS substrate includes routine translational errors and numerous human disease alleles, such as the most common cause of cystic fibrosis, ΔF508-CFTR. Yet, there is no systematic way to discover novel examples of these "minimally misfolded" substrates. To address that shortcoming, we designed a genetic screen to isolate functional-but-degraded point mutants, and we used the screen to study soluble, monomeric proteins with known structures. These simple parent proteins yielded diverse substrates, allowing us to investigate the structural features, cytotoxicity, and small-molecule regulation of minimal misfolding. Our screen can support numerous lines of inquiry, and it provides broad access to a class of poorly understood but biomedically critical quality-control substrates.
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Affiliation(s)
- Matthew P. Flagg
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Breanna Lam
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Darren K. Lam
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Tiffany M. Le
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Andy Kao
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Yousif I. Slaiwa
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
| | - Randolph Y. Hampton
- Division of Biological Sciences, the Section of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093
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25
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Maes S, Deploey N, Peelman F, Eyckerman S. Deep mutational scanning of proteins in mammalian cells. CELL REPORTS METHODS 2023; 3:100641. [PMID: 37963462 PMCID: PMC10694495 DOI: 10.1016/j.crmeth.2023.100641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/06/2023] [Accepted: 10/20/2023] [Indexed: 11/16/2023]
Abstract
Protein mutagenesis is essential for unveiling the molecular mechanisms underlying protein function in health, disease, and evolution. In the past decade, deep mutational scanning methods have evolved to support the functional analysis of nearly all possible single-amino acid changes in a protein of interest. While historically these methods were developed in lower organisms such as E. coli and yeast, recent technological advancements have resulted in the increased use of mammalian cells, particularly for studying proteins involved in human disease. These advancements will aid significantly in the classification and interpretation of variants of unknown significance, which are being discovered at large scale due to the current surge in the use of whole-genome sequencing in clinical contexts. Here, we explore the experimental aspects of deep mutational scanning studies in mammalian cells and report the different methods used in each step of the workflow, ultimately providing a useful guide toward the design of such studies.
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Affiliation(s)
- Stefanie Maes
- VIB Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium; Department of Biochemistry and Microbiology, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium
| | - Nick Deploey
- VIB Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium
| | - Frank Peelman
- VIB Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium
| | - Sven Eyckerman
- VIB Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium.
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26
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Ljungdahl A, Kohani S, Page NF, Wells ES, Wigdor EM, Dong S, Sanders SJ. AlphaMissense is better correlated with functional assays of missense impact than earlier prediction algorithms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.24.562294. [PMID: 37961354 PMCID: PMC10634779 DOI: 10.1101/2023.10.24.562294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Missense variants that alter a single amino acid in the encoded protein contribute to many human disorders but pose a substantial challenge in interpretation. Though these variants can be reliably identified through sequencing, distinguishing the clinically significant ones remains difficult, such that "Variants of Unknown Significance" outnumber those classified as "Pathogenic" or "Likely Pathogenic." Numerous in silico approaches have been developed to predict the functional impact of missense variants to inform clinical interpretation, the latest being AlphaMissense, which uses artificial intelligence methods trained on predicted protein structure. To independently assess the performance of AlphaMissense and 38 other predictors of missense severity, we compared predictions to data from multiplexed assays of variant effect (MAVE). MAVE experiments generate almost every possible individual amino acid change in a gene and measure their functional impact using a high-throughput assay. Assessing 17,696 variants across five genes (DDX3X, MSH2, PTEN, KCNQ4, and BRCA1), we find that AlphaMissense is consistently one of the top five algorithms based on correlation with functional impact and is the best-correlated algorithm for two genes. We conclude that AlphaMissense represents the current best-in-class predictor by this metric; however, the improvement over other algorithms is modest. We note that multiple missense predictors, including AlphaMissense, appear to overcall variants as pathogenic despite minimal functional impact and that substantially more high-quality training data, including consistently analyzed patient cohorts and MAVE analyses, are required to improve accuracy.
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Affiliation(s)
- Alicia Ljungdahl
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Sayeh Kohani
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
| | - Nicholas F. Page
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Eloise S. Wells
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
| | - Emilie M. Wigdor
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
| | - Shan Dong
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Stephan J. Sanders
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
- New York Genome Center, New York, NY 10013, USA
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27
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Walker R, Mahmood K, Como J, Clendenning M, Joo JE, Georgeson P, Joseland S, Preston SG, Pope BJ, Chan JM, Austin R, Bojadzieva J, Campbell A, Edwards E, Gleeson M, Goodwin A, Harris MT, Ip E, Kirk J, Mansour J, Mar Fan H, Nichols C, Pachter N, Ragunathan A, Spigelman A, Susman R, Christie M, Jenkins MA, Pai RK, Rosty C, Macrae FA, Winship IM, Buchanan DD. DNA Mismatch Repair Gene Variant Classification: Evaluating the Utility of Somatic Mutations and Mismatch Repair Deficient Colonic Crypts and Endometrial Glands. Cancers (Basel) 2023; 15:4925. [PMID: 37894291 PMCID: PMC10605939 DOI: 10.3390/cancers15204925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/03/2023] [Accepted: 10/03/2023] [Indexed: 10/29/2023] Open
Abstract
Germline pathogenic variants in the DNA mismatch repair (MMR) genes (Lynch syndrome) predispose to colorectal (CRC) and endometrial (EC) cancer. Lynch syndrome specific tumor features were evaluated for their ability to support the ACMG/InSiGHT framework in classifying variants of uncertain clinical significance (VUS) in the MMR genes. Twenty-eight CRC or EC tumors from 25 VUS carriers (6xMLH1, 9xMSH2, 6xMSH6, 4xPMS2), underwent targeted tumor sequencing for the presence of microsatellite instability/MMR-deficiency (MSI-H/dMMR) status and identification of a somatic MMR mutation (second hit). Immunohistochemical testing for the presence of dMMR crypts/glands in normal tissue was also performed. The ACMG/InSiGHT framework reclassified 7/25 (28%) VUS to likely pathogenic (LP), three (12%) to benign/likely benign, and 15 (60%) VUS remained unchanged. For the seven re-classified LP variants comprising nine tumors, tumor sequencing confirmed MSI-H/dMMR (8/9, 88.9%) and a second hit (7/9, 77.8%). Of these LP reclassified variants where normal tissue was available, the presence of a dMMR crypt/gland was found in 2/4 (50%). Furthermore, a dMMR endometrial gland in a carrier of an MSH2 exon 1-6 duplication provides further support for an upgrade of this VUS to LP. Our study confirmed that identifying these Lynch syndrome features can improve MMR variant classification, enabling optimal clinical care.
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Affiliation(s)
- Romy Walker
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Khalid Mahmood
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
- Melbourne Bioinformatics, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Julia Como
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Mark Clendenning
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Jihoon E. Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Sharelle Joseland
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Susan G. Preston
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Bernard J. Pope
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
- Melbourne Bioinformatics, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - James M. Chan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Rachel Austin
- Genetic Health Queensland, Royal Brisbane and Women’s Hospital, Brisbane, QLD 4006, Australia; (R.A.); (H.M.F.)
| | - Jasmina Bojadzieva
- Clinical Genetics Unit, Austin Health, Melbourne, VIC 3084, Australia; (J.B.); (A.C.)
| | - Ainsley Campbell
- Clinical Genetics Unit, Austin Health, Melbourne, VIC 3084, Australia; (J.B.); (A.C.)
| | - Emma Edwards
- Familial Cancer Service, Westmead Hospital, Sydney, NSW 2145, Australia;
| | - Margaret Gleeson
- Hunter Family Cancer Service, Newcastle, NSW 2298, Australia; (M.G.); (J.K.); (A.R.)
| | - Annabel Goodwin
- Cancer Genetics Department, Royal Prince Alfred Hospital, Camperdown, NSW 2050, Australia; (A.G.); (A.S.)
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2050, Australia
| | - Marion T. Harris
- Monash Health Familial Cancer Centre, Clayton, VIC 3168, Australia;
| | - Emilia Ip
- Cancer Genetics Service, Liverpool Hospital, Liverpool, NSW 2170, Australia;
| | - Judy Kirk
- Hunter Family Cancer Service, Newcastle, NSW 2298, Australia; (M.G.); (J.K.); (A.R.)
| | - Julia Mansour
- Tasmanian Clinical Genetics Service, Royal Hobart Hospital, Hobart, TAS 7000, Australia;
| | - Helen Mar Fan
- Genetic Health Queensland, Royal Brisbane and Women’s Hospital, Brisbane, QLD 4006, Australia; (R.A.); (H.M.F.)
| | - Cassandra Nichols
- Genetic Services of Western Australia, King Edward Memorial Hospital, Perth, WA 6008, Australia; (C.N.); (N.P.)
| | - Nicholas Pachter
- Genetic Services of Western Australia, King Edward Memorial Hospital, Perth, WA 6008, Australia; (C.N.); (N.P.)
- Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA 6009, Australia
- School of Medicine, Curtin University, Perth, WA 6102, Australia
| | - Abiramy Ragunathan
- Hunter Family Cancer Service, Newcastle, NSW 2298, Australia; (M.G.); (J.K.); (A.R.)
| | - Allan Spigelman
- Cancer Genetics Department, Royal Prince Alfred Hospital, Camperdown, NSW 2050, Australia; (A.G.); (A.S.)
- St Vincent’s Cancer Genetics Unit, Sydney, NSW 2010, Australia
- Surgical Professorial Unit, UNSW Clinical School of Clinical Medicine, Sydney, NSW 2052, Australia
| | - Rachel Susman
- Genetic Health Queensland, Royal Brisbane and Women’s Hospital, Brisbane, QLD 4006, Australia; (R.A.); (H.M.F.)
| | - Michael Christie
- Department of Medicine, Royal Melbourne Hospital, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia;
- Department of Pathology, The Royal Melbourne Hospital, Melbourne, VIC 3052, Australia
| | - Mark A. Jenkins
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Rish K. Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ 85259, USA;
| | - Christophe Rosty
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
- Envoi Specialist Pathologists, Brisbane, QLD 4059, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD 4072, Australia
| | - Finlay A. Macrae
- Genomic Medicine and Familial Cancer Centre, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia; (F.A.M.); (I.M.W.)
- Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Melbourne, VIC 3052, Australia
- Department of Medicine, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Ingrid M. Winship
- Genomic Medicine and Familial Cancer Centre, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia; (F.A.M.); (I.M.W.)
- Department of Medicine, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia; (K.M.); (J.C.); (M.C.); (J.E.J.); (P.G.); (S.J.); (S.G.P.); (B.J.P.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC 3000, Australia;
- Genomic Medicine and Familial Cancer Centre, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia; (F.A.M.); (I.M.W.)
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O'Neill MJ, Yang T, Laudeman J, Calandranis M, Solus J, Roden DM, Glazer AM. ParSE-seq: A Calibrated Multiplexed Assay to Facilitate the Clinical Classification of Putative Splice-altering Variants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.04.23295019. [PMID: 37732247 PMCID: PMC10508793 DOI: 10.1101/2023.09.04.23295019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Background Interpreting the clinical significance of putative splice-altering variants outside 2-base pair canonical splice sites remains difficult without functional studies. Methods We developed Parallel Splice Effect Sequencing (ParSE-seq), a multiplexed minigene-based assay, to test variant effects on RNA splicing quantified by high-throughput sequencing. We studied variants in SCN5A, an arrhythmia-associated gene which encodes the major cardiac voltage-gated sodium channel. We used the computational tool SpliceAI to prioritize exonic and intronic candidate splice variants, and ClinVar to select benign and pathogenic control variants. We generated a pool of 284 barcoded minigene plasmids, transfected them into Human Embryonic Kidney (HEK293) cells and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), sequenced the resulting pools of splicing products, and calibrated the assay to the American College of Medical Genetics and Genomics scheme. Variants were interpreted using the calibrated functional data, and experimental data were compared to SpliceAI predictions. We further studied some splice-altering missense variants by cDNA-based automated patch clamping (APC) in HEK cells and assessed splicing and sodium channel function in CRISPR-edited iPSC-CMs. Results ParSE-seq revealed the splicing effect of 224 SCN5A variants in iPSC-CMs and 244 variants in HEK293 cells. The scores between the cell types were highly correlated (R2=0.84). In iPSCs, the assay had concordant scores for 21/22 benign/likely benign and 24/25 pathogenic/likely pathogenic control variants from ClinVar. 43/112 exonic variants and 35/70 intronic variants with determinate scores disrupted splicing. 11 of 42 variants of uncertain significance were reclassified, and 29 of 34 variants with conflicting interpretations were reclassified using the functional data. SpliceAI computational predictions correlated well with experimental data (AUC = 0.96). We identified 20 unique SCN5A missense variants that disrupted splicing, and 2 clinically observed splice-altering missense variants of uncertain significance had normal function when tested with the cDNA-based APC assay. A splice-altering intronic variant detected by ParSE-seq, c.1891-5C>G, also disrupted splicing and sodium current when introduced into iPSC-CMs at the endogenous locus by CRISPR editing. Conclusions ParSE-seq is a calibrated, multiplexed, high-throughput assay to facilitate the classification of candidate splice-altering variants.
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Affiliation(s)
| | - Tao Yang
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Julie Laudeman
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Maria Calandranis
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Joseph Solus
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Dan M Roden
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Andrew M Glazer
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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Livesey BJ, Marsh JA. Updated benchmarking of variant effect predictors using deep mutational scanning. Mol Syst Biol 2023; 19:e11474. [PMID: 37310135 PMCID: PMC10407742 DOI: 10.15252/msb.202211474] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 05/30/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
The assessment of variant effect predictor (VEP) performance is fraught with biases introduced by benchmarking against clinical observations. In this study, building on our previous work, we use independently generated measurements of protein function from deep mutational scanning (DMS) experiments for 26 human proteins to benchmark 55 different VEPs, while introducing minimal data circularity. Many top-performing VEPs are unsupervised methods including EVE, DeepSequence and ESM-1v, a protein language model that ranked first overall. However, the strong performance of recent supervised VEPs, in particular VARITY, shows that developers are taking data circularity and bias issues seriously. We also assess the performance of DMS and unsupervised VEPs for discriminating between known pathogenic and putatively benign missense variants. Our findings are mixed, demonstrating that some DMS datasets perform exceptionally at variant classification, while others are poor. Notably, we observe a striking correlation between VEP agreement with DMS data and performance in identifying clinically relevant variants, strongly supporting the validity of our rankings and the utility of DMS for independent benchmarking.
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Affiliation(s)
- Benjamin J Livesey
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Joseph A Marsh
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
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30
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Johnson A, Ng PKS, Kahle M, Castillo J, Amador B, Wang Y, Zeng J, Holla V, Vu T, Su F, Kim SH, Conway T, Jiang X, Chen K, Shaw KRM, Yap TA, Rodon J, Mills GB, Meric-Bernstam F. Actionability classification of variants of unknown significance correlates with functional effect. NPJ Precis Oncol 2023; 7:67. [PMID: 37454202 DOI: 10.1038/s41698-023-00420-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 07/03/2023] [Indexed: 07/18/2023] Open
Abstract
Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either "Unknown" or "Potentially" actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.
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Affiliation(s)
- Amber Johnson
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Patrick Kwok-Shing Ng
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael Kahle
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Julia Castillo
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Bianca Amador
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yujia Wang
- Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jia Zeng
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Vijaykumar Holla
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Thuy Vu
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fei Su
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sun-Hee Kim
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tara Conway
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xianli Jiang
- Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ken Chen
- Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kenna R Mills Shaw
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Timothy A Yap
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Investigational Cancer Therapeutics (Phase I Program), The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jordi Rodon
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Investigational Cancer Therapeutics (Phase I Program), The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gordon B Mills
- Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA
| | - Funda Meric-Bernstam
- Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Investigational Cancer Therapeutics (Phase I Program), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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Kristmundsdottir S, Jonsson H, Hardarson MT, Palsson G, Beyter D, Eggertsson HP, Gylfason A, Sveinbjornsson G, Holley G, Stefansson OA, Halldorsson GH, Olafsson S, Arnadottir GA, Olason PI, Eiriksson O, Masson G, Thorsteinsdottir U, Rafnar T, Sulem P, Helgason A, Gudbjartsson DF, Halldorsson BV, Stefansson K. Sequence variants affecting the genome-wide rate of germline microsatellite mutations. Nat Commun 2023; 14:3855. [PMID: 37386006 PMCID: PMC10310707 DOI: 10.1038/s41467-023-39547-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 06/16/2023] [Indexed: 07/01/2023] Open
Abstract
Microsatellites are polymorphic tracts of short tandem repeats with one to six base-pair (bp) motifs and are some of the most polymorphic variants in the genome. Using 6084 Icelandic parent-offspring trios we estimate 63.7 (95% CI: 61.9-65.4) microsatellite de novo mutations (mDNMs) per offspring per generation, excluding one bp repeats motifs (homopolymers) the estimate is 48.2 mDNMs (95% CI: 46.7-49.6). Paternal mDNMs occur at longer repeats than maternal ones, which are in turn larger with a mean size of 3.4 bp vs 3.1 bp for paternal ones. mDNMs increase by 0.97 (95% CI: 0.90-1.04) and 0.31 (95% CI: 0.25-0.37) per year of father's and mother's age at conception, respectively. Here, we find two independent coding variants that associate with the number of mDNMs transmitted to offspring; The minor allele of a missense variant (allele frequency (AF) = 1.9%) in MSH2, a mismatch repair gene, increases transmitted mDNMs from both parents (effect: 13.1 paternal and 7.8 maternal mDNMs). A synonymous variant (AF = 20.3%) in NEIL2, a DNA damage repair gene, increases paternally transmitted mDNMs (effect: 4.4 mDNMs). Thus, the microsatellite mutation rate in humans is in part under genetic control.
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Affiliation(s)
- Snaedis Kristmundsdottir
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | - Marteinn T Hardarson
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | - Doruk Beyter
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
| | | | | | | | | | | | - Gisli H Halldorsson
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Gudny A Arnadottir
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Gisli Masson
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Agnar Helgason
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics / Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Bjarni V Halldorsson
- deCODE genetics / Amgen Inc., Reykjavik, Iceland.
- School of Technology, Reykjavik University, Reykjavik, Iceland.
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Li C, Wilborn J, Pittman S, Daw J, Alonso-Pérez J, Díaz-Manera J, Weihl CC, Haller G. Comprehensive functional characterization of SGCB coding variants predicts pathogenicity in limb-girdle muscular dystrophy type R4/2E. J Clin Invest 2023; 133:e168156. [PMID: 37317968 PMCID: PMC10266784 DOI: 10.1172/jci168156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 04/27/2023] [Indexed: 06/16/2023] Open
Abstract
Genetic testing is essential for patients with a suspected hereditary myopathy. More than 50% of patients clinically diagnosed with a myopathy carry a variant of unknown significance in a myopathy gene, often leaving them without a genetic diagnosis. Limb-girdle muscular dystrophy (LGMD) type R4/2E is caused by mutations in β-sarcoglycan (SGCB). Together, β-, α-, γ-, and δ-sarcoglycan form a 4-protein transmembrane complex (SGC) that localizes to the sarcolemma. Biallelic loss-of-function mutations in any subunit can lead to LGMD. To provide functional evidence for the pathogenicity of missense variants, we performed deep mutational scanning of SGCB and assessed SGC cell surface localization for all 6,340 possible amino acid changes. Variant functional scores were bimodally distributed and perfectly predicted pathogenicity of known variants. Variants with less severe functional scores more often appeared in patients with slower disease progression, implying a relationship between variant function and disease severity. Amino acid positions intolerant to variation mapped to points of predicted SGC interactions, validated in silico structural models, and enabled accurate prediction of pathogenic variants in other SGC genes. These results will be useful for clinical interpretation of SGCB variants and improving diagnosis of LGMD; we hope they enable wider use of potentially life-saving gene therapy.
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Affiliation(s)
| | - Jackson Wilborn
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | | | - Jorge Alonso-Pérez
- Neuromuscular Disease Unit, Neurology Department, Hospital Universitario Nuestra Señora de Candelaria, Fundación Canaria Instituto de Investigación Sanitaria de Canarias, Tenerife, Spain
| | - Jordi Díaz-Manera
- John Walton Muscular Dystrophy Research Center, Newcastle University, Newcastle Upon Tyne, United Kingdom
| | | | - Gabe Haller
- Department of Neurology and
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
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Wilcox JE, Beussink-Nelson L, Cao J, Kumar R, Jordan E, Ni H, Shah SJ, Hershberger RE, Kinnamon DD. Differences in Cardiac Mechanics among Genetically At-Risk First-Degree Relatives: The DCM Precision Medicine Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.30.23290123. [PMID: 37398079 PMCID: PMC10312893 DOI: 10.1101/2023.05.30.23290123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Aims Among genetically at-risk first-degree relatives (FDRs) of probands with dilated cardiomyopathy (DCM), the ability to detect changes in left ventricular (LV) mechanics with normal LV size and ejection fraction (LVEF) remains incompletely explored. We sought to define a pre-DCM phenotype among at-risk FDRs, including those with variants of uncertain significance (VUSs), using echocardiographic measures of cardiac mechanics. Methods and Results LV structure and function, including speckle-tracking analysis for LV global longitudinal strain (GLS), were evaluated in 124 FDRs (65% female; median age 44.9 [IQR: 30.6-60.3] years) of 66 DCM probands of European ancestry sequenced for rare variants in 35 DCM genes. FDRs had normal LV size and LVEF. Negative FDRs of probands with pathogenic or likely pathogenic (P/LP) variants (n=28) were a reference group to which negative FDRs of probands without P/LP variants (n=30), FDRs with only VUSs (n=27), and FDRs with P/LP variants (n=39) were compared. In an analysis accounting for age-dependent penetrance, FDRs below the median age showed minimal differences in LV GLS across groups while those above it with P/LP variants or VUSs had lower absolute values than the reference group (-3.9 [95% CI: -5.7, -2.1] or -3.1 [-4.8, -1.4] %-units) and negative FDRs of probands without P/LP variants (-2.6 [-4.0, -1.2] or -1.8 [-3.1, -0.6]). Conclusions Older FDRs with normal LV size and LVEF who harbored P/LP variants or VUSs had lower absolute LV GLS values, indicating that some DCM-related VUSs are clinically relevant. LV GLS may have utility for defining a pre-DCM phenotype. Clinical Trial Registration clinicaltrials.gov, NCT03037632.
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Affiliation(s)
- Jane E. Wilcox
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Lauren Beussink-Nelson
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Jinwen Cao
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, OH
- The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH
| | - Ritika Kumar
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Elizabeth Jordan
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, OH
- The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH
| | - Hanyu Ni
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, OH
- The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH
| | - Sanjiv J. Shah
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Ray E. Hershberger
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, OH
- The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH
- Division of Cardiovascular Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH
| | - Daniel D. Kinnamon
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, OH
- The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH
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34
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Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, Fiziev PP, Kuderna LFK, Sundaram L, Wu Y, Adhikari A, Field Y, Chen C, Batzoglou S, Aguet F, Lemire G, Reimers R, Balick D, Janiak MC, Kuhlwilm M, Orkin JD, Manu S, Valenzuela A, Bergman J, Rousselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath JE, Hvilsom C, Juan D, Frandsen P, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, do Amaral JV, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Bataillon T, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin A, Guschanski K, Schierup MH, Beck RMD, Umapathy G, Roos C, Boubli JP, Lek M, Sunyaev S, O'Donnell-Luria A, Rehm HL, Xu J, Rogers J, Marques-Bonet T, Farh KKH. The landscape of tolerated genetic variation in humans and primates. Science 2023; 380:eabn8153. [PMID: 37262156 DOI: 10.1126/science.abn8197] [Citation(s) in RCA: 52] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/22/2023] [Indexed: 06/03/2023]
Abstract
Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.
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Affiliation(s)
- Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Tobias Hamp
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Jeffrey Ede
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Joshua G Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Jeremy McRae
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Moriel Singer-Berk
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
| | - Yanshen Yang
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | | | - Petko P Fiziev
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Lukas F K Kuderna
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Laksshman Sundaram
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Yibing Wu
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Aashish Adhikari
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Yair Field
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Chen Chen
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Serafim Batzoglou
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Francois Aguet
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Rebecca Reimers
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel Balick
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Mareike C Janiak
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Martin Kuhlwilm
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, 1030 Vienna, Austria
| | - Joseph D Orkin
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Département d'anthropologie, Université de Montréal, 3150 Jean-Brillant, Montréal, QC H3T 1N8, Canada
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Alejandro Valenzuela
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University, 8000 Aarhus, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development, Estrada da Bexiga 2584, Tefé, Amazonas, CEP 69553-225, Brazil
- Evolutionary Biology and Ecology (EBE), Département de Biologie des Organismes, Université libre de Bruxelles (ULB), Av. Franklin D. Roosevelt 50, CP 160/12, B-1050 Brussels, Belgium
| | - Lidia Agueda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Ian Goodhead
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - R Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
| | | | - Julie E Horvath
- North Carolina Museum of Natural Sciences, Raleigh, NC 27601, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | | | - Fabrício Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah, Salt Lake City, UT 84102, USA
| | - Iracilda Sampaio
- Universidade Federal do Para, Guamá, Belém - PA, 66075-110, Brazil
| | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
| | - João Valsecchi do Amaral
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development, Tefé, Amazonas, 69553-225, Brazil
- Rede de Pesquisa para Estudos sobre Diversidade, Conservação e Uso da Fauna na Amazônia - RedeFauna, Manaus, Amazonas, 69080-900, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica - ComFauna, Iquitos, Loreto, 16001, Peru
| | - Mariluce Messias
- Universidade Federal de Rondonia, Porto Velho, Rondônia, 78900-000, Brazil
- PPGREN - Programa de Pós-Graduação "Conservação e Uso dos Recursos Naturais and BIONORTE - Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Rede BIONORTE, Universidade Federal de Rondonia, Porto Velho, Rondônia, 78900-000, Brazil
| | - Maria N F da Silva
- Instituto Nacional de Pesquisas da Amazonia, Petrópolis, Manaus - AM, 69067-375, Brazil
| | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Rogerio Rossi
- Universidade Federal do Mato Grosso, Boa Esperança, Cuiabá - MT, 78060-900, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas, 69080-900, Brazil
- Department of Biology, Trinity University, San Antonio, TX 78212, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | - Clément J Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, 401, Madagascar
| | | | | | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Christian Abee
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Joe H Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Eduardo Fernandez-Duque
- Yale University, New Haven, CT 06520, USA
- Universidad Nacional de Formosa, Argentina Fundacion ECO, Formosa, Argentina
| | | | - Fekadu Shiferaw
- Guinea Worm Eradication Program, The Carter Center Ethiopia, PoB 16316, Addis Ababa 1000, Ethiopia
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
- Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Shangcheng District, Hangzhou 310006, China
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Head Office, P.O. Box 661, Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, 17493 Greifswald - Insei Riems, Germany
| | - Minh D Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University, Hanoi 100000, Vietnam
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart, 70191 Stuttgart, Germany
| | - Arcadi Navarro
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Av. Doctor Aiguader, N88, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C. Wellington 30, 08005 Barcelona, Spain
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
| | - Tilo Nadler
- Cuc Phuong Commune, Nho Quan District, Ninh Binh Province 430000, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
| | - Jessica Lee
- Mandai Nature, 80 Mandai Lake Road, Singapore 729826, Republic of Singapore
| | - Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore 168582, Republic of Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore 168582, Republic of Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore 168582, Republic of Singapore
| | - Andrew C Kitchener
- Department of Natural Sciences, National Museums Scotland, Chambers Street, Edinburgh EH1 1JF, UK
- School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077 Göttingen, Germany
- Leibniz Science Campus Primate Cognition, 37077 Göttingen, Germany
| | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra, Pg. Luís Companys 23, 08010 Barcelona, Spain
| | - Amanda Melin
- Department of Anthropology & Archaeology, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
- Department of Medical Genetics, 3330 Hospital Drive NW, HMRB 202, Calgary, AB T2N 4N1, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH8 9XP, UK
| | | | - Robin M D Beck
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Jean P Boubli
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Shamil Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jinbo Xu
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA
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35
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Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich A, Fiziev P, Kuderna L, Sundaram L, Wu Y, Adhikari A, Field Y, Chen C, Batzoglou S, Aguet F, Lemire G, Reimers R, Balick D, Janiak MC, Kuhlwilm M, Orkin JD, Manu S, Valenzuela A, Bergman J, Rouselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath J, Hvilsom C, Juan D, Frandsen P, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, do Amaral JV, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Batallion T, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin A, Guschanski K, Schierup MH, Beck RMD, Umapathy G, Roos C, Boubli JP, Lek M, Sunyaev S, O’Donnell A, Rehm H, Xu J, Rogers J, Marques-Bonet T, Kai-How Farh K. The landscape of tolerated genetic variation in humans and primates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.01.538953. [PMID: 37205491 PMCID: PMC10187174 DOI: 10.1101/2023.05.01.538953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence Summary Deep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.
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Affiliation(s)
- Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Tobias Hamp
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Jeffrey Ede
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Joshua G. Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Jeremy McRae
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Moriel Singer-Berk
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
| | - Yanshen Yang
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Anastasia Dietrich
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Petko Fiziev
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Lukas Kuderna
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Laksshman Sundaram
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Yibing Wu
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Aashish Adhikari
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Yair Field
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Chen Chen
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Serafim Batzoglou
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Francois Aguet
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Rebecca Reimers
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Daniel Balick
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Mareike C. Janiak
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Martin Kuhlwilm
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna; Djerassiplatz 1, 1030, Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna; 1030, Vienna, Austria
| | - Joseph D. Orkin
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Département d’anthropologie, Université de Montréal; 3150 Jean-Brillant, Montréal, QC, H3T 1N8, Canada
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR); Ghaziabad, 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Alejandro Valenzuela
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University; Aarhus, 8000, Denmark
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University; Aarhus, 8000, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development; Estrada da Bexiga 2584, Tefé, Amazonas, CEP 69553-225, Brazil
- Faculty of Sciences, Department of Organismal Biology, Unit of Evolutionary Biology and Ecology, Université Libre de Bruxelles (ULB); Avenue Franklin D. Roosevelt 50, 1050, Brussels, Belgium
| | - Lidia Agueda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Ian Goodhead
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - R. Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University; SE-75236, Uppsala, Sweden
| | | | - Julie Horvath
- North Carolina Museum of Natural Sciences; Raleigh, North Carolina, 27601, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University; Durham, North Carolina , 27707, USA
- Department of Biological Sciences, North Carolina State University; Raleigh, North Carolina , 27695, USA
- Department of Evolutionary Anthropology, Duke University; Durham, North Carolina , 27708, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | | | - Fabricio Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah; Salt Lake City, Utah, 84102, USA
| | - Iracilda Sampaio
- Universidade Federal do Para; Guamá, Belém - PA, 66075-110, Brazil
| | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
| | - João Valsecchi do Amaral
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development; Tefé, Amazonas, 69553-225, Brazil
- Rede de Pesquisa para Estudos sobre Diversidade, Conservação e Uso da Fauna na Amazônia – RedeFauna; Manaus, Amazonas, 69080-900, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica – ComFauna; Iquitos, Loreto, 16001, Peru
| | - Mariluce Messias
- Universidade Federal de Rondonia; Porto Velho, Rondônia, 78900-000, Brazil
- PPGREN - Programa de Pós-Graduação “Conservação e Uso dos Recursos Naturais and BIONORTE - Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Rede BIONORTE, Universidade Federal de Rondonia; Porto Velho, Rondônia, 78900-000, Brazil
| | - Maria N. F. da Silva
- Instituto Nacional de Pesquisas da Amazonia; Petrópolis, Manaus - AM, 69067-375, Brazil
| | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Rogerio Rossi
- Universidade Federal do Mato Grosso; Boa Esperança, Cuiabá - MT, 78060-900, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL); Manaus, Amazonas, 69080-900, Brazil
- Department of Biology, Trinity University; San Antonio, Texas, 78212, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | - Clément J. Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga; Mahajanga, 401, Madagascar
| | | | | | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center; Houston, Texas, 77030, USA
| | | | - Joe H. Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center; Houston, Texas, 77030, USA
| | - Eduardo Fernandez-Duque
- Yale University; New Haven, Connecticut, 06520, USA
- Universidad Nacional de Formosa, Argentina Fundacion ECO, Formosa, Argentina
| | | | | | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences; Kunming, Yunnan, 650223, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences; Kunming, Yunnan, 650223, China
| | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen; Copenhagen, DK-2100, Denmark
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center; 1369 West Wenyi Road, Hangzhou, 311121, China
- Women’s Hospital, School of Medicine, Zhejiang University; 1 Xueshi Road, Shangcheng District, Hangzhou, 310006, China
| | - Julius D. Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Head Office; P.O.Box 661, Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health; 17493 Greifswald - Isle of Riems, Germany
| | - Minh D. Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University; Hanoi, 100000, Vietnam
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain; Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart; 70191 Stuttgart, Germany
| | - Arcadi Navarro
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology; Av. Doctor Aiguader, N88, Barcelona, 08003, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation; C. Wellington 30, Barcelona, 08005, Spain
| | - Thomas Batallion
- Bioinformatics Research Centre, Aarhus University; Aarhus, 8000, Denmark
| | - Tilo Nadler
- Cuc Phuong Commune; Nho Quan District, Ninh Binh Province, 430000, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
| | - Jessica Lee
- Mandai Nature; 80 Mandai Lake Road, Singapore 729826, Republic of Singapore
| | - Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore 138672, Republic of Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM); Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School; Singapore 168582, Republic of Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM); Singapore 168582, Republic of Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School; Singapore 168582, Republic of Singapore
- SingHealth Duke-NUS Genomic Medicine Centre; Singapore 168582, Republic of Singapore
| | - Andrew C. Kitchener
- Department of Natural Sciences, National Museums Scotland; Chambers Street, Edinburgh, EH1 1JF, UK
- School of Geosciences, University of Edinburgh; Drummond Street, Edinburgh, EH8 9XP, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research; 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen; 37077 Göttingen, Germany
| | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
- Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
| | - Amanda Melin
- Leibniz Science Campus Primate Cognition; 37077 Göttingen, Germany
- Department of Anthropology & Archaeology and Department of Medical Genetics
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University; SE-75236, Uppsala, Sweden
- Alberta Children’s Hospital Research Institute; University of Calgary; 2500 University Dr NW T2N 1N4, Calgary, Alberta, Canada
| | | | - Robin M. D. Beck
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR); Ghaziabad, 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology; Hyderabad, 500007, India
| | - Christian Roos
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh; Edinburgh, EH8 9XP, UK
| | - Jean P. Boubli
- School of Science, Engineering & Environment, University of Salford; Salford, M5 4WT, United Kingdom
| | - Monkol Lek
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research; Kellnerweg 4, 37077 Göttingen, Germany
| | - Shamil Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
- Department of Genetics, Yale School of Medicine; New Haven, Connecticut, 06520, USA
| | - Anne O’Donnell
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School; Boston, Massachusetts, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Heidi Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Boston, Massachusetts, 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School; Boston, Massachusetts, 02115, USA
| | - Jinbo Xu
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
- Toyota Technological Institute at Chicago; Chicago, Illinois, 60637, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas, 77030, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC); PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST); Baldiri i Reixac 4, 08028, Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain; Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra, Pg. Luís Companys 23, Barcelona, 08010, Spain
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc.; Foster City, California, 94404, USA
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Luppino F, Adzhubei IA, Cassa CA, Toth-Petroczy A. DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features. Nat Commun 2023; 14:2230. [PMID: 37076482 PMCID: PMC10115847 DOI: 10.1038/s41467-023-37661-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 03/27/2023] [Indexed: 04/21/2023] Open
Abstract
Despite the increasing use of genomic sequencing in clinical practice, the interpretation of rare genetic variants remains challenging even in well-studied disease genes, resulting in many patients with Variants of Uncertain Significance (VUSs). Computational Variant Effect Predictors (VEPs) provide valuable evidence in variant assessment, but they are prone to misclassifying benign variants, contributing to false positives. Here, we develop Deciphering Mutations in Actionable Genes (DeMAG), a supervised classifier for missense variants trained using extensive diagnostic data available in 59 actionable disease genes (American College of Medical Genetics and Genomics Secondary Findings v2.0, ACMG SF v2.0). DeMAG improves performance over existing VEPs by reaching balanced specificity (82%) and sensitivity (94%) on clinical data, and includes a novel epistatic feature, the 'partners score', which leverages evolutionary and structural partnerships of residues. The 'partners score' provides a general framework for modeling epistatic interactions, integrating both clinical and functional information. We provide our tool and predictions for all missense variants in 316 clinically actionable disease genes (demag.org) to facilitate the interpretation of variants and improve clinical decision-making.
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Affiliation(s)
- Federica Luppino
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307, Dresden, Germany
- Center for Systems Biology Dresden, 01307, Dresden, Germany
| | - Ivan A Adzhubei
- Brigham and Women's Hospital Division of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Christopher A Cassa
- Brigham and Women's Hospital Division of Genetics, Harvard Medical School, Boston, MA, 02115, USA.
| | - Agnes Toth-Petroczy
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307, Dresden, Germany.
- Center for Systems Biology Dresden, 01307, Dresden, Germany.
- Cluster of Excellence Physics of Life, TU Dresden, 01062, Dresden, Germany.
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Mao L, Wang Y, An L, Zeng B, Wang Y, Frishman D, Liu M, Chen Y, Tang W, Xu H. Molecular Mechanisms and Clinical Phenotypes of GJB2 Missense Variants. BIOLOGY 2023; 12:biology12040505. [PMID: 37106706 PMCID: PMC10135792 DOI: 10.3390/biology12040505] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 03/29/2023]
Abstract
The GJB2 gene is the most common gene responsible for hearing loss (HL) worldwide, and missense variants are the most abundant type. GJB2 pathogenic missense variants cause nonsyndromic HL (autosomal recessive and dominant) and syndromic HL combined with skin diseases. However, the mechanism by which these different missense variants cause the different phenotypes is unknown. Over 2/3 of the GJB2 missense variants have yet to be functionally studied and are currently classified as variants of uncertain significance (VUS). Based on these functionally determined missense variants, we reviewed the clinical phenotypes and investigated the molecular mechanisms that affected hemichannel and gap junction functions, including connexin biosynthesis, trafficking, oligomerization into connexons, permeability, and interactions between other coexpressed connexins. We predict that all possible GJB2 missense variants will be described in the future by deep mutational scanning technology and optimizing computational models. Therefore, the mechanisms by which different missense variants cause different phenotypes will be fully elucidated.
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Affiliation(s)
- Lu Mao
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Yueqiang Wang
- Basecare Medical Device Co., Ltd., Suzhou 215000, China
| | - Lei An
- Translational Medicine Center, Huaihe Hospital of Henan University, Kaifeng 475000, China
| | - Beiping Zeng
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Yanyan Wang
- The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China
| | - Dmitrij Frishman
- Wissenschaftszentrum Weihenstephan, Technische Universitaet Muenchen, Am Staudengarten 2, 85354 Freising, Germany
| | - Mengli Liu
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Yanyu Chen
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Wenxue Tang
- The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China
| | - Hongen Xu
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450052, China
- The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China
- Correspondence:
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38
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Llargués-Sistac G, Bonjoch L, Castellvi-Bel S. HAP1, a new revolutionary cell model for gene editing using CRISPR-Cas9. Front Cell Dev Biol 2023; 11:1111488. [PMID: 36936678 PMCID: PMC10020200 DOI: 10.3389/fcell.2023.1111488] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/22/2023] [Indexed: 03/06/2023] Open
Abstract
The use of next-generation sequencing (NGS) technologies has been instrumental in the characterization of the mutational landscape of complex human diseases like cancer. But despite the enormous rise in the identification of disease candidate genetic variants, their functionality is yet to be fully elucidated in order to have a clear implication in patient care. Haploid human cell models have become the tool of choice for functional gene studies, since they only contain one copy of the genome and can therefore show the unmasked phenotype of genetic variants. Over the past few years, the human near-haploid cell line HAP1 has widely been consolidated as one of the favorite cell line models for functional genetic studies. Its rapid turnover coupled with the fact that only one allele needs to be modified in order to express the subsequent desired phenotype has made this human cell line a valuable tool for gene editing by CRISPR-Cas9 technologies. This review examines the recent uses of the HAP1 cell line model in functional genetic studies and high-throughput genetic screens using the CRISPR-Cas9 system. It covers its use in an attempt to develop new and relevant disease models to further elucidate gene function, and create new ways to understand the genetic basis of human diseases. We will cover the advantages and potential of the use of CRISPR-Cas9 technology on HAP1 to easily and efficiently study the functional interpretation of gene function and human single-nucleotide genetic variants of unknown significance identified through NGS technologies, and its implications for changes in clinical practice and patient care.
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Affiliation(s)
- Gemma Llargués-Sistac
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Gastroenterology Department, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Hospital Clínic, Barcelona, Spain
| | | | - Sergi Castellvi-Bel
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Gastroenterology Department, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Hospital Clínic, Barcelona, Spain
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39
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Abildgaard AB, Nielsen SV, Bernstein I, Stein A, Lindorff-Larsen K, Hartmann-Petersen R. Lynch syndrome, molecular mechanisms and variant classification. Br J Cancer 2023; 128:726-734. [PMID: 36434153 PMCID: PMC9978028 DOI: 10.1038/s41416-022-02059-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 10/31/2022] [Accepted: 11/02/2022] [Indexed: 11/27/2022] Open
Abstract
Patients with the heritable cancer disease, Lynch syndrome, carry germline variants in the MLH1, MSH2, MSH6 and PMS2 genes, encoding the central components of the DNA mismatch repair system. Loss-of-function variants disrupt the DNA mismatch repair system and give rise to a detrimental increase in the cellular mutational burden and cancer development. The treatment prospects for Lynch syndrome rely heavily on early diagnosis; however, accurate diagnosis is inextricably linked to correct clinical interpretation of individual variants. Protein variant classification traditionally relies on cumulative information from occurrence in patients, as well as experimental testing of the individual variants. The complexity of variant classification is due to (1) that variants of unknown significance are rare in the population and phenotypic information on the specific variants is missing, and (2) that individual variant testing is challenging, costly and slow. Here, we summarise recent developments in high-throughput technologies and computational prediction tools for the assessment of variants of unknown significance in Lynch syndrome. These approaches may vastly increase the number of interpretable variants and could also provide important mechanistic insights into the disease. These insights may in turn pave the road towards developing personalised treatment approaches for Lynch syndrome.
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Affiliation(s)
- Amanda B Abildgaard
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sofie V Nielsen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Inge Bernstein
- Department of Surgical Gastroenterology, Aalborg University Hospital, Aalborg, Denmark
- Institute of Clinical Medicine, Aalborg University Hospital, Aalborg University, Aalborg, Denmark
| | - Amelie Stein
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Rasmus Hartmann-Petersen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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van Loggerenberg W, Sowlati-Hashjin S, Weile J, Hamilton R, Chawla A, Gebbia M, Kishore N, Frésard L, Mustajoki S, Pischik E, Di Pierro E, Barbaro M, Floderus Y, Schmitt C, Gouya L, Colavin A, Nussbaum R, Friesema ECH, Kauppinen R, To-Figueras J, Aarsand AK, Desnick RJ, Garton M, Roth FP. Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.06.527353. [PMID: 36798224 PMCID: PMC9934555 DOI: 10.1101/2023.02.06.527353] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Defects in hydroxymethylbilane synthase (HMBS) can cause Acute Intermittent Porphyria (AIP), an acute neurological disease. Although sequencing-based diagnosis can be definitive, ~⅓ of clinical HMBS variants are missense variants, and most clinically-reported HMBS missense variants are designated as "variants of uncertain significance" (VUS). Using saturation mutagenesis, en masse selection, and sequencing, we applied a multiplexed validated assay to both the erythroid-specific and ubiquitous isoforms of HMBS, obtaining confident functional impact scores for >84% of all possible amino-acid substitutions. The resulting variant effect maps generally agreed with biochemical expectation. However, the maps showed variants at the dimerization interface to be unexpectedly well tolerated, and suggested residue roles in active site dynamics that were supported by molecular dynamics simulations. Most importantly, these HMBS variant effect maps can help discriminate pathogenic from benign variants, proactively providing evidence even for yet-to-be-observed clinical missense variants.
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Affiliation(s)
- Warren van Loggerenberg
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Shahin Sowlati-Hashjin
- Institute of Biomedical Engineering, University of Toronto, ON, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, ON, Canada
| | - Jochen Weile
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Rayna Hamilton
- Advanced Academic Programs, Johns Hopkins University, Washington, DC, USA
| | - Aditya Chawla
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Marinella Gebbia
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Nishka Kishore
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | | | - Sami Mustajoki
- Research Program in Molecular Medicine, Biomedicum-Helsinki, University of Helsinki
| | - Elena Pischik
- Research Program in Molecular Medicine, Biomedicum-Helsinki, University of Helsinki
| | - Elena Di Pierro
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Unit of Medicine and Metabolic Diseases, Milan, Italy
| | - Michela Barbaro
- Porphyria Centre Sweden, Centre for Inherited Metabolic Diseases, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Ylva Floderus
- Porphyria Centre Sweden, Centre for Inherited Metabolic Diseases, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Caroline Schmitt
- Centre Français des Porphyries, Hôpital Louis Mourier, Assistance Publique-Hôpitaux de Paris, Colombes and Centre de Recherche sur l’Inflammation, UMR1149 INSERM, Université Paris Cité, Paris, France
| | - Laurent Gouya
- Centre Français des Porphyries, Hôpital Louis Mourier, Assistance Publique-Hôpitaux de Paris, Colombes and Centre de Recherche sur l’Inflammation, UMR1149 INSERM, Université Paris Cité, Paris, France
| | | | | | - Edith C. H. Friesema
- Porphyria Expertcenter Rotterdam, Center for Lysosomal and Metabolic Diseases, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - Raili Kauppinen
- Research Program in Molecular Medicine, Biomedicum-Helsinki, University of Helsinki
| | - Jordi To-Figueras
- Biochemistry and Molecular Genetics Department, Hospital Clínic, IDIBAPS, University of Barcelona, Barcelona, Spain
| | - Aasne K Aarsand
- Norwegian Porphyria Centre, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
| | - Robert J. Desnick
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Garton
- Institute of Biomedical Engineering, University of Toronto, ON, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, ON, Canada
| | - Frederick P. Roth
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
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41
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Peltomäki P, Nyström M, Mecklin JP, Seppälä TT. Lynch Syndrome Genetics and Clinical Implications. Gastroenterology 2023; 164:783-799. [PMID: 36706841 DOI: 10.1053/j.gastro.2022.08.058] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 01/29/2023]
Abstract
Lynch syndrome (LS) is one of the most prevalent hereditary cancer syndromes in humans and accounts for some 3% of unselected patients with colorectal or endometrial cancer and 10%-15% of those with DNA mismatch repair-deficient tumors. Previous studies have established the genetic basis of LS predisposition, but there have been significant advances recently in the understanding of the molecular pathogenesis of LS tumors, which has important implications in clinical management. At the same time, immunotherapy has revolutionized the treatment of advanced cancers with DNA mismatch repair defects. We aim to review the recent progress in the LS field and discuss how the accumulating epidemiologic, clinical, and molecular information has contributed to a more accurate and complete picture of LS, resulting in genotype- and immunologic subtype-specific strategies for surveillance, cancer prevention, and treatment.
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Affiliation(s)
- Päivi Peltomäki
- Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.
| | - Minna Nyström
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Jukka-Pekka Mecklin
- Department of Education and Science, Nova Hospital, Central Finland Health Care District, Jyväskylä, Finland; Faculty of Sports and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Toni T Seppälä
- Department of Surgery, Helsinki University Hospital, Helsinki, Finland; Applied Tumor Genomics Research Programs Unit, University of Helsinki, Helsinki, Finland; Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere University Hospital, Tampere, Finland
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Guo L, Yu Z, Li Q, Liang X, Yang L. Correlation of MLH1 and MSH2 levels with clinicopathologic characteristics in colorectal cancer. Am J Transl Res 2023; 15:1107-1116. [PMID: 36915797 PMCID: PMC10006755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/16/2022] [Indexed: 03/16/2023]
Abstract
OBJECTIVE To determine the correlation of MLH1 and MSH2 expressions with clinicopathologic characteristics in colorectal cancer (CC). METHODS Clinical data, CC tissue, and paracancerous tissue from 88 patients treated in Baoji City People's Hospital from February 2015 to February 2017 were analyzed retrospectively. The relative expression levels of MLH1 and MSH2 in the tissues were measured with qRT-PCR, and the relationship of MLH1 and MSH2 with the pathological data of patients was analyzed. The value of MLH1 and MSH2 in the diagnosis of clinical stage, lymph node metastasis, and degree of differentiation in CC patients was analyzed by receiver operating curve (ROC). Cox regression analysis was applied to identify factors affecting prognosis. RESULTS The relative expression levels of MLH1 and MSH2 in CC tissue were lower than those in paracancerous tissue (P < 0.001). Tumor node metastasis stage (III + IV), poor differentiation, and lymph node metastasis were significantly increased in patients with low MLH1 and MSH2 expressions (P < 0.05). The levels of MLH1 and MSH2 in CC tissue of patients at stage I with moderately- or well-differentiated non-metastatic disease were higher than those in patients at stage II-IV with poor differentiation and lymph node metastasis, showing a good predictive ability. The 5-year survival rate of patients with low MLH1 and MSH2 expressions was lower as compared to its counterpart (P < 0.01). CONCLUSION The low expressions of MSH2 and MLH1 in CC tissue have a correlation with pathological characteristics and survival, so they can be used as auxiliary references for the prognosis in CC patients.
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Affiliation(s)
- Ling Guo
- Pathology Department, The First People's Hospital of Xianyang No. 10, Biyuan West Road, Qindu District, Xianyang 712000, Shaanxi, P. R. China
| | - Zhaohui Yu
- Gastrointestinal Surgery, The First People's Hospital of Xianyang No. 10, Biyuan West Road, Qindu District, Xianyang 712000, Shaanxi, P. R. China
| | - Qin Li
- Geriatric Medicine Department, Baoji City People's Hospital No. 24 Xinhua Lane, Jinger Road, Weibin, Baoji 721000, Shaanxi, P. R. China
| | - Xiaohu Liang
- Oncology Surgery, Baoji City People's Hospital No. 24 Xinhua Lane, Jinger Road, Weibin, Baoji 721000, Shaanxi, P. R. China
| | - Lindong Yang
- Department of Emergency, Baoji City People's Hospital No. 24 Xinhua Lane, Jinger Road, Weibin, Baoji 721000, Shaanxi, P. R. China
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Scott A, Hernandez F, Chamberlin A, Smith C, Karam R, Kitzman JO. Saturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome. Genome Biol 2022; 23:266. [PMID: 36550560 PMCID: PMC9773515 DOI: 10.1186/s13059-022-02839-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Lynch syndrome (LS) is a cancer predisposition syndrome affecting more than 1 in every 300 individuals worldwide. Clinical genetic testing for LS can be life-saving but is complicated by the heavy burden of variants of uncertain significance (VUS), especially missense changes. RESULT To address this challenge, we leverage a multiplexed analysis of variant effect (MAVE) map covering >94% of the 17,746 possible missense variants in the key LS gene MSH2. To establish this map's utility in large-scale variant reclassification, we overlay it on clinical databases of >15,000 individuals with LS gene variants uncovered during clinical genetic testing. We validate these functional measurements in a cohort of individuals with paired tumor-normal test results and find that MAVE-based function scores agree with the clinical interpretation for every one of the MSH2 missense variants with an available classification. We use these scores to attempt reclassification for 682 unique missense VUS, among which 34 scored as deleterious by our function map, in line with previously published rates for other cancer predisposition genes. Combining functional data and other evidence, ten missense VUS are reclassified as pathogenic/likely pathogenic, and another 497 could be moved to benign/likely benign. Finally, we apply these functional scores to paired tumor-normal genetic tests and identify a subset of patients with biallelic somatic loss of function, reflecting a sporadic Lynch-like Syndrome with distinct implications for treatment and relatives' risk. CONCLUSION This study demonstrates how high-throughput functional assays can empower scalable VUS resolution and prospectively generate strong evidence for variant classification.
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Affiliation(s)
- Anthony Scott
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Division of Genetic Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Felicia Hernandez
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA
| | - Adam Chamberlin
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA
| | - Cathy Smith
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Rachid Karam
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Jacob O. Kitzman
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
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Rath A, Radecki AA, Rahman K, Gilmore RB, Hudson JR, Cenci M, Tavtigian SV, Grady JP, Heinen CD. A calibrated cell-based functional assay to aid classification of MLH1 DNA mismatch repair gene variants. Hum Mutat 2022; 43:2295-2307. [PMID: 36054288 PMCID: PMC9772141 DOI: 10.1002/humu.24462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/21/2022] [Accepted: 08/30/2022] [Indexed: 01/25/2023]
Abstract
Functional assays provide important evidence for classifying the disease significance of germline variants in DNA mismatch repair genes. Numerous laboratories, including our own, have developed functional assays to study mismatch repair gene variants. However, previous assays are limited due to the model system employed, the manner of gene expression, or the environment in which function is assessed. Here, we developed a human cell-based approach for testing the function of variants of uncertain significance (VUS) in the MLH1 gene. Using clustered regularly interspaced short palindromic repeats gene editing, we knocked in MLH1 VUS into the endogenous MLH1 loci in human embryonic stem cells. We examined their impact on RNA and protein, including their ability to prevent microsatellite instability and instigate a DNA damage response. A statistical clustering analysis determined the range of functions associated with known pathogenic or benign variants, and linear regression was performed using existing odds in favor of pathogenicity scores for these control variants to calibrate our functional assay results. By converting the functional outputs into a single odds in favor of pathogenicity score, variant classification expert panels can use these results to readily reassess these VUS. Ultimately, this information will guide proper diagnosis and disease management for suspected Lynch syndrome patients.
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Affiliation(s)
- Abhijit Rath
- Center for Molecular Oncology, UConn Health, Farmington, CT
| | | | - Kaussar Rahman
- Center for Molecular Oncology, UConn Health, Farmington, CT
| | - Rachel B. Gilmore
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT
| | - Jonathan R. Hudson
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT
| | - Matthew Cenci
- Center for Molecular Oncology, UConn Health, Farmington, CT
| | - Sean V. Tavtigian
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT
| | - James P. Grady
- Connecticut Institute for Clinical and Translational Science, UConn Health, Farmington, CT
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Dace P, Findlay GM. Reducing uncertainty in genetic testing with Saturation Genome Editing. MED GENET-BERLIN 2022; 34:297-304. [PMID: 38836089 PMCID: PMC11006300 DOI: 10.1515/medgen-2022-2159] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Accurate interpretation of human genetic data is critical for optimizing outcomes in the era of genomic medicine. Powerful methods for testing genetic variants for functional effects are allowing researchers to characterize thousands of variants across disease genes. Here, we review experimental tools enabling highly scalable assays of variants, focusing specifically on Saturation Genome Editing (SGE). We discuss examples of how this technique is being implemented for variant testing at scale and describe how SGE data for BRCA1 have been clinically validated and used to aid variant interpretation. The initial success at predicting variant pathogenicity with SGE has spurred efforts to expand this and related techniques to many more genes.
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Affiliation(s)
- Phoebe Dace
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
| | - Gregory M Findlay
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
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46
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Tabet D, Parikh V, Mali P, Roth FP, Claussnitzer M. Scalable Functional Assays for the Interpretation of Human Genetic Variation. Annu Rev Genet 2022; 56:441-465. [PMID: 36055970 DOI: 10.1146/annurev-genet-072920-032107] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.
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Affiliation(s)
- Daniel Tabet
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Victoria Parikh
- Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Prashant Mali
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Frederick P Roth
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Genomic Medicine and Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA;
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47
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An L, Wang Y, Wu G, Wang Z, Shi Z, Liu C, Wang C, Yi M, Niu C, Duan S, Li X, Tang W, Wu K, Chen S, Xu H. Defining the sensitivity landscape of EGFR variants to tyrosine kinase inhibitors. Transl Res 2022; 255:14-25. [PMID: 36347492 DOI: 10.1016/j.trsl.2022.11.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 10/06/2022] [Accepted: 11/01/2022] [Indexed: 11/08/2022]
Abstract
Tyrosine kinase inhibitor (TKI) is a standard treatment for patients with NSCLC harboring constitutively active epidermal growth factor receptor (EGFR) mutations. However, most rare EGFR mutations lack treatment regimens except for the well-studied ones. We constructed two EGFR variant libraries containing substitutions, deletions, or insertions using the saturation mutagenesis method. All the variants were located in the EGFR mutation hotspot (exons 18-21). The sensitivity of these variants to afatinib, erlotinib, gefitinib, icotinib, and osimertinib was systematically studied by determining their enrichment in massively parallel cytotoxicity assays using an endogenous EGFR-depleted cell line. A total of 3914 and 70,475 variants were detected in the constructed EGFR Substitution-Deletion (Sub-Del) and exon 20 Insertion (Ins) libraries. Of the 3914 Sub-Del variants, 221 proliferated fast in the control assay and were sensitive to EGFR-TKIs. For the 70,475 Ins variants, insertions at amino acid positions 770-774 were highly enriched in all 5 TKI cytotoxicity assays. Moreover, the top 5% of the enriched insertion variants included a glycine or serine insertion at high frequency. We present a comprehensive reference for the sensitivity of EGFR variants to five commonly used TKIs. The approach used here should be applicable to other genes and targeted drugs. BACKGROUND: Tyrosine kinase inhibitors (TKIs) therapy is a standard treatment for patients with advanced non-small-cell lung carcinoma (NSCLC) when activating epidermal growth factor receptor (EGFR) mutations are detected. However, except for the well-studied EGFR mutations, most EGFR mutations lack treatment regimens. TRANSLATIONAL SIGNIFICANCE: The results demonstrated that patients with rare EGFR mutations were most likely to benefit from osimertinib therapy compared to afatinib, erlotinib, gefitinib, or icotinib therapy. This study provides a case of deep mutational scanning that simultaneously assayed substitution, deletion, and insertion variants. This approach is applicable for other oncogenes and targeted drugs.
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Affiliation(s)
- Lei An
- Translational Medicine Center, Huaihe Hospital of Henan University, Henan University, Kaifeng 475000, China
| | | | - Guangyao Wu
- Translational Medicine Center, Huaihe Hospital of Henan University, Henan University, Kaifeng 475000, China
| | - Zhenxing Wang
- Translational Medicine Center, Huaihe Hospital of Henan University, Henan University, Kaifeng 475000, China
| | - Zeyuan Shi
- Translational Medicine Center, Huaihe Hospital of Henan University, Henan University, Kaifeng 475000, China
| | - Chang Liu
- School of Pharmacy, Henan University, Kaifeng 475000, China
| | - Chunli Wang
- School of Pharmacy, Henan University, Kaifeng 475000, China
| | - Ming Yi
- Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Chenguang Niu
- Key Laboratory of Clinical Resources Translation, The First Affiliated Hospital of Henan University, Kaifeng 475000, China
| | - Shaofeng Duan
- School of Pharmacy, Henan University, Kaifeng 475000, China
| | - Xiaodong Li
- Translational Medicine Center, Huaihe Hospital of Henan University, Henan University, Kaifeng 475000, China
| | - Wenxue Tang
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450000, China; The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Kongming Wu
- Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shuqing Chen
- Shenzhen Typhoon HealthCare, Shenzhen 518000, China.
| | - Hongen Xu
- Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Zhengzhou 450000, China; The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China.
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48
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Micolonghi C, Piane M, Germani A, Sadeghi S, Libi F, Savio C, Fabiani M, Mancini R, Ranieri D, Pizzuti A, Corleto VD, Parisi P, Visco V, Di Nardo G, Petrucci S. A New SMAD4 Splice Site Variant in a Three-Generation Italian Family with Juvenile Polyposis Syndrome. Diagnostics (Basel) 2022; 12:diagnostics12112684. [PMID: 36359527 PMCID: PMC9689379 DOI: 10.3390/diagnostics12112684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
Juvenile polyposis syndrome (JPS) is an autosomal dominant disorder characterized by hyperplastic polyps in the upper and lower gastrointestinal (GI) tract with a high risk of developing GI cancers. We have described a three-generation Italian family with all the spectrum of SMAD4 phenotype. A multigene panel test was performed on the genomic DNA of the proband by next-generation sequencing, including genes related to hereditary GI tumor syndromes. Molecular analysis revealed the presence of the c.1140-2A>G substitution in the SMAD4 gene, a novel splice variant that has never been described before. Our family is remarkable in that it illustrates the variable expressivity of the SMAD4 phenotype within the same family. The possibility of phenotype variability should also be considered within family members carrying the same mutation. In JPS, a timely genetic diagnosis allows clinicians to better manage patients and to provide early surveillance and intervention for their asymptomatic mutated relatives in the early decades of life.
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Affiliation(s)
- Caterina Micolonghi
- Department of Experimental Medicine, Faculty of Medicine and Dentistry, Sapienza University of Rome, 00161 Rome, Italy
| | - Maria Piane
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
- S. Andrea University Hospital, 00189 Rome, Italy
| | - Aldo Germani
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Soha Sadeghi
- Department of Experimental Medicine, Faculty of Medicine and Dentistry, Sapienza University of Rome, 00161 Rome, Italy
| | - Fabio Libi
- S. Andrea University Hospital, 00189 Rome, Italy
| | | | - Marco Fabiani
- Department of Experimental Medicine, Faculty of Medicine and Dentistry, Sapienza University of Rome, 00161 Rome, Italy
- ALTAMEDICA, Human Genetics, 00198 Rome, Italy
| | - Rita Mancini
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
- S. Andrea University Hospital, 00189 Rome, Italy
| | - Danilo Ranieri
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Antonio Pizzuti
- Department of Experimental Medicine, Faculty of Medicine and Dentistry, Sapienza University of Rome, 00161 Rome, Italy
- Medical Genetics Unit, IRCCS Mendel Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy
| | - Vito Domenico Corleto
- S. Andrea University Hospital, 00189 Rome, Italy
- Department of Medical-Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Pasquale Parisi
- S. Andrea University Hospital, 00189 Rome, Italy
- Department of Neuroscience, Mental Health and Sense Organs (NESMOS), Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Vincenzo Visco
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
- S. Andrea University Hospital, 00189 Rome, Italy
| | - Giovanni Di Nardo
- S. Andrea University Hospital, 00189 Rome, Italy
- Department of Neuroscience, Mental Health and Sense Organs (NESMOS), Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Simona Petrucci
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
- S. Andrea University Hospital, 00189 Rome, Italy
- Medical Genetics Unit, IRCCS Mendel Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy
- Correspondence: ; Tel.: +39-0633-776-103
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Zhang H, Xu MS, Fan X, Chung WK, Shen Y. Predicting functional effect of missense variants using graph attention neural networks. NAT MACH INTELL 2022; 4:1017-1028. [PMID: 37484202 PMCID: PMC10361701 DOI: 10.1038/s42256-022-00561-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 10/07/2022] [Indexed: 11/16/2022]
Abstract
Accurate prediction of damaging missense variants is critically important for interpreting a genome sequence. Although many methods have been developed, their performance has been limited. Recent advances in machine learning and the availability of large-scale population genomic sequencing data provide new opportunities to considerably improve computational predictions. Here we describe the graphical missense variant pathogenicity predictor (gMVP), a new method based on graph attention neural networks. Its main component is a graph with nodes that capture predictive features of amino acids and edges weighted by co-evolution strength, enabling effective pooling of information from the local protein context and functionally correlated distal positions. Evaluation of deep mutational scan data shows that gMVP outperforms other published methods in identifying damaging variants in TP53, PTEN, BRCA1 and MSH2. Furthermore, it achieves the best separation of de novo missense variants in neuro developmental disorder cases from those in controls. Finally, the model supports transfer learning to optimize gain- and loss-of-function predictions in sodium and calcium channels. In summary, we demonstrate that gMVP can improve interpretation of missense variants in clinical testing and genetic studies.
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Affiliation(s)
- Haicang Zhang
- Department of Systems Biology, Columbia University, New York, NY, USA
| | | | - Xiao Fan
- Department of Systems Biology, Columbia University, New York, NY, USA
- Department of Pediatrics, Columbia University, New York, NY, USA
| | - Wendy K. Chung
- Department of Pediatrics, Columbia University, New York, NY, USA
- Department of Medicine, Columbia University, New York, NY, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University, New York, NY, USA
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- JP Sulzberger Columbia Genome Center, Columbia University, New York, NY, USA
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50
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Meulemans L, Baert Desurmont S, Waill MC, Castelain G, Killian A, Hauchard J, Frebourg T, Coulet F, Martins A, Muleris M, Gaildrat P. Comprehensive RNA and protein functional assessments contribute to the clinical interpretation of MSH2 variants causing in-frame splicing alterations. J Med Genet 2022; 60:450-459. [PMID: 36113988 DOI: 10.1136/jmg-2022-108576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/26/2022] [Indexed: 11/04/2022]
Abstract
BackgroundSpliceogenic variants in disease-causing genes are often presumed pathogenic since most induce frameshifts resulting in loss of function. However, it was recently shown in cancer predisposition genes that some may trigger in-frame anomalies that preserve function. Here, we addressed this question by using MSH2, a DNA mismatch repair gene implicated in Lynch syndrome, as a model system.MethodsEighteen MSH2 variants, mostly localised within canonical splice sites, were analysed by using minigene splicing assays. The impact of the resulting protein alterations was assessed in a methylation tolerance-based assay. Clinicopathological characteristics of variant carriers were collected.ResultsThree in-frame RNA biotypes were identified based on variant-induced spliceogenic outcomes: exon skipping (E3, E4, E5 and E12), segmental exonic deletions (E7 and E15) and intronic retentions (I3, I6, I12 and I13). The 10 corresponding protein isoforms exhibit either large deletions (49–93 amino acids (aa)), small deletions (12 or 16 aa) or insertions (3–10 aa) within different functional domains. We showed that all these modifications abrogate MSH2 function, in agreement with the clinicopathological features of variant carriers.ConclusionAltogether, these data demonstrate that MSH2 function is intolerant to in-frame indels caused by the spliceogenic variants analysed in this study, supporting their pathogenic nature. This work stresses the importance of combining complementary RNA and protein approaches to ensure accurate clinical interpretation of in-frame spliceogenic variants.
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Affiliation(s)
- Laëtitia Meulemans
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
| | - Stéphanie Baert Desurmont
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, and CHU Rouen, Department of Genetics, F-76000 Rouen, France
| | - Marie-Christine Waill
- Department of Genetics, AP-HP.Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Gaia Castelain
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
| | - Audrey Killian
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
| | - Julie Hauchard
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
| | - Thierry Frebourg
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, and CHU Rouen, Department of Genetics, F-76000 Rouen, France
| | - Florence Coulet
- Department of Genetics, AP-HP.Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inserm UMR-S 938, Centre de Recherche Saint-Antoine, CRSA, Paris, France
| | - Alexandra Martins
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
| | - Martine Muleris
- Department of Genetics, AP-HP.Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inserm UMR-S 938, Centre de Recherche Saint-Antoine, CRSA, Paris, France
| | - Pascaline Gaildrat
- Normandie Univ, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, F-76000 Rouen, France
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