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Argov CM, Shneyour A, Jubran J, Sabag E, Mansbach A, Sepunaru Y, Filtzer E, Gruber G, Volozhinsky M, Yogev Y, Birk O, Chalifa-Caspi V, Rokach L, Yeger-Lotem E. Tissue-aware interpretation of genetic variants advances the etiology of rare diseases. Mol Syst Biol 2024:10.1038/s44320-024-00061-6. [PMID: 39285047 DOI: 10.1038/s44320-024-00061-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/08/2024] [Accepted: 08/09/2024] [Indexed: 09/19/2024] Open
Abstract
Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we report a machine-learning framework, denoted "Tissue Risk Assessment of Causality by Expression for variants" (TRACEvar, https://netbio.bgu.ac.il/TRACEvar/ ), that offers two advancements. First, TRACEvar predicts pathogenic variants that disrupt the normal physiology of specific tissues. This was achieved by creating 14 tissue-specific models that were trained on over 14,000 variants and combined 84 attributes of genetic variants with 495 attributes derived from tissue omics. TRACEvar outperformed 10 well-established and tissue-oblivious variant effect prediction tools. Second, the resulting models are interpretable, thereby illuminating variants' mode of action. Application of TRACEvar to variants of 52 rare-disease patients highlighted pathogenicity mechanisms and relevant disease processes. Lastly, the interpretation of all tissue models revealed that top-ranking determinants of pathogenicity included attributes of disease-affected tissues, particularly cellular process activities. Collectively, these results show that tissue contexts and interpretable machine-learning models can greatly enhance the etiology of rare diseases.
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Affiliation(s)
- Chanan M Argov
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Ariel Shneyour
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Juman Jubran
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Eric Sabag
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Avigdor Mansbach
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Yair Sepunaru
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Emmi Filtzer
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Gil Gruber
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Miri Volozhinsky
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Yuval Yogev
- Morris Kahn Laboratory of Human Genetics and the Genetics Institute at Soroka Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Ohad Birk
- Morris Kahn Laboratory of Human Genetics and the Genetics Institute at Soroka Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, 84105, Israel
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Vered Chalifa-Caspi
- Ilse Katz Institute for Nanoscale Science & Technology, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
| | - Lior Rokach
- Department of Software & Information Systems Engineering, Faculty of Engineering Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel.
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel.
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Hekselman I, Vital A, Ziv-Agam M, Kerber L, Yairi I, Yeger-Lotem E. Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data. eLife 2024; 13:e84613. [PMID: 38197427 PMCID: PMC10830129 DOI: 10.7554/elife.84613] [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: 11/01/2022] [Accepted: 12/08/2023] [Indexed: 01/11/2024] Open
Abstract
Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.
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Affiliation(s)
- Idan Hekselman
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Assaf Vital
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Maya Ziv-Agam
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Lior Kerber
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Ido Yairi
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the NegevBe’er ShevaIsrael
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Simonovsky E, Sharon M, Ziv M, Mauer O, Hekselman I, Jubran J, Vinogradov E, Argov CM, Basha O, Kerber L, Yogev Y, Segrè AV, Im HK, Birk O, Rokach L, Yeger‐Lotem E. Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation. Mol Syst Biol 2023; 19:e11407. [PMID: 37232043 PMCID: PMC10407743 DOI: 10.15252/msb.202211407] [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: 10/20/2022] [Revised: 04/30/2023] [Accepted: 05/10/2023] [Indexed: 05/27/2023] Open
Abstract
How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we developed "Tissue Risk Assessment of Causality by Expression" (TRACE), a machine learning approach to predict genes that underlie tissue-selective diseases and selectivity-related features. TRACE utilized 4,744 biologically interpretable tissue-specific gene features that were inferred from heterogeneous omics datasets. Application of TRACE to 1,031 disease genes uncovered known and novel selectivity-related features, the most common of which was previously overlooked. Next, we created a catalog of tissue-associated risks for 18,927 protein-coding genes (https://netbio.bgu.ac.il/trace/). As proof-of-concept, we prioritized candidate disease genes identified in 48 rare-disease patients. TRACE ranked the verified disease gene among the patient's candidate genes significantly better than gene prioritization methods that rank by gene constraint or tissue expression. Thus, tissue selectivity combined with machine learning enhances genetic and clinical understanding of hereditary diseases.
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Affiliation(s)
- Eyal Simonovsky
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Moran Sharon
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Maya Ziv
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Omry Mauer
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Idan Hekselman
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Juman Jubran
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Ekaterina Vinogradov
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Chanan M Argov
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Omer Basha
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Lior Kerber
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Yuval Yogev
- Morris Kahn Laboratory of Human Genetics and the Genetics Institute at Soroka Medical Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
| | - Ayellet V Segrè
- Ocular Genomics Institute, Massachusetts Eye and EarHarvard Medical SchoolBostonMAUSA
- The Broad Institute of MIT and HarvardCambridgeMAUSA
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of MedicineThe University of ChicagoChicagoILUSA
| | | | - Ohad Birk
- Morris Kahn Laboratory of Human Genetics and the Genetics Institute at Soroka Medical Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
- The National Institute for Biotechnology in the NegevBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Lior Rokach
- Department of Software & Information Systems EngineeringBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Esti Yeger‐Lotem
- Department of Clinical Biochemistry and PharmacologyBen‐Gurion University of the NegevBeer ShevaIsrael
- The National Institute for Biotechnology in the NegevBen‐Gurion University of the NegevBeer ShevaIsrael
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Applying the CRISPR/Cas9 for treating human and animal diseases: a comprehensive review. ANNALS OF ANIMAL SCIENCE 2023. [DOI: 10.2478/aoas-2023-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
Abstract
Recently, genome editing tools have been extensively used in many biomedical sciences. The gene editing system is applied to modify the DNA sequences in the cellular system to comprehend their physiological response. A developing genome editing technology like clustered regularly short palindromic repeats (CRISPR) is widely expended in medical sciences. CRISPR and CRISPR-associated protein 9 (CRISPR/Cas9) system is being exploited to edit any DNA mutations related to inherited ailments to investigate in animals (in vivo) and cell lines (in vitro). Remarkably, CRISPR/Cas9 could be employed to examine treatments of many human genetic diseases such as Cystic fibrosis, Tyrosinemia, Phenylketonuria, Muscular dystrophy, Parkinson’s disease, Retinoschisis, Hemophilia, β-Thalassemia and Atherosclerosis. Moreover, CRISPR/Cas9 was used for disease resistance such as Tuberculosis, Johne’s diseases, chronic enteritis, and Brucellosis in animals. Finally, this review discusses existing progress in treating hereditary diseases using CRISPR/Cas9 technology and the high points accompanying obstacles.
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