1
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Chignon A, Lettre G. Using omics data and genome editing methods to decipher GWAS loci associated with coronary artery disease. Atherosclerosis 2025; 401:118621. [PMID: 39909615 DOI: 10.1016/j.atherosclerosis.2024.118621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/18/2024] [Accepted: 10/03/2024] [Indexed: 02/07/2025]
Abstract
Coronary artery disease (CAD) is due to atherosclerosis, a pathophysiological process that involves several cell-types and results in the accumulation of lipid-rich plaque that disrupt the normal blood flow through the coronary arteries to the heart. Genome-wide association studies have identified 1000s of genetic variants robustly associated with CAD or its traditional risk factors (e.g. blood pressure, blood lipids, type 2 diabetes, smoking). However, gaining biological insights from these genetic discoveries remain challenging because of linkage disequilibrium and the difficulty to interpret the functions of non-coding regulatory elements in the human genome. In this review, we present different statistical methods (e.g. Mendelian randomization) and molecular datasets (e.g. expression or protein quantitative trait loci) that have helped connect CAD-associated variants with genes, biological pathways, and cell-types or tissues. We emphasize that these various strategies make predictions, which need to be validated in orthologous systems. We discuss specific examples where the integration of omics data with GWAS results has prioritized causal CAD variants and genes. Finally, we review how targeted and genome-wide genome editing experiments using the CRISPR/Cas9 toolbox have been used to characterize new CAD genes in human cells. Researchers now have the statistical and bioinformatic methods, the molecular datasets, and the experimental tools to dissect comprehensively the loci that contribute to CAD risk in humans.
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Affiliation(s)
- Arnaud Chignon
- Montreal Heart Institute, Montreal, Quebec, Canada; Faculté de Médecine, Université de Montréal, Montreal, Quebec, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, Quebec, Canada; Faculté de Médecine, Université de Montréal, Montreal, Quebec, Canada.
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2
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Choi S, Dalloul RSD, Vemulapalli PB, Yousef S, Goswami N, Schmidt F. Comprehensive Proteomic Profiling of Converted Adipocyte-like Cells from Normal Human Dermal Fibroblasts Using Data-Independent Acquisition Mass Spectrometry. ACS OMEGA 2024; 9:40034-40050. [PMID: 39346858 PMCID: PMC11425921 DOI: 10.1021/acsomega.4c05852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 08/28/2024] [Accepted: 09/01/2024] [Indexed: 10/01/2024]
Abstract
Adipocytes play an important role in the regulation of systemic energy homeostasis and are closely related to metabolic disorders, such as type-2 diabetes and inflammatory bowel diseases. Particularly, there is an increasing need for a human adipocyte model for studying metabolic diseases and obesity. However, utilizing human primary adipocyte culture and stem-cell-based models presents several practical limitations due to their time-consuming nature, requirement for relatively intensive labor, and high cost. Here, we applied direct conversion of normal human dermal fibroblasts (NHDFs) into adipocyte-like cells using an adipogenic cocktail containing 3-isobutyl-1-methylxanthine (IBMX), dexamethasone, insulin, and rosiglitazone and confirmed prominent lipid droplet accumulation in the converted cells. For profiling the proteome changes in the converted cells, we conducted a comprehensive quantitative proteome analysis of both the intracellular and extracellular proteome fractions using data-independent acquisition mass spectrometry. We observed that several proteins, which are known to be highly expressed in adipocytes specifically, were dominantly increased in the converted cells. In this study, we suggest that NHDFs can be converted into adipocyte-like cells by an adipogenic cocktail and can serve as a useful tool for studying human adipocytes and their metabolism.
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Affiliation(s)
- Sunkyu Choi
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
| | - Rajaa S D Dalloul
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
| | - Praveen Babu Vemulapalli
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
| | - Sondos Yousef
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
| | - Neha Goswami
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
| | - Frank Schmidt
- Proteomics Core, Research, Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, P.O. 24144 Doha, Qatar
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3
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Dubin RF, Deo R, Ren Y, Wang J, Pico AR, Mychaleckyj JC, Kozlitina J, Arthur V, Lee H, Shah A, Feldman H, Bansal N, Zelnick L, Rao P, Sukul N, Raj DS, Mehta R, Rosas SE, Bhat Z, Weir MR, He J, Chen J, Kansal M, Kimmel PL, Ramachandran VS, Waikar SS, Segal MR, Ganz P. Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification. Eur Heart J 2024; 45:2752-2767. [PMID: 38757788 PMCID: PMC11313584 DOI: 10.1093/eurheartj/ehae288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 04/09/2024] [Accepted: 04/25/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND AND AIMS Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed. METHODS In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score. RESULTS Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787). CONCLUSIONS Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.
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Affiliation(s)
- Ruth F Dubin
- Division of Nephrology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, H5.122E, Dallas, TX 75390, USA
| | - Rajat Deo
- Division of Cardiovascular Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Yue Ren
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jianqiao Wang
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alexander R Pico
- Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Julia Kozlitina
- McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Victoria Arthur
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hongzhe Lee
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amil Shah
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Harold Feldman
- Patient-Centered Outcomes Research Institute, Washington, DC, USA
| | - Nisha Bansal
- Division of Nephrology, University of Washington Medical Center, Seattle, WA, USA
| | - Leila Zelnick
- Division of Nephrology, University of Washington Medical Center, Seattle, WA, USA
| | - Panduranga Rao
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Nidhi Sukul
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Dominic S Raj
- Division of Kidney Diseases and Hypertension, George Washington University School of Medicine, Washington, DC, USA
| | - Rupal Mehta
- Division of Nephrology and Hypertension, Northwestern University Feinberg School of Medicine, USA
| | - Sylvia E Rosas
- Joslin Diabetes Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Zeenat Bhat
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Matthew R Weir
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Jing Chen
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Mayank Kansal
- Division of Cardiology, University of Illinois College of Medicine, Chicago, IL, USA
| | - Paul L Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Vasan S Ramachandran
- University of Texas School of Public Health San Antonio and the University of Texas Health Sciences Center in San Antonio, Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Mark R Segal
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Peter Ganz
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
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Danev N, Li G, Duan J(E, Van de Walle GR. Comparative transcriptomic analysis of bovine mesenchymal stromal cells reveals tissue-source and species-specific differences. iScience 2024; 27:108886. [PMID: 38318381 PMCID: PMC10838956 DOI: 10.1016/j.isci.2024.108886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/27/2023] [Accepted: 01/08/2024] [Indexed: 02/07/2024] Open
Abstract
Mesenchymal stromal cells (MSCs) have the potential to be used as therapeutics, but their efficacy varies due to cellular heterogeneity, which is not fully understood. After characterizing donor-matched bovine MSC from adipose tissue (AT), bone marrow (BM), and peripheral blood (PB), we performed single-cell RNA sequencing (scRNA-seq) to evaluate overarching similarities and differences across these three tissue-derived MSCs. Next, the transcriptomic profiles of the bovine MSCs were compared to those of equine MSCs, derived from the same tissue sources and previously published by our group, and revealed species-specific differences. Finally, the transcriptomic profile from bovine BM-MSCs was compared to mouse and human BM-MSCs and demonstrated that bovine BM-MSCs share more common functionally relevant gene expression profiles with human BM-MSCs than compared to murine BM-MSCs. Collectively, this study presents the cow as a potential non-traditional animal model for translational MSC studies based on transcriptomic profiles similar to human MSCs.
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Affiliation(s)
- Nikola Danev
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Guangsheng Li
- Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA
| | - Jingyue (Ellie) Duan
- Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA
| | - Gerlinde R. Van de Walle
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
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5
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Gaita L, Timar B, Timar R, Fras Z, Gaita D, Banach M. Lipid Disorders Management Strategies (2024) in Prediabetic and Diabetic Patients. Pharmaceuticals (Basel) 2024; 17:219. [PMID: 38399434 PMCID: PMC10892910 DOI: 10.3390/ph17020219] [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: 12/28/2023] [Revised: 01/28/2024] [Accepted: 02/04/2024] [Indexed: 02/25/2024] Open
Abstract
Dyslipidaemia is a modifiable risk factor commonly associated with diabetes mellitus and prediabetes, with a major impact on the early development of atherosclerotic cardiovascular disease. Various studies have tried to identify the key treatment targets, their optimal values according to patients' CV risk, and the most efficient yet safe therapeutic agents which, alongside lifestyle changes, would improve lipid levels and reduce cardiovascular mortality and morbidity. Currently, there are multiple pharmacologic options that can be used in the management of dyslipidaemia, such as statins, ezetimibe, bempedoic acid, PCSK9 inhibitors, n-3 polyunsaturated fatty acids or fibrates, to name only a few, while many other are under development. In the current setting of a continuously increasing population of patients with metabolic disorders, this review aims to summarise current knowledge regarding lipid disorders and the recommendations of recent guidelines in treating dyslipidaemia in patients with diabetes mellitus or prediabetes.
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Affiliation(s)
- Laura Gaita
- Second Department of Internal Medicine, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- “Pius Brinzeu” Emergency Hospital, 300723 Timisoara, Romania
| | - Bogdan Timar
- Second Department of Internal Medicine, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- “Pius Brinzeu” Emergency Hospital, 300723 Timisoara, Romania
| | - Romulus Timar
- Second Department of Internal Medicine, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- “Pius Brinzeu” Emergency Hospital, 300723 Timisoara, Romania
| | - Zlatko Fras
- Department of Vascular Disease, University Medical Center Ljubljana, 1000 Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Dan Gaita
- Department of Cardiology, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- Institutul de Boli Cardiovasculare, 300310 Timisoara, Romania
| | - Maciej Banach
- Department of Preventive Cardiology and Lipidology, Medical University of Lodz (MUL), 90-419 Lodz, Poland
- Department of Cardiology and Congenital Heart Disease of Adults, Polish Mother’s Memorial Hospital Research Institute (PMMHRI), 93-338 Lodz, Poland
- Cardiovascular Research Centre, University of Zielona Gora, 65-417 Zielona Gora, Poland
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6
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Hamilton MC, Fife JD, Akinci E, Yu T, Khowpinitchai B, Cha M, Barkal S, Thi TT, Yeo GH, Ramos Barroso JP, Francoeur MJ, Velimirovic M, Gifford DK, Lettre G, Yu H, Cassa CA, Sherwood RI. Systematic elucidation of genetic mechanisms underlying cholesterol uptake. CELL GENOMICS 2023; 3:100304. [PMID: 37228746 PMCID: PMC10203276 DOI: 10.1016/j.xgen.2023.100304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/02/2022] [Accepted: 03/24/2023] [Indexed: 05/27/2023]
Abstract
Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we substantially improve the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of the genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.
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Affiliation(s)
- Marisa C. Hamilton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - James D. Fife
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ersin Akinci
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Benyapa Khowpinitchai
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minsun Cha
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sammy Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Thi Tun Thi
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Grace H.T. Yeo
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Juan Pablo Ramos Barroso
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Matthew Jake Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minja Velimirovic
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David K. Gifford
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Haojie Yu
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
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7
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Shan H, Fei T. CRISPR screening in cardiovascular research. Front Cell Dev Biol 2023; 11:1175849. [PMID: 37123412 PMCID: PMC10130668 DOI: 10.3389/fcell.2023.1175849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
The recent advent and widespread application of CRISPR-based genome editing tools have revolutionized biomedical research and beyond. Taking advantage of high perturbation efficiency and scalability, CRISPR screening has been regarded as one of the most powerful technologies in functional genomics which allows investigation of different genetic subjects at a large scale in parallel. Significant progress has been made using various CRISPR screening tools especially in cancer research, however, fewer attempts and less success are reported in other contexts. In this mini-review, we discuss how CRISPR screening has been implemented in studies on cardiovascular research and related metabolic disorders, highlight the scientific progress utilizing CRISPR screening, and further envision how to fully unleash the power of this technique to expedite scientific discoveries in these fields.
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Affiliation(s)
- Haihuan Shan
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, China
| | - Teng Fei
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, China
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8
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Musunuru K. CRISPR and cardiovascular diseases. Cardiovasc Res 2023; 119:79-93. [PMID: 35388882 DOI: 10.1093/cvr/cvac048] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/13/2022] [Accepted: 02/15/2022] [Indexed: 11/13/2022] Open
Abstract
CRISPR technologies have progressed by leaps and bounds over the past decade, not only having a transformative effect on biomedical research but also yielding new therapies that are poised to enter the clinic. In this review, I give an overview of (i) the various CRISPR DNA-editing technologies, including standard nuclease gene editing, base editing, prime editing, and epigenome editing, (ii) their impact on cardiovascular basic science research, including animal models, human pluripotent stem cell models, and functional screens, and (iii) emerging therapeutic applications for patients with cardiovascular diseases, focusing on the examples of hypercholesterolaemia, transthyretin amyloidosis, and Duchenne muscular dystrophy.
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Affiliation(s)
- Kiran Musunuru
- Cardiovascular Institute, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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9
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Hamilton MC, Fife JD, Akinci E, Yu T, Khowpinitchai B, Cha M, Barkal S, Thi TT, Yeo GH, Ramos Barroso JP, Jake Francoeur M, Velimirovic M, Gifford DK, Lettre G, Yu H, Cassa CA, Sherwood RI. Systematic elucidation of genetic mechanisms underlying cholesterol uptake. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.09.500804. [PMID: 36711952 PMCID: PMC9881906 DOI: 10.1101/2023.01.09.500804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we have substantially improved the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.
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Affiliation(s)
- Marisa C. Hamilton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - James D. Fife
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ersin Akinci
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Benyapa Khowpinitchai
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minsun Cha
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sammy Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Thi Tun Thi
- Precision Medicine Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Cardiovascular Disease Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Grace H.T. Yeo
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Juan Pablo Ramos Barroso
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Matthew Jake Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minja Velimirovic
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David K. Gifford
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, Québec, H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Haojie Yu
- Precision Medicine Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Cardiovascular Disease Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
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10
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Mechanism Underlying Naringenin Hypocholesterolemic Effects: Involvement of Estrogen Receptor α Subtype. Int J Mol Sci 2022; 23:ijms232415809. [PMID: 36555447 PMCID: PMC9779308 DOI: 10.3390/ijms232415809] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/08/2022] [Accepted: 12/10/2022] [Indexed: 12/15/2022] Open
Abstract
Naringenin (Nar) is one of major citrus flavonoids predominantly found in grapefruit and orange. In vivo studies have demonstrated Nar potential as a normolipidemic agent capable to reduce circulating cholesterol in hypercholesterolemic rabbits, rats, and patients, suggesting a new role for this molecule in cardiovascular disease prevention. Although Nar cholesterol-lowering effects are known, the underlying mechanisms have not yet been elucidated. Interestingly, Nar binds to the estrogen receptors (ERs), modulating both transcriptional and membrane-initiating signals. Although estrogen and ERs are deeply involved in lipid metabolism, no data are available regarding a putative role of these nuclear receptors as mediators of the hypocholesterolemic effect exerted by Nar. Thus, the aim of this work was to study the involvement of ERs in Nar-induced modulation of cholesterol metabolism. Results obtained in HepG2 cell line demonstrate that Nar can modulate the molecular network of cholesterol homeostasis. However, these effects were only partially dependent on the activity of estrogen receptor α. As a whole, our data highlight new molecular mechanisms by which Nar influences cholesterol metabolism, opening a new scenery about dietary impact on human health.
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Dong M, Liu J, Liu C, Wang H, Sun W, Liu B. CRISPR/CAS9: A promising approach for the research and treatment of cardiovascular diseases. Pharmacol Res 2022; 185:106480. [PMID: 36191879 DOI: 10.1016/j.phrs.2022.106480] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 09/27/2022] [Accepted: 09/29/2022] [Indexed: 10/31/2022]
Abstract
The development of gene-editing technology has been one of the biggest advances in biomedicine over the past two decades. Not only can it be used as a research tool to build a variety of disease models for the exploration of disease pathogenesis at the genetic level, it can also be used for prevention and treatment. This is done by intervening with the expression of target genes and carrying out precise molecular targeted therapy for diseases. The simple and flexible clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene-editing technology overcomes the limitations of zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). For this reason, it has rapidly become a preferred method for gene editing. As a new gene intervention method, CRISPR/Cas9 has been widely used in the clinical treatment of tumours and rare diseases; however, its application in the field of cardiovascular diseases is currently limited. This article reviews the application of the CRISPR/Cas9 editing technology in cardiovascular disease research and treatment, and discusses the limitations and prospects of this technology.
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Affiliation(s)
- Mengying Dong
- Department of Cardiology, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, China, 130041
| | - Jiangen Liu
- Department of Cardiology, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, China, 130041
| | - Caixia Liu
- Department of Neurology, The Liaoning Province People's Hospital, 33 Wenyi Road, ShenYang, China, 110016
| | - He Wang
- Department of Cardiology, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, China, 130041
| | - Wei Sun
- Department of Cardiology, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, China, 130041.
| | - Bin Liu
- Department of Cardiology, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, China, 130041.
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