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Valančienė J, Melaika K, Šliachtenko A, Šiaurytė-Jurgelėnė K, Ekkert A, Jatužis D. Stroke genetics and how it Informs novel drug discovery. Expert Opin Drug Discov 2024; 19:553-564. [PMID: 38494780 DOI: 10.1080/17460441.2024.2324916] [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: 12/05/2023] [Accepted: 02/26/2024] [Indexed: 03/19/2024]
Abstract
INTRODUCTION Stroke is one of the main causes of death and disability worldwide. Nevertheless, despite the global burden of this disease, our understanding is limited and there is still a lack of highly efficient etiopathology-based treatment. It is partly due to the complexity and heterogenicity of the disease. It is estimated that around one-third of ischemic stroke is heritable, emphasizing the importance of genetic factors identification and targeting for therapeutic purposes. AREAS COVERED In this review, the authors provide an overview of the current knowledge of stroke genetics and its value in diagnostics, personalized treatment, and prognostication. EXPERT OPINION As the scale of genetic testing increases and the cost decreases, integration of genetic data into clinical practice is inevitable, enabling assessing individual risk, providing personalized prognostic models and identifying new therapeutic targets and biomarkers. Although expanding stroke genetics data provides different diagnostics and treatment perspectives, there are some limitations and challenges to face. One of them is the threat of health disparities as non-European populations are underrepresented in genetic datasets. Finally, a deeper understanding of underlying mechanisms of potential targets is still lacking, delaying the application of novel therapies into routine clinical practice.
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Affiliation(s)
| | | | | | - Kamilė Šiaurytė-Jurgelėnė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | | | - Dalius Jatužis
- Center of Neurology, Vilnius University, Vilnius, Lithuania
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Park JK, Brake MA, Schulman S. Human Genetic Variation in F3 and Its Impact on Tissue Factor-Dependent Disease. Semin Thromb Hemost 2024; 50:188-199. [PMID: 37201535 DOI: 10.1055/s-0043-1769079] [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] [Indexed: 05/20/2023]
Abstract
Tissue factor (TF) is the primary initiator of blood coagulation in humans. As improper intravascular TF expression and procoagulant activity underlie numerous thrombotic disorders, there has been longstanding interest in the contribution of heritable genetic variation in F3, the gene encoding TF, to human disease. This review seeks to comprehensively and critically synthesize small case-control studies focused on candidate single nucleotide polymorphisms (SNPs), as well as modern genome-wide association studies (GWAS) seeking to discover novel associations between variants and clinical phenotypes. Where possible, correlative laboratory studies, expression quantitative trait loci, and protein quantitative trait loci are evaluated to glean potential mechanistic insights. Most disease associations implicated in historical case-control studies have proven difficult to replicate in large GWAS. Nevertheless, SNPs linked to F3, such as rs2022030, are associated with increased F3 mRNA expression, monocyte TF expression after endotoxin exposure, and circulating levels of the prothrombotic biomarker D-dimer, consistent with the central role of TF in the initiation of blood coagulation.
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Affiliation(s)
- Jin K Park
- Division of Health, Sciences, and Technology, Massachusetts Institute of Technology and Harvard Medical School, Boston, Massachusetts
| | - Marisa A Brake
- Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Sol Schulman
- Division of Health, Sciences, and Technology, Massachusetts Institute of Technology and Harvard Medical School, Boston, Massachusetts
- Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
- Division of Hematology and Hematologic Malignancies, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
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3
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Akinyemi RO, Tiwari HK, Srinivasasainagendra V, Akpa O, Sarfo FS, Akpalu A, Wahab K, Obiako R, Komolafe M, Owolabi L, Osaigbovo GO, Mamaeva OA, Halloran BA, Akinyemi J, Lackland D, Obiabo OY, Sunmonu T, Chukwuonye II, Arulogun O, Jenkins C, Adeoye A, Agunloye A, Ogah OS, Ogbole G, Fakunle A, Uvere E, Coker MM, Okekunle A, Asowata O, Diala S, Ogunronbi M, Adeleye O, Laryea R, Tagge R, Adeniyi S, Adusei N, Oguike W, Olowoyo P, Adebajo O, Olalere A, Oladele O, Yaria J, Fawale B, Ibinaye P, Oyinloye O, Mensah Y, Oladimeji O, Akpalu J, Calys-Tagoe B, Dambatta HA, Ogunniyi A, Kalaria R, Arnett D, Rotimi C, Ovbiagele B, Owolabi MO. Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans. Genome Med 2024; 16:25. [PMID: 38317187 PMCID: PMC10840175 DOI: 10.1186/s13073-023-01273-5] [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: 06/07/2023] [Accepted: 12/12/2023] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans. METHODS Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation. RESULTS We observed genome-wide significant (P-value < 5.0E-8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E-6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E-6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E-6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping. CONCLUSIONS Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke's risk prediction and development of new targeted interventions to prevent or treat stroke.
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Affiliation(s)
- Rufus O Akinyemi
- Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Onoja Akpa
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Fred S Sarfo
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Albert Akpalu
- Department of Medicine, University of Ghana Medical School, Accra, Ghana
| | - Kolawole Wahab
- Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Reginald Obiako
- Department of Medicine, Ahmadu Bello University, Zaria, Nigeria
| | - Morenikeji Komolafe
- Department of Medicine, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria
| | - Lukman Owolabi
- Department of Medicine, Aminu Kano Teaching Hospital, Kano, Nigeria
| | | | - Olga A Mamaeva
- Department of Epidemiology, School of Public Health University of Alabama at Birmingham, Birmingham, USA
| | - Brian A Halloran
- Department of Pediatrics, Volker Hall University of Alabama at Birmingham, Birmingham, USA
| | - Joshua Akinyemi
- Department of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | | | - Olugbo Y Obiabo
- Delta State University/Delta State University Teaching Hospital, Oghara, Nigeria
| | - Taofik Sunmonu
- Department of Medicine, Federal Medical Centre, Ondo State, Owo, Nigeria
| | - Innocent I Chukwuonye
- Department of Medicine, Federal Medical Centre Umuahia, Abia State, Umuahia, Nigeria
| | - Oyedunni Arulogun
- Department of Health Education, Faculty of Public Health, University of Ibadan, Ibadan, Nigeria
| | | | - Abiodun Adeoye
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Atinuke Agunloye
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Okechukwu S Ogah
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Godwin Ogbole
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Adekunle Fakunle
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Public Health, College of Health Sciences, Osun State University, Osogbo, Nigeria
| | - Ezinne Uvere
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Motunrayo M Coker
- Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Genetics and Cell Biology Unit, Department of Zoology, Faculty of Science, University of Ibadan, Ibadan, Nigeria
| | - Akinkunmi Okekunle
- Department of Food and Nutrition, Seoul National University, Seoul, South Korea
| | - Osahon Asowata
- Department of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Samuel Diala
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Mayowa Ogunronbi
- Department of Medicine, Federal Medical Centre, Abeokuta, Nigeria
| | - Osi Adeleye
- Department of Medicine, Federal Medical Centre, Abeokuta, Nigeria
| | - Ruth Laryea
- Department of Medicine, University of Ghana Medical School, Accra, Ghana
| | - Raelle Tagge
- Weill Institute for Neurosciences, School of Medicine, University of California San-Francisco, San Francisco, USA
| | - Sunday Adeniyi
- Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Nathaniel Adusei
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Wisdom Oguike
- Department of Medicine, Ahmadu Bello University, Zaria, Nigeria
| | - Paul Olowoyo
- Federal Teaching Hospital, Ido-Ekiti, Ekiti State, Nigeria
| | - Olayinka Adebajo
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Abimbola Olalere
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Olayinka Oladele
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Joseph Yaria
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Bimbo Fawale
- Department of Medicine, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria
| | - Philip Ibinaye
- Department of Medicine, Ahmadu Bello University, Zaria, Nigeria
| | - Olalekan Oyinloye
- Department of Medicine, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria
| | - Yaw Mensah
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Omotola Oladimeji
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Josephine Akpalu
- Department of Medicine, University of Ghana Medical School, Accra, Ghana
| | - Benedict Calys-Tagoe
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | | | - Adesola Ogunniyi
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Rajesh Kalaria
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Donna Arnett
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA
| | - Charles Rotimi
- Center for Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Bruce Ovbiagele
- Genetics and Cell Biology Unit, Department of Zoology, Faculty of Science, University of Ibadan, Ibadan, Nigeria
| | - Mayowa O Owolabi
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria.
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria.
- University College Hospital, Ibadan, Nigeria.
- Lebanese American University of Beirut, Beirut, Lebanon.
- Blossom Specialist Medical Center, Ibadan, Nigeria.
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Zhang K, Loong SSE, Yuen LZH, Venketasubramanian N, Chin HL, Lai PS, Tan BYQ. Genetics in Ischemic Stroke: Current Perspectives and Future Directions. J Cardiovasc Dev Dis 2023; 10:495. [PMID: 38132662 PMCID: PMC10743455 DOI: 10.3390/jcdd10120495] [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: 11/15/2023] [Revised: 12/01/2023] [Accepted: 12/11/2023] [Indexed: 12/23/2023] Open
Abstract
Ischemic stroke is a heterogeneous condition influenced by a combination of genetic and environmental factors. Recent advancements have explored genetics in relation to various aspects of ischemic stroke, including the alteration of individual stroke occurrence risk, modulation of treatment response, and effectiveness of post-stroke functional recovery. This article aims to review the recent findings from genetic studies related to various clinical and molecular aspects of ischemic stroke. The potential clinical applications of these genetic insights in stratifying stroke risk, guiding personalized therapy, and identifying new therapeutic targets are discussed herein.
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Affiliation(s)
- Ka Zhang
- Division of Neurology, Department of Medicine, National University Hospital, Singapore 119074, Singapore;
| | - Shaun S. E. Loong
- Cardiovascular-Metabolic Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore;
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
| | - Linus Z. H. Yuen
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
| | | | - Hui-Lin Chin
- Khoo Teck Puat National University Children’s Medical Institute, National University Hospital, Singapore 119074, Singapore;
| | - Poh San Lai
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore;
| | - Benjamin Y. Q. Tan
- Division of Neurology, Department of Medicine, National University Hospital, Singapore 119074, Singapore;
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
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Khvorykh GV, Sapozhnikov NA, Limborska SA, Khrunin AV. Evaluation of Density-Based Spatial Clustering for Identifying Genomic Loci Associated with Ischemic Stroke in Genome-Wide Data. Int J Mol Sci 2023; 24:15355. [PMID: 37895035 PMCID: PMC10607504 DOI: 10.3390/ijms242015355] [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: 07/22/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
The genetic architecture of ischemic stroke (IS), which is one of the leading causes of death worldwide, is complex and underexplored. The traditional approach for associative gene mapping is genome-wide association studies (GWASs), testing individual single-nucleotide polymorphisms (SNPs) across the genomes of case and control groups. The purpose of this research is to develop an alternative approach in which groups of SNPs are examined rather than individual ones. We proposed, validated and applied to real data a new workflow consisting of three key stages: grouping SNPs in clusters, inferring the haplotypes in the clusters and testing haplotypes for the association with phenotype. To group SNPs, we applied the clustering algorithms DBSCAN and HDBSCAN to linkage disequilibrium (LD) matrices, representing pairwise r2 values between all genotyped SNPs. These clustering algorithms have never before been applied to genotype data as part of the workflow of associative studies. In total, 883,908 SNPs and insertion/deletion polymorphisms from people of European ancestry (4929 cases and 652 controls) were processed. The subsequent testing for frequencies of haplotypes restored in the clusters of SNPs revealed dozens of genes associated with IS and suggested the complex role that protocadherin molecules play in IS. The developed workflow was validated with the use of a simulated dataset of similar ancestry and the same sample sizes. The results of classic GWASs are also provided and discussed. The considered clustering algorithms can be applied to genotypic data to identify the genomic loci associated with different qualitative traits, using the workflow presented in this research.
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Affiliation(s)
| | | | | | - Andrey V. Khrunin
- National Research Centre “Kurchatov Institute”, Kurchatov Sq. 2, Moscow 123182, Russia; (G.V.K.); (N.A.S.); (S.A.L.)
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Doumatey AP, Bentley AR, Akinyemi R, Olanrewaju TO, Adeyemo A, Rotimi C. Genes, environment, and African ancestry in cardiometabolic disorders. Trends Endocrinol Metab 2023; 34:601-621. [PMID: 37598069 PMCID: PMC10548552 DOI: 10.1016/j.tem.2023.07.007] [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: 05/19/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/21/2023]
Abstract
The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field.
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Affiliation(s)
- Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Rufus Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training and Centre for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria; Department of Neurology, University College Hospital, Ibadan, Nigeria
| | - Timothy O Olanrewaju
- Division of Nephrology, Department of Medicine, University of Ilorin & University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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7
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Du Z, Zhang Z, Han X, Xie H, Yan W, Tian D, Liu M, Rao C. Comprehensive Analysis of Sideroflexin 4 in Hepatocellular Carcinoma by Bioinformatics and Experiments. Int J Med Sci 2023; 20:1300-1315. [PMID: 37786439 PMCID: PMC10542026 DOI: 10.7150/ijms.86990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/01/2023] [Indexed: 10/04/2023] Open
Abstract
Background: Sideroflexins (SFXNs) are a family of highly conserved mitochondrial transporters which regulate iron homeostasis and mitochondrial respiratory chain. However, the roles and mechanisms of SFXNs in HCC remain unknown. Methods: SFXNs expression and prognostic value in HCC was comprehensively analyzed. Proteins interacting with SFXN4 were analyzed in STRING database. The co-expression genes of SFXN4 were analyzed in cBioPortal database, and function of SFXN4 co-expression genes were annotated. The putative transcription factors and miRNA targeting SFXN4 were analyzed in NetworkAnalyst. The correlation between SFXN4 expression and immune infiltration was analyzed by ssGSEA. Cancer pathway activity and drug sensitivity related to SFXN4 were explored in GSCALite. The roles of SFXN4 in proliferation, migration and invasion of HCC were assessed in vitro and in vivo. Results: SFXN4 was consistently elevated in HCC, positively correlated with clinicopathological characteristics and predicted poor outcome. Functional enrichment showed SFXN4 was mainly related to oxidative phosphorylation, reactive oxygen species and metabolic pathways. SFXN4 expression was regulated by multiple transcription factors and miRNAs, and SFXN4 expression in HCC was associated with several cancer pathways and drug sensitivity. SFXN4 expression correlated with immune infiltration in HCC. In vitro, knockdown of SFXN4 inhibited HCC proliferation, migration and invasion, and decreased the expression of cyclin D1 and MMP2. In vivo, knockdown of SFXN4 inhibited the growth of tumor xenografts in mice. Conclusion: SFXN4 was upregulated in HCC, predicted poor prognosis, and may facilitate HCC development and progression via various mechanisms. For HCC, SFXN4 may provide both prognostic information and therapeutic potential.
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Affiliation(s)
- Zhipeng Du
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhongchao Zhang
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xu Han
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huaping Xie
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Yan
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dean Tian
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mei Liu
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Caijun Rao
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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8
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Surakka I, Wu KH, Hornsby W, Wolford BN, Shen F, Zhou W, Huffman JE, Pandit A, Hu Y, Brumpton B, Skogholt AH, Gabrielsen ME, Walters RG, Hveem K, Kooperberg C, Zöllner S, Wilson PW, Sutton NR, Daly MJ, Neale BM, Willer CJ. Multi-ancestry meta-analysis identifies 5 novel loci for ischemic stroke and reveals heterogeneity of effects between sexes and ancestries. CELL GENOMICS 2023; 3:100345. [PMID: 37601974 PMCID: PMC10435368 DOI: 10.1016/j.xgen.2023.100345] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/18/2022] [Accepted: 05/26/2023] [Indexed: 08/22/2023]
Abstract
Stroke is the second leading cause of death and disability worldwide. Stroke prevalence varies by sex and ancestry, possibly due to genetic heterogeneity between subgroups. We performed a genome-wide meta-analysis of 16 biobanks across multiple ancestries to study the genetics of ischemic stroke (60,176 cases, 1,310,725 controls) as part of the Global Biobank Meta-analysis Initiative (GBMI) and further combined the results with previously published MegaStroke. Five novel loci for ischemic stroke (LAMC1, CALCRL, PLSCR1, CDKN1A, and SWAP70) were identified after replication in four additional datasets. One previously reported locus showed significant ancestry heterogeneity (ABO), and one showed significant sex heterogeneity (ALDH2). The ALDH2 association was male specific (males p = 1.67e-24, females p = 0.126) and was additionally observed only in the East Asian ancestry (male) samples. These findings emphasize the need for more diverse datasets with large sample sizes to further understand the genetic predisposition of stroke in different ancestry and sex groups.
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Affiliation(s)
- Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kuan-Han Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Whitney Hornsby
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Brooke N. Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Fred Shen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jennifer E. Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Anita Pandit
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maiken E. Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Robin G. Walters
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - The TOPMed Stroke Working Group
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Million Veteran Program (MVP)
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sebastian Zöllner
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Peter W.F. Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Nadia R. Sutton
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Cristen J. Willer
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - on behalf of the Global Biobank Meta-analysis Initiative (GBMI)
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
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9
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Soremekun O, Musanabaganwa C, Uwineza A, Ardissino M, Rajasundaram S, Wani AH, Jansen S, Mutabaruka J, Rutembesa E, Soremekun C, Cheickna C, Wele M, Mugisha J, Nash O, Kinyanda E, Nitsch D, Fornage M, Chikowore T, Gill D, Wildman DE, Mutesa L, Uddin M, Fatumo S. A Mendelian randomization study of genetic liability to post-traumatic stress disorder and risk of ischemic stroke. Transl Psychiatry 2023; 13:237. [PMID: 37391434 PMCID: PMC10313806 DOI: 10.1038/s41398-023-02542-y] [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: 03/08/2022] [Revised: 06/21/2023] [Accepted: 06/23/2023] [Indexed: 07/02/2023] Open
Abstract
Observational studies have shown an association between post-traumatic stress disorder (PTSD) and ischemic stroke (IS) but given the susceptibility to confounding it is unclear if these associations represent causal effects. Mendelian randomization (MR) facilitates causal inference that is robust to the influence of confounding. Using two sample MR, we investigated the causal effect of genetic liability to PTSD on IS risk. Ancestry-specific genetic instruments of PTSD and four quantitative sub-phenotypes of PTSD, including hyperarousal, avoidance, re-experiencing, and total symptom severity score (PCL-Total) were obtained from the Million Veteran Programme (MVP) using a threshold P value (P) of <5 × 10-7, clumping distance of 1000 kilobase (Mb) and r2 < 0.01. Genetic association estimates for IS were obtained from the MEGASTROKE consortium (Ncases = 34,217, Ncontrols = 406,111) for European ancestry individuals and from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) (Ncases = 3734, Ncontrols = 18,317) for African ancestry individuals. We used the inverse-variance weighted (IVW) approach as the main analysis and performed MR-Egger and the weighted median methods as pleiotropy-robust sensitivity analyses. In European ancestry individuals, we found evidence of an association between genetic liability to PTSD avoidance, and PCL-Total and increased IS risk (odds ratio (OR)1.04, 95% Confidence Interval (CI) 1.007-1.077, P = 0.017 for avoidance and (OR 1.02, 95% CI 1.010-1.040, P = 7.6 × 10-4 for PCL total). In African ancestry individuals, we found evidence of an association between genetically liability to PCL-Total and reduced IS risk (OR 0.95 (95% CI 0.923-0.991, P = 0.01) and hyperarousal (OR 0.83 (95% CI 0.691-0.991, P = 0.039) but no association was observed for PTSD case-control, avoidance, or re-experiencing. Similar estimates were obtained with MR sensitivity analyses. Our findings suggest that specific sub-phenotypes of PTSD, such as hyperarousal, avoidance, PCL total, may have a causal effect on people of European and African ancestry's risk of IS. This shows that the molecular mechanisms behind the relationship between IS and PTSD may be connected to symptoms of hyperarousal and avoidance. To clarify the precise biological mechanisms involved and how they may vary between populations, more research is required.
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Affiliation(s)
- Opeyemi Soremekun
- The African Computational Genomics (TACG) Research group, MRC/UVRI and LSHTM, Entebbe, Uganda
- Discipline of Pharmaceutical Chemistry, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | | | - Annette Uwineza
- Department of Biochemistry, Molecular Biology and Genetics, CMHS, University of Rwanda, Kigali, Rwanda
- Center for Human Genetics at the College of Medicine and Health Sciences-University of Rwanda, Kigali, Rwanda
| | - Maddalena Ardissino
- Department of Epidemiology and Biostatistics, Medical School Building, St Mary's Hospital, Imperial College London, London, UK
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK
- Faculty of Medicine, Imperial College London, London, UK
| | - Agaz H Wani
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Stefan Jansen
- Directorate of Research and Innovation, University of Rwanda, Kigali, Rwanda
| | - Jean Mutabaruka
- Department of Clinical Psychology, University of Rwanda, Kigali, Rwanda
| | - Eugene Rutembesa
- Department of Clinical Psychology, University of Rwanda, Kigali, Rwanda
| | - Chisom Soremekun
- The African Computational Genomics (TACG) Research group, MRC/UVRI and LSHTM, Entebbe, Uganda
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | - Cisse Cheickna
- The African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako (USTTB), Bamako, Mali
| | - Mamadou Wele
- The African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako (USTTB), Bamako, Mali
| | | | - Oyekanmi Nash
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | | | - Dorothea Nitsch
- Department of Non-communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, London, UK
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Austin, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Austin, USA
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, Medical School Building, St Mary's Hospital, Imperial College London, London, UK
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Leon Mutesa
- Center for Human Genetics at the College of Medicine and Health Sciences-University of Rwanda, Kigali, Rwanda
| | - Monica Uddin
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research group, MRC/UVRI and LSHTM, Entebbe, Uganda.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
- MRC/UVRI and LSHTM, Entebbe, Uganda.
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10
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Kurvits S, Harro A, Reigo A, Ott A, Laur S, Särg D, Tampuu A, Alasoo K, Vilo J, Milani L, Haller T. Common clinical blood and urine biomarkers for ischemic stroke: an Estonian Electronic Health Records database study. Eur J Med Res 2023; 28:133. [PMID: 36966315 PMCID: PMC10039346 DOI: 10.1186/s40001-023-01087-6] [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: 06/12/2022] [Accepted: 03/04/2023] [Indexed: 03/27/2023] Open
Abstract
BACKGROUND Ischemic stroke (IS) is a major health risk without generally usable effective measures of primary prevention. Early warning signals that are easy to detect and widely available can save lives. Estonia has one nation-wide Electronic Health Record (EHR) database for the storage of medical information of patients from hospitals and primary care providers. METHODS We extracted structured and unstructured data from the EHRs of participants of the Estonian Biobank (EstBB) and evaluated different formats of input data to understand how this continuously growing dataset should be prepared for best prediction. The utility of the EHR database for finding blood- and urine-based biomarkers for IS was demonstrated by applying different analytical and machine learning (ML) methods. RESULTS Several early trends in common clinical laboratory parameter changes (set of red blood indices, lymphocyte/neutrophil ratio, etc.) were established for IS prediction. The developed ML models predicted the future occurrence of IS with very high accuracy and Random Forests was proved as the most applicable method to EHR data. CONCLUSIONS We conclude that the EHR database and the risk factors uncovered are valuable resources in screening the population for risk of IS as well as constructing disease risk scores and refining prediction models for IS by ML.
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Affiliation(s)
- Siim Kurvits
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ainika Harro
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anne Ott
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Software Technology and Applications Competence Center, Tartu, Estonia
| | - Sven Laur
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Software Technology and Applications Competence Center, Tartu, Estonia
| | - Dage Särg
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Software Technology and Applications Competence Center, Tartu, Estonia
| | - Ardi Tampuu
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | | | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Jaak Vilo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Software Technology and Applications Competence Center, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Toomas Haller
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.
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11
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Deng XD, Ke JL, Chen TY, Gao Q, Zhao ZL, Zhang W, Liu H, Xiang ML, Wang LZ, Ma Y, Liu Y. ERCC1 polymorphism and its expression associated with ischemic stroke in Chinese population. Front Neurol 2023; 13:998428. [PMID: 36712419 PMCID: PMC9878395 DOI: 10.3389/fneur.2022.998428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 12/23/2022] [Indexed: 01/15/2023] Open
Abstract
Background Excision repair cross-complementing group 1 (ERCC1) was considered a potential candidate gene for ischemic stroke, and its polymorphisms might be associated with the susceptibility to ischemic stroke. Methods A total of 513 patients with ischemic stroke and 550 control subjects were recruited. The expression levels of ERCC1 messenger RNA (mRNA) in peripheral blood mononuclear cells and its protein in plasma were detected by quantitative real-time PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA), respectively. Rs3212986 polymorphism of ERCC1 was detected by PCR-restriction fragment length polymorphism (RFLP-PCR) and was confirmed by sequencing. The association between the ERCC1 rs3212986 polymorphism or its expression and ischemic stroke was further analyzed. Results The ERCC1 mRNA level in patients with ischemic stroke was lower than that in the control group (P < 0.05). However, the ERCC1 protein level in patients with ischemic stroke was higher than that in the control group (P < 0.05). The A allele of rs3212986 was associated with increased ischemic stroke risk (OR = 1.287, 95% CI = 1.076-1.540, P = 0.006). The association between rs3212986 polymorphism and ischemic stroke susceptibility was found in both recessive (OR = 2.638, 95% CI = 1.744-3.989, P < 0.001) and additive models (OR = 1.309, 95% CI = 1.028-1.667, P = 0.031), respectively. Similar results were obtained in the recessive model (OR = 2.015, 95% CI = 1.087-3.704, P = 0.026) after adjusting for demographic information and other variables. Additionally, the level of ERCC1 mRNA in the CC/CA genotype was higher than that in the AA genotype (P < 0.05). Conclusion It was suggested that the ERCC1 rs3212986 polymorphism was associated with ischemic stroke susceptibility in a Chinese Han population and that an A allele of rs3212986 was related to increased ischemic stroke risk. The altered ERCC1 expression level caused by the rs3212986 polymorphism might participate in the pathophysiological process of ischemic stroke.
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Affiliation(s)
- Xiao-Dong Deng
- Department of Forensic Pathology, School of Basic Medical Science and Forensic Medicine, North Sichuan Medical College, Nanchong, China
| | - Jian-Lin Ke
- Department of Forensic Pathology, School of Basic Medical Science and Forensic Medicine, North Sichuan Medical College, Nanchong, China
| | - Tai-Yu Chen
- Department of Intergrated Western and Chinese Colorectal and Anal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Qin Gao
- Department of Internal Medicine, Nanchong Jialing District People's Hospital, Nanchong, China
| | - Zhuo-Lin Zhao
- Department of Neurology, The Second People's Hospital of Yibin, Yibin, China
| | - Wei Zhang
- Department of Forensic Pathology, School of Basic Medical Science and Forensic Medicine, North Sichuan Medical College, Nanchong, China
| | - Huan Liu
- Department of Preventive Medicine, North Sichuan Medical College, Nanchong, China
| | - Ming-Liang Xiang
- Department of Forensic Pathology, School of Basic Medical Science and Forensic Medicine, North Sichuan Medical College, Nanchong, China
| | - Li-Zhen Wang
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ying Ma
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China,*Correspondence: Ying Ma ✉
| | - Yun Liu
- Department of Forensic Pathology, School of Basic Medical Science and Forensic Medicine, North Sichuan Medical College, Nanchong, China,Sichuan Key Laboratory of Medical Imaging, Affiliated Hospital of North Sichuan Medical College, Nanchong, China,Yun Liu ✉
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12
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Bonnechère B, Liu J, Thompson A, Amin N, van Duijn C. Does ethnicity influence dementia, stroke and mortality risk? Evidence from the UK Biobank. Front Public Health 2023; 11:1111321. [PMID: 37124771 PMCID: PMC10140594 DOI: 10.3389/fpubh.2023.1111321] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 03/10/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction The number of people with dementia and stroke is increasing worldwide. There is increasing evidence that there are clinically relevant genetic differences across ethnicities. This study aims to quantify risk factors of dementia, stroke, and mortality in Asian and black participants compared to whites. Methods 272,660 participants from the UK Biobank were included in the final analysis, among whom the vast majority are white (n = 266,671, 97.80%), followed by Asian (n = 3,790, 1.35%), and black (n = 2,358, 0.84%) participants. Cumulative incidence risk was calculated based on all incident cases occurring during the follow-up of the individuals without dementia and stroke at baseline. We compared the allele frequency of variants in Asian and black participants with the referent ethnicity, whites, by chi-square test. Hierarchical cluster analysis was used in the clustering analysis. Significance level corrected for the false discovery rate was considered. Results After adjusting for risk factors, black participants have an increased risk of dementia and stroke compared to white participants, while Asians has similar odds to the white. The risk of mortality is not different in blacks and white participants but Asians have a decreased risk. Discussion The study provides important insights into the potential differences in the risk of dementia and stroke among different ethnic groups. Specifically, the study found that black individuals had a higher incidence of dementia and stroke compared to white individuals living in the UK. These findings are particularly significant as they suggest that there may be underlying factors that contribute to these differences, including genetic, environmental, and social factors. By identifying these differences, the study helps to inform interventions and policies aimed at reducing the risk of dementia and stroke, particularly among high-risk populations.
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Affiliation(s)
- Bruno Bonnechère
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
- Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, Hasselt University, Diepenbeek, Belgium
| | - Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Alexander Thompson
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Najaf Amin
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Cornelia van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- *Correspondence: Cornelia van Duijn,
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13
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Tang H, Zhang H, Liu D, Wang Z, Yu D, Fan W, Guo Z, Huang W, Hou S, Zhou Z. Genome-wide association study reveals the genetic determinism of serum biochemical indicators in ducks. BMC Genomics 2022; 23:856. [PMID: 36575369 PMCID: PMC9795613 DOI: 10.1186/s12864-022-09080-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 12/12/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND The serum is rich in nutrients and plays an essential role in electrolyte and acid-base balance, maintaining cellular homeostasis. In addition, serum parameters have been commonly used as essential biomarkers for clinical diagnosis. However, little is known about the genetic mechanism of the serum parameters in ducks. RESULTS This study measured 18 serum parameters in 320 samples of the F2 segregating population generated by Mallard × Pekin duck. The phenotypic correlations showed a high correlation between LDH, HBDH, AST, and ALT (0.59-0.99), and higher coefficients were also observed among TP, ALB, HDL-C, and CHO (0.46-0.87). And then, we performed the GWAS to reveal the genetic basis of the 18 serum biochemical parameters in ducks. Fourteen candidate protein-coding genes were identified with enzyme traits (AST, ALP, LDH, HBDH), and 3 protein-coding genes were associated with metabolism and protein-related serum parameters (UA, TG). Moreover, the expression levels of the above candidate protein-coding genes in different stages of breast muscle and different tissues were analyzed. Furthermore, the genes located within the high-LD region (r2 > 0.4 and - log10(P) < 4) neighboring the significant locus also remained. Finally, 86 putative protein-coding genes were used for GO and KEGG enrichment analysis, the enzyme-linked receptor protein signaling pathway and ErbB signaling pathway deserve further focus. CONCLUSIONS The obtained results can contribute to new insights into blood metabolism and provide new genetic biomarkers for application in duck breeding programs.
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Affiliation(s)
- Hehe Tang
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - He Zhang
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Dapeng Liu
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Zhen Wang
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Daxin Yu
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Wenlei Fan
- grid.412608.90000 0000 9526 6338College of Food Science and Engineering, Qingdao Agricultural University, Qingdao, PR China
| | - Zhanbao Guo
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Wei Huang
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Shuisheng Hou
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Zhengkui Zhou
- grid.410727.70000 0001 0526 1937Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, PR China
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14
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Circulating MicroRNA Profiling Identifies Distinct MicroRNA Signatures in Acute Ischemic Stroke and Transient Ischemic Attack Patients. Int J Mol Sci 2022; 24:ijms24010108. [PMID: 36613546 PMCID: PMC9820644 DOI: 10.3390/ijms24010108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 12/04/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022] Open
Abstract
Transient ischemic attack (TIA) refers to a momentary neurologic deficit caused by focal cerebral, spinal or retinal ischemic insult. TIA is associated with a high risk of impending acute ischemic stroke (AIS), a neurologic dysfunction characterized by focal cerebral, spinal or retinal infarction. Understanding the differences in molecular pathways in AIS and TIA has merit for deciphering the underlying cause for neuronal deficits with long-term effects and high risks of morbidity and mortality. In this study, we performed comprehensive investigations into the circulating microRNA (miRNA) profiles of AIS (n = 191) and TIA (n = 61) patients. We performed RNA-Seq on serum samples collected within 24 hrs of clinical diagnosis and randomly divided the study populations into discovery and validation cohorts. We identified a panel of 11 differentially regulated miRNAs at FDR < 0.05. Hsa-miR-548c-5p, -20a-5p, -18a-5p, -484, -652-3p, -486-3p, -24-3p, -181a-5p and -222-3p were upregulated, while hsa-miR-500a-3p and -206 were downregulated in AIS patients compared to TIA patients. We also probed the previously validated gene targets of our identified miRNA panel to highlight the molecular pathways affected in AIS. Moreover, we developed a multivariate classifier with potential utilization as a discriminative biomarker for AIS and TIA patients. The underlying molecular pathways in AIS compared to TIA may be explored further in functional studies for therapeutic targeting in clinical translation.
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Ryu JR, Ahuja S, Arnold CR, Potts KG, Mishra A, Yang Q, Sargurupremraj M, Mahoney DJ, Seshadri S, Debette S, Childs SJ. Stroke-associated intergenic variants modulate a human FOXF2 transcriptional enhancer. Proc Natl Acad Sci U S A 2022; 119:e2121333119. [PMID: 35994645 PMCID: PMC9436329 DOI: 10.1073/pnas.2121333119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 07/28/2022] [Indexed: 11/18/2022] Open
Abstract
SNPs associated with human stroke risk have been identified in the intergenic region between Forkhead family transcription factors FOXF2 and FOXQ1, but we lack a mechanism for the association. FoxF2 is expressed in vascular mural pericytes and is important for maintaining pericyte number and stabilizing small vessels in zebrafish. The stroke-associated SNPs are located in a previously unknown transcriptional enhancer for FOXF2, functional in human cells and zebrafish. We identify critical enhancer regions for FOXF2 gene expression, including binding sites occupied by transcription factors ETS1, RBPJ, and CTCF. rs74564934, a stroke-associated SNP adjacent to the ETS1 binding site, decreases enhancer function, as does mutation of RPBJ sites. rs74564934 is significantly associated with the increased risk of any stroke, ischemic stroke, small vessel stroke, and elevated white matter hyperintensity burden in humans. Foxf2 has a conserved function cross-species and is expressed in vascular mural pericytes of the vessel wall. Thus, stroke-associated SNPs modulate enhancer activity and expression of a regulator of vascular stabilization, FOXF2, thereby modulating stroke risk.
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Affiliation(s)
- Jae-Ryeon Ryu
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Suchit Ahuja
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Corey R. Arnold
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Kyle G. Potts
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Microbiology, Immunology, and Infectious Diseases, University of Calgary, Calgary AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Aniket Mishra
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - Qiong Yang
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118
| | - Muralidharan Sargurupremraj
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX 78229
- Boston University and the NHLBI’s Framingham Heart Study, Boston, MA 02215
| | - Douglas J. Mahoney
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Microbiology, Immunology, and Infectious Diseases, University of Calgary, Calgary AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX 78229
- Boston University and the NHLBI’s Framingham Heart Study, Boston, MA 02215
| | - Stéphanie Debette
- University of Bordeaux, INSERM, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118
- Department of Neurology, CHU de Bordeaux, 33000 Bordeaux, France
| | - Sarah J. Childs
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary AB T2N 4N1, Canada
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary AB T2N 4N1, Canada
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16
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Thomas EA, Enduru N, Tin A, Boerwinkle E, Griswold ME, Mosley TH, Gottesman RF, Fornage M. Polygenic Risk, Midlife Life's Simple 7, and Lifetime Risk of Stroke. J Am Heart Assoc 2022; 11:e025703. [PMID: 35862192 PMCID: PMC9375491 DOI: 10.1161/jaha.122.025703] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Background Recent genetic discoveries in stroke have unleashed the potential of using genetic information for risk prediction and health interventions aimed at disease prevention. We sought to estimate the lifetime risk of stroke (LTRS) by levels of genetic risk and to investigate whether optimal cardiovascular health can offset the negative impact of high genetic risk on lifetime risk of stroke. Methods and Results Study participants were 11 568 middle‐aged adults (56% women, 23% Black adults), who were free of stroke at baseline and were followed up for a median of 28 years. The remaining LTRS was estimated according to levels of genetic risk based on a validated stroke polygenic risk score, and to levels of cardiovascular health based on the American Heart Association Life's Simple 7 recommendations. At age 45, individuals with high, intermediate, and low polygenic risk score had a remaining LTRS of 23.2% (95% CI, 20.8%–25.5%), 13.8% (95% CI, 11.7%–15.8%), and 9.6% (95% CI, 7.3%–11.8%), respectively. Those with both a high genetic risk and an inadequate Life's Simple 7 experienced the highest LTRS: 24.8% (95% CI, 22.0%–27.6%). Across all polygenic risk score categories, those with an optimal Life's Simple 7 had a ≈30% to 43% lower LTRS than those with an inadequate Life's Simple 7. This corresponded to almost 6 additional years lived free of stroke. Conclusions The LTRS varies by levels of polygenic risk and cardiovascular health. Maintaining an optimal cardiovascular health can partially offset a high genetic risk, emphasizing the importance of modifiable risk factors and illustrating the potential of personalizing genetic risk information to motivate lifestyle changes for stroke prevention.
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Affiliation(s)
- Emy A Thomas
- Brown Foundation Institute of Molecular Medicine McGovern Medical School, University of Texas Health Science Center at Houston Houston TX
| | - Nitesh Enduru
- Brown Foundation Institute of Molecular Medicine McGovern Medical School, University of Texas Health Science Center at Houston Houston TX
| | - Adrienne Tin
- Department of Medicine University of Mississippi Jackson MS
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health University of Texas Health Science Center at Houston Houston TX
| | | | - Thomas H Mosley
- Department of Medicine University of Mississippi Jackson MS.,The MIND Center University of Mississippi Medical Center Jackson MS
| | - Rebecca F Gottesman
- Stroke Branch National Institute of Neurological Disorders and Stroke Bethesda MD
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine McGovern Medical School, University of Texas Health Science Center at Houston Houston TX.,Human Genetics Center, School of Public Health University of Texas Health Science Center at Houston Houston TX
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17
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Li J, Chaudhary D, Griessenauer CJ, Carey DJ, Zand R, Abedi V. Predicting mortality among ischemic stroke patients using pathways-derived polygenic risk scores. Sci Rep 2022; 12:12358. [PMID: 35853973 PMCID: PMC9296485 DOI: 10.1038/s41598-022-16510-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/11/2022] [Indexed: 12/19/2022] Open
Abstract
We aim to determine whether ischemic stroke(IS)-related PRSs are also associated with and further predict 3-year all-cause mortality. 1756 IS patients with European ancestry were randomly split into training (n = 1226) and testing (n = 530) groups with 3-year post-event observations. Univariate Cox proportional hazards regression model (CoxPH) was used for primary screening of individual prognostic PRSs. Only the significantly associated PRSs and clinical risk factors with the same direction for a causal relationship with IS were used to construct a multivariate CoxPH. Feature selection was conducted by the LASSO method. After feature selection, a prediction model with 11 disease-associated pathway-specific PRSs outperformed the base model, as demonstrated by a higher concordance index (0.751, 95%CI [0.693–0.809] versus 0.729, 95%CI [0.676–0.782]) in the testing sample. A PRS derived from endothelial cell apoptosis showed independent predictability in the multivariate CoxPH (Hazard Ratio = 1.193 [1.027–1.385], p = 0.021). These PRSs fine-tuned the model by better stratifying high, intermediate, and low-risk groups. Several pathway-specific PRSs were associated with clinical risk factors in an age-dependent manner and further confirmed some known etiologies of IS and all-cause mortality. In conclusion, Pathway-specific PRSs for IS are associated with all-cause mortality, and the integrated multivariate risk model provides prognostic value in this context.
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Affiliation(s)
- Jiang Li
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA, 17822, USA
| | - Durgesh Chaudhary
- Neuroscience Institute, Geisinger Health System, Danville, PA, 17822, USA
| | - Christoph J Griessenauer
- Neuroscience Institute, Geisinger Health System, Danville, PA, 17822, USA.,Research Institute of Neurointervention, Paracelsus Medical University, Salzburg, Austria
| | - David J Carey
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA, 17822, USA
| | - Ramin Zand
- Neuroscience Institute, Geisinger Health System, Danville, PA, 17822, USA.
| | - Vida Abedi
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA, 17822, USA. .,Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA, USA.
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18
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Abstract
Stroke is the second leading cause of death worldwide and a complex, heterogeneous condition. In this review, we provide an overview of the current knowledge on monogenic and multifactorial forms of stroke, highlighting recent insight into the continuum between these. We describe how, in recent years, large-scale genome-wide association studies have enabled major progress in deciphering the genetic basis for stroke and its subtypes, although more research is needed to interpret these findings. We cover the potential of stroke genetics to reveal novel pathophysiological processes underlying stroke, to accelerate the discovery of new therapeutic approaches, and to identify individuals in the population who are at high risk of stroke and could be targeted for tailored preventative interventions.
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Affiliation(s)
- Stéphanie Debette
- Bordeaux Population Health Research Center, Inserm U1219, University of Bordeaux, France (S.D.).,Department of Neurology, Bordeaux University Hospital, Institute for Neurodegenerative Diseases, France (S.D.)
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, United Kingdom (H.S.M.)
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19
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Armstrong ND, Srinivasasainagendra V, Patki A, Tanner RM, Hidalgo BA, Tiwari HK, Limdi NA, Lange EM, Lange LA, Arnett DK, Irvin MR. Genetic Contributors of Incident Stroke in 10,700 African Americans With Hypertension: A Meta-Analysis From the Genetics of Hypertension Associated Treatments and Reasons for Geographic and Racial Differences in Stroke Studies. Front Genet 2022; 12:781451. [PMID: 34992631 PMCID: PMC8724550 DOI: 10.3389/fgene.2021.781451] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/23/2021] [Indexed: 11/25/2022] Open
Abstract
Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals. Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs aiming to evaluate cross-ethnic performance. Results: We identified 10 statistically significant (p < 5.00E-08) and 90 additional suggestive (p < 1.00E-06) variants associated with incident stroke in the meta-analysis. Six of the top 10 variants were located in an intergenic region on chromosome 18 (LINC01443-LOC644669). Additional variants of interest were located in or near the COL12A1, SNTG1, PCDH7, TMTC1, and NTM genes. Replication was conducted in the Warfarin Pharmacogenomics Cohort (WPC), and while none of the variants were directly validated, seven intronic variants of NTM proximal to our target variants, had a p-value <5.00E-04 in the WPC. The inclusion of the PRS did not improve the prediction accuracy compared to a reference model adjusting for age, sex, and genetic ancestry in either study and had lower predictive accuracy compared to models accounting for established stroke risk factors. These results demonstrate the necessity for PRS derivation in AAs, particularly for diseases that affect AAs disproportionately. Conclusion: This study highlights biologically plausible genetic determinants for incident stroke in hypertensive AAs. Ultimately, a better understanding of genetic risk factors for stroke in AAs may give new insight into stroke burden and potential clinical tools for those among the highest at risk.
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Affiliation(s)
- Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | | | - Amit Patki
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Rikki M Tanner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Bertha A Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Nita A Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ethan M Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
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20
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Abstract
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.
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21
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Prapiadou S, Demel SL, Hyacinth HI. Genetic and Genomic Epidemiology of Stroke in People of African Ancestry. Genes (Basel) 2021; 12:1825. [PMID: 34828431 PMCID: PMC8619587 DOI: 10.3390/genes12111825] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/17/2021] [Accepted: 11/17/2021] [Indexed: 11/16/2022] Open
Abstract
Stroke is one of the leading causes of disability and death worldwide and places a significant burden on healthcare systems. There are significant racial/ethnic differences in the incidence, subtype, and prognosis of stroke, between people of European and African ancestry, of which only about 50% can be explained by traditional stroke risk facts. However, only a small number of genetic studies include individuals of African descent, leaving many gaps in our understanding of stroke genetics among this population. This review article highlights the need for and significance of including African-ancestry individuals in stroke genetic studies and points to the efforts that have been made towards this direction. Additionally, we discuss the caveats, opportunities, and next steps in African stroke genetics-a field still in its infancy but with great potential for expanding our understanding of stroke biology and for developing new therapeutic strategies.
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Affiliation(s)
- Savvina Prapiadou
- Department of Medicine, University of Patras School of Medicine, 26223 Patras, Greece;
| | - Stacie L. Demel
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH 45221, USA;
| | - Hyacinth I. Hyacinth
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH 45221, USA;
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22
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Fatumo S, Karhunen V, Chikowore T, Sounkou T, Udosen B, Ezenwa C, Nakabuye M, Soremekun O, Daghlas I, Ryan DK, Taylor A, Mason AM, Damrauer SM, Vujkovic M, Keene KL, Fornage M, Järvelin MR, Burgess S, Gill D. Metabolic Traits and Stroke Risk in Individuals of African Ancestry: Mendelian Randomization Analysis. Stroke 2021; 52:2680-2684. [PMID: 34078102 PMCID: PMC8312569 DOI: 10.1161/strokeaha.121.034747] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/18/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Metabolic traits affect ischemic stroke (IS) risk, but the degree to which this varies across different ethnic ancestries is not known. Our aim was to apply Mendelian randomization to investigate the causal effects of type 2 diabetes (T2D) liability and lipid traits on IS risk in African ancestry individuals, and to compare them to estimates obtained in European ancestry individuals. METHODS For African ancestry individuals, genetic proxies for T2D liability and circulating lipids were obtained from a meta-analysis of the African Partnership for Chronic Disease Research study, the UK Biobank, and the Million Veteran Program (total N=77 061). Genetic association estimates for IS risk were obtained from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (3734 cases and 18 317 controls). For European ancestry individuals, genetic proxies for the same metabolic traits were obtained from Million Veteran Program (lipids N=297 626, T2D N=148 726 cases, and 965 732 controls), and genetic association estimates for IS risk were obtained from the MEGASTROKE study (34 217 cases and 406 111 controls). Random-effects inverse-variance weighted Mendelian randomization was used as the main method, complemented with sensitivity analyses more robust to pleiotropy. RESULTS Higher genetically proxied T2D liability, LDL-C (low-density lipoprotein cholesterol), total cholesterol and lower genetically proxied HDL-C (high-density lipoprotein cholesterol) were associated with increased risk of IS in African ancestry individuals (odds ratio per doubling the odds of T2D liability [95% CI], 1.09 [1.07-1.11]; per standard-deviation increase in LDL-C, 1.12 [1.04-1.21]; total cholesterol: 1.23 [1.06-1.43]; HDL-C, 0.93 [0.89-0.99]). There was no evidence for differences in these estimates when performing analyses in European ancestry individuals. CONCLUSIONS Our analyses support a causal effect of T2D liability and lipid traits on IS risk in African ancestry individuals, with Mendelian randomization estimates similar to those obtained in European ancestry individuals.
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Affiliation(s)
- Segun Fatumo
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
- Department of Non-communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine London, United Kingdom (S.F.)
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria (S.F., C.E.)
- MRC Biostatistics Unit, School of Clinical Medicine (S.F., S.B.), University of Cambridge, United Kingdom
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Medical School Building, St Mary’s Hospital, Imperial College London, United Kingdom (V.K., M.-R.J., D.G.)
- Center for Life Course Health Research, Faculty of Medicine (V.K., M.-R.J.), University of Oulu, Finland
- Research Unit of Mathematical Sciences (V.K.), University of Oulu, Finland
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics (T.C.), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience (T.C.), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Toure Sounkou
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Mali (T.S., B.U.)
| | - Brenda Udosen
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Mali (T.S., B.U.)
| | - Chisom Ezenwa
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria (S.F., C.E.)
| | - Mariam Nakabuye
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
| | - Opeyemi Soremekun
- The African Computational genomics (TACG) Research group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda (S.F., T.S., B.U., C.E., M.N., O.S.)
| | | | - David K. Ryan
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom (D.K.R., A.T., D.G.)
| | - Amybel Taylor
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom (D.K.R., A.T., D.G.)
| | - Amy M. Mason
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (A.M.M., S.B.), University of Cambridge, United Kingdom
- National Institute for Health Research, Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, United Kingdom (A.M.M.)
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA (S.M.D., M.V.)
- Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.M.D.)
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA (S.M.D., M.V.)
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (M.V.)
| | - Keith L. Keene
- Department of Biology; Brody School of Medicine Center for Health Disparities, East Carolina University, Greenville, NC (K.L.K.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston (M.F.)
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, Medical School Building, St Mary’s Hospital, Imperial College London, United Kingdom (V.K., M.-R.J., D.G.)
- Center for Life Course Health Research, Faculty of Medicine (V.K., M.-R.J.), University of Oulu, Finland
- Biocenter Oulu (M.-R.J.), University of Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Finland (M.-R.J.)
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, United Kingdom (M.-R.J.)
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine (S.F., S.B.), University of Cambridge, United Kingdom
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (A.M.M., S.B.), University of Cambridge, United Kingdom
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, Medical School Building, St Mary’s Hospital, Imperial College London, United Kingdom (V.K., M.-R.J., D.G.)
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom (D.K.R., A.T., D.G.)
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, United Kingdom (D.G.)
- Novo Nordisk Research Centre Oxford, Old Road Campus, United Kingdom (D.G.)
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23
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Poon CL, Chen CY. Exploring the Impact of Cerebrovascular Disease and Major Depression on Non-diseased Human Tissue Transcriptomes. Front Genet 2021; 12:696836. [PMID: 34349785 PMCID: PMC8327210 DOI: 10.3389/fgene.2021.696836] [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: 04/17/2021] [Accepted: 06/21/2021] [Indexed: 11/13/2022] Open
Abstract
Background The development of complex diseases is contributed by the combination of multiple factors and complicated interactions between them. Inflammation has recently been associated with many complex diseases and may cause long-term damage to the human body. In this study, we examined whether two types of complex disease, cerebrovascular disease (CVD) or major depression (MD), systematically altered the transcriptomes of non-diseased human tissues and whether inflammation is linked to identifiable molecular signatures, using post-mortem samples from the Genotype-Tissue Expression (GTEx) project. Results Following a series of differential expression analyses, dozens to hundreds of differentially expressed genes (DEGs) were identified in multiple tissues between subjects with and without a history of CVD or MD. DEGs from these disease-associated tissues-the visceral adipose, tibial artery, caudate, and spinal cord for CVD; and the hypothalamus, putamen, and spinal cord for MD-were further analyzed for functional enrichment. Many pathways associated with immunological events were enriched in the upregulated DEGs of the CVD-associated tissues, as were the neurological and metabolic pathways in DEGs of the MD-associated tissues. Eight gene-tissue pairs were found to overlap with those prioritized by our transcriptome-wide association studies, indicating a potential genetic effect on gene expression for circulating cytokine phenotypes. Conclusion Cerebrovascular disease and major depression cause detectable changes in the gene expression of non-diseased tissues, suggesting that a possible long-term impact of diseases, lifestyles and environmental factors may together contribute to the appearance of "transcriptomic scars" on the human body. Furthermore, inflammation is probably one of the systemic and long-lasting effects of cerebrovascular events.
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Affiliation(s)
- Chi-Lam Poon
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, United States
| | - Cho-Yi Chen
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
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Yu J, Liao X, Zhong Y, Wu Y, Lai X, Jiao H, Yan M, Zhang Y, Ma C, Wang S. The Candidate Schizophrenia Risk Gene Tmem108 Regulates Glucose Metabolism Homeostasis. Front Endocrinol (Lausanne) 2021; 12:770145. [PMID: 34690937 PMCID: PMC8531597 DOI: 10.3389/fendo.2021.770145] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 09/23/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a severe psychiatric disease affected by genetic factors and environmental contributors, and premorbid abnormality of glucose metabolism is one of the SCZ characteristics supposed to contribute to the disease's pathological process. Transmembrane protein 108 (Tmem108) is a susceptible gene associated with multiple psychiatric diseases, including SCZ. Moreover, Tmem108 mutant mice exhibit SCZ-like behaviors in the measurement of sensorimotor gating. However, it is unknown whether Tmem108 regulates glucose metabolism homeostasis while it involves SCZ pathophysiological process. RESULTS In this research, we found that Tmem108 mutant mice exhibited glucose intolerance, insulin resistance, and disturbed metabolic homeostasis. Food and oxygen consumption decreased, and urine production increased, accompanied by weak fatigue resistance in the mutant mice. Simultaneously, the glucose metabolic pathway was enhanced, and lipid metabolism decreased in the mutant mice, consistent with the elevated respiratory exchange ratio (RER). Furthermore, metformin attenuated plasma glucose levels and improved sensorimotor gating in Tmem108 mutant mice. CONCLUSIONS Hyperglycemia occurs more often in SCZ patients than in control, implying that these two diseases share common biological mechanisms, here we demonstrate that the Tmem108 mutant may represent such a comorbid mechanism.
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Affiliation(s)
- Jianbo Yu
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Xufeng Liao
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Yanzi Zhong
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- Department of Biology, Senior Middle School of Yongfeng, Ji’an, China
| | - Yongqiang Wu
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Xinsheng Lai
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Huifeng Jiao
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Min Yan
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Yu Zhang
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Chaolin Ma
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
- *Correspondence: Chaolin Ma, ; Shunqi Wang,
| | - Shunqi Wang
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
- *Correspondence: Chaolin Ma, ; Shunqi Wang,
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