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Shah PW, Reinberger T, Hashmi S, Aherrahrou Z, Erdmann J. MRAS in coronary artery disease-Unchartered territory. IUBMB Life 2024; 76:300-312. [PMID: 38251784 DOI: 10.1002/iub.2805] [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: 07/04/2023] [Accepted: 12/03/2023] [Indexed: 01/23/2024]
Abstract
Genome-wide association studies (GWAS) have identified coronary artery disease (CAD) susceptibility locus on chromosome 3q22.3. This locus contains a cluster of several genes that includes muscle rat sarcoma virus (MRAS). Common MRAS variants are also associated with CAD causing risk factors such as hypertension, dyslipidemia, obesity, and type II diabetes. The MRAS gene is an oncogene that encodes a membrane-bound small GTPase. It is involved in a variety of signaling pathways, regulating cell differentiation and cell survival (mitogen-activated protein kinase [MAPK]/extracellular signal-regulated kinase and phosphatidylinositol 3-kinase) as well as acute phase response signaling (tumor necrosis factor [TNF] and interleukin 6 [IL6] signaling). In this review, we will summarize the role of genetic MRAS variants in the etiology of CAD and its comorbidities with the focus on tissue distribution of MRAS isoforms, cell type/tissue specificity, and mode of action of single nucleotide variants in MRAS associated complex traits. Finally, we postulate that CAD risk variants in the MRAS locus are specific to smooth muscle cells and lead to higher levels of MRAS, particularly in arterial and cardiac tissue, resulting in MAPK-dependent tissue hypertrophy or hyperplasia.
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Affiliation(s)
- Pashmina Wiqar Shah
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Satwat Hashmi
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Zouhair Aherrahrou
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
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2
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Zhukova M, Schedl P, Shidlovskii YV. The role of secondary structures in the functioning of 3' untranslated regions of mRNA: A review of functions of 3' UTRs' secondary structures and hypothetical involvement of secondary structures in cytoplasmic polyadenylation in Drosophila. Bioessays 2024; 46:e2300099. [PMID: 38161240 PMCID: PMC11337203 DOI: 10.1002/bies.202300099] [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] [Revised: 12/11/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024]
Abstract
3' untranslated regions (3' UTRs) of mRNAs have many functions, including mRNA processing and transport, translational regulation, and mRNA degradation and stability. These different functions require cis-elements in 3' UTRs that can be either sequence motifs or RNA structures. Here we review the role of secondary structures in the functioning of 3' UTRs and discuss some of the trans-acting factors that interact with these secondary structures in eukaryotic organisms. We propose potential participation of 3'-UTR secondary structures in cytoplasmic polyadenylation in the model organism Drosophila melanogaster. Because the secondary structures of 3' UTRs are essential for post-transcriptional regulation of gene expression, their disruption leads to a wide range of disorders, including cancer and cardiovascular diseases. Trans-acting factors, such as STAU1 and nucleolin, which interact with 3'-UTR secondary structures of target transcripts, influence the pathogenesis of neurodegenerative diseases and tumor metastasis, suggesting that they are possible therapeutic targets.
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Affiliation(s)
- Mariya Zhukova
- Laboratory of Gene Expression Regulation in Development, Russian Academy of Sciences, Institute of Gene Biology, Moscow, Russia
| | - Paul Schedl
- Laboratory of Gene Expression Regulation in Development, Russian Academy of Sciences, Institute of Gene Biology, Moscow, Russia
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Yulii V. Shidlovskii
- Laboratory of Gene Expression Regulation in Development, Russian Academy of Sciences, Institute of Gene Biology, Moscow, Russia
- Department of Biology and General Genetics, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
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3
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Kita N, Hamamoto A, Gowda SGB, Takatsu H, Nakayama K, Arita M, Hui SP, Shin HW. Glucosylceramide flippases contribute to cellular glucosylceramide homeostasis. J Lipid Res 2024; 65:100508. [PMID: 38280458 PMCID: PMC10910339 DOI: 10.1016/j.jlr.2024.100508] [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: 12/19/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 01/29/2024] Open
Abstract
Lipid transport is an essential cellular process with importance to human health, disease development, and therapeutic strategies. Type IV P-type ATPases (P4-ATPases) have been identified as membrane lipid flippases by utilizing nitrobenzoxadiazole (NBD)-labeled lipids as substrates. Among the 14 human type IV P-type ATPases, ATP10D was shown to flip NBD-glucosylceramide (GlcCer) across the plasma membrane. Here, we found that conversion of incorporated GlcCer (d18:1/12:0) to other sphingolipids is accelerated in cells exogenously expressing ATP10D but not its ATPase-deficient mutant. These findings suggest that 1) ATP10D flips unmodified GlcCer as well as NBD-GlcCer at the plasma membrane and 2) ATP10D can translocate extracellular GlcCer, which is subsequently converted to other metabolites. Notably, exogenous expression of ATP10D led to the reduction in cellular hexosylceramide levels. Moreover, the expression of GlcCer flippases, including ATP10D, also reduced cellular hexosylceramide levels in fibroblasts derived from patients with Gaucher disease, which is a lysosomal storage disorder with excess GlcCer accumulation. Our study highlights the contribution of ATP10D to the regulation of cellular GlcCer levels and maintaining lipid homeostasis.
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Affiliation(s)
- Natsuki Kita
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Asuka Hamamoto
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Siddabasave Gowda B Gowda
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan; Graduate School of Global Food Resources, Hokkaido University, Sapporo, Japan
| | - Hiroyuki Takatsu
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Kazuhisa Nakayama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Makoto Arita
- Laboratory for Metabolomics, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - Shu-Ping Hui
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan
| | - Hye-Won Shin
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan.
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Nöthen MM, Spielmann M. Nachruf Prof. Dr. rer. nat. Jeanette Erdmann. MED GENET-BERLIN 2023; 35:299-300. [PMID: 38841555 PMCID: PMC11006360 DOI: 10.1515/medgen-2023-2046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Affiliation(s)
- Markus M. Nöthen
- Universitätsklinikum BonnInstitut für HumangenetikVenusberg-Campus 153127BonnDeutschland
| | - Malte Spielmann
- Universitätsklinikum Schleswig-HolsteinCampus Lübeck, Institut für HumangenetikLübeckDeutschland
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Aherrahrou R, Eschenhagen T, König IR, Samani NJ, Schunkert H, Aherrahrou Z. Jeanette Erdmann (1965-2023). Nat Genet 2023; 55:2016-2017. [PMID: 37985820 DOI: 10.1038/s41588-023-01599-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Affiliation(s)
- Redouane Aherrahrou
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Thomas Eschenhagen
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Hamburg, Germany
| | - Inke R König
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
- Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Lübeck, Germany
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Zouhair Aherrahrou
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany.
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Silva S, Nitsch D, Fatumo S. Genome-wide association studies on coronary artery disease: A systematic review and implications for populations of different ancestries. PLoS One 2023; 18:e0294341. [PMID: 38019802 PMCID: PMC10686512 DOI: 10.1371/journal.pone.0294341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/28/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Cardiovascular diseases are some of the leading causes of death worldwide, with coronary artery disease leading as one of the primary causes of mortality in both the developing and developed worlds. Despite its prevalence, there is a disproportionately small number of studies conducted in populations of non-European ancestry, with the limited sample sizes of such studies further restricting the power and generalizability of respective findings. This research aimed at understanding the differences in the genetic architecture of coronary artery disease (CAD) in populations of diverse ancestries in order to contribute towards the understanding of the pathophysiology of coronary artery disease. METHODS We performed a systematic review on the 6th of October, 2022 summarizing genome-wide association studies on coronary artery disease, while employing the GWAS Catalog as an independent database to support the search. We developed a framework to assess the methodological quality of each study. We extracted and grouped associated single nucleotide polymorphisms and genes according to ancestry groups of participants. RESULTS We identified 3100 studies, of which, 36 relevant studies were included in this research. Three of the studies that were included were not listed in the GWAS Catalog, highlighting the value of conducting an independent search alongside established databases in order to ensure the full research landscape has been captured. 743,919 CAD case participants from 25 different countries were analysed, with 61% of the studies identified in this research conducted in populations of European ancestry. No studies investigated populations of Africans living in continental Africa or admixed American ancestry groups besides African-Americans, while limited sample sizes were included of population groups besides Europeans and East Asians. This observed disproportionate population representation highlights the gaps in the literature, which limits our ability to understand coronary artery disease as a global disease. 71 genetic loci were identified to be associated with coronary artery disease in more than one article, with ancestry-specific genetic loci identified in each respective population group which were not detected in studies of other ancestries. CONCLUSIONS Although the replication and validation of these variants are still warranted, these finding are indicative of the value of including diverse ancestry populations in GWAS reference panels, as a more comprehensive understanding of the genetic architecture and pathophysiology of CAD can be achieved.
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Affiliation(s)
- Sarah Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Segun Fatumo
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda
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Mosconi MW, Stevens CJ, Unruh KE, Shafer R, Elison JT. Endophenotype trait domains for advancing gene discovery in autism spectrum disorder. J Neurodev Disord 2023; 15:41. [PMID: 37993779 PMCID: PMC10664534 DOI: 10.1186/s11689-023-09511-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/09/2023] [Indexed: 11/24/2023] Open
Abstract
Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.
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Affiliation(s)
- Matthew W Mosconi
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA.
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA.
| | - Cassandra J Stevens
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - Kathryn E Unruh
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Robin Shafer
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
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Iyer DR, Venkatraman J, Tanguy E, Vitale N, Mahapatra NR. Chromogranin A and its derived peptides: potential regulators of cholesterol homeostasis. Cell Mol Life Sci 2023; 80:271. [PMID: 37642733 PMCID: PMC11072126 DOI: 10.1007/s00018-023-04908-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 08/02/2023] [Accepted: 08/03/2023] [Indexed: 08/31/2023]
Abstract
Chromogranin A (CHGA), a member of the granin family of proteins, has been an attractive therapeutic target and candidate biomarker for several cardiovascular, neurological, and inflammatory disorders. The prominence of CHGA stems from the pleiotropic roles of several bioactive peptides (e.g., catestatin, pancreastatin, vasostatins) generated by its proteolytic cleavage and by their wide anatomical distribution. These peptides are emerging as novel modulators of cardiometabolic diseases that are often linked to high blood cholesterol levels. However, their impact on cholesterol homeostasis is poorly understood. The dynamic nature of cholesterol and its multitudinous roles in almost every aspect of normal body function makes it an integral component of metabolic physiology. A tightly regulated coordination of cholesterol homeostasis is imperative for proper functioning of cellular and metabolic processes. The deregulation of cholesterol levels can result in several pathophysiological states. Although studies till date suggest regulatory roles for CHGA and its derived peptides on cholesterol levels, the mechanisms by which this is achieved still remain unclear. This review aims to aggregate and consolidate the available evidence linking CHGA with cholesterol homeostasis in health and disease. In addition, we also look at common molecular regulatory factors (viz., transcription factors and microRNAs) which could govern the expression of CHGA and genes involved in cholesterol homeostasis under basal and pathological conditions. In order to gain further insights into the pathways mediating cholesterol regulation by CHGA/its derived peptides, a few prospective signaling pathways are explored, which could act as primers for future studies.
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Affiliation(s)
- Dhanya R Iyer
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Janani Venkatraman
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Emeline Tanguy
- Institut des Neurosciences Cellulaires et Intégratives, CNRS UPR 3212 and Université de Strasbourg, 5 Rue Blaise Pascal, 67000, Strasbourg, France
| | - Nicolas Vitale
- Institut des Neurosciences Cellulaires et Intégratives, CNRS UPR 3212 and Université de Strasbourg, 5 Rue Blaise Pascal, 67000, Strasbourg, France.
| | - Nitish R Mahapatra
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India.
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Schunkert H, Aherrahrou Z. In Memoriam: Prof. Dr. Jeanette Erdmann (1965-2023). CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:315-316. [PMID: 37492962 DOI: 10.1161/circgen.123.004315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Affiliation(s)
- Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich (H.S.)
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich (H.S.)
| | - Zouhair Aherrahrou
- Institute for Cardiogenetics, University of Lübeck (Z.A.)
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany (Z.A.)
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DeForest N, Kavitha B, Hu S, Isaac R, Krohn L, Wang M, Du X, De Arruda Saldanha C, Gylys J, Merli E, Abagyan R, Najmi L, Mohan V, Flannick J, Peloso GM, Gordts PL, Heinz S, Deaton AM, Khera AV, Olefsky J, Radha V, Majithia AR. Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of atherogenic lipoproteins. CELL GENOMICS 2023; 3:100339. [PMID: 37492105 PMCID: PMC10363808 DOI: 10.1016/j.xgen.2023.100339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/08/2023] [Accepted: 05/03/2023] [Indexed: 07/27/2023]
Abstract
Loss-of-function mutations in hepatocyte nuclear factor 1A (HNF1A) are known to cause rare forms of diabetes and alter hepatic physiology through unclear mechanisms. In the general population, 1:100 individuals carry a rare, protein-coding HNF1A variant, most of unknown functional consequence. To characterize the full allelic series, we performed deep mutational scanning of 11,970 protein-coding HNF1A variants in human hepatocytes and clinical correlation with 553,246 exome-sequenced individuals. Surprisingly, we found that ∼1:5 rare protein-coding HNF1A variants in the general population cause molecular gain of function (GOF), increasing the transcriptional activity of HNF1A by up to 50% and conferring protection from type 2 diabetes (odds ratio [OR] = 0.77, p = 0.007). Increased hepatic expression of HNF1A promoted a pro-atherogenic serum profile mediated in part by enhanced transcription of risk genes including ANGPTL3 and PCSK9. In summary, ∼1:300 individuals carry a GOF variant in HNF1A that protects carriers from diabetes but enhances hepatic secretion of atherogenic lipoproteins.
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Affiliation(s)
- Natalie DeForest
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Babu Kavitha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
| | - Siqi Hu
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Roi Isaac
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | | | - Minxian Wang
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xiaomi Du
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Camila De Arruda Saldanha
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jenny Gylys
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Edoardo Merli
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Ruben Abagyan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Laeya Najmi
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
| | - Viswanathan Mohan
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Alnylam Human Genetics
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
- Alnylam Pharmaceuticals, Cambridge, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - AMP-T2D Consortium
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
- Alnylam Pharmaceuticals, Cambridge, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jason Flannick
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Philip L.S.M. Gordts
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
| | - Sven Heinz
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | | | - Amit V. Khera
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jerrold Olefsky
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
| | - Amit R. Majithia
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
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Zhao W, He A, Zou P. Genetic association between the lncRNA ANRIL rs10757272 polymorphism and intracranial aneurysm susceptibility in Asians. Neurosurg Rev 2022; 46:15. [PMID: 36512102 DOI: 10.1007/s10143-022-01927-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022]
Abstract
Current epidemiological studies reporting the role of lncRNA ANRIL rs10757272 polymorphism and intracranial aneurysm risk remain controversial. In the present study, we conducted a meta-analysis to resolve this inconsistency. PubMed and EMBASE databases were retrieved to collect the publications evaluating the association with a time limit of August 20, 2021. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the strength of the association. Subgroup analysis, heterogeneity analyses, and publication bias were assessed in the meta-analysis. Finally, 2853 cases and 13,426 controls were enrolled in this meta-analysis based on inclusion criteria. The pooled results indicated that the rs10757272 polymorphism is significantly associated with the risk of intracranial aneurysms in all genetic models (homozygous model, odds ratio (OR) = 1.48, 95% confidence interval (CI) = 1.28-1.71, Pheterogeneity = 0.11, I2 = 50.9; heterozygous model, OR = 1.26, 95% CI = 1.09-1.46, Pheterogeneity = 0.15, I2 = 42.8; dominant model, OR = 1.37, 95% CI = 1.19-1.57, Pheterogeneity = 0.12, I2 = 48.1; and recessive model, OR = 1.23, 95% CI = 1.13-1.34, Pheterogeneity = 0.24, I2 = 28.8). Subgroup analyses showed consistent results. In conclusion, our findings provided evidence that the rs10757272 polymorphism is associated with susceptibility to intracranial aneurysms in Asians.
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Affiliation(s)
- Wei Zhao
- Department of Neurosurgery, Yuhuangding Hospital of Yantai, Peng Zou, No. 20, Yuhuangding East Road, Zhifu District, Yantai, 264000, Shandong, China
| | - Aijie He
- Department of Neurosurgery, Yuhuangding Hospital of Yantai, Peng Zou, No. 20, Yuhuangding East Road, Zhifu District, Yantai, 264000, Shandong, China
| | - Peng Zou
- Department of Neurosurgery, Yuhuangding Hospital of Yantai, Peng Zou, No. 20, Yuhuangding East Road, Zhifu District, Yantai, 264000, Shandong, China.
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12
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Saad M, El-Menyar A, Kunji K, Ullah E, Al Suwaidi J, Kullo IJ. Validation of Polygenic Risk Scores for Coronary Heart Disease in a Middle Eastern Cohort Using Whole Genome Sequencing. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003712. [PMID: 36252120 PMCID: PMC9770120 DOI: 10.1161/circgen.122.003712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Enthusiasm for using polygenic risk scores (PRSs) in clinical practice is tempered by concerns about their portability to diverse ancestry groups, thus motivating genome-wide association studies in non-European ancestry cohorts. METHODS We conducted a genome-wide association study for coronary heart disease in a Middle Eastern cohort using whole genome sequencing and assessed the performance of 6 PRSs developed with methods including LDpred (PGS000296), metaGRS (PGS000018), Pruning and Thresholding (PGS000337), and an EnsemblePRS we developed. Additionally, we evaluated the burden of rare variants in lipid genes in cases and controls. Whole genome sequencing at 30× coverage was performed in 1067 coronary heart disease cases (mean age=59 years; 70.3% males) and 6170 controls (mean age=40 years; 43.5% males). RESULTS The majority of PRSs performed well; odds ratio (OR) per 1 SD increase (OR1sd) was highest for PGS000337 (OR1sd=1.81, 95% CI [1.66-1.98], P=3.07×10-41). EnsemblePRS performed better than individual PRSs (OR1sd=1.8, 95% CI [1.66-1.96], P=5.89×10-44). The OR for the 10th decile versus the remaining deciles was >3.2 for PGS000337, PGS000296, PGS000018, and reached 4.58 for EnsemblePRS. Of 400 known genome-wide significant loci, 33 replicated at P<10-4. However, the 9p21 locus did not replicate. Six suggestive (P<10-5) new loci/genes with plausible biological function were identified (eg, CORO7, RBM47, PDE4D). The burden of rare functional variants in LDLR, APOB, PCSK9, and ANGPTL4 was greater in cases than controls. CONCLUSIONS Overall, we demonstrate that PRSs derived from European ancestry genome-wide association studies performed well in a Middle Eastern cohort, suggesting these could be used in the clinical setting while ancestry-specific PRSs are developed.
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Affiliation(s)
- Mohamad Saad
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | | | - Khalid Kunji
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | - Ehsan Ullah
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | | | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, and the Gonda Vascular Center, Mayo Clinic, Rochester, MN (I.J.K.)
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13
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Zarkasi KA, Abdullah N, Abdul Murad NA, Ahmad N, Jamal R. Genetic Factors for Coronary Heart Disease and Their Mechanisms: A Meta-Analysis and Comprehensive Review of Common Variants from Genome-Wide Association Studies. Diagnostics (Basel) 2022; 12:2561. [PMID: 36292250 PMCID: PMC9601486 DOI: 10.3390/diagnostics12102561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/18/2022] [Accepted: 10/20/2022] [Indexed: 11/17/2022] Open
Abstract
Genome-wide association studies (GWAS) have discovered 163 loci related to coronary heart disease (CHD). Most GWAS have emphasized pathways related to single-nucleotide polymorphisms (SNPs) that reached genome-wide significance in their reports, while identification of CHD pathways based on the combination of all published GWAS involving various ethnicities has yet to be performed. We conducted a systematic search for articles with comprehensive GWAS data in the GWAS Catalog and PubMed, followed by a meta-analysis of the top recurring SNPs from ≥2 different articles using random or fixed-effect models according to Cochran Q and I2 statistics, and pathway enrichment analysis. Meta-analyses showed significance for 265 of 309 recurring SNPs. Enrichment analysis returned 107 significant pathways, including lipoprotein and lipid metabolisms (rs7412, rs6511720, rs11591147, rs1412444, rs11172113, rs11057830, rs4299376), atherogenesis (rs7500448, rs6504218, rs3918226, rs7623687), shared cardiovascular pathways (rs72689147, rs1800449, rs7568458), diabetes-related pathways (rs200787930, rs12146487, rs6129767), hepatitis C virus infection/hepatocellular carcinoma (rs73045269/rs8108632, rs56062135, rs188378669, rs4845625, rs11838776), and miR-29b-3p pathways (rs116843064, rs11617955, rs146092501, rs11838776, rs73045269/rs8108632). In this meta-analysis, the identification of various genetic factors and their associated pathways associated with CHD denotes the complexity of the disease. This provides an opportunity for the future development of novel CHD genetic risk scores relevant to personalized and precision medicine.
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Affiliation(s)
- Khairul Anwar Zarkasi
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
- Biochemistry Unit, Faculty of Medicine and Defence Health, Universiti Pertahanan Nasional Malaysia (UPNM), Kuala Lumpur 57000, Malaysia
| | - Noraidatulakma Abdullah
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
- Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 50300, Malaysia
| | - Nor Azian Abdul Murad
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
| | - Norfazilah Ahmad
- Epidemiology and Statistics Unit, Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
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14
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Vilne B, Ķibilds J, Siksna I, Lazda I, Valciņa O, Krūmiņa A. Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery Disease. Front Microbiol 2022; 13:627892. [PMID: 35479632 PMCID: PMC9036178 DOI: 10.3389/fmicb.2022.627892] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 02/24/2022] [Indexed: 12/14/2022] Open
Abstract
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and the main leading cause of morbidity and mortality worldwide, posing a huge socio-economic burden to the society and health systems. Therefore, timely and precise identification of people at high risk of CAD is urgently required. Most current CAD risk prediction approaches are based on a small number of traditional risk factors (age, sex, diabetes, LDL and HDL cholesterol, smoking, systolic blood pressure) and are incompletely predictive across all patient groups, as CAD is a multi-factorial disease with complex etiology, considered to be driven by both genetic, as well as numerous environmental/lifestyle factors. Diet is one of the modifiable factors for improving lifestyle and disease prevention. However, the current rise in obesity, type 2 diabetes (T2D) and CVD/CAD indicates that the “one-size-fits-all” approach may not be efficient, due to significant variation in inter-individual responses. Recently, the gut microbiome has emerged as a potential and previously under-explored contributor to these variations. Hence, efficient integration of dietary and gut microbiome information alongside with genetic variations and clinical data holds a great promise to improve CAD risk prediction. Nevertheless, the highly complex nature of meals combined with the huge inter-individual variability of the gut microbiome poses several Big Data analytics challenges in modeling diet-gut microbiota interactions and integrating these within CAD risk prediction approaches for the development of personalized decision support systems (DSS). In this regard, the recent re-emergence of Artificial Intelligence (AI) / Machine Learning (ML) is opening intriguing perspectives, as these approaches are able to capture large and complex matrices of data, incorporating their interactions and identifying both linear and non-linear relationships. In this Mini-Review, we consider (1) the most used AI/ML approaches and their different use cases for CAD risk prediction (2) modeling of the content, choice and impact of dietary factors on CAD risk; (3) classification of individuals by their gut microbiome composition into CAD cases vs. controls and (4) modeling of the diet-gut microbiome interactions and their impact on CAD risk. Finally, we provide an outlook for putting it all together for improved CAD risk predictions.
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Affiliation(s)
- Baiba Vilne
- Bioinformatics Lab, Riga Stradins University, Riga, Latvia
- COST Action CA18131 - Statistical and Machine Learning Techniques in Human Microbiome Studies, Brussels, Belgium
- *Correspondence: Baiba Vilne
| | - Juris Ķibilds
- Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia
| | - Inese Siksna
- Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia
| | - Ilva Lazda
- Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia
| | - Olga Valciņa
- Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia
| | - Angelika Krūmiņa
- Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia
- Department of Infectology and Dermatology, Riga Stradins University, Riga, Latvia
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15
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Zeng L, Moser S, Mirza-Schreiber N, Lamina C, Coassin S, Nelson CP, Annilo T, Franzén O, Kleber ME, Mack S, Andlauer TFM, Jiang B, Stiller B, Li L, Willenborg C, Munz M, Kessler T, Kastrati A, Laugwitz KL, Erdmann J, Moebus S, Nöthen MM, Peters A, Strauch K, Müller-Nurasyid M, Gieger C, Meitinger T, Steinhagen-Thiessen E, März W, Metspalu A, Björkegren JLM, Samani NJ, Kronenberg F, Müller-Myhsok B, Schunkert H. Cis-epistasis at the LPA locus and risk of cardiovascular diseases. Cardiovasc Res 2022; 118:1088-1102. [PMID: 33878186 PMCID: PMC8930071 DOI: 10.1093/cvr/cvab136] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 04/16/2021] [Indexed: 12/28/2022] Open
Abstract
AIMS Coronary artery disease (CAD) has a strong genetic predisposition. However, despite substantial discoveries made by genome-wide association studies (GWAS), a large proportion of heritability awaits identification. Non-additive genetic effects might be responsible for part of the unaccounted genetic variance. Here, we attempted a proof-of-concept study to identify non-additive genetic effects, namely epistatic interactions, associated with CAD. METHODS AND RESULTS We tested for epistatic interactions in 10 CAD case-control studies and UK Biobank with focus on 8068 SNPs at 56 loci with known associations with CAD risk. We identified a SNP pair located in cis at the LPA locus, rs1800769 and rs9458001, to be jointly associated with risk for CAD [odds ratio (OR) = 1.37, P = 1.07 × 10-11], peripheral arterial disease (OR = 1.22, P = 2.32 × 10-4), aortic stenosis (OR = 1.47, P = 6.95 × 10-7), hepatic lipoprotein(a) (Lp(a)) transcript levels (beta = 0.39, P = 1.41 × 10-8), and Lp(a) serum levels (beta = 0.58, P = 8.7 × 10-32), while individual SNPs displayed no association. Further exploration of the LPA locus revealed a strong dependency of these associations on a rare variant, rs140570886, that was previously associated with Lp(a) levels. We confirmed increased CAD risk for heterozygous (relative OR = 1.46, P = 9.97 × 10-32) and individuals homozygous for the minor allele (relative OR = 1.77, P = 0.09) of rs140570886. Using forward model selection, we also show that epistatic interactions between rs140570886, rs9458001, and rs1800769 modulate the effects of the rs140570886 risk allele. CONCLUSIONS These results demonstrate the feasibility of a large-scale knowledge-based epistasis scan and provide rare evidence of an epistatic interaction in a complex human disease. We were directed to a variant (rs140570886) influencing risk through additive genetic as well as epistatic effects. In summary, this study provides deeper insights into the genetic architecture of a locus important for cardiovascular diseases.
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Affiliation(s)
- Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
| | - Sylvain Moser
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich 80804, Germany
| | - Nazanin Mirza-Schreiber
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Stefan Coassin
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, BHF Cardiovascular Research Centre, Glenfield Hospital, Groby Rd, Leicester LE3 9QP, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Tarmo Annilo
- Estonian Genome Center, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Oscar Franzén
- Department of Genetics and Genomic Sciences and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, 14186 Stockholm, Sweden
| | - Marcus E Kleber
- Medizinische Klinik V (Nephrologie, Hypertensiologie, Rheumatologie, Endokrinologie, Diabetologie), Medizinische Fakultät Mannheim der Universität Heidelberg, 69120 Heidelberg, Germany
| | - Salome Mack
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Till F M Andlauer
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Beibei Jiang
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany
| | - Barbara Stiller
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
| | - Ling Li
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
| | - Christina Willenborg
- Institute for Cardiogenetics and University Heart Center Luebeck, University of Lübeck, 23562 Lübeck, Germany
| | - Matthias Munz
- Institute for Cardiogenetics and University Heart Center Luebeck, University of Lübeck, 23562 Lübeck, Germany
- Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Partner Site Hamburg/Lübeck/Kiel, 23562 Lübeck, Germany
- Charité – University Medicine Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, 14197 Berlin, Germany
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
- Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Partner Site Munich Heart Alliance, 80636 Munich, Germany
| | - Adnan Kastrati
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
- Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Partner Site Munich Heart Alliance, 80636 Munich, Germany
| | - Karl-Ludwig Laugwitz
- Medizinische Klinik, Klinikum rechts der Isar, Technische Universität München, 81675 Munich, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics and University Heart Center Luebeck, University of Lübeck, 23562 Lübeck, Germany
- Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Partner Site Hamburg/Lübeck/Kiel, 23562 Lübeck, Germany
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, 45147 Essen, Germany
- Centre for Urbane Epidemiology, University Hospital Essen, 45147 Essen, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, 53012 Bonn, Germany
| | - Annette Peters
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, 81377 Munich, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, 81377 Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101 Mainz, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, 81377 Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101 Mainz, Germany
- Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, 81377 Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | | | - Winfried März
- Medizinische Klinik V (Nephrologie, Hypertensiologie, Rheumatologie, Endokrinologie, Diabetologie), Medizinische Fakultät Mannheim der Universität Heidelberg, 69120 Heidelberg, Germany
- Synlab Akademie, Synlab Holding Deutschland GmbH, Mannheim und Augsburg, 86156 Augsburg, Germany
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge, 14186 Stockholm, Sweden
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, BHF Cardiovascular Research Centre, Glenfield Hospital, Groby Rd, Leicester LE3 9QP, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany
- Munich Cluster of Systems Biology, SyNergy, 81377 Munich, Germany
- Department of Health Data Science, University of Liverpool, Liverpool L69 3BX, UK
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, 80636 Munich, Germany
- Deutsches Zentrum für Herz- und Kreislauf-Forschung (DZHK), Partner Site Hamburg/Lübeck/Kiel, 23562 Lübeck, Germany
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16
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Vilne B, Sawant A, Rudaka I. Examining the Association between Mitochondrial Genome Variation and Coronary Artery Disease. Genes (Basel) 2022; 13:genes13030516. [PMID: 35328073 PMCID: PMC8953999 DOI: 10.3390/genes13030516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/11/2022] [Accepted: 03/14/2022] [Indexed: 12/04/2022] Open
Abstract
Large-scale genome-wide association studies have identified hundreds of single-nucleotide variants (SNVs) significantly associated with coronary artery disease (CAD). However, collectively, these explain <20% of the heritability. Hypothesis: Here, we hypothesize that mitochondrial (MT)-SNVs might present one potential source of this “missing heritability”. Methods: We analyzed 265 MT-SNVs in ~500,000 UK Biobank individuals, exploring two different CAD definitions: a more stringent (myocardial infarction and/or revascularization; HARD = 20,405), and a more inclusive (angina and chronic ischemic heart disease; SOFT = 34,782). Results: In HARD cases, the most significant (p < 0.05) associations were for m.295C>T (control region) and m.12612A>G (ND5), found more frequently in cases (OR = 1.05), potentially related to reduced cardiorespiratory fitness in response to exercise, as well as for m.12372G>A (ND5) and m.11467A>G (ND4), present more frequently in controls (OR = 0.97), previously associated with lower ROS production rate. In SOFT cases, four MT-SNVs survived multiple testing corrections (at FDR < 5%), all potentially conferring increased CAD risk. Of those, m.11251A>G (ND4) and m.15452C>A (CYB) have previously shown significant associations with body height. In line with this, we observed that CAD cases were slightly less physically active, and their average body height was ~2.00 cm lower compared to controls; both traits are known to be related to increased CAD risk. Gene-based tests identified CO2 associated with HARD/SOFT CAD, whereas ND3 and CYB associated with SOFT cases (p < 0.05), dysfunction of which has been related to MT oxidative stress, obesity/T2D (CO2), BMI (ND3), and angina/exercise intolerance (CYB). Finally, we observed that macro-haplogroup I was significantly (p < 0.05) more frequent in HARD cases vs. controls (3.35% vs. 3.08%), potentially associated with response to exercise. Conclusions: We found only spurious associations between MT genome variation and HARD/SOFT CAD and conclude that more MT-SNV data in even larger study cohorts may be needed to conclusively determine the role of MT DNA in CAD.
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Affiliation(s)
- Baiba Vilne
- Bioinformatics Lab, Rīga Stradiņš University, LV-1007 Riga, Latvia;
- Correspondence:
| | - Aniket Sawant
- Bioinformatics Lab, Rīga Stradiņš University, LV-1007 Riga, Latvia;
| | - Irina Rudaka
- Scientific Laboratory of Molecular Genetics, Rīga Stradiņš University, LV-1007 Riga, Latvia;
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17
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Li L, Chen Z, von Scheidt M, Li S, Steiner A, Güldener U, Koplev S, Ma A, Hao K, Pan C, Lusis AJ, Pang S, Kessler T, Ermel R, Sukhavasi K, Ruusalepp A, Gagneur J, Erdmann J, Kovacic JC, Björkegren JLM, Schunkert H. Transcriptome-wide association study of coronary artery disease identifies novel susceptibility genes. Basic Res Cardiol 2022; 117:6. [PMID: 35175464 PMCID: PMC8852935 DOI: 10.1007/s00395-022-00917-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/18/2022] [Accepted: 02/01/2022] [Indexed: 01/31/2023]
Abstract
The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P < 3.85e-6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes, RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.
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Affiliation(s)
- Ling Li
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Fakultät für Informatik, Technische Universität München, Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Zhifen Chen
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Moritz von Scheidt
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Shuangyue Li
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andrea Steiner
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ulrich Güldener
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Calvin Pan
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Aldons J. Lusis
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Shichao Pang
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany ,Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Raili Ermel
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Arno Ruusalepp
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia ,Clinical Gene Networks AB, Stockholm, Sweden
| | - Julien Gagneur
- Fakultät für Informatik, Technische Universität München, Munich, Germany
| | - Jeanette Erdmann
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany ,Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia ,St Vincent’s Clinical School, University of New South Wales, Sydney, Australia ,Icahn School of Medicine at Mount Sinai, Cardiovascular Research Institute, New York, NY 10029-6574 USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA ,Clinical Gene Networks AB, Stockholm, Sweden ,Department of Medicine, Huddinge, Karolinska Institutet, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
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18
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Myocardial ischemia and its complications. Cardiovasc Pathol 2022. [DOI: 10.1016/b978-0-12-822224-9.00022-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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19
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Neiburga KD, Vilne B, Bauer S, Bongiovanni D, Ziegler T, Lachmann M, Wengert S, Hawe JS, Güldener U, Westerlund AM, Li L, Pang S, Yang C, Saar K, Huebner N, Maegdefessel L, DigiMed Bayern Consortium, Lange R, Krane M, Schunkert H, von Scheidt M. Vascular Tissue Specific miRNA Profiles Reveal Novel Correlations with Risk Factors in Coronary Artery Disease. Biomolecules 2021; 11:1683. [PMID: 34827683 PMCID: PMC8615466 DOI: 10.3390/biom11111683] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/01/2021] [Accepted: 11/06/2021] [Indexed: 12/12/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Non-coding RNAs have already been linked to CVD development and progression. While microRNAs (miRs) have been well studied in blood samples, there is little data on tissue-specific miRs in cardiovascular relevant tissues and their relation to cardiovascular risk factors. Tissue-specific miRs derived from Arteria mammaria interna (IMA) from 192 coronary artery disease (CAD) patients undergoing coronary artery bypass grafting (CABG) were analyzed. The aims of the study were 1) to establish a reference atlas which can be utilized for identification of novel diagnostic biomarkers and potential therapeutic targets, and 2) to relate these miRs to cardiovascular risk factors. Overall, 393 individual miRs showed sufficient expression levels and passed quality control for further analysis. We identified 17 miRs-miR-10b-3p, miR-10-5p, miR-17-3p, miR-21-5p, miR-151a-5p, miR-181a-5p, miR-185-5p, miR-194-5p, miR-199a-3p, miR-199b-3p, miR-212-3p, miR-363-3p, miR-548d-5p, miR-744-5p, miR-3117-3p, miR-5683 and miR-5701-significantly correlated with cardiovascular risk factors (correlation coefficient >0.2 in both directions, p-value (p < 0.006, false discovery rate (FDR) <0.05). Of particular interest, miR-5701 was positively correlated with hypertension, hypercholesterolemia, and diabetes. In addition, we found that miR-629-5p and miR-98-5p were significantly correlated with acute myocardial infarction. We provide a first atlas of miR profiles in IMA samples from CAD patients. In perspective, these miRs might play an important role in improved risk assessment, mechanistic disease understanding and local therapy of CAD.
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Affiliation(s)
| | - Baiba Vilne
- Bioinformatics Lab, Riga Stradiņš University, LV-1007 Riga, Latvia;
- SIA Net-OMICS, LV-1011 Riga, Latvia
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Sabine Bauer
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
| | - Dario Bongiovanni
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
- Department of Internal Medicine I, School of Medicine, University Hospital Rechts der Isar, Technical University of Munich, 81675 Munich, Germany; (T.Z.); (M.L.)
| | - Tilman Ziegler
- Department of Internal Medicine I, School of Medicine, University Hospital Rechts der Isar, Technical University of Munich, 81675 Munich, Germany; (T.Z.); (M.L.)
| | - Mark Lachmann
- Department of Internal Medicine I, School of Medicine, University Hospital Rechts der Isar, Technical University of Munich, 81675 Munich, Germany; (T.Z.); (M.L.)
| | - Simon Wengert
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, 85764 Neuherberg, Germany;
| | - Johann S. Hawe
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Ulrich Güldener
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Annie M. Westerlund
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Munich, Germany
| | - Ling Li
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Shichao Pang
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Chuhua Yang
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
| | - Kathrin Saar
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany; (K.S.); (N.H.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 10785 Berlin, Germany
| | - Norbert Huebner
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany; (K.S.); (N.H.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 10785 Berlin, Germany
- Charité-Universitätsmedizin, 10117 Berlin, Germany
| | - Lars Maegdefessel
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
- Department of Vascular and Endovascular Surgery, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
| | | | - Rüdiger Lange
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
- German Heart Centre Munich, Department of Cardiac Surgery, Technical University Munich, 80636 Munich, Germany
| | - Markus Krane
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
- German Heart Centre Munich, Department of Cardiac Surgery, Technical University Munich, 80636 Munich, Germany
- Division of Cardiac Surgery, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
| | - Moritz von Scheidt
- German Heart Centre Munich, Department of Cardiology, Technical University Munich, 80636 Munich, Germany; (S.B.); (J.S.H.); (U.G.); (A.M.W.); (L.L.); (S.P.); (C.Y.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany; (D.B.); (L.M.); (R.L.); (M.K.)
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20
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Weber SM, Carroll SL. The Role of R-Ras Proteins in Normal and Pathologic Migration and Morphologic Change. THE AMERICAN JOURNAL OF PATHOLOGY 2021; 191:1499-1510. [PMID: 34111428 PMCID: PMC8420862 DOI: 10.1016/j.ajpath.2021.05.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 05/11/2021] [Accepted: 05/26/2021] [Indexed: 12/20/2022]
Abstract
The contributions that the R-Ras subfamily [R-Ras, R-Ras2/teratocarcinoma 21 (TC21), and M-Ras] of small GTP-binding proteins make to normal and aberrant cellular functions have historically been poorly understood. However, this has begun to change with the realization that all three R-Ras subfamily members are occasionally mutated in Noonan syndrome (NS), a RASopathy characterized by the development of hematopoietic neoplasms and abnormalities affecting the immune, cardiovascular, and nervous systems. Consistent with the abnormalities seen in NS, a host of new studies have implicated R-Ras proteins in physiological and pathologic changes in cellular morphology, adhesion, and migration in the cardiovascular, immune, and nervous systems. These changes include regulating the migration and homing of mature and immature immune cells, vascular stabilization, clotting, and axonal and dendritic outgrowth during nervous system development. Dysregulated R-Ras signaling has also been linked to the pathogenesis of cardiovascular disease, intellectual disabilities, and human cancers. This review discusses the structure and regulation of R-Ras proteins and our current understanding of the signaling pathways that they regulate. It explores the phenotype of NS patients and their implications for the R-Ras subfamily functions. Next, it covers recent discoveries regarding physiological and pathologic R-Ras functions in key organ systems. Finally, it discusses how R-Ras signaling is dysregulated in cancers and mechanisms by which this may promote neoplasia.
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Affiliation(s)
- Shannon M Weber
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - Steven L Carroll
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, South Carolina.
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21
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Li YY, Wang H, Zhang YY. CDKN2B-AS1 gene rs4977574 A/G polymorphism and coronary heart disease: A meta-analysis of 40,979 subjects. J Cell Mol Med 2021; 25:8877-8889. [PMID: 34418317 PMCID: PMC8435436 DOI: 10.1111/jcmm.16849] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 06/05/2021] [Accepted: 07/31/2021] [Indexed: 12/23/2022] Open
Abstract
It has been implied that there is a possible relationship between cyclin‐dependent protein kinase inhibitors antisense RNA 1 (CDKN2B‐AS1) gene rs4977574 A/G polymorphism and coronary heart disease (CHD) susceptibility. However, as the research results are discrepant, no distinct consensus on this issue has been reached so far. In order to further elaborate the latent association of the CDKN2B‐AS1 gene rs4977574 A/G polymorphism and CHD, this present meta‐analysis was conducted. There were 40,979 subjects of 17 individual studies in the present meta‐analysis. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were estimated to determine the association strength. Considering the significant heterogeneity among the individual studies, the random‐effect models were used. In the current meta‐analysis, a significant association between CDKN2B‐AS1 gene rs4977574 A/G polymorphism and CHD was found under allelic (OR: 1.18, 95% CI: 1.08–1.29, p = 4.83×10−4), recessive (OR: 1.36, 95% CI: 1.11–1.67, p = 0.003), dominant (OR: 0.71, 95% CI: 0.58–0.86, p = 6.26×10−4), heterozygous (OR:1.210, 95% CI: 1.076–1.360, p = 0.001), homozygous (OR: 1.394, 95% CI: 1.163–1.671, p = 3.31×10−4) and additive (OR: 1.180, 95% CI: 1.075–1.295, p = 4.83×10−4) genetic models. A more significant association between them was found in the Asian population than that in the whole population under these genetic models (p < 0.05). However, no significant association between them was found in the Caucasian population (p > 0.05). CDKN2B‐AS1 gene rs4977574 A/G polymorphism was associated with CHD susceptibility, especially in the Asian population. G allele of CDKN2B‐AS1 gene rs4977574 A/G polymorphism is the risk allele for CHD.
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Affiliation(s)
- Yan-Yan Li
- Clinical Research Center, First Affiliated Hospital of Nanjing Medical University, Nanjing, China.,Department of Geriatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hui Wang
- Department of Cardiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yang-Yang Zhang
- Department of General Practice, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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22
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Muse ED, Chen SF, Torkamani A. Monogenic and Polygenic Models of Coronary Artery Disease. Curr Cardiol Rep 2021; 23:107. [PMID: 34196841 DOI: 10.1007/s11886-021-01540-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/17/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE OF THE REVIEW Coronary artery disease (CAD) is a common disease globally attributable to the interplay of complex genetic and lifestyle factors. Here, we review how genomic sequencing advances have broadened the fundamental understanding of the monogenic and polygenic contributions to CAD and how these insights can be utilized, in part by creating polygenic risk estimates, for improved disease risk stratification at the individual patient level. RECENT FINDINGS Initial studies linking premature CAD with rare familial cases of elevated blood lipids highlighted high-risk monogenic contributions, predominantly presenting as familial hypercholesterolemia (FH). More commonly CAD genetic risk is a function of multiple, higher frequency variants each imparting lower magnitude of risk, which can be combined to form polygenic risk scores (PRS) conveying significant risk to individuals at the extremes. However, gaps remain in clinical validation of PRSs, most notably in non-European populations. With improved and more broadly utilized genomic sequencing technologies, the genetic underpinnings of coronary artery disease are being unraveled. As a result, polygenic risk estimation is poised to become a widely used and powerful tool in the clinical setting. While the use of PRSs to augment current clinical risk stratification for optimization of cardiovascular disease risk by lifestyle change or therapeutic targeting is promising, we await adequately powered, prospective studies, demonstrating the clinical utility of polygenic risk estimation in practice.
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Affiliation(s)
- Evan D Muse
- Scripps Research Translational Institute, Scripps Research, 3344 N Torrey Pines Court, Suite 300, La Jolla, CA, 92037, USA.,Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, CA, 92037, USA
| | - Shang-Fu Chen
- Scripps Research Translational Institute, Scripps Research, 3344 N Torrey Pines Court, Suite 300, La Jolla, CA, 92037, USA
| | - Ali Torkamani
- Scripps Research Translational Institute, Scripps Research, 3344 N Torrey Pines Court, Suite 300, La Jolla, CA, 92037, USA.
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Arthiya M, Bhavani S, Jenisha J, Sharmila D, Varghese S, Kulanthaivel L, Subbaraj GK. LDLR, MTHFR and KLOTHO gene polymorphisms as an early predictor in the risk of coronary artery disease: A meta-analysis. GENE REPORTS 2021. [DOI: 10.1016/j.genrep.2021.101120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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24
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Roberts R, Chang CC, Hadley T. Genetic Risk Stratification: A Paradigm Shift in Prevention of Coronary Artery Disease. ACTA ACUST UNITED AC 2021; 6:287-304. [PMID: 33778213 PMCID: PMC7987546 DOI: 10.1016/j.jacbts.2020.09.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 09/08/2020] [Accepted: 09/13/2020] [Indexed: 12/12/2022]
Abstract
CAD is a pandemic that can be prevented. Conventional risk factors are inadequate to detect who is at risk early in the asymptomatic stage. Genetic risk for CAD can be determined at birth, and those at highest genetic risk have been shown to respond to lifestyle changes and statin therapy with a 40% to 50% reduction in cardiac events. Genetic risk stratification for CAD should be brought to the bedside in an attempt to prevent this pandemic disease.
Coronary artery disease (CAD) is a pandemic disease that is highly preventable as shown by secondary prevention. Primary prevention is preferred knowing that 50% of the population can expect a cardiac event in their lifetime. Risk stratification for primary prevention using the American Heart Association/American College of Cardiology predicted 10-year risk based on conventional risk factors for CAD is less than optimal. Conventional risk factors such as hypertension, cholesterol, and age are age-dependent and not present until the sixth or seventh decade of life. The genetic risk score (GRS), which is estimated from the recently discovered genetic variants predisposed to CAD, offers a potential solution to this dilemma. The GRS, which is derived from genotyping the population with a microarray containing these genetic risk variants, has indicated that genetic risk stratification based on the GRS is superior to that of conventional risk factors in detecting those at high risk and who would benefit most from statin therapy. Studies performed in >1 million individuals confirmed genetic risk stratification is superior and primarily independent of conventional risk factors. Prospective clinical trials based on risk stratification for CAD using the GRS have shown lifestyle changes, physical activity, and statin therapy are associated with 40% to 50% reduction in cardiac events in the high genetic risk group (20%). Genetic risk stratification has the advantage of being innate to an individual’s DNA, and because DNA does not change in a lifetime, it is independent of age. Genetic risk stratification is inexpensive and can be performed worldwide, providing risk analysis at any age and thus has the potential to revolutionize primary prevention.
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Key Words
- ACC, American College of Cardiology
- AHA, American Heart Association
- ANRIL, antisense non-coding RNA in the INK4 Locust
- CAD, coronary artery disease
- GRS, genetic risk score
- GWAS, genome-wide association study
- LDL-C, low-density lipoprotein cholesterol
- MR, Mendelian randomization
- SNP, single nucleotide polymorphism
- bp, base pair
- cardiovascular genetics
- coronary artery disease
- genetic risk score for CAD
- genome-wide association studies
- prevention of CAD
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Affiliation(s)
- Robert Roberts
- Department of Medicine, Dignity Health at St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Chih Chao Chang
- Department of Medicine, Dignity Health at St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
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25
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Inflammation-Related Risk Loci in Genome-Wide Association Studies of Coronary Artery Disease. Cells 2021; 10:cells10020440. [PMID: 33669721 PMCID: PMC7921935 DOI: 10.3390/cells10020440] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 02/02/2021] [Accepted: 02/17/2021] [Indexed: 12/13/2022] Open
Abstract
Although the importance of inflammation in atherosclerosis is now well established, the exact molecular processes linking inflammation to the development and course of the disease are not sufficiently understood. In this context, modern genetics—as applied by genome-wide association studies (GWAS)—can serve as a comprehensive and unbiased tool for the screening of potentially involved pathways. Indeed, a considerable proportion of loci discovered by GWAS is assumed to affect inflammatory processes. Despite many well-replicated association findings, however, translating genomic hits to specific molecular mechanisms remains challenging. This review provides an overview of the currently most relevant inflammation-related GWAS findings in coronary artery disease and explores their potential clinical perspectives.
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26
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Jha CK, Mir R, Banu S, Elfaki I, Chahal SMS. Heterozygosity in LDLR rs2228671 and rs72658855 Gene is Associated with Increased Risk of Developing Coronary Artery Disease in India -A Case-Control Study. Endocr Metab Immune Disord Drug Targets 2021; 20:388-399. [PMID: 31613733 DOI: 10.2174/1871530319666191015164505] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 07/09/2019] [Accepted: 09/13/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Coronary artery disease (CAD) is one of the most common causes of death worldwide. Risk factors of CAD include high LDL-C, low high-density lipoprotein (HDL), hypertension, lack of exercise, genetic factors, etc. Polymorphisms of the LDLR gene have been associated with CAD in previous studies. METHODS The LDLR-rs72658855 C>T genotyping was detected by using allele-specific PCR (ASPCR). The association of rs2228671 and rs72658855 with CAD in a south Indian cohort (200 CAD patients and 200 matched healthy controls was studied. RESULTS Our findings showed that rs2228671 gene variability is associated with increased susceptibility to coronary artery disease in the codominant inheritance model for variant CC vs. CT OR 3.42(1.09-10.7), with P<0.034. A non-significant association was reported in the recessive inheritance model for the variant (CC+CT) vs. TT OR 0.56(0.16-1.95), at P<0.36. and in the dominant inheritance model for variant CC vs. (CT+TT) OR 2.8(1.07-7.34), at P<0.032 .In case of allelic comparison, it was indicated that the LDLR rs2228671-T allele was associated with an increased risk of developing CAD compared to C allele OR=2.4, with 95% CI (1.05-5.64) and P< 0.036 . Our findings showed that LDLR rs72658855 C>T gene variability was associated with an increased susceptibility to coronary artery disease in the codominant inheritance model for variant CC vs. CT OR 1.7(1.1-2.6), at P<0.015 and in the dominant inheritance model for variant CC vs. (CT+TT) OR 1.66(1.07-2.58), at P<0.0.02.. In case of allelic comparison, a non-significant association was reported in LDLR rs72658855-T and C allele. CONCLUSION We concluded that the heterozygosity in LDLR-rs72658855 and rs2228671 and T allele in LDLR rs2228671 are strongly associated with increased susceptibility to coronary artery disease. These results must be validated by future well-designed studies with larger sample sizes and different populations.
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Affiliation(s)
- Chandan K Jha
- Department of Human Genetics, Punjabi University, Patiala, Punjab 147002, India
| | - Rashid Mir
- Department of Medical Lab Technology, Prince Fahd Bin Sultan Research Chair, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia
| | - Shaheena Banu
- Sri Jayadeva Institute of Cardiovascular science and Research, Bangalore, India
| | - Imadeldin Elfaki
- Department of Biochemistry, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi Arabia
| | - Sukh M S Chahal
- Department of Human Genetics, Punjabi University, Patiala, Punjab 147002, India
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27
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Cheng CF, Lin YJ, Lin MC, Liang WM, Chen CC, Chen CH, Wu JY, Lin TH, Liao CC, Huang SM, Hsieh AR, Tsai FJ. Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus. J Gene Med 2020; 23:e3305. [PMID: 33350037 DOI: 10.1002/jgm.3305] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/21/2020] [Accepted: 12/08/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Patients with type 2 diabetes mellitus (T2DM) experience a two-fold increased risk of cardiovascular diseases. Genome-wide association studies (GWAS) have identified T2DM susceptibility genetic variants. Interestingly, the genetic variants associated with cardiovascular disease risk in T2DM Han Chinese remain to be elucidated. The present study aimed to investigate the genetic variants associated with cardiovascular disease risk in T2DM. METHODS We performed bootstrapping, GWAS and an investigation of genetic variants associated with cardiovascular disease risk in a discovery T2DM cohort and in a replication cohort. The discovery cohort included 326 cardiovascular disease patients and 1209 noncardiovascular disease patients. The replication cohort included 68 cardiovascular disease patients and 317 noncardiovascular disease patients. The main outcome measures were genetic variants for genetic risk score (GRS) in cardiovascular disease risk in T2DM. RESULTS In total, 35 genetic variants were associated with cardiovascular disease risk. A GRS was generated by combining risk alleles from these variants weighted by their estimated effect sizes (log odds ratio [OR]). T2DM patients with weighted GRS ≥ 12.63 had an approximately 15-fold increase in cardiovascular disease risk (odds ratio = 15.67, 95% confidence interval [CI] = 10.33-24.00) compared to patients with weighted GRS < 10.39. With the addition of weighted GRS, receiver-operating characteristic curves showed that area under the curve with conventional risk factors was improved from 0.719 (95% CI = 0.689-0.750) to 0.888 (95% CI = 0.866-0.910). CONCLUSIONS These 35 genetic variants are associated with cardiovascular disease risk in T2DM, alone and cumulatively. T2DM patients with higher levels of weighted genetic risk score have higher cardiovascular disease risks.
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Affiliation(s)
- Chi-Fung Cheng
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan.,Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Ying-Ju Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Mei-Chen Lin
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan
| | - Wen-Miin Liang
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan
| | - Ching-Chu Chen
- Division of Endocrinology and Metabolism, Department of Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Chien-Hsiun Chen
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Institute of Biomedical Sciences, Taipei, Taiwan
| | - Jer-Yuarn Wu
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Institute of Biomedical Sciences, Taipei, Taiwan
| | - Ting-Hsu Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chiu-Chu Liao
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Shao-Mei Huang
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei, Taiwan
| | - Fuu-Jen Tsai
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
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28
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Yu T, Jiang H, Fan Y, Xu Y, Wang N. The association of CDKN2BAS gene polymorphisms and intracranial aneurysm: A meta-analysis. Medicine (Baltimore) 2020; 99:e23209. [PMID: 33285697 PMCID: PMC7717858 DOI: 10.1097/md.0000000000023209] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Intracranial aneurysm (IA) is one of the main causes of subarachnoid hemorrhage (SAH) leading to a high percentage of disability and mortality worldwide. In addition to environmental factors, the risk of rupture or prognosis of intracranial aneurysm is also closely related to gene. Thus, a lot of genetic studies have been used to explore associated risk genes as well as variant loci of intracranial aneurysm and found several chromosome variates including 9p21.3 (CDKN2BAS) related to Intracranial aneurysm. However, due to differences in population and the existence of SNP, it is still not determined that whether these genetic changes can be identified as independent risk factors for intracranial aneurysm. Therefore, we performed a meta-analysis of CDKN2BAS SNPs to explore its association with intracranial aneurysms and the results show a significance relation between rs10757272, rs1333040, and rs6475606 with intracranial aneurysm. This will open a new perspective for future intracranial aneurysm gene research and therapy.
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Affiliation(s)
- Ting Yu
- Department of Neurosurgery, Tiantai People's Hospital, Taizhou
| | - Hailong Jiang
- Department of Neurosurgery, Tiantai People's Hospital, Taizhou
| | - Yunren Fan
- Department of Neurosurgery, Tiantai People's Hospital, Taizhou
| | - Yunfeng Xu
- Department of Neurosurgery, Tiantai People's Hospital, Taizhou
| | - Ning Wang
- Department of Neurosurgery, Zhuji People's Hospital, Zhuji City, Zhejiang Province, PR China
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29
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Hao M, Zhao X, Xu W. Competing risk modeling and testing for X-chromosome genetic association. Comput Stat Data Anal 2020. [DOI: 10.1016/j.csda.2020.107007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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30
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Endo T. M-Ras is Muscle-Ras, Moderate-Ras, Mineral-Ras, Migration-Ras, and Many More-Ras. Exp Cell Res 2020; 397:112342. [PMID: 33130177 DOI: 10.1016/j.yexcr.2020.112342] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 10/23/2020] [Indexed: 11/19/2022]
Abstract
The Ras family of small GTPases comprises about 36 members in humans. M-Ras is related to classical Ras with regard to its regulators and effectors, but solely constitutes a subfamily among the Ras family members. Although classical Ras strongly binds Raf and highly activates the ERK pathway, M-Ras less strongly binds Raf and moderately but sustainedly activates the ERK pathway to induce neuronal differentiation. M-Ras also possesses specific effectors, including RapGEFs and the PP1 complex Shoc2-PP1c, which dephosphorylates Raf to activate the ERK pathway. M-Ras is highly expressed in the brain and plays essential roles in dendrite formation during neurogenesis, in contrast to the axon formation by R-Ras. M-Ras is also highly expressed in the bone and induces osteoblastic differentiation and transdifferentiation accompanied by calcification. Moreover, M-Ras elicits epithelial-mesenchymal transition-mediated collective and single cell migration through the PP1 complex-mediated ERK pathway activation. Activating missense mutations in the MRAS gene have been detected in Noonan syndrome, one of the RASopathies, and MRAS gene amplification occurs in several cancers. Furthermore, several SNPs in the MRAS gene are associated with coronary artery disease, obesity, and dyslipidemia. Therefore, M-Ras carries out a variety of cellular, physiological, and pathological functions. Further investigations may reveal more functions of M-Ras.
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Affiliation(s)
- Takeshi Endo
- Department of Biology, Graduate School of Science, Chiba University, 1-33 Yayoicho, Inageku, Chiba, Chiba 263-8522, Japan.
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31
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Koyama S, Ito K, Terao C, Akiyama M, Horikoshi M, Momozawa Y, Matsunaga H, Ieki H, Ozaki K, Onouchi Y, Takahashi A, Nomura S, Morita H, Akazawa H, Kim C, Seo JS, Higasa K, Iwasaki M, Yamaji T, Sawada N, Tsugane S, Koyama T, Ikezaki H, Takashima N, Tanaka K, Arisawa K, Kuriki K, Naito M, Wakai K, Suna S, Sakata Y, Sato H, Hori M, Sakata Y, Matsuda K, Murakami Y, Aburatani H, Kubo M, Matsuda F, Kamatani Y, Komuro I. Population-specific and trans-ancestry genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease. Nat Genet 2020; 52:1169-1177. [PMID: 33020668 DOI: 10.1038/s41588-020-0705-3] [Citation(s) in RCA: 174] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 08/28/2020] [Indexed: 12/12/2022]
Abstract
To elucidate the genetics of coronary artery disease (CAD) in the Japanese population, we conducted a large-scale genome-wide association study of 168,228 individuals of Japanese ancestry (25,892 cases and 142,336 controls) with genotype imputation using a newly developed reference panel of Japanese haplotypes including 1,781 CAD cases and 2,636 controls. We detected eight new susceptibility loci and Japanese-specific rare variants contributing to disease severity and increased cardiovascular mortality. We then conducted a trans-ancestry meta-analysis and discovered 35 additional new loci. Using the meta-analysis results, we derived a polygenic risk score (PRS) for CAD, which outperformed those derived from either Japanese or European genome-wide association studies. The PRS prioritized risk factors among various clinical parameters and segregated individuals with increased risk of long-term cardiovascular mortality. Our data improve the clinical characterization of CAD genetics and suggest the utility of trans-ancestry meta-analysis for PRS derivation in non-European populations.
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Affiliation(s)
- Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Masato Akiyama
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Department of Ocular Pathology and Imaging Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Hiroshi Matsunaga
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hirotaka Ieki
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kouichi Ozaki
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Division for Genomic Medicine, Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yoshihiro Onouchi
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Department of Public Health, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Atsushi Takahashi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.,Department of Genomic Medicine, Research Institute, National Cerebral, and Cardiovascular Center, Suita, Japan
| | - Seitaro Nomura
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Morita
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Akazawa
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Changhoon Kim
- Bioinformatics Institute, Macrogen Inc., Seoul, Republic of Korea
| | - Jeong-Sun Seo
- Bioinformatics Institute, Macrogen Inc., Seoul, Republic of Korea.,Precision Medicine Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Koichiro Higasa
- Department of Genome Analysis, Institute of Biomedical Science, Kansai Medical University, Hirakata, Japan.,Human Disease Genomics, Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Taiki Yamaji
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Norie Sawada
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Shoichiro Tsugane
- Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Kyushu University Graduate School of Medical Sciences, Faculty of Medical Sciences, Fukuoka, Japan
| | - Naoyuki Takashima
- Department of Public Health, Faculty of Medicine, Kindai University, Osaka, Japan.,Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Kokichi Arisawa
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Mariko Naito
- Department of Oral Epidemiology, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan.,Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Shinichiro Suna
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Suita, Japan
| | - Yasuhiko Sakata
- Department of Cardiovascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Hiroshi Sato
- School of Human Welfare Studies Health Care Center and Clinic, Kwansei Gakuin University, Nishinomiya, Japan
| | - Masatsugu Hori
- Osaka Prefectural Hospital Organization, Osaka International Cancer Institute, Osaka, Japan
| | - Yasushi Sakata
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Science, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Aburatani
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Fumihiko Matsuda
- Human Disease Genomics, Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan. .,Human Disease Genomics, Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan. .,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
| | - Issei Komuro
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
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32
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Lechner K, Kessler T, Schunkert H. Should We Use Genetic Scores in the Determination of Treatment Strategies to Control Dyslipidemias? Curr Cardiol Rep 2020; 22:146. [DOI: 10.1007/s11886-020-01408-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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33
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Jung SY, Scott PA, Papp JC, Sobel EM, Pellegrini M, Yu H, Han S, Zhang ZF. Genome-wide Association Analysis of Proinflammatory Cytokines and Gene-lifestyle Interaction for Invasive Breast Cancer Risk: The WHI dbGaP Study. Cancer Prev Res (Phila) 2020; 14:41-54. [PMID: 32928877 DOI: 10.1158/1940-6207.capr-20-0256] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/21/2020] [Accepted: 08/25/2020] [Indexed: 12/11/2022]
Abstract
Immune-related etiologic pathways to influence invasive breast cancer risk may interact with lifestyle factors, but the interrelated molecular genetic pathways are incompletely characterized. We used data from the Women's Health Initiative Database for Genotypes and Phenotypes Study including 16,088 postmenopausal women, a population highly susceptible to inflammation, obesity, and increased risk for breast cancer. With 21,784,812 common autosomal single-nucleotide polymorphisms (SNP), we conducted a genome-wide association (GWA) gene-environment interaction (G × E) analysis in six independent GWA Studies for proinflammatory cytokines [IL6 and C-reactive protein (CRP)] and their gene-lifestyle interactions. Subsequently, we tested for the association of the GWA SNPs with breast cancer risk. In women overall and stratified by obesity status (body mass index, waist circumference, and waist-to-hip ratio) and obesity-related lifestyle factors (exercise and high-fat diet), 88 GWA SNPs in 10 loci were associated with proinflammatory cytokines: 3 associated with IL6 (1 index SNP in MAPK1 and 1 independent SNP in DEC1); 85 with CRP (3 index SNPs in CRPP1, CRP, RP11-419N10.5, HNF1A-AS1, HNF1A, and C1q2orf43; and two independent SNPs in APOE and APOC1). Of those, 27 in HNF1A-AS1, HNF1A, and C1q2orf43 displayed significantly increased risk for breast cancer. We found a number of novel top markers for CRP and IL6, which interacted with obesity factors. A substantial proportion of those SNPs' susceptibility influenced breast cancer risk. Our findings may contribute to better understanding of genetic associations between pro-inflammation and cancer and suggest intervention strategies for women who carry the risk genotypes, reducing breast cancer risk. PREVENTION RELEVANCE: The top GWA-SNPs associated with pro-inflammatory biomarkers have implications for breast carcinogenesis by interacting with obesity factors. Our findings may suggest interventions for women who carry the inflammatory-risk genotypes to reduce breast cancer risk.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California, Los Angeles, Los Angeles, California.
| | - Peter A Scott
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California
| | - Jeanette C Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Eric M Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.,Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, Life Sciences Division, University of California, Los Angeles, Los Angeles, California
| | - Herbert Yu
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Sihao Han
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California.,Center for Human Nutrition, David Geffen School of Medicine, University of California, Los Angeles, California
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Zhang YH, Pan X, Zeng T, Chen L, Huang T, Cai YD. Identifying the RNA signatures of coronary artery disease from combined lncRNA and mRNA expression profiles. Genomics 2020; 112:4945-4958. [PMID: 32919019 DOI: 10.1016/j.ygeno.2020.09.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 07/28/2020] [Accepted: 09/05/2020] [Indexed: 12/23/2022]
Abstract
Coronary artery disease (CAD) is the most common cardiovascular disease. CAD research has greatly progressed during the past decade. mRNA is a traditional and popular pipeline to investigate various disease, including CAD. Compared with mRNA, lncRNA has better stability and thus may serve as a better disease indicator in blood. Investigating potential CAD-related lncRNAs and mRNAs will greatly contribute to the diagnosis and treatment of CAD. In this study, a computational analysis was conducted on patients with CAD by using a comprehensive transcription dataset with combined mRNA and lncRNA expression data. Several machine learning algorithms, including feature selection methods and classification algorithms, were applied to screen for the most CAD-related RNA molecules. Decision rules were also reported to provide a quantitative description about the effect of these RNA molecules on CAD progression. These new findings (CAD-related RNA molecules and rules) can help understand mRNA and lncRNA expression levels in CAD.
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Affiliation(s)
- Yu-Hang Zhang
- School of Life Sciences, Shanghai University, Shanghai 200444, China; Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Xiaoyong Pan
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240 Shanghai, China.
| | - Tao Zeng
- Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai 201210, China.
| | - Lei Chen
- College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
| | - Tao Huang
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Yu-Dong Cai
- School of Life Sciences, Shanghai University, Shanghai 200444, China.
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35
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Association of the PSRC1 rs599839 Variant with Coronary Artery Disease in a Mexican Population. ACTA ACUST UNITED AC 2020; 56:medicina56090427. [PMID: 32858814 PMCID: PMC7559377 DOI: 10.3390/medicina56090427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 07/29/2020] [Accepted: 08/12/2020] [Indexed: 12/14/2022]
Abstract
Background and Objectives: Coronary artery disease (CAD) is a major health problem in México. The identification of modifiable risk factors and genetic biomarkers is crucial for an integrative and personalized CAD risk evaluation. In this work, we aimed to validate in a Mexican population a set of eight selected polymorphisms previously associated with CAD, myocardial infarction (MI), or dyslipidemia. Materials and Methods: A sample of 907 subjects (394 CAD cases and 513 controls) 40–80 years old was genotyped for eight loci: PSRC1 (rs599839), MRAS (rs9818870), BTN2A1 (rs6929846), MTHFD1L (rs6922269), CDKN2B (rs1333049), KIAA1462 (rs3739998), CXCL12 (rs501120), and HNF1A (rs2259816). The association between single nucleotide polymorphisms (SNPs) and CAD was evaluated by logistic regression models. Results: Multiple logistic regression analysis with adjustment by age, gender, and body mass index showed that rs599839 was significantly associated with CAD (ORADD = 0.72, p = 0.009; ORDOM = 0.66, p = 0.007). Conclusions: The PSRC1 rs599839 polymorphism shows a significant protective association with CAD in this sample of the Mexican population.
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36
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Li L, Pang S, Zeng L, Güldener U, Schunkert H. Genetically determined intelligence and coronary artery disease risk. Clin Res Cardiol 2020; 110:211-219. [PMID: 32740755 PMCID: PMC7862508 DOI: 10.1007/s00392-020-01721-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/23/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Epidemiological studies have shown inverse association between intelligence and coronary artery disease (CAD) risk, but the underlying mechanisms remain unclear. METHODS Based on 242 SNPs independently associated with intelligence, we calculated the genetic intelligence score (gIQ) for participants from 10 CAD case-control studies (n = 34,083) and UK Biobank (n = 427,306). From UK Biobank, we extracted phenotypes including body mass index (BMI), type 2 diabetes (T2D), smoking, hypertension, HDL cholesterol, LDL cholesterol, measured intelligence score, and education attainment. To estimate the effects of gIQ on CAD and its related risk factors, regression analyses was applied. Next, we studied the mediatory roles of measured intelligence and educational attainment. Lastly, Mendelian randomization was performed to validate the findings. RESULTS In CAD case-control studies, one standard deviation (SD) increase of gIQ was related to a 5% decrease of CAD risk (odds ratio [OR] of 0.95; 95% confidence interval [CI] 0.93 to 0.98; P = 4.93e-5), which was validated in UK Biobank (OR = 0.97; 95% CI 0.96 to 0.99; P = 6.4e-4). In UK Biobank, we also found significant inverse correlations between gIQ and risk factors of CAD including smoking, BMI, T2D, hypertension, and a positive correlation with HDL cholesterol. The association signals between gIQ and CAD as well as its risk factors got largely attenuated after the adjustment of measured intelligence and educational attainment. The causal role of intelligence in mediating CAD risk was confirmed by Mendelian randomization analyses. CONCLUSION Genetic components of intelligence affect measured intelligence and educational attainment, which subsequently affect the prevalence of CAD via a series of unfavorable risk factor profiles.
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Affiliation(s)
- Ling Li
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany
| | - Shichao Pang
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany
| | - Lingyao Zeng
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany
| | - Ulrich Güldener
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany. .,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Munich Heart Alliance, Munich, Germany.
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37
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Han D, Hao M, Qu L, Xu W. A novel model for the X-chromosome inactivation association on survival data. Stat Methods Med Res 2020; 29:1305-1314. [PMID: 31258049 DOI: 10.1177/0962280219859037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The X-linked genetic association is overlooked in most of the genetic studies because of the complexity of X-chromosome inactivation process. In fact, the biological process of the gene at the same locus can vary across different subjects. Besides, the skewness of X-chromosome inactivation is inherently subject-specific (even tissue-specific within subjects) and cannot be accurately represented by a population-level parameter. To tackle this issue, a new model is proposed to incorporate the X-linked genetic association into right-censored survival data. The novel model can present that the X-linked genes on different subjects may go through different biological processes via a mixed distribution. Further, a random effect is employed to describe the uncertainty of the biological process for every subject. The proposed method can derive the probability for the escape of X-chromosome inactivation and derive the unbiased estimates of the model parameters. The Legendre-Gauss Quadrature method is used to approximate the integration over the random effect. Finite sample performance of this method is examined via extensive simulation studies. An application is illustrated with the implementation on a cancer genetic study with right-censored survival data.
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Affiliation(s)
- Dongxiao Han
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Meiling Hao
- School of Statistics, University of International Business and Economics, Beijing, China
| | - Lianqiang Qu
- School of Mathematics and Statistics, Central China Normal University, Wuhan, China
| | - Wei Xu
- Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
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Zeng L, Talukdar HA, Koplev S, Giannarelli C, Ivert T, Gan LM, Ruusalepp A, Schadt EE, Kovacic JC, Lusis AJ, Michoel T, Schunkert H, Björkegren JLM. Contribution of Gene Regulatory Networks to Heritability of Coronary Artery Disease. J Am Coll Cardiol 2020; 73:2946-2957. [PMID: 31196451 DOI: 10.1016/j.jacc.2019.03.520] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Revised: 02/27/2019] [Accepted: 03/16/2019] [Indexed: 12/21/2022]
Abstract
BACKGROUND Genetic variants currently known to affect coronary artery disease (CAD) risk explain less than one-quarter of disease heritability. The heritability contribution of gene regulatory networks (GRNs) in CAD, which are modulated by both genetic and environmental factors, is unknown. OBJECTIVES This study sought to determine the heritability contributions of single nucleotide polymorphisms affecting gene expression (eSNPs) in GRNs causally linked to CAD. METHODS Seven vascular and metabolic tissues collected in 2 independent genetics-of-gene-expression studies of patients with CAD were used to identify eSNPs and to infer coexpression networks. To construct GRNs with causal relations to CAD, the prior information of eSNPs in the coexpression networks was used in a Bayesian algorithm. Narrow-sense CAD heritability conferred by the GRNs was calculated from individual-level genotype data from 9 European genome-wide association studies (GWAS) (13,612 cases, 13,758 control cases). RESULTS The authors identified and replicated 28 independent GRNs active in CAD. The genetic variation in these networks contributed to 10.0% of CAD heritability beyond the 22% attributable to risk loci identified by GWAS. GRNs in the atherosclerotic arterial wall (n = 7) and subcutaneous or visceral abdominal fat (n = 9) were most strongly implicated, jointly explaining 8.2% of CAD heritability. In all, these 28 GRNs (each contributing to >0.2% of CAD heritability) comprised 24 to 841 genes, whereof 1 to 28 genes had strong regulatory effects (key disease drivers) and harbored many relevant functions previously associated with CAD. The gene activity in these 28 GRNs also displayed strong associations with genetic and phenotypic cardiometabolic disease variations both in humans and mice, indicative of their pivotal roles as mediators of gene-environmental interactions in CAD. CONCLUSIONS GRNs capture a major portion of genetic variance and contribute to heritability beyond that of genetic loci currently known to affect CAD risk. These networks provide a framework to identify novel risk genes/pathways and study molecular interactions within and across disease-relevant tissues leading to CAD.
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Affiliation(s)
- Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Husain A Talukdar
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Simon Koplev
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Chiara Giannarelli
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York; Cardiovascular Research Centre, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Torbjörn Ivert
- Department of Thoracic Surgery, Karolinska University Hospital and Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Li-Ming Gan
- Cardiovascular, Renal and Metabolism Translational Medicines Unit, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia; Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric E Schadt
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jason C Kovacic
- Cardiovascular Research Centre, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Aldons J Lusis
- Departments of Medicine, Cardiology, Human Genetics, Microbiology, Immunology & Molecular Genetics, University of California-Los Angeles, Los Angeles, California
| | - Tom Michoel
- Clinical Gene Networks AB, Stockholm, Sweden; Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany.
| | - Johan L M Björkegren
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany; Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden; Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York; Clinical Gene Networks AB, Stockholm, Sweden.
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Gola D, Erdmann J, Müller‐Myhsok B, Schunkert H, König IR. Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status. Genet Epidemiol 2020; 44:125-138. [DOI: 10.1002/gepi.22279] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 12/05/2019] [Accepted: 12/23/2019] [Indexed: 02/06/2023]
Affiliation(s)
- Damian Gola
- Institut für Medizinische Biometrie und StatistikUniversität zu Lübeck Lübeck Germany
| | | | - Bertram Müller‐Myhsok
- Department of Translational Research in PsychiatryMax Planck Institute of PsychiatryMunich Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum MünchenTechnische Universität MünchenMünchen Germany
| | - Inke R. König
- Institut für Medizinische Biometrie und StatistikUniversität zu Lübeck Lübeck Germany
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Ohlsson MA, Kennedy LMA, Juhlin T, Melander O. Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors. Resuscitation 2020; 146:74-79. [PMID: 31759070 DOI: 10.1016/j.resuscitation.2019.11.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 11/05/2019] [Accepted: 11/08/2019] [Indexed: 12/30/2022]
Abstract
OBJECTIVES Coronary heart disease (CHD) is a leading cause of death globally, commonly through sudden cardiac death. Cardiac arrest of cardiac origin (CA) is associated with a poor prognosis and there is a great need for risk assessment and intensified preventive actions. In this study we aim to assess if a genetic risk score for CHD, composed of 50 common CHD susceptibility variants (GRS), predicts CA and to evaluate a novel composite risk score including traditional risk factors as well as GRS. METHODS The GRS score alone and in combination with traditional CHD risk factors were examined in relation to CA incidence among 23 000 middle aged subjects during 18.9 years of follow-up. The cohort excluded patients with a diagnosed history of CHD, heart failure or stroke. RESULTS Two-hundred-fifty-two patients suffered a cardiac arrest during the follow up, of which 181 were CA. In a multivariate model with CHD risk factors, high versus low genetic risk predicted CA with a hazard ratio (HR) of 2.49 {(95% CI 1.50-4.12) (P < 0.001)}, surpassed only by higher estimates for male sex {HR = 2.91 (95% CI 2.09-4.06) (P < 0.001)}, ages 50-65 {HR = 2.74 (95% CI 1.42-5.25) (P = 0.003)} and ages 65-74 {HR = 5.10 (95% CI 2.56-10.16) (P < 0.001)}. Smoking, dyslipidemia, hypertension and diabetes mellitus also predicted CA but with lower HRs than GRS. A novel composite risk score including CHD risk factors as well as GRS predicted CA with a HR = 110.81 {(95% CI 15.43-795.63) (P < 0.001)} for the highest (5) versus the lowest quintile (1) of the risk score. CONCLUSIONS Genetic risk of CHD is strongly associated with incident CA and when combined with traditional CHD risk factors may identify individuals who benefit from intensified preventive pharmacological treatment.
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Affiliation(s)
- Marcus Andreas Ohlsson
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden.
| | - Linn Maria Anna Kennedy
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Tord Juhlin
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Olle Melander
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
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Kessler T, Schunkert H. Genomic Strategies Toward Identification of Novel Therapeutic Targets. Handb Exp Pharmacol 2020; 270:429-462. [PMID: 32399778 DOI: 10.1007/164_2020_360] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Coronary artery disease, myocardial infarction, and secondary damages of the myocardium in the form of ischemic heart disease remain major causes of death in Western countries. Beyond traditional risk factors such as smoking, hypertension, dyslipidemia, or diabetes, a positive family history is known to increase risk. The genetic factors underlying this observation remained unknown for decades until genetic studies were able to identify multiple genomic loci contributing to the heritability of the trait. Knowledge of the affected genes and the resulting molecular and cellular mechanisms leads to improved understanding of the pathophysiology leading to coronary atherosclerosis. Major goals are also to improve prevention and therapy of coronary artery disease and its sequelae via improved risk prediction tools and pharmacological targets. In this chapter, we recapitulate recent major findings. We focus on established novel targets and discuss possible further targets which are currently explored in translational studies.
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Affiliation(s)
- Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany. .,Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany.
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany
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Song Y, Ma R, Zhang H. The influence of MRAS gene variants on ischemic stroke and serum lipid levels in Chinese Han population. Medicine (Baltimore) 2019; 98:e18065. [PMID: 31770223 PMCID: PMC6890362 DOI: 10.1097/md.0000000000018065] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Previous studies have indicated that muscle RAS oncogene homolog (MRAS) gene played an important role in cardiovascular diseases. However, the effect of MRAS genetic variations on ischemic stroke (IS) is still not clear. The aim of the current study was to investigate the association between the MRAS polymorphism and IS risk in Han populations.Three SNPs (rs40593, rs751357, rs6782181) at MRAS were selected for genotyping in a sample of 240 IS patients and 430 controls. Logistic regression was performed to evaluate the association of 3 SNPs with IS and IS subgroups.No association of MRAS SNPs with IS risk was observed, while G allele of rs40593 was associated with increased risk of cerebral infarction area. Compared with carriers of the AA genotype, the risk of carriers of the AG+GG genotype increased, with an OR (95%CI) of 2.337 (1.175-4.647), P = .016. In relation to lipid profile, rs40593, rs751357, rs6782181 were associated with increased total cholesterol (TC) levels.Summarily, this study suggested that MRAS rs40593 may contribute to the increased risk of area of cerebral infarction of IS in Han population. rs40593, rs751357, and rs6782181 were associated with higher serum TC levels.
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Affiliation(s)
| | - Rui Ma
- Department of Hemodialysis, Jieshou City People's Hospital, Fuyang, China
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Rouhani B, Ghaderian SMH, Salehi Z. Investigation of LPA sequence variants rs6415084, rs3798220 with conventional coronary artery disease in Iranian CAD patients. Hum Antibodies 2019; 27:99-104. [PMID: 30594920 DOI: 10.3233/hab-180353] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Conventional coronary artery disease (CAD) is the leading cause of morbidity and mortality in the general population. In recent years, multiple CAD promising risk factors have been reported and used for risk stratification. Lipoprotein(a) [LPA] concentration in plasma was shown associated with CAD risk and LPA genetic variants in different ethnic groups remains less clear. METHODS We obtained data from 100 affected patients with established CAD and 100 healthy controls. We tested Body mass index (BMI), total cholesterol level (TC), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), fasting blood sugar (FBS) and two LPA (rs10455872 and rs3798220 SNPs) between cases and healthy controls. TaqMan SNP genotyping assays were performed to detect variants. RESULTS Obtained data for BMI, TC, SBP, DBP, and LDL have significantly difference between two groups. Individually, the single SNPs were not associated with CAD in different analysis models. Also there was no significant difference in the incidence of CAD among cases carrying different genotypes of the two variants in LPA with p> 0.05. DISCUSSION In this study patients with CAD, lipoprotein(a) concentrations and genetic variants showed no associations and we conclude that these variables are not useful risk factors to predict progression to disease is Iranian population. However, the prevalence and association of LPA SNPs with size of LPA and isoforms are highly variable and genetic background-specific. CONCLUSION Our data did not indicate a relationship between genomic LPA variants (rs10455872 and rs3798220) and subsequent cardiovascular events in Iranian CAD patients. We did not confirm the association of the theses SNPs with CAD in our samples of Iranian patients. For the studied variants, our finding is consistent with reports which showed the lack of this genetic association in other populations.
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Affiliation(s)
- Borzu Rouhani
- Department of Genetic, Faculty of Science, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran
| | | | - Zivar Salehi
- Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
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Zeng L, Ntalla I, Kessler T, Kastrati A, Erdmann J, Danesh J, Watkins H, Samani NJ, Deloukas P, Schunkert H. Genetically modulated educational attainment and coronary disease risk. Eur Heart J 2019; 40:2413-2420. [PMID: 31170283 PMCID: PMC6669407 DOI: 10.1093/eurheartj/ehz328] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 08/30/2017] [Accepted: 05/03/2019] [Indexed: 12/11/2022] Open
Abstract
AIMS Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment-an important denominator of lifestyle-and coronary artery disease (CAD) risk. METHODS AND RESULTS Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a 'genetic education score' in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10-8; odds ratio (OR) 0.79, 95% confidence interval (CI) 0.73-0.85 for the higher compared with the lowest score quintile]. We replicated in 146 514 individuals from UK Biobank (P = 1.85 × 10-6) and also found strong associations between the 'genetic education score' with 'modifiable' risk factors including smoking (P = 5.36 × 10-23), body mass index (BMI) (P = 1.66 × 10-30), and hypertension (P = 3.86 × 10-8). Interestingly, these associations were only modestly attenuated by adjustment for years spent in school. In contrast, a model adjusting for BMI and smoking abolished the association signal between the 'genetic education score' and CAD risk suggesting an intermediary role of these two risk factors. Mendelian randomization analyses performed with summary statistics from large genome-wide meta-analyses and sensitivity analysis using 1271 variants affecting educational attainment (OR 0.68 for the higher compared with the lowest score quintile; 95% CI 0.63-0.74; P = 3.99 × 10-21) further strengthened these findings. CONCLUSION Genetic variants known to affect educational attainment may have implications for a health-conscious lifestyle later in life and subsequently affect the risk of CAD.
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Affiliation(s)
- Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstr. 36, Munich, Germany
| | - Ioanna Ntalla
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts & The London Medical School, Queen Mary University of London, Charterhouse Square, London, UK
- Centre for Genomic Health, Queen Mary University of London, Charterhouse Square, London, UK
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstr. 36, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Adnan Kastrati
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstr. 36, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics and University Heart Center Luebeck, University of Lübeck, Maria–Goeppert–Straße 1, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | | | - John Danesh
- Department of Public Health and Primary Care, MRC/BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, NIHR Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Cardiovascular Biomedical Research Centre, Leicester, UK
| | - Panos Deloukas
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts & The London Medical School, Queen Mary University of London, Charterhouse Square, London, UK
- Centre for Genomic Health, Queen Mary University of London, Charterhouse Square, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Al-Malae'b St, Jeddah, Saudi Arabia
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstr. 36, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
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Erdmann J, Kessler T, Munoz Venegas L, Schunkert H. A decade of genome-wide association studies for coronary artery disease: the challenges ahead. Cardiovasc Res 2019; 114:1241-1257. [PMID: 29617720 DOI: 10.1093/cvr/cvy084] [Citation(s) in RCA: 132] [Impact Index Per Article: 26.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 03/29/2018] [Indexed: 12/12/2022] Open
Abstract
In this review, we summarize current knowledge on the genetics of coronary artery disease, based on 10 years of genome-wide association studies. The discoveries began with individual studies using 200K single nucleotide polymorphism arrays and progressed to large-scale collaborative efforts, involving more than a 100 000 people and up to 40 Mio genetic variants. We discuss the challenges ahead, including those involved in identifying causal genes and deciphering the links between risk variants and disease pathology. We also describe novel insights into disease biology based on the findings of genome-wide association studies. Moreover, we discuss the potential for discovery of novel treatment targets through the integration of different layers of 'omics' data and the application of systems genetics approaches. Finally, we provide a brief outlook on the potential for precision medicine to be enhanced by genome-wide association study findings in the cardiovascular field.
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Affiliation(s)
- Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Maria-Geoppert-Str. 1, Lübeck, Germany.,DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany.,University Heart Center Lübeck, Ratzeburger Allee 160, Lübeck, Germany
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstraβe 36, Munich, Germany.,DZHK (German Center for Cardiovascular Research) e.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Loreto Munoz Venegas
- Institute for Cardiogenetics, University of Lübeck, Maria-Geoppert-Str. 1, Lübeck, Germany.,DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany.,University Heart Center Lübeck, Ratzeburger Allee 160, Lübeck, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Lazarettstraβe 36, Munich, Germany.,DZHK (German Center for Cardiovascular Research) e.V., Partner Site Munich Heart Alliance, Munich, Germany
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A multilocus genetic risk score is associated with arterial stiffness in hypertensive patients: the CARE NORTH study. J Hypertens 2019; 36:1882-1888. [PMID: 29878972 DOI: 10.1097/hjh.0000000000001773] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Arterial stiffness is recognized as an intermediate phenotype and predictor of cardiovascular disease. Arterial stiffness is complex in origin with contributions from lifestyle and genetic factors. However, the association between single nucleotide polymorphisms (SNPs) and arterial stiffness remains unclear. OBJECTIVE The aim is to assess whether a multilocus genetic risk score (GRS), composed of selected SNPs linked to cardiovascular traits and outcomes, is associated with arterial stiffness in patients with hypertension. DESIGN AND METHODS This study included 730 participants derived from the CARE NORTH study. The arterial stiffness was evaluated by carotid-femoral pulse wave velocity (cfPWV). An adjusted linear regression was used to evaluate the association between cfPWV and each individual SNP using multiple genetic models. The association between a constructed GRS and cfPWV was tested in an unadjusted and adjusted model. RESULTS We selected 13 SNPs found to be associated with cfPWV (P < .05): 6 SNPs in additive, 4 SNPs in recessive and 3 SNPs in dominant mode of inheritance. The GRS based on these SNPs was positively associated with cfPWV both in unadjusted and adjusted models (β = 0.2 m/s, 95% CI 0.11 - 0.29, P = 7.6 × 10 and β = 0.22 m/s, 95% CI 0.15 - 0.28, P = 1.4 × 10, respectively). The GRS explained an additional 3.6% cfPWV variance above clinical covariates. CONCLUSION We demonstrate that the GRS composed of 13 SNPs related to cardiovascular phenotypes is associated with an increased arterial stiffness in hypertensive patients. Our findings may help to clarify genetic basis of arterial stiffening and provide insight into mechanisms underlying this phenotype.
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Liu J, Mao R, Ren G, Liu X, Zhang Y, Wang J, Wang Y, Li M, Qiu Q, Wang L, Liu G, Jin S, Ma L, Ma Y, Zhao N, Yan J, Zhang H, Lin B. Whole Exome Sequencing Identifies Putative Predictors of Recurrent Prostate Cancer with High Accuracy. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 23:380-388. [PMID: 31194651 DOI: 10.1089/omi.2019.0044] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Prostate cancer (PCa) is a highly common cancer among men but lacks robust diagnostics that can predict disease recurrence after initial treatment, for example, with radical prostatectomy. Recent advances in genomics and next-generation sequencing heralded the discovery of biomarkers such as the androgen receptor gene (AR) splice events, the TMPRSS2:EGR gene fusion, long noncoding RNA MALAT-1 and SCHLAP1 for PCa prognosis. Still, the question of why some patients experience recurrence, whereas others do not introduce marked uncertainty for both patients and physicians. We report here the whole exome sequencing of 30 recurrent and 44 nonrecurrent PCa patients. We identified 72 and 34 specific somatic single nucleotide variations in the recurrent and the nonrecurrent group, respectively, and developed a classification model to forecast PCa recurrence using a random forest model. The model displayed a sensitivity and specificity of 87.8% and 94.4%, respectively, for identifying the patients with recurrent PCa. These observations warrant further research in independent and larger clinical samples so as to inform future diagnostics innovation for PCa prognosis and recurrence.
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Affiliation(s)
- Jie Liu
- 1College of Life Science, Zhejiang University, Hangzhou, China.,2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Ruifang Mao
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Guoping Ren
- 3Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou, China
| | - Xiaoyan Liu
- 3Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou, China
| | - Yanling Zhang
- 3Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou, China.,4Department of Gynecology and Obstetrics, Sir Run Run Shaw Hospital, Zhejiang University Medical College, Hangzhou, China
| | - Jili Wang
- 3Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou, China
| | - Yan Wang
- 3Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou, China
| | - Meiling Li
- 5Department of Epidemiology, Second Military Medical University, Shanghai, China
| | - Qingchong Qiu
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Lin Wang
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Guanfeng Liu
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Shanshan Jin
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Liang Ma
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Yingying Ma
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Na Zhao
- 2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China
| | - Jiajun Yan
- 6Department of Urology, Shaoxing People's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China
| | - Hongwei Zhang
- 5Department of Epidemiology, Second Military Medical University, Shanghai, China
| | - Biaoyang Lin
- 1College of Life Science, Zhejiang University, Hangzhou, China.,2Systems Biology Division, Zhejiang-California International Nanosystems Institute (ZCNI), Zhejiang University, Hangzhou, China.,7Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,8Department of Urology, University of Washington, Seattle, Washington
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Osadnik T, Osadnik K, Pawlas N, Strzelczyk J, Kasperczyk J, Poloński L, Gąsior M. Metabolic and genetic profiling of young adults with and without a family history of premature coronary heart disease (MAGNETIC). Study design and methodology. Arch Med Sci 2019; 15:590-597. [PMID: 31110523 PMCID: PMC6524187 DOI: 10.5114/aoms.2018.75895] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 03/22/2018] [Indexed: 12/15/2022] Open
Abstract
INTRODUCTION First-degree relatives of individuals with premature coronary artery disease (CAD) are at increased risk of CAD. The research hypothesis of this project assumes that there are differences in the metabolic profiles between individuals with and without a positive family history (FH) of premature CAD. MATERIAL AND METHODS The study group will comprise healthy patients (n = 500) aged 18-35 years with a FH of premature CAD, and the control group (n = 500) will consist of healthy subjects without a FH of premature CAD. Blood tests assessing the lipid profile will be carried out. Patients will respond to a questionnaire regarding FH and dietary habits. Measurement of carotid intima media thickness will be performed. Analysis of single-nucleotide polymorphisms (SNPs) associated with premature CAD will be carried out for every patient. Metabolomic profiling will be performed using a high-sensitivity Bruker AVANCE II 600 MHz NMR spectroscope. RESULTS The results of this study will include a comparison of metabolic profiles assessed by 1H-NMR spectroscopy in the study and control groups and the results of analyses of the relationship between the metabolic profiles and genetic risk score calculated based on evaluated SNPs associated with premature CAD. CONCLUSIONS This study will deepen our knowledge of the aetiopathogenesis of atherosclerosis by identifying metabolic patterns associated with a positive FH of premature CAD. Obtaining a detailed FH will enable adjustments for major risk factors of premature CAD in the proband's first-degree relatives. This research project also provides a chance to discover new biomarkers associated with the risk of premature CAD.
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Affiliation(s)
- Tadeusz Osadnik
- Department of Pharmacology, Medical University of Silesia, School of Medicine with the Division of Dentistry, Zabrze, Poland
- 2 Department of Cardiology, Silesian Centre for Heart Diseases, Zabrze, Poland
| | - Kamila Osadnik
- Department of Pharmacology, Medical University of Silesia, School of Medicine with the Division of Dentistry, Zabrze, Poland
| | - Natalia Pawlas
- Department of Pharmacology, Medical University of Silesia, School of Medicine with the Division of Dentistry, Zabrze, Poland
- Institute of Occupational Medicine and Environmental Health, Sosnowiec, Poland
| | - Joanna Strzelczyk
- Department of Medical and Molecular Biology, School of Medicine with the Division of Dentistry in Zabrze, Medical University of Silesia in Katowice, Poland
| | - Janusz Kasperczyk
- Centre of Polymer and Carbon Materials, the Polish Academy of Sciences, Zabrze, Poland
| | - Lech Poloński
- 2 Department of Cardiology, Silesian Centre for Heart Diseases, Zabrze, Poland
| | - Mariusz Gąsior
- Third Department of Cardiology, SMDZ in Zabrze, Medical University of Silesia, Katowice, Poland
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Postolache TT, del Bosque-Plata L, Jabbour S, Vergare M, Wu R, Gragnoli C. Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome. Am J Med Genet B Neuropsychiatr Genet 2019; 180:186-203. [PMID: 30729689 PMCID: PMC6492942 DOI: 10.1002/ajmg.b.32712] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Revised: 11/16/2018] [Accepted: 12/07/2018] [Indexed: 12/20/2022]
Abstract
Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.
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Affiliation(s)
- Teodor T. Postolache
- Department of Psychiatry, Mood and Anxiety Program, University of Maryland School of Medicine, Baltimore, Maryland,Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC), Veterans Integrated Service Network (VISN) 19, Military and Veteran Microbiome: Consortium for Research and Education (MVM-CoRE), Denver, Colorado,Mental Illness Research Education and Clinical Center (MIRECC), Veterans Integrated Service Network (VISN) 5, VA Capitol Health Care Network, Baltimore, Maryland
| | - Laura del Bosque-Plata
- National Institute of Genomic Medicine, Nutrigenetics and Nutrigenomic Laboratory, Mexico City, Mexico
| | - Serge Jabbour
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolic Disease, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Michael Vergare
- Department of Psychiatry and Human Behavior, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Rongling Wu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania,Department of Statistics, Penn State College of Medicine, Hershey, Pennsylvania
| | - Claudia Gragnoli
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolic Disease, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania,Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania,Molecular Biology Laboratory, Bios Biotech Multi-Diagnostic Health Center, Rome, Italy
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Wang Y, Wang JG. Genome-Wide Association Studies of Hypertension and Several Other Cardiovascular Diseases. Pulse (Basel) 2019; 6:169-186. [PMID: 31049317 PMCID: PMC6489084 DOI: 10.1159/000496150] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 12/07/2018] [Indexed: 12/30/2022] Open
Abstract
Genome-wide association studies (GWAS) have greatly expanded our understanding of the genetic architecture of cardiovascular diseases in the past decade. They have revealed hundreds of suggestive genetic loci that replicate known biological candidate genes and indicate the existence of a previously unsuspected new biology relevant to cardiovascular disorders. These data have been used successfully to create genetic risk scores that may improve risk prediction and the identification of susceptive individuals. Furthermore, these GWAS-identified novel pathways may herald a new era of novel drug development and stratification of patients. In this review, we will briefly summarize the literature on the candidate genes and signals discovered by GWAS on hypertension and coronary artery disease and discuss their implications on clinical medicine.
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Affiliation(s)
| | - Ji-Guang Wang
- Shanghai Key Laboratory of Hypertension, The Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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