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      Research on the circular RNA bioinformatics in patients with acute myocardial infarction

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          Abstract

          Objective

          Through the detection of circular RNA (circRNA) using expression profiling chips, we searched for circRNAs related to acute myocardial infarction (AMI) and explored their relationship and possible mechanisms with AMI.

          Method

          The study subjects included 3 AMI patients and 3 controls, and circRNA expression profiling analysis was performed using a microarray gene chip to identify circRNAs with large differences in expression between groups and to construct a circRNA‐miRNA network.

          Results

          Compared with the control group, there were 650 differentially expressed circRNAs found in AMI patients ( P < .05, fold change > 2), including 535 up‐regulated circRNAs, such as hsa_circ_0050908, hsa_circRNA4010‐22, hsa_circ_0081241, hsa_circ_0010551, hsa_circRNA4010‐20, hsa_circRNA14702, hsa_circ_0115392, has_circRNA1825‐44, has_circRNA8493‐7, and hsa_circ_0025097. Furthermore, there were 115 down‐regulated circRNAs, such as hsa_circ_0066439, hsa_circ_0054211, hsa_circ_0095920, hsa_circ_0122984, hsa_circ_0113067, hsa_circ_0039155, hsa_circRNA4014‐45, hsa_circ_0122979, hsa_circ_0059665, and hsa_circ_0009319. The circRNAs hsa_circ_0066439, hsa_circ_0081241, and hsa_circ_0122984 can regulate multiple signal pathways to participate in the AMI process through hsa‐miR‐1254, hsa‐miR‐328‐5p, and other miRNAs. In addition, the expression of circRNA‐miRNA in peripheral blood is related to the network. Differentially expressed circRNAs are involved in chromatin organization, chromatin‐modifying enzymes, signal transduction, lysine degradation, the mitogen‐activated protein kinase (MAPK) signaling pathway, focal adhesion, and a variety of other pathways, such as myocardial infarction, coronary heart disease, hypertension, and other diseases. The gene ontology analysis results show that molecular function mainly involves binding and molecular structural activity, whereas the biological process mainly involves a single biological process, a cellular component for organization, and a cellular process, and the cellular component mainly involves a protein complex, an extracellular matrix, and a membrane.

          Conclusion

          circRNA and microRNA interact to participate in the development of AMI. circRNA may be involved in the pathogenesis of AMI.

          Abstract

          650 circRNAs are differentially expressed in AMI disease, and the interaction between circRNA and miRNA is involved in the occurrence and development of AMI. Among them, hsa_circ_0066439, hsa_circ_0081241, hsa_circ_0122984, and other highly different circRNAs (hsa_circ_0043563, hsa_circ_0119137, hsa_circ_0025097, hsa_circ_0106804, hsa_circ_0085214, and hsa_circ_0028302) may regulate multiple signaling pathways by combining with miR‐328‐5p, and then participate in the pathogenesis of AMI, providing a new breakthrough point for AMI diagnosis or targeted therapy.

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          Most cited references29

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          Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017

          Summary Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries—Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5–23·9), representing an additional 7·61 million (7·20–8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0–8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0–24·0) and the death rate by 31·8% (30·1–33·3). Total deaths from injuries increased by 2·3% (0·5–4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2–15·1) to 57·9 deaths (55·9–59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000–289 000) globally in 2007 to 352 000 (334 000–363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8–148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2–40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2–36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990—neonatal disorders, lower respiratory infections, and diarrhoeal diseases—were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Funding Bill & Melinda Gates Foundation.
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            Circular RNAs are a large class of animal RNAs with regulatory potency.

            Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.
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              Network biology: understanding the cell's functional organization.

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                Author and article information

                Contributors
                271101521@qq.com
                Journal
                J Clin Lab Anal
                J Clin Lab Anal
                10.1002/(ISSN)1098-2825
                JCLA
                Journal of Clinical Laboratory Analysis
                John Wiley and Sons Inc. (Hoboken )
                0887-8013
                1098-2825
                15 October 2020
                February 2021
                : 35
                : 2 ( doiID: 10.1002/jcla.v35.2 )
                : e23621
                Affiliations
                [ 1 ] Department of Clinical Laboratory Nanning Second People's Hospital the Third Affiliated Hospital of Guangxi Medical University Nanning Guangxi China
                [ 2 ] Department of Clinical Laboratory Guangxi Hospital Of Traditional Chinese Medicine The First Affiliated Hospital of Guangxi University of Chinese Medicine Nanning Guangxi China
                [ 3 ] Emergency cardiothoracic Department Nanning Second People's Hospital the Third Affiliated Hospital of Guangxi Medical University, Nanning Guangxi China
                Author notes
                [*] [* ] Correspondence

                Yinghua Tang, Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, No. 89‐9 Dongge Road, Nanning 530023, Guangxi, China.

                Email: 271101521@ 123456qq.com

                Author information
                https://orcid.org/0000-0003-4425-1592
                https://orcid.org/0000-0002-5655-9650
                Article
                JCLA23621
                10.1002/jcla.23621
                7891515
                33063376
                020b16b7-8728-4233-9632-cae003df392f
                © 2020 The Authors. Journal of Clinical Laboratory Analysis Published by Wiley Periodicals LLC

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 August 2020
                : 16 September 2020
                : 18 September 2020
                Page count
                Figures: 7, Tables: 4, Pages: 26, Words: 17463
                Funding
                Funded by: Health and Family Planning Commission of the Guangxi Zhuang Autonomous Region
                Award ID: Z20170797
                Funded by: Nanning science and Technology Bureau
                Award ID: 20193103
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                February 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.7 mode:remove_FC converted:18.02.2021

                Clinical chemistry
                acute myocardial infarction,bioinformatics,circrna
                Clinical chemistry
                acute myocardial infarction, bioinformatics, circrna

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