{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T03:01:29Z","timestamp":1792119689729,"version":"4.4.0"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T00:00:00Z","timestamp":1640217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["1DP1DA048968-01"],"award-info":[{"award-number":["1DP1DA048968-01"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006444","name":"University of Maryland, College Park","doi-asserted-by":"publisher","award":["MPower Brain Health and Human Performance seed grant"],"award-info":[{"award-number":["MPower Brain Health and Human Performance seed grant"]}],"id":[{"id":"10.13039\/100006444","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Genome-wide association studies (GWAS) have identified and reproduced thousands of diseases associated loci, but many of them are not directly interpretable due to the strong linkage disequilibrium among variants. Transcriptome-wide association studies (TWAS) incorporated expression quantitative trait loci (eQTL) cohorts as a reference panel to detect associations with the phenotype at the gene level and have been gaining popularity in recent years. For nicotine addiction, several important susceptible genetic variants were identified by GWAS, but TWAS that detected genes associated with nicotine addiction and unveiled the underlying molecular mechanism were still lacking. In this study, we used eQTL data from the Genotype-Tissue Expression (GTEx) consortium as a reference panel to conduct tissue-specific TWAS on cigarettes per day (CPD) over thirteen brain tissues in two large cohorts: UK Biobank (UKBB; number of participants (N) = 142,202) and the GWAS &amp; Sequencing Consortium of Alcohol and Nicotine use (GSCAN; N = 143,210), then meta-analyzing the results across tissues while considering the heterogeneity across tissues. We identified three major clusters of genes with different meta-patterns across tissues consistent in both cohorts, including homogenous genes associated with CPD in all brain tissues; partially homogeneous genes associated with CPD in cortex, cerebellum, and hippocampus tissues; and, lastly, the tissue-specific genes associated with CPD in only a few specific brain tissues. Downstream enrichment analyses on each gene cluster identified unique biological pathways associated with CPD and provided important biological insights into the regulatory mechanism of nicotine dependence in the brain.<\/jats:p>","DOI":"10.3390\/genes13010037","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T10:16:18Z","timestamp":1640254578000},"page":"37","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Meta-Analysis of Transcriptome-Wide Association Studies across 13 Brain Tissues Identified Novel Clusters of Genes Associated with Nicotine Addiction"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhenyao","family":"Ye","sequence":"first","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"},{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Mo","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"},{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongjie","family":"Ke","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Yan","sequence":"additional","affiliation":[{"name":"Irving Medical Center, Department of Obstetrics & Gynecology, Columbia University, New York, NY 10032, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chixiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Kochunov","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L. Elliot","family":"Hong","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4920-4744","authenticated-orcid":false,"given":"Braxton D.","family":"Mitchell","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Chen","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"},{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3605-0811","authenticated-orcid":false,"given":"Tianzhou","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1038\/s42003-018-0261-x","article-title":"A scientometric review of genome-wide association studies","volume":"2","author":"Mills","year":"2019","journal-title":"Commun. Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1038\/s41576-019-0127-1","article-title":"Benefits and limitations of genome-wide association studies","volume":"20","author":"Tam","year":"2019","journal-title":"Nat. Rev. Genet."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ajhg.2017.06.005","article-title":"10 Years of GWAS discovery: Biology, function, and translation","volume":"101","author":"Visscher","year":"2017","journal-title":"Am. J. Hum. Genet."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.ajhg.2011.11.029","article-title":"Five years of GWAS discovery","volume":"90","author":"Visscher","year":"2012","journal-title":"Am. J. Hum. Genet."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1126\/science.1156409","article-title":"Genetic mapping in human disease","volume":"322","author":"Altshuler","year":"2008","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/ng.2653","article-title":"The genotype-tissue expression (GTEx) project","volume":"45","author":"Lonsdale","year":"2013","journal-title":"Nat. Genet."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1038\/s41588-019-0385-z","article-title":"Opportunities and challenges for transcriptome-wide association studies","volume":"51","author":"Wainberg","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1038\/ng.3367","article-title":"A gene-based association method for mapping traits using reference transcriptome data","volume":"47","author":"Gamazon","year":"2015","journal-title":"Nat. Genet."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"141","DOI":"10.15302\/J-QB-020-0228","article-title":"Transcriptome wide association studies: General framework and methods","volume":"9","author":"Xie","year":"2021","journal-title":"Quant. Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s40484-020-0207-4","article-title":"Transcriptome-wide association studies: A view from Mendelian randomization","volume":"9","author":"Zhu","year":"2020","journal-title":"Quant. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.1038\/s41467-018-03621-1","article-title":"Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics","volume":"9","author":"Barbeira","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Barbeira, A.N., Pividori, M., Zheng, J., Wheeler, H.E., Nicolae, D.L., and Im, H.K. (2019). Integrating predicted transcriptome from multiple tissues improves association detection. PLoS Genet., 15.","DOI":"10.1371\/journal.pgen.1007889"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1038\/s41588-019-0345-7","article-title":"A statistical framework for cross-tissue transcriptome-wide association analysis","volume":"51","author":"Hu","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1017\/S0033291798008022","article-title":"A population-based twin study in women of smoking initiation and nicotine dependence","volume":"29","author":"Kendler","year":"1999","journal-title":"Psychol. Med."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/s10519-004-1327-8","article-title":"Heritability of smoking initiation and nicotine dependence","volume":"35","author":"Vink","year":"2005","journal-title":"Behav. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1016\/j.tins.2016.10.005","article-title":"The CHRNA5\u2013A3\u2013B4 gene cluster and smoking: From discovery to therapeutics","volume":"39","author":"Lassi","year":"2016","journal-title":"Trends Neurosci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2212","DOI":"10.1038\/s41380-020-0702-z","article-title":"Genome-wide association meta-analysis of nicotine metabolism and cigarette consumption measures in smokers of European descent","volume":"26","author":"Buchwald","year":"2021","journal-title":"Mol. Psychiatry"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5562","DOI":"10.1038\/s41467-020-19265-z","article-title":"Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits","volume":"11","author":"Quach","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1038\/s41398-021-01231-y","article-title":"Multi-omic and multi-species meta-analyses of nicotine consumption","volume":"11","author":"Palmer","year":"2021","journal-title":"Transl. Psychiatry"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1534\/genetics.117.300435","article-title":"Efficient prioritization of multiple causal eQTL variants via sparse polygenic modeling","volume":"207","author":"Nariai","year":"2017","journal-title":"Genetics"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3777","DOI":"10.1093\/nar\/gkr1255","article-title":"Comprehensive literature review and statistical considerations for GWAS meta-analysis","volume":"40","author":"Begum","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3785","DOI":"10.1093\/nar\/gkr1265","article-title":"Comprehensive literature review and statistical considerations for microarray meta-analysis","volume":"40","author":"Tseng","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Fisher, R.A. (1992). Statistical methods for research workers. Breakthroughs in Statistics, Springer.","DOI":"10.1007\/978-1-4612-4380-9_6"},{"key":"ref_24","unstructured":"Stouffer, S.A., Suchman, E.A., DeVinney, L.C., Star, S.A., and Williams, R.M. (1949). The American Soldier: Adjustment during Army Life. (Studies in Social Psychology in World War II), Volume 1, Princeton University Press."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1214\/10-AOAS393","article-title":"An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies","volume":"5","author":"Li","year":"2011","journal-title":"Ann. Appl. Stat."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1111\/rssc.12199","article-title":"Biomarker detection and categorization in ribonucleic acid sequencing meta-analysis using bayesian hierarchical models","volume":"66","author":"Ma","year":"2017","journal-title":"J. R. Stat. Soc. Ser. C Appl. Stat."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"651546","DOI":"10.3389\/fgene.2021.651546","article-title":"Biomarker categorization in transcriptomic meta-analysis by concordant patterns with application to Pan-cancer studies","volume":"12","author":"Ye","year":"2021","journal-title":"Front. Genet."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., and Landray, M. (2015). UK biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med., 12.","DOI":"10.1371\/journal.pmed.1001779"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1038\/s41588-018-0307-5","article-title":"Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use","volume":"51","author":"Liu","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5302","DOI":"10.1038\/s41467-020-18489-3","article-title":"Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals","volume":"11","author":"Xu","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2392","DOI":"10.1038\/s41380-018-0313-0","article-title":"Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci","volume":"25","author":"Erzurumluoglu","year":"2020","journal-title":"Mol. Psychiatry"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"s13742-015-0047-8","DOI":"10.1186\/s13742-015-0047-8","article-title":"Second-generation PLINK: Rising to the challenge of larger and richer datasets","volume":"4","author":"Chang","year":"2015","journal-title":"Gigascience"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene ontology: Tool for the unification of biology","volume":"25","author":"Ashburner","year":"2000","journal-title":"Nat. Genet."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"D353","DOI":"10.1093\/nar\/gkw1092","article-title":"KEGG: New perspectives on genomes, pathways, diseases and drugs","volume":"45","author":"Kanehisa","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"D481","DOI":"10.1093\/nar\/gkv1351","article-title":"The reactome pathway knowledgebase","volume":"44","author":"Fabregat","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1128\/MMBR.00040-05","article-title":"Nuclear ADP-ribosylation reactions in mammalian cells: Where are we today and where are we going?","volume":"70","author":"Hassa","year":"2006","journal-title":"Microbiol. Mol. Biol. Rev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/aps.2009.64","article-title":"Nicotinic acetylcholine receptor-mediated calcium signaling in the nervous system","volume":"30","author":"Shen","year":"2009","journal-title":"Acta Pharmacol. Sin."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"S283","DOI":"10.1038\/sj.bjp.0707510","article-title":"Presynaptic nicotinic receptors: A dynamic and diverse cholinergic filter of striatal dopamine neurotransmission","volume":"153","author":"Exley","year":"2008","journal-title":"Br. J. Pharmacol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1186\/s13039-014-0058-7","article-title":"Smoking-induced chromosomal segregation anomalies identified by FISH analysis of sperm","volume":"7","author":"Pereira","year":"2014","journal-title":"Mol. Cytogenet."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"10508","DOI":"10.1523\/JNEUROSCI.3353-07.2007","article-title":"Nicotine regulates multiple synaptic proteins by inhibiting proteasomal activity","volume":"27","author":"Rezvani","year":"2007","journal-title":"J. Neurosci."},{"key":"ref_41","first-page":"1","article-title":"Magnesium and zinc involvement in tobacco addiction","volume":"S2","author":"Nechifor","year":"2012","journal-title":"J. Addict. Res. Ther."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1652","DOI":"10.1111\/jnc.15356","article-title":"Addiction-related neuroadaptations following chronic nicotine exposure","volume":"157","author":"Wills","year":"2021","journal-title":"J. Neurochem."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Tai, H.-C. (2010). Characterization of the Brain Proteasome and Its Interacting Proteins and Their Regulation by Neuronal Activity, California Institute of Technology.","DOI":"10.3389\/fnmol.2010.00012"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1176\/appi.ajp.157.4.632","article-title":"High levels of dopamine activity in the basal ganglia of cigarette smokers","volume":"157","author":"Salokangas","year":"2000","journal-title":"Am. J. Psychiatry"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Lee, S.-H., Ahn, W.-Y., Seweryn, M., and Sadee, W. (2018). Combined genetic influence of the nicotinic receptor gene cluster CHRNA5\/A3\/B4 on nicotine dependence. BMC Genom., 19.","DOI":"10.1186\/s12864-018-5219-3"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1038\/mp.2014.159","article-title":"Transcriptome organization for chronic alcohol abuse in human brain","volume":"20","author":"Farris","year":"2015","journal-title":"Mol. Psychiatry"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1016\/S2215-0366(20)30339-4","article-title":"A large-scale genome-wide association study meta-analysis of cannabis use disorder","volume":"7","author":"Johnson","year":"2020","journal-title":"Lancet Psychiatry"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Li, B., Veturi, Y., Verma, A., Bradford, Y., Daar, E.S., Gulick, R.M., Riddler, S.A., Robbins, G.K., Lennox, J.L., and Haas, D.W. (2021). Tissue specificity-aware TWAS (TSA-TWAS) framework identifies novel associations with metabolic, immunologic, and virologic traits in HIV-positive adults. PLoS Genet., 17.","DOI":"10.1371\/journal.pgen.1009464"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1862","DOI":"10.1002\/ijc.32771","article-title":"Transcriptome-wide association study reveals candidate causal genes for lung cancer","volume":"146","author":"Li","year":"2020","journal-title":"Int. J. Cancer"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1002\/gepi.22274","article-title":"Some statistical consideration in transcriptome-wide association studies","volume":"44","author":"Xue","year":"2020","journal-title":"Genet. Epidemiol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1038\/ng.3538","article-title":"Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets","volume":"48","author":"Zhu","year":"2016","journal-title":"Nat. Genet."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1038\/s41588-019-0367-1","article-title":"Probabilistic fine-mapping of transcriptome-wide association studies","volume":"51","author":"Mancuso","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1093\/aje\/kwx246","article-title":"Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population","volume":"186","author":"Fry","year":"2017","journal-title":"Am. J. Epidemiol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.hlpt.2012.07.003","article-title":"UK Biobank: Current status and what it means for epidemiology","volume":"1","author":"Allen","year":"2012","journal-title":"Health Policy Technol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1016\/S0140-6736(12)60404-8","article-title":"What makes UK Biobank special?","volume":"379","author":"Collins","year":"2012","journal-title":"Lancet"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1007\/s11682-014-9297-9","article-title":"Who wants a free brain scan? Assessing and correcting for recruitment biases in a population-based sMRI pilot study","volume":"9","author":"Ganguli","year":"2015","journal-title":"Brain Imaging Behav."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1093\/aje\/kwq084","article-title":"Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial","volume":"172","author":"Cole","year":"2010","journal-title":"Am. J. Epidemiol."}],"container-title":["Genes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4425\/13\/1\/37\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:52:08Z","timestamp":1760169128000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4425\/13\/1\/37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,23]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["genes13010037"],"URL":"https:\/\/doi.org\/10.3390\/genes13010037","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202111.0386.v1","asserted-by":"object"}]},"ISSN":["2073-4425"],"issn-type":[{"value":"2073-4425","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,23]]}}}