ZSCAN25 methylation predicts seizures and severe alcohol withdrawal syndrome

References

• Academic ED SBIRT Research Collaborative. The impact of screening, brief intervention, and referral for treatment on emergency department patients’ alcohol use. Ann Emerg Med. 2007; 50:699–710. e696. doi: 10.1016/j.annemergmed.2007.06.486
   PubMed Web of Science ®Google Scholar
• Suen LW, Makam AN, Snyder HR, et al. National prevalence of alcohol and other substance use disorders among emergency department visits and hospitalizations: NHAMCS 2014–2018. J Gen Intern Med. 2022;37(10):2420–14. doi: 10.1007/s11606-021-07069-w
   PubMed Web of Science ®Google Scholar
• Carlson RW, Kumar NN, Wong-Mckinstry E, et al. Alcohol withdrawal syndrome. Crit Care Clin. 2012;28(4):549–585. doi: 10.1016/j.ccc.2012.07.004
   PubMed Web of Science ®Google Scholar
• Schuckit MA. Recognition and management of withdrawal delirium (delirium tremens). New England Journal of Medicine. 2014 Nov 27;371(22):2109–13.
   PubMed Web of Science ®Google Scholar
• Kosten TR, O’Connor PG. Management of drug and alcohol withdrawal. N Engl J Med. 2003;348(18):1786–1795. doi: 10.1056/NEJMra020617
   PubMed Web of Science ®Google Scholar
• Wood E, Albarqouni L, Tkachuk S, et al. Will this hospitalized patient develop severe alcohol withdrawal syndrome?: the rational clinical examination systematic review. JAMA. 2018;320(8):825–833. doi: 10.1001/jama.2018.10574
   PubMed Web of Science ®Google Scholar
• Maldonado JR, Sher Y, Ashouri JF, et al. The “prediction of alcohol withdrawal severity scale”(PAWSS): systematic literature review and pilot study of a new scale for the prediction of complicated alcohol withdrawal syndrome. Alcohol. 2014;48(4):375–390. doi: 10.1016/j.alcohol.2014.01.004
   PubMed Web of Science ®Google Scholar
• Wetterling T, Weber B, Depfenhart M, et al. DEVELOPMENT of a RATING SCALE to PREDICT the SEVERITY of ALCOHOL WITHDRAWAL SYNDROME. Alcohol Alcohol. 2006;41(6):611–615. doi: 10.1093/alcalc/agl068
   PubMed Web of Science ®Google Scholar
• Philibert R, Miller S, Noel A, et al. A four marker digital PCR toolkit for detecting heavy alcohol consumption and the effectiveness of its treatment. J Insur Med. 2019;48(1):90–102. doi: 10.17849/insm-48-1-1-1.1
   PubMedGoogle Scholar
• Miller S, Mills JA, Long J, et al. A comparison of the predictive power of DNA methylation with carbohydrate deficient transferrin for heavy alcohol consumption. Epigenetics. 2020;16(9):969–979. doi: 10.1080/15592294.2020.1834918
   PubMed Web of Science ®Google Scholar
• Lei M-K, Gibbons FX, Gerrard M, et al. Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing. Epigenetics. 2022;17(13):1–15. doi: 10.1080/15592294.2022.2100684
   PubMed Web of Science ®Google Scholar
• Beach SR, Ong ML, Gibbons FX, et al. Epigenetic and proteomic biomarkers of elevated alcohol use predict epigenetic aging and cell-type variation better than self-report. Genes. 2022;13(10):1888. doi: 10.3390/genes13101888
   PubMed Web of Science ®Google Scholar
• Isbell H, Fraser HF, Wikler A, et al. An experimental study of the etiology of “rum fits” and delirium tremens. Q J Stud Alcohol. 1955;16(1):1–33. doi: 10.15288/qjsa.1955.16.001
   PubMedGoogle Scholar
• Mendelson JH, La Dou J. Part 1. Background and experimental design. J Stud Alcohol Suppl. 1964;25(S2):1–13. doi: 10.15288/qjsas.1964.s2.001
   Google Scholar
• Turner RC, Lichstein PR, Peden JG, et al. Alcohol withdrawal syndromes. J Gen Intern Med. 1989;4(5):432–444. doi: 10.1007/BF02599697
   PubMed Web of Science ®Google Scholar
• Grüner Nielsen D, Andersen K, Søgaard Nielsen A, et al. Consistency between self-reported alcohol consumption and biological markers among patients with alcohol use disorder – a systematic review. Neuroscience & Biobehavioral Reviews. 2021;124:370–385. doi:10.1016/j.neubiorev.2021.02.006
   PubMed Web of Science ®Google Scholar
• Verheij C, Haagsma JA, Koch BCP, et al. Screening for hazardous alcohol use in the emergency department: comparison of phosphatidylethanol with the alcohol use disorders identification test and the timeline follow-back. Alcoholism Clin & Exp Res. 2022;46(12):2225–2235. doi: 10.1111/acer.14958
   PubMedGoogle Scholar
• Cabarcos P, Álvarez I, Tabernero MJ, et al. Determination of direct alcohol markers: a review. Anal Bioanaly Chem. 2015;407(17):4907–4925. doi: 10.1007/s00216-015-8701-7
   PubMed Web of Science ®Google Scholar
• Niemelä O, Alatalo P. Biomarkers of alcohol consumption and related liver disease. Scand J Clin Lab Invest. 2010;70(5):305–312. doi: 10.3109/00365513.2010.486442
   PubMed Web of Science ®Google Scholar
• Novak L, Soravia LM, Bünter A, et al. Alcohol biomarker Phosphatidylethanol as a predictor of the severity of alcohol withdrawal syndrome. Alcohol Alcohol. 2023;58(2):198–202. doi: 10.1093/alcalc/agac071
   PubMed Web of Science ®Google Scholar
• Helander A, Böttcher M, Dahmen N, et al. Elimination characteristics of the alcohol biomarker phosphatidylethanol (PEth) in blood during alcohol detoxification. Alcohol Alcohol. 2019;54(3):251–257. doi: 10.1093/alcalc/agz027
   PubMed Web of Science ®Google Scholar
• Helander A, Zheng Y. Molecular species of the alcohol biomarker phosphatidylethanol in human blood measured by LC-MS. Clin Chem. 2009;55(7):1395–1405. doi: 10.1373/clinchem.2008.120923
   PubMed Web of Science ®Google Scholar
• Karagülle D, Heberlein A, Wilhelm J, et al. Biological markers for alcohol withdrawal seizures: a retrospective analysis. Eur Addict Res. 2012;18(3):97–102. doi: 10.1159/000335273
   PubMed Web of Science ®Google Scholar
• Wetterling T, Kanitz R-D, Renner F, et al. Does carbohydrate-deficient transferrin predict the severity of alcohol withdrawal syndrome? Alcoholism Clin & Exp Res. 1998;22(5):1053–1056. doi: 10.1111/j.1530-0277.1998.tb03698.x
   PubMed Web of Science ®Google Scholar
• Moon H-W, Yun Y-M, Kim S, et al. Determination of carbohydrate-deficient transferrin levels by using capillary electrophoresis in a Korean population. Korean J Lab Med. 2010;30(5):477–484. doi: 10.3343/kjlm.2010.30.5.477
   PubMedGoogle Scholar
• Philibert R, Dogan M, Noel A, et al. Genome-wide and digital polymerase chain reaction epigenetic assessments of alcohol consumption. Am J Med Genet B Neuropsychiatr Genet. 2018;177(5):479–488. doi: 10.1002/ajmg.b.32636
   PubMed Web of Science ®Google Scholar
• Philibert R, Penaluna B, White T, et al. A pilot examination of the genome-wide DNA methylation signatures of subjects entering and exiting short-term alcohol dependence treatment programs. Epigenetics. 2014;9(9):1212–1219. doi: 10.4161/epi.32252
   PubMed Web of Science ®Google Scholar
• Pidsley R, Y Wong CC, Volta M, et al. A data-driven approach to preprocessing illumina 450K methylation array data. BMC Genomics. 2013;14(1):1–10. doi: 10.1186/1471-2164-14-293
   PubMedGoogle Scholar
• Triche JRT. FDb.InfiniumMethylation.hg19: annotation package for illumina infinium DNA methylation probes. R package version 2.2.0. 2014 [cited 2022 Jul 1]. Available from: https://bioconductor.org/packages/release/data/annotation/html/FDb.InfiniumMethylation.hg19.html
   Google Scholar
• Davis S, Du P, Bilke S, et al. methylumi: Handle Illumina methylation data. R package version 2.22.0. 2017 [cited 2022 Jul 1]. Available from: https://bioconductor.statistik.tu-dortmund.de/packages/3.5/bioc/html/methylumi.html
   Google Scholar
• Dogan M, Beach S, Simons R, et al. Blood-based biomarkers for predicting the risk for five-year incident coronary heart disease in the framingham heart study via machine learning. Genes. 2018;9(12):641. doi: 10.3390/genes9120641
   PubMed Web of Science ®Google Scholar
• Dogan MV, Grumbach IM, Michaelson JJ, et al. Integrated genetic and epigenetic prediction of coronary heart disease in the framingham heart study. PLoS One. 2018;13(1):e0190549. doi: 10.1371/journal.pone.0190549
   PubMed Web of Science ®Google Scholar
• Bonferroni C. Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commericiali di Firenze. 1936;8:3–62.
   Google Scholar
• Student, S. The probable error of a mean. Biometrika. 1908;6(1):1–25. doi: 10.2307/2331554
   Google Scholar
• Hamilton CM, Strader LC, Pratt JG, et al. The PhenX toolkit: get the most from your measures. Am J Epidemiol. 2011;174(3):253–260. doi: 10.1093/aje/kwr193
   PubMed Web of Science ®Google Scholar
• Salzman C, Balter M, Ellinwood E, et al. American Psychiatric Association task force on benzodiazepine dependency, toxicity, and abuse. Washington (DC): American Psychiatric Press; 1990.
   Google Scholar
• Philibert R, Dawes K, Philibert W, et al. Alcohol use intensity decreases in response to successful smoking cessation therapy. Genes. 2021;13(1):2. doi: 10.3390/genes13010002
   PubMed Web of Science ®Google Scholar
• Fang F, Andersen AM, Philibert R, et al. Epigenetic biomarkers for smoking cessation. Addiction Neuroscience. 2023;6:100079. doi:10.1016/j.addicn.2023.100079
   PubMedGoogle Scholar
• Schellenberg F, Wielders JP. Evaluation of capillary electrophoresis assay for CDT on SEBIA’s capillarys system: intra and inter laboratory precision, reference interval and cut-off. Clinica Chimica Acta. 2010;411:1888–1893. doi:10.1016/j.cca.2010.07.015 23–24
   PubMed Web of Science ®Google Scholar
• Team RC. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012. (ISBN 3-900051-07-0, 2014).
   Google Scholar
• Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinf. 2011;12(1):77. doi: 10.1186/1471-2105-12-77
   PubMed Web of Science ®Google Scholar
• Kent WJ, Sugnet CW, Furey TS, et al. The human genome browser at UCSC. Genome Res. 2002;12(6):996–1006. doi: 10.1101/gr.229102
   PubMed Web of Science ®Google Scholar
• Oks M, Cleven KL, Healy L, et al. The safety and utility of phenobarbital use for the treatment of severe alcohol withdrawal syndrome in the medical intensive care unit. J Intensive Care Med. 2020;35(9):844–850. doi: 10.1177/0885066618783947
   PubMed Web of Science ®Google Scholar
• Puck JM, Deschenes SM, Porter JC, et al. The interleukin-2 receptor γ chain maps to Xq13.1 and is mutated in X-linked severe combined immunodeficiency, SCIDX1. Hum Mol Genet. 1993;2(8):1099–1104. doi: 10.1093/hmg/2.8.1099
   PubMed Web of Science ®Google Scholar
• Lei M-K, Gibbons FX, Gerrard M, et al. Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing. Epigenetics. 2022;17(13):1991–2005. doi: 10.1080/15592294.2022.2100684
   PubMed Web of Science ®Google Scholar
• St George SM, Van Horn ML, Lawman HG, et al. Reliability of 24-hour dietary recalls as a measure of diet in African-American youth. J Acad Nutr Diet. 2016;116:1551–1559. doi:10.1016/j.jand.2016.05.011
   PubMed Web of Science ®Google Scholar
• Ravelli MN, Schoeller DA. Traditional self-reported dietary instruments are prone to inaccuracies and new approaches are needed. Front Nutr. 2020;7. doi: 10.3389/fnut.2020.00090
   PubMed Web of Science ®Google Scholar
• Mainerova B, Prasko J, Latalova K, et al. Alcohol withdrawal delirium-diagnosis, course and treatment. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2015;159(1):044–052. doi: 10.5507/bp.2013.089
   PubMed Web of Science ®Google Scholar