1,633
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Pruning and thresholding approach for methylation risk scores in multi-ancestry populations

, , , , , , , , & ORCID Icon show all
Article: 2187172 | Received 18 Oct 2022, Accepted 07 Feb 2023, Published online: 12 Mar 2023

References

  • Berger SL, Kouzarides T, Shiekhattar R, et al. An operational definition of epigenetics: figure 1. Genes Deve. Apr 1 2009;23(7):781–14.
  • Rakyan VK, Down TA, Balding DJ, et al. Epigenome-wide association studies for common human diseases. Nat Rev Genet. 2011 12 07;12(8):529–541.
  • Wei S, Tao J, Xu J, et al. Ten Years of EWAS. Adv Sci. Aug 11 2021;8(20):e2100727. DOI:10.1002/advs.202100727
  • Wahl S, Drong A, Lehne B, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature. Jan 5 2017;541(7635):81–86. DOI:10.1038/nature20784
  • McCartney DL, Hillary RF, Stevenson AJ, et al. Epigenetic prediction of complex traits and death. Genome Bio. 2018;19(1):136. DOI:10.1186/s13059-018-1514-1
  • Heiss JA, Brenner H. Epigenome-wide discovery and evaluation of leukocyte DNA methylation markers for the detection of colorectal cancer in a screening setting. Clin Epigenetics. 2017;9(1):24.
  • Ka G, Shaikhibrahim Z, Ocker M, et al. Targeting epigenetic regulators for cancer therapy: modulation of bromodomain proteins, methyltransferases, demethylases, and microRnas. Expert Opin Ther Targets. 2016 Jul;20(7):783–799. DOI:10.1517/14728222.2016.1134490.
  • Krushkal J, Silvers T, Reinhold WC, et al. Epigenome-wide DNA methylation analysis of small cell lung cancer cell lines suggests potential chemotherapy targets. Clin Epigenetics. 2020;12(1):93. DOI:10.1186/s13148-020-00876-8
  • Guan Z, Yu H, Cuk K, et al. Whole-blood DNA methylation markers in early detection of breast cancer: a systematic literature review. Cancer Epidemiol Biomarkers Prev. 2019 Mar;28(3):496–505.
  • Hüls A, Czamara D. Methodological challenges in constructing DNA methylation risk scores. Epigenetics. 2020 Jan-Feb;15(1–2):1–11.
  • Wray NR, Lee SH, Mehta D, et al. Research review: polygenic methods and their application to psychiatric traits. J Child Psychol Psychiatry. 2014 Oct;55(10):1068–1087.
  • Martin EM, Fry RC. Environmental influences on the epigenome: exposure- associated DNA methylation in human populations. Ann Rev Public Health. 2018 01 04;39(1):309–333.
  • Notterman DA, Mitchell C. Epigenetics and understanding the impact of social determinants of health. Pediatr Clin North Am. 2015 Oct;62(5):1227–1240.
  • Borrell LN, Elhawary JR, Fuentes-Afflick E, et al. Race and genetic ancestry in medicine — a time for reckoning with racism. N Engl J Med. 2021 04 02;384(5):474–480.
  • Cronjé HT, Elliott HR, Nienaber-Rousseau C, et al. Replication and expansion of epigenome-wide association literature in a black South African population. Clin Epigenetics. 2020 07 01;12(1):6.
  • Khera AV, Chaffin M, Zekavat SM, et al. Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction. Circulation. Mar 26 2019;139(13):1593–1602. DOI:10.1161/circulationaha.118.035658
  • Martin AR, Kanai M, Kamatani Y, et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nature Genet. 2019 01 04;51(4):584–591.
  • Horvath S. DNA methylation age of human tissues and cell types. Genome Bio. 2013;14(10):R115. 10/2110/21/accepted 2013 10.1186/gb-2013-14-10-r115.
  • Thompson M, Hill BL, Rakocz N, et al. Methylation risk scores are associated with a collection of phenotypes within electronic health record systems. NPJ Genom Med. 2022 25 08;7(1):50.
  • Goldstein BA, Yang L, Salfati E, et al. Contemporary considerations for constructing a genetic risk score: an empirical approach. Genet Epidemiol. 2015 Sep;39(6):439–445.
  • Euesden J, Lewis CM, O’reilly PF. Prsice: polygenic risk score software. Bioinformatics. 2015;31(9):1466–1468.
  • Gatev E, Gladish N, Mostafavi S, et al. DNA methylation array data analysis for co-methylated regions. Bioinformatics. May 1 2020;36(9):2675–2683. DOI:10.1093/bioinformatics/btaa049.
  • Shah S, Bonder MJ, Marioni RE, et al. Improving phenotypic prediction by combining genetic and epigenetic associations. Am J Hum Genet. Jul 2 2015;97(1):75–85. DOI:10.1016/j.ajhg.2015.05.014
  • Odintsova VV, Rebattu V, Fa H, et al. Predicting complex traits and exposures from polygenic scores and blood and buccal DNA methylation profiles. Front Psychiatry. 2021;12:688464.
  • Wu J, Pfeiffer RM, Gail MH. Strategies for developing prediction models from genome-wide association studies. Genet Epidemiol. 2013 Dec;37(8):768–777.
  • Privé F, Vilhjálmsson BJ, Aschard H, et al. Making the most of clumping and thresholding for polygenic scores. Am J Hum Genet. 2019;105(6):1213–1221.
  • Choi SW, O’reilly PF. Prsice-2: polygenic risk score software for biobank-scale data. Gigascience. 2019;8(7). DOI:10.1093/gigascience/giz082
  • Vanker A, Barnett W, Workman L, et al. Early-life exposure to indoor air pollution or tobacco smoke and lower respiratory tract illness and wheezing in African infants: a longitudinal birth cohort study. Lancet Planet Health. 2017 Nov;1(8):e328–336.
  • Leek JT, Johnson WE, Parker HS, et al. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. Mar 15 2012;28(6):882–883.
  • Ritchie ME, Phipson B, Wu D, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. Apr 20 2015;43(7):e47. DOI:10.1093/nar/gkv007
  • Barfield RT, Almli LM, Kilaru V, et al. Accounting for population stratification in DNA methylation studies. Genet Epidemiol. 2014 Apr;38(3):231–241. DOI:10.1002/gepi.21789.
  • Teschendorff AE, Breeze CE, Zheng SC, et al. A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies. BMC Bioinf. Feb 13 2017;18(1):105.
  • Zar HJ, Barnett W, Myer L, et al. Investigating the early-life determinants of illness in Africa: the drakenstein child health study. Thorax. 2015 Jun;70(6):592–594.
  • Stein DJ, Koen N, Donald KA, et al. Investigating the psychosocial determinants of child health in Africa: the drakenstein child health study. J Neurosci Methods. Aug 30 2015;252:27–35. DOI:10.1016/j.jneumeth.2015.03.016.
  • Hüls A, Wedderburn CJ, Groenewold NA, et al. Newborn differential DNA methylation and subcortical brain volumes as early signs of severe neurodevelopmental delay in a South African birth cohort study. World J Biol Psychiatry. 1–12. Jan 12 2022. DOI:10.1080/15622975.2021.2016955
  • Sikdar S, Joehanes R, Joubert BR, et al. Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking. Epigenomics. 2019 Oct;11(13):1487–1500.
  • Reese SE, Zhao S, Wu MC, et al. DNA methylation score as a biomarker in newborns for sustained maternal smoking during pregnancy. Environ Health Perspect. 2017 Apr;125(4):760–766.
  • Joubert BR, Felix Janine F, Yousefi P, et al. DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis. Am J Hum Genet. 2016;98(4):680–696.
  • Richmond RC, Suderman M, Langdon R, et al. DNA methylation as a marker for prenatal smoke exposure in adults. Int J Epidemiol. 2018;47(4):1120–1130.
  • Yu H, Raut JR, Schöttker B, et al. Individual and joint contributions of genetic and methylation risk scores for enhancing lung cancer risk stratification: data from a population-based cohort in Germany. Clin Epigenetics. Jun 18 2020;12(1):89.
  • Westerman K, Fernández-Sanlés A, Patil P, et al. Epigenomic assessment of cardiovascular disease risk and interactions with traditional risk metrics. J Am Heart Assoc. Apr 21 2020;9(8):e015299. DOI:10.1161/jaha.119.015299
  • Guan Z, Raut JR, Weigl K, et al. Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk. Mol Oncol. 2020;14(1):42–53. DOI:10.1002/1878-0261.12594
  • Grant CD, Jafari N, Hou L, et al. A longitudinal study of DNA methylation as a potential mediator of age-related diabetes risk. Geroscience. 2017 Dec;39(5–6):475–489.
  • García-Calzón S, Perfilyev A, Martinell M, et al. Epigenetic markers associated with metformin response and intolerance in drug-naïve patients with type 2 diabetes. Sci, Trans Med. Sep 16 2020;12(561). DOI:10.1126/scitranslmed.aaz1803
  • Deng Y, Wan H, Tian J, et al. CpG-methylation-based risk score predicts progression in colorectal cancer. Epigenomics. 2020 Apr;12(7):605–615.
  • . Kilanowski A, Chen J, Everson T, et al. Methylation risk scores for childhood aeroallergen sensitization: results from the {LISA} birth cohor. Authorea. Nov2021;doi:10.22541/au.163620398.85835627/v1
  • Pattee J, Pan W, Zhang D. Penalized regression and model selection methods for polygenic scores on summary statistics. PLoS Comput Biol. 2020 Oct;16(10):e1008271.
  • VanderWeele TJ, Robinson WR. On the causal interpretation of race in regressions adjusting for confounding and mediating variables. Epidemiology. 2014 Jul;25(4):473–484.
  • Gibson G, Barsh GS. On the utilization of polygenic risk scores for therapeutic targeting. PLoS Genet. 2019 Apr;15(4):e1008060.