References
- Horvath S . DNA methylation age of human tissues and cell types. Genome Biol. 14(10), R115 (2013).
- Shah S , Mcrae AF , Marioni RE et al. Genetic and environmental exposures constrain epigenetic drift over the human life course. Genome Res. 24(11), 1725–1733 (2014).
- Aref-Eshghi E , Kerkhof J , Pedro VP et al. Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders. Am. J. Hum. Genet. 106(3), 356–370 (2020).
- Chen L , Saykin AJ , Yao B , Zhao F , (Adni) ASDNI . Multi-task deep autoencoder to predict Alzheimer’s disease progression using temporal DNA methylation data in peripheral blood. Comput. Struct. Biotechnol. J. 20, 5761–5774 (2022).
- Gunasekara CJ , Hannon E , Mackay H et al. A machine learning case-control classifier for schizophrenia based on DNA methylation in blood. Transl. Psychiatry 11(1), 412 (2021).
- Barbu MC , Shen X , Walker RM et al. Epigenetic prediction of major depressive disorder. Mol. Psychiatry 26(9), 5112–5123 (2021).
- Dunn CM , Sturdy C , Velasco C et al. Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project. Arthritis Rheumatol. 75(1), 28–40 (2023).
- Zhang X , Wang C , He D et al. Identification of DNA methylation-regulated genes as potential biomarkers for coronary heart disease via machine learning in the Framingham Heart Study. Clin. Epigenetics 14(1), 122 (2022).
- Lu AT , Quach A , Wilson JG et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY) 11(2), 303–327 (2019).
- Maas SCE , Vidaki A , Teumer A et al. Validating biomarkers and models for epigenetic inference of alcohol consumption from blood. Clin. Epigenetics 13(1), 198 (2021).
- Lee YC , Christensen JJ , Parnell LD et al. Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions. Front. Genet. 12, 783845 (2021).
- Lu AK , Hsieh S , Yang CT , Wang XY , Lin SH . DNA methylation signature of psychological resilience in young adults: constructing a methylation risk score using a machine learning method. Front. Genet. 13, 1046700 (2022).
- 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. 7(1), 50 (2022).
- Pedersen JS , Valen E , Velazquez AM et al. Genome-wide nucleosome map and cytosine methylation levels of an ancient human genome. Genome Res. 24(3), 454–466 (2014).
- Hack LM , Nishitani S , Knight AK et al. Epigenetic prediction of 17β-estradiol and relationship to trauma-related outcomes in women. Compr. Psychoneuroendocrinol 6, 100045 (2021).
- Nishitani S . Hacks_E2_predictor. https://github.com/snishit/Hacks_E2_predictor (2023).
- Shepherd R , Bretherton I , Pang K et al. Gender-affirming hormone therapy induces specific DNA methylation changes in blood. Clin. Epigenetics 14(1), 24 (2022).