medigraphic.com
ISSN 2448-8011 (Digital)
Revista de Divulgación del INSTITUTO DE MEDICINA FORENSE de la UNIVERSIDAD VERACRUZANA

2019, Número 1

<< Anterior Siguiente >>

Rev Mex Med Forense 2019; 4 (1)


Predicción de edad mediante la metilación del ADN

Sandoval RA, Lagunes TTJ, Barrientos SC

Idioma: Español
Referencias bibliográficas: 30
Paginas: 43-52
Archivo PDF: 492.45 Kb.


RESUMEN

La predicción de edad es una parte fundamental para la ciencia forense; con la determinación de esta se puede establecer un perfil más estrecho para la búsqueda de sospechosos o para la identificación de un cadáver. En diversos artículos basados en el estudio del genoma se ha informado que la metilación del ADN promete ser un marcador de alta precisión para la estimación de edad cronológica. En el presente estudio se analizaron artículos que diseñaron modelos experimentales de predicción de edad por medio de los patrones de metilación de genes característicos relacionados por la literatura al envejecimiento. A pesar de ser pocos los análisis que se han enfocado en la metilación del ADN para determinar la edad, en la gran mayoría de ellos se obtuvieron resultados favorables con una estadística de regresión multivariante; se estudiaron algunos de los cientos de sitios CpG; aunque un mayor número de sitios CpG pueden proporcionar una mayor precisión que un menor número de ellos, no se puede aplicar dicho enfoque dado que las muestras comúnmente encontradas en la escena del crimen suelen ser limitadas.


REFERENCIAS (EN ESTE ARTÍCULO)

  1. Vidaki, et al., ADN methylation-based forensic age prediction using artificial neural networks and next generation sequencing, Forensic Sci. Int. Genet. (2017), http://dx.doi.org/10.1016/j.fsigen.2017.02.009

  2. Bell, JT., et al. (2012). Epigenome-Wide Scans Identify Differentially Methylated Regions for Age and Age-Related Phenotypes in a Healthy Ageing Population. PLoS GENETICS, 8, pp. 1-12.

  3. Bjornsson, HT., et al. (2008). Intra-individual Change Over Time in ADN Methylation With Familial Clustering. American Medical Association, 299, pp. 2877-2883.

  4. Bocklandt, S., et al. (2011). Epigenetic Predictor of Age. PLoS one, 6, pp. 1-6.

  5. Bork, S., et al. (2010). ADN methylation pattern changes upon long-term culture and aging of human mesenchymal stromal cells. Aging Cell, 9, pp. 54-63.

  6. Eipel, M., et al. (2016). Epigenetic age predictions based on buccal swabs are more precise in combination with cell type‐specific ADN methylation signatures. AGING, 8, pp. 1034-1044.

  7. Garagnani, P., et al. (2012). Methylation of ELOVL2 gene as a new epigenetic marker of age. Aging Cell, 11, pp. 1132-1134.

  8. Hamano, Y., Manabe, S., Morimoto, C., Fujimoto, S., & Tamaki, Keiji.. (2017). Forensic age prediction for saliva samples using methylationsensitive high resolution melting: exploratory application for cigarette butts. Scientific Reports, 7, pp. 1-8.

  9. Hernandez, DG., et al. (2011). Distinct ADN methylation changes highly correlated with chronological age in the human brain. Human Molecular Genetics, 20, pp. 1164-1172.

  10. Heyn, H., et al. (2012). Distinct ADN methylomes of newborns and centenarians. PNAS, 109, pp. 10522-10527.

  11. Hussain Alghanim, Joana Antunes, Deborah Soares Bispo Santos Silva, Clarice Sampaio Alho, Kuppareddi Balamurugan, Bruce McCord, Detection and evaluation of ADN methylation markers found at SCGN and KLF14 loci to estimate human age, Forensic Science International: Geneticshttp://dx.doi.org/10.1016/j.fsigen.2017.07.011

  12. Jenkins, TG., Aston, KI., Cairns, B., Smith, A., & Carrell, DT. (2018). Paternal germ line aging: ADN methylation age prediction from human sperm. BMC Genomics, 19, pp. 1-10.

  13. Jung, SE., Shin, KJ., & Lee, Hwan, YL. (2017). ADN methylation-based age prediction from various tissues and body fluids. BMB Reports, 50, 546-553.

  14. Kayser, M. (2015). Forensic ADN Phenotyping: Predicting human appearance from crime scene material for investigative purposes$. Forensic Science International: Genetics, 18, pp. 33-48.

  15. Koch, CM., & Wagner, W. (2011). Epigenetic‐aging‐signature to determine age in different tissues. AGING, 3, pp. 1-10.

  16. Marioni, RE., Belsky, DW., Deary, IJ., & Wagner, W. (2018). Association of facial ageing with ADN methylation and epigenetic age predictions. Clinical Epigenetics, 10, pp. 1-3.

  17. McEwen, LM., et al. (2018). Systematic evaluation of ADN methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array. Clinical Epigenetics, 10, pp. 1-9.

  18. Meissner, C., & Ritz-Timme. (2010). Molecular pathology and age estimation§. Forensic Science International, 203, pp. 34-43.

  19. Murgatroyd, C., Wu, Y., Bockmühl, Y., & Spengler, D. (2010). The Janus face of ADN methylation in aging. AGING, 2, pp. 107-110.

  20. Park, JL., et al. (2016). Identification and evaluation of age-correlated ADN methylation markers for forensic use. Forensic Science International: Genetics, 23, pp. 64-70.

  21. Rakyan, VK., et al. (2018). An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs). Genome Research, 27, pp. 1518-1529.

  22. Sae, RH., Kyoung, JS., Sang, EJ., Eun, HL., & Hwan, YL. (2018). Platform-independent models for age prediction using ADN methylation data. Forensic Science International: Genetics, 38, pp. 39-47.

  23. Sae, RH., Sang, EJ., Eun HL., Kyoung, JS., Woo, IY., & Hwan YL. (2017). ADN methylation-based age prediction from saliva: High age predictability by combination of 7 CpG markers. Forensic Science International: Genetics, 29, pp. 118-125.

  24. Shao, HL., Long, CX., Kun, M., Rong, ZY., & Dai, XH. (2014). Isolation and identification of age-related ADN methylation markers for forensic age-prediction. Forensic Science International: Genetics, 11, pp. 117-125.

  25. Silva, D., Antunes, J., Balamurugan, K., Duncan, G., Alho, CS., & McCord, B. (2016). Developmental validation studies of epigenetic ADN methylation markers for the detection of blood, semen and saliva samples. Forensic Science International: Genetics, 23, pp. 55-63.

  26. Steegenga, WT., et al. (2014). Genome-wide age-related changes in ADN methylation and gene expression inhuman PBMCs. Springer, 36, pp. 1523-1540.

  27. Teschendorff, AE., et al. (2018). Age-dependent ADN methylation of genes that are suppressed in stem cells is a hallmark of cancer. Genome Research, 27, pp. 440-446.

  28. Ward, C. et al. (2018). Age-related ADN methylation and hemostatic factors. www.bloodjournal.org, 132, p. 1736.

  29. Zbiec-Piekarska, R. et al. (2015). Development of a forensically useful age prediction method based on ADN methylation analysis. Forensic Science International: Genetics, 17, pp. 173-179.

  30. Zbiec-Piekarska, R. et al. (2015). Examination of ADN methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science. Forensic Science International: Genetics, 14, pp. 161-167.




2020     |     www.medigraphic.com