法医学杂志 ›› 2023, Vol. 39 ›› Issue (1): 72-82.DOI: 10.12116/j.issn.1004-5619.2021.510604
王紫薇1,2(), 徐倩南1,3, 李成涛1(
), 刘希玲1(
)
收稿日期:
2021-06-29
发布日期:
2023-02-25
出版日期:
2023-02-28
通讯作者:
李成涛,刘希玲
作者简介:
刘希玲,女,副研究员,硕士研究生导师,主要从事法医遗传学研究;E-mail:liuxl@ssfjd.cn基金资助:
Zi-wei WANG1,2(), Qian-nan XU1,3, Cheng-tao LI1(
), Xi-ling LIU1(
)
Received:
2021-06-29
Online:
2023-02-25
Published:
2023-02-28
Contact:
Cheng-tao LI,Xi-ling LIU
摘要:
随着DNA甲基化检测技术的发展,年龄相关甲基化修饰位点的研究发现了更多跨组织的年龄特异性位点,这使得个体年龄推断的灵敏度和准确性都有了提高。此外,各种统计模型的建立,也为不同来源组织的年龄推断提供了新的方向。本文从检测技术、年龄相关胞嘧啶鸟嘌呤二核苷酸位点和模型的选择等方面,对近年来DNA甲基化位点年龄推断的相关研究进行综述。
中图分类号:
王紫薇, 徐倩南, 李成涛, 刘希玲. DNA甲基化年龄推断及其在法医学中的应用展望[J]. 法医学杂志, 2023, 39(1): 72-82.
Zi-wei WANG, Qian-nan XU, Cheng-tao LI, Xi-ling LIU. Age Estimation Based on DNA Methylation and Its Application Prospects in Forensic Medicine[J]. Journal of Forensic Medicine, 2023, 39(1): 72-82.
技术 | 血液 | 唾液 | 精液 | 月经血 | 阴道分泌物 | 参考文献 |
---|---|---|---|---|---|---|
Infinium? HumanMethylation450K | cg08792630 cg06379435 | cg26107890 cg20691722 | cg17610929 cg23521140 | - | cg26107890 cg20691722 | [ |
Infinium? HumanMethylation450K、SNaPshot、焦磷酸测序 | cg06379435 cg08792630 | cg09652652-2d | cg17610929 cg26763284 | cg09696411 cg18069290 | cg26079753-7d cg09765089-231d | [ |
Infinium? HumanMethylation27、Infinium? HumanMethylation450K、甲基化敏感性单核苷酸引物延伸、二代测序技术 | cg26285698 cg03363565 | cg21597595 cg15227982 | cg22407458 cg05656364 | cg09696411 | cg14991487 cg03874199 | [ |
表1 不同体液中的年龄相关DNA甲基化位点
Tab. 1 Age-related CpG in different body fluids
技术 | 血液 | 唾液 | 精液 | 月经血 | 阴道分泌物 | 参考文献 |
---|---|---|---|---|---|---|
Infinium? HumanMethylation450K | cg08792630 cg06379435 | cg26107890 cg20691722 | cg17610929 cg23521140 | - | cg26107890 cg20691722 | [ |
Infinium? HumanMethylation450K、SNaPshot、焦磷酸测序 | cg06379435 cg08792630 | cg09652652-2d | cg17610929 cg26763284 | cg09696411 cg18069290 | cg26079753-7d cg09765089-231d | [ |
Infinium? HumanMethylation27、Infinium? HumanMethylation450K、甲基化敏感性单核苷酸引物延伸、二代测序技术 | cg26285698 cg03363565 | cg21597595 cg15227982 | cg22407458 cg05656364 | cg09696411 | cg14991487 cg03874199 | [ |
时间 | 样本量/例 | 检材 | 年龄/岁 | 方法 | 模型 | 误差 | 参考文献 |
---|---|---|---|---|---|---|---|
2018年 | 390 | 血液 | 15~75 | EpiTYPER、 焦磷酸测序 | 多元线性回归 | R2=0.92,MAD=2.89 | [ |
支持向量机 | R2=0.92,MAD=2.91 | ||||||
人工神经网络 | R2=0.92,MAD=2.71 | ||||||
2018年 | 110 | 血液 | 11~93 | MPS | 支持向量机 | RMSE=4.9,MAE=4.1 | [ |
2019年 | 95 | 唾液 | 18~65 | MPS | 人工神经网络 | MAPE=8.89%,MAD=3.19 | [ |
SNaPshot | 多元线性回归 | MAPE=10.44%,MAD=3.69 | |||||
2020年 | 310 | 血液 | 2~86 | SNaPshot | 逐步线性回归 | R2=0.85,MAD=4.22 | [ |
支持向量回归 | R2=0.86,MAD=4.01 | ||||||
2021年 | 141 | 口腔拭子 | 21~69 | 焦磷酸测序、微测序 | 逐步线性回归 | MAD1=5.16,MAD2=6.44 | [ |
2022年 | 240 | 血液 | 1~81 | 焦磷酸测序 | 逐步线性回归 | RMSE=3.89,MAD=2.97 | [ |
支持向量回归 | RMSE=2.95,MAD=2.22 | ||||||
随机森林回归 | RMSE=1.77,MAD=1.29 | ||||||
2022年 | 529 | 血液 | 2~82 | SNaPshot | 逐步线性回归 | R2=0.923,MAE=3.52 | [ |
支持向量回归 | R2=0.935,MAE=2.88 |
表2 部分年龄推断研究相关信息统计
Tab. 2 Summary of some relevant information about age determination model
时间 | 样本量/例 | 检材 | 年龄/岁 | 方法 | 模型 | 误差 | 参考文献 |
---|---|---|---|---|---|---|---|
2018年 | 390 | 血液 | 15~75 | EpiTYPER、 焦磷酸测序 | 多元线性回归 | R2=0.92,MAD=2.89 | [ |
支持向量机 | R2=0.92,MAD=2.91 | ||||||
人工神经网络 | R2=0.92,MAD=2.71 | ||||||
2018年 | 110 | 血液 | 11~93 | MPS | 支持向量机 | RMSE=4.9,MAE=4.1 | [ |
2019年 | 95 | 唾液 | 18~65 | MPS | 人工神经网络 | MAPE=8.89%,MAD=3.19 | [ |
SNaPshot | 多元线性回归 | MAPE=10.44%,MAD=3.69 | |||||
2020年 | 310 | 血液 | 2~86 | SNaPshot | 逐步线性回归 | R2=0.85,MAD=4.22 | [ |
支持向量回归 | R2=0.86,MAD=4.01 | ||||||
2021年 | 141 | 口腔拭子 | 21~69 | 焦磷酸测序、微测序 | 逐步线性回归 | MAD1=5.16,MAD2=6.44 | [ |
2022年 | 240 | 血液 | 1~81 | 焦磷酸测序 | 逐步线性回归 | RMSE=3.89,MAD=2.97 | [ |
支持向量回归 | RMSE=2.95,MAD=2.22 | ||||||
随机森林回归 | RMSE=1.77,MAD=1.29 | ||||||
2022年 | 529 | 血液 | 2~82 | SNaPshot | 逐步线性回归 | R2=0.923,MAE=3.52 | [ |
支持向量回归 | R2=0.935,MAE=2.88 |
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