An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Search
2.2. Exclusion and Inclusion Criteria
2.3. Statistical Analysis
3. Results
3.1. Study Selection
3.2. PCA Results
3.3. ELOVL2 Methylation-Based Prediction Models
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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PubMed/MEDLINE | Scopus |
---|---|
((((ELOVL fatty acid elongase 2[All Fields]) OR ELOVL2[All Fields]))) AND (((Age[Title/Abstract]) OR aging[Title/Abstract]) OR ageing[Title/Abstract]) AND (pyrosequencing[All Fields]) | ((ALL (ELOVL AND fatty AND acid AND elongase AND 2) OR ALL (ELOVL2))) AND ((TITLE-ABS-KEY (age) OR TITLE-ABS-KEY (aging) OR TITLE-ABS-KEY (ageing))) AND (ALL (pyrosequencing)) |
Study | Year of Publication | Population | Age Range (Years) | Sample Size | Reference |
---|---|---|---|---|---|
Al-Ghanmy et al. | 2021 | Iraqi | 18–93 | 92 | [20] |
Bekaert et al. | 2015 | Belgium | 0–91 | 206 | [21] |
Cho et al. | 2017 | Korean | 20–74 | 100 | [22] |
Fan et al. | 2021 | Chinese | 1–81 | 240 | [8] |
Garali et al. | 2020 | French | 19–65 | 100 | [16] |
Lucknuch et al. | 2022 | Thailand | 5–60 | 52 * | [23] |
Montesanto et al. | 2020 | Italian | 20–89 | 323 ** | [24] |
Park et al. | 2016 | Korean | 1–100 | 765 | [25] |
Zbieć-Piekarska et al. | 2015 | Polish | 2–75 | 420 | [15] |
MLR | MQR | SVM | GBR | PC | |
---|---|---|---|---|---|
MLR | 6.575 | 0.1174 | <0.001 | <0.001 | 0.0118 |
MQR | 0.256 (−0.083, 0.558) | 6.319 | <0.001 | <0.001 | 0.8826 |
SVM | 0.93 (0.708, 1.151) | 0.674 (0.351, 1.042) | 5.645 | 0.4295 | <0.001 |
GBR | 0.989 (0.766, 1.213) | 0.733 (0.385, 1.131) | 0.059 (−0.087, 0.206) | 5.586 | <0.001 |
PC | 0.226 (0.048, 0.404) | −0.029 (−0.376, 0.367) | −0.703 (−0.908, −0.492) | −0.762 (−0.971, −0.554) | 6.348 |
Holdout Study | Best Model | Best MAE | MAE Garali SVM 6,7 | MAE Garali GBM 6,7 * |
---|---|---|---|---|
Montesanto et al. [24] | SVM | 7.77 | 7.380 | 7.976 |
Cho et al. [22] | GBR | 5.214 | 13.666 | 13.293 |
Bekaert et al. [21] | SVM | 5.984 | 4.478 | 4.355 |
Zbieć-Piekarska et al. [15] | SVM | 6.136 | 5.399 | 4.398 |
Park et al. [25] | SVM | 7.303 | 5.871 | 4.924 |
Garali et al. [16] | GBR | 8.572 | 4.173 | 5.430 |
Lucknuch et al. [23] | GBR | 7.892 | 27.301 | 27.865 |
Al-Ghanmy et al. [20] | SVM | 9.218 | 24.452 | 23.468 |
Fan et al. [8] | SVM | 7.367 | 13.125 | 15.275 |
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Paparazzo, E.; Lagani, V.; Geracitano, S.; Citrigno, L.; Aceto, M.A.; Malvaso, A.; Bruno, F.; Passarino, G.; Montesanto, A. An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review. Int. J. Mol. Sci. 2023, 24, 2254. https://doi.org/10.3390/ijms24032254
Paparazzo E, Lagani V, Geracitano S, Citrigno L, Aceto MA, Malvaso A, Bruno F, Passarino G, Montesanto A. An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review. International Journal of Molecular Sciences. 2023; 24(3):2254. https://doi.org/10.3390/ijms24032254
Chicago/Turabian StylePaparazzo, Ersilia, Vincenzo Lagani, Silvana Geracitano, Luigi Citrigno, Mirella Aurora Aceto, Antonio Malvaso, Francesco Bruno, Giuseppe Passarino, and Alberto Montesanto. 2023. "An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review" International Journal of Molecular Sciences 24, no. 3: 2254. https://doi.org/10.3390/ijms24032254