# Proteomics in Forensic Analysis: Applications for Human Samples
## 3 Applications of Forensic Proteomics for Human Samples
### Bone Proteome  
Bone proteins are present in the extracellular matrix and mostly consist of collagenous proteins (\(\sim\)90%) [142]. Bone collagens are extremely stable due to their cross-linked structure and the protection of the bone matrix [143]. Thus, [PERSON] et al. determined a peptide with 33 amino acids derived from collagen, which could be used to distinguish between sheep and goat bone because this peptide differs between the two species at two positions [144]. A study by [PERSON] et al. found that while many low-abundance proteins in bone degraded with time, serum albumin, alpha-2-HS-glycoprotein (AHSG) could be easily recovered in ancient bone [145]. Other proteins such as lumican, chondro, and biglyscan also survive well because of their interactions with bone collagen. They can be useful for identifying species and studying phylogenetic inferences in archeological and paleontological bones. Several studies have investigated bone proteomes to estimate biological age (age-at-death) and PMI of skeletal tissue in simulated forensic contexts. [PERSON] et al. studied the relationship between biological age (age-at-death) and the abundance of some proteins in proteomic analysis of pig bones [40]. They found that AHSG decreased with age. In addition, two serum proteins (alpha-1 antitrypsin and chromogranin-A) positively correlated with biological age (Figure 3a). This group later reported a similar relationship between AHSG abundance and the biological age of human 4000-5500-year-old ancient mandibular bone [41]. [PERSON] et al. revealed a strong negative correlation between the abundance of AHSG in human bone samples and the biological age of the specimens [42]. The authors used the exponentially modified protein abundance index (emPAI) score [146] and established a relationship between the normalized emPAI score of AHSG and age. A strong negative correlation was demonstrated by Pearson's r of \(-0.9826\), \(p\)-value of \(1.295\times 10^{-5}\), and Bonferroni-corrected \(p\)-value of \(5.95\times 10^{-4}\) (Figure 3b). In addition, the study showed that the normalized emPAI scores of albumin, kininogen-1 (KNG1), insulin-like growth factor-binding protein 5 (IGFBP5), and pigment epithelium-derived factor (SERPINF1) were significantly correlated with age. [PERSON] et al. later performed a proteomic study on porcine bones to investigate both PMI and biological age [29]. They revealed the stability of AHSG after death in forensic contexts without significant inter-individual variability, as well as the correlation between its relative abundance and the biological age of an individual. AHSG has a great affinity to the mineral matrix of the bone, and thus is protected and can be recovered after hundreds of years. Based on these findings, the authors suggested that AHSG could be a potential biomarker for the estimation of age at death. The study also found that the abundance of some plasma and muscle proteins (hemoglobin A and B, transferrin, lactoferrin, haptoglobin, creatine kinase M-type, myosin type 2 and 6) reduced quickly within 4 months of PMI. Notably, asparagine deamidation of biglyscan (a protein with an important role in modulating bone growth and mineralization) increased consistently with PMI (Figure 3c) and could be useful for identifying specific PMIs (from one to six months). [PERSON] et al. performed proteomic analysis on 40 femur bones from 40 different cadavers and selected 32 proteins that allowed discrimination between PMI of 5-12 years and PMI of 13-20 years [30]. They included 25 non-collogenous proteins (ADAMTS17, ANXA2R, AREG, BMP5, CD163L1, CDH11, CTC1, CTNNB, DLX5, ENPP1, FBN1, FGFR1, INSIG2, JAG2, LAMA2, LMNA, MAF, MED12, MUC15, MYSM1, PAPPA, PHOSPHO1, SLC26A1, SOX6, SUCO) and seven collagen proteins (CILP, COL10A1, COL11A2, COL5A2, COL9A2, COMP, and PCOLCE). [PERSON] et al.