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Amino Acid Composition of Human Scalp Hair as a Biometric Classifier and Investigative Lead

NCJ Number
249277
Date Published
January 2015
Length
12 pages
Author(s)
Ayat H.B. Rashaid, Peter B. Harrington, Glen P. Jackson
Agencies
NIJ-Sponsored
Annotation
This study analyzed the amino acid composition of scalp hair of 64 Jordanian subjects (33 males and 31 females) with ages ranging from 1 to 77 years.
Abstract
Hair shaft analysis is becoming increasingly important in several applications of forensic science. Keratin is the key component of human scalp hair and is composed of all 21 known amino acids, albeit in very different proportions. The techniques developed through this paper could complement the current methods of hair analysis, which include physical examinations and genomic or mitochondrial DNA analysis. The method for the amino acid determination included protein acid hydrolysis followed by trimethylsilyl (TMS) derivatization of the amino acids, and the subsequent quantitation using gas chromatography/mass spectrometry (GC/MS). Statistical comparisons between classification groups were based on the abundance of 14 abundant and acid-resistant amino acids, and included classification of hairs with a fuzzy rule building system (FuRES). Using leave-one-individual-out cross-validation, the FuRES classification rate was 94 percent for sex, 83 percent for age group, and 61 percent for the region of origin. For predicting sex from amino acid concentration in hair, the essential amino acids Phe and Thr gave the most significant differences with respect to their F statistic (i.e., ratio of between-group to within-group variation), so they are the most discriminating for sex. Based on the same hair analyses, the non-essential amino acids Gly and Ala provide the largest loading scores classifying the subjects into two arbitrary age groups, <49 and >49 years. For region of origin classification, the amino acids Cys and Tyr had the highest loading scores in the classification rules and were therefore most discriminating. (Publisher abstract modified)
Date Created: July 14, 2016