Identification of human age using trace element concentrations in hair and the support vector machine method

Area of Science:

• Environmental Health
• Human Biology
• Biochemistry

Background:

• Hair trace element analysis offers insights into human health and aging.
• Geographic regions with high longevity (
• longevity counties
• ) provide unique populations for studying aging factors.

Purpose of the Study:

• To investigate the relationship between age and trace element content in human hair.
• To identify specific trace elements that change with age and may be associated with longevity.

Main Methods:

• Hair samples were collected from individuals in Chinese longevity counties across three age groups: children (0-15 years), elderly (80-99 years), and centenarians (≥100 years).
• Trace element concentrations in hair were determined and compared across age groups.
• Support vector machine classification was employed to analyze age-related differences.

Main Results:

• Calcium (Ca) and Cadmium (Cd) levels in hair were not significantly affected by age.
• Lithium (Li), Magnesium (Mg), Manganese (Mn), Zinc (Zn), Chromium (Cr), Copper (Cu), and Nickel (Ni) showed significant age-dependent variations.
• Copper (Cu) content decreased with age, while centenarians exhibited higher Li and Mn, and lower Cr, Cu, and Ni compared to younger groups.

Conclusions:

• Hair trace element profiles change significantly with aging, with notable differences observed in centenarians.
• Specific trace elements like Copper (Cu), Zinc (Zn), and Nickel (Ni) are strongly influenced by age.
• Elevated Lithium (Li) and Manganese (Mn), and reduced Chromium (Cr), Copper (Cu), and Nickel (Ni) in centenarian hair may contribute to their exceptional lifespan.