Optimized analytical strategy based on high-resolution mass spectrometry for unveiling associations between long-term chemical exposome in hair and Alzheimer’s disease

Abstract

Exposure to environmental pollutants or contaminants is correlated with detrimental effects on human health, such as neurodegenerative diseases. Adopting hair as a biological matrix for biomonitoring is a significant innovation, since it can reflect the long-term chemical exposome, spanning months to years. However, only a limited number of studies have developed analytical strategies for profiling the chemical exposome in this heterogeneous biological matrix. In this study, a systematic investigation of the chemical extraction procedure from human hair was conducted, using a design of experiments and a high-resolution mass spectrometry (HRMS)-based suspect screening approach. The PlackettBurman (PB) design was applied to identify the significant variables influencing the number of detected features. Then, a central composite design was implemented to optimize the levels of each identified significant variable. Under the optimal conditions—15-minute pulverization, 25 mg of hair weight, 40 min of sonication, and a sonication temperature of 35 °C—approximately 32,000 and 15,000 aligned features were detected in positive and negative ion modes, respectively. This optimized analytical procedure was applied to hair samples from patients with Alzheimer's disease (AD) and individuals with normal cognitive function. Overall, 307 chemicals were identified using the suspect screening approach, with 37 chemicals differentiating patients with AD from controls. This study not only optimized an analytical procedure for characterizing the long-term chemical exposome in human hair but also explored the associations between AD and environmental factors.

Keywords

• Hair
• Chemical exposome
• Optimization
• High-resolution mass spectrometry
• Suspect screening