Reassessing metrics: The limitations of brain function as indicators of brain health

Objective: This study aimed to evaluate brain health using cognition, vision, hearing, emotional well-being, aging, and motor function as predictors, with blood neurofilament light (NfL), neuron-specific enolase (NSE), and phosphorylated tau (pTau) as response variables for detecting chronic brain injury. Methodology: This is a predictive cross-sectional modelling study carried out in various settings across Peshawar, Pakistan in which a total of 75 healthy adults were included from May 2022 to February 2023. Various tests were performed including visual fields, audiometry, dynamometry, Mini-Mental State Examination (MMSE), and Trait Emotional Intelligence Questionnaire (TEIQue-SF). Serum levels of NfL, pTau, and NSE were measured via ELISA and multiple linear regression models were developed. These biomarkers were selected based on a preliminary scoping review. Results: Statistically significant discrepancies were present between predicted and actual biomarker values (NfL: actual 0.026±0.011 ng/ml vs. predicted 0.001±0.000 ng/ml, p<0.001; NSE: actual 10.46±1.52 ng/ml vs. predicted 4.127±1.8 ng/ml, p<0.001; pTau: actual 4.48±3.23 ng/ml vs. predicted 1.027±0.85 ng/ml, p<0.001), indicating poor prediction model performance. The k-fold cross-validation confirmed this, with over 2% deviation in all subsets. Conclusion: Brain health prediction models based solely on neuro-biomarkers and brain function parameters may not generalize well to healthy populations, indicating the need for additional factors influencing brain health.