Research Paper Volume 13, Issue 24 pp 25729—25738
Factors influencing serum neurofilament light chain levels in normal aging
- 1 Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- 2 Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
- 3 Department of Neurology, Medical University of Graz, Graz, Austria
- 4 Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
- 5 Neurology Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
Received: July 21, 2021 Accepted: December 8, 2021 Published: December 18, 2021https://doi.org/10.18632/aging.203790
How to Cite
Copyright: © 2021 Koini et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Objective: Serum neurofilament light (sNfL) is a promising marker for neuro-axonal damage and it is now well known that its levels also increase with higher age. However, the effect of other determinants besides age is still poorly investigated. We therefore aimed to identify factors influencing the sNfL concentration by analysing a large set of demographical, life-style and clinical variables in a normal aging cohort.
Methods: sNfL was quantified by single molecule array (Simoa) assay in 327 neurologically inconspicuous individuals (median age 67.8±10.7 years, 192 female) who participated in the Austrian Stroke Prevention Family Study (ASPS-Fam). Random forest regression analysis was used to rank the association of included variables with sNfL in the entire cohort and in age-stratified subgroups. Linear regression then served to identify factors independently influencing sNfL concentration.
Results: Age (β=0.513, p<0.001) was by far the most important factor influencing sNfL, which was mainly driven by individuals ≥60 years. In age stratified sub-groups, body mass index (BMI) (β=-0.298, p<0.001) independently predicted sNfL in individuals aged 38-60 years. In individuals ≥60 years, age (β=0.394, p<0.001), renal function (β=0.376, p<0.001), blood volume (β=-0.198, p=0.008) and high density lipoprotein (HDL) (β=0.149, p=0.013) were associated with sNfL levels.
Conclusions: Age is the most important factor influencing sNfL concentrations, getting increasingly relevant in elderly people. BMI further influences sNfL levels, especially at younger age, whereas renal function gets increasingly relevant in the elderly.
AP: alkaline phosphatase; ASPS: Austrian Stroke Prevention Study; ASPS-Fam: Austrian Stroke Prevention Family Study; BCa-method: bias corrected and accelerated; BMI: body mass index; CI: confidence interval; CSF: cerebrospinal fluid; CVs: coefficients of variation; eGFR: estimated glomerular filtration rate; GGT: gamma-glutamyl transferase; GOT: glutamic oxaloacetic transaminase; GPT: glutamate pyruvate transaminase; HBA1C: glycated hemoglobin; HDL: high density lipoprotein; IQR: interquartile range; kDa: kilodalton; LDL: high-density lipid protein; MMSE: Mini Mental Status Examination; MRI: Magnetic Resonance Imaging; Simoa: single molecule array; sNfL: Serum neurofilament light; VIF: variance inflation factor; WHR: waist-hip-ratio.