Systematic proteomics reveals plasma NEFL as a robust predictor and pathological associate in <i>C9ORF72</i>-related neurodegeneration.

Overview

1. Department of Neurology, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
2. Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
3. Department of Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
4. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Abstract

Background: The C9ORF72 repeat expansion is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). While neurofilament light chain (NEFL) is an established biomarker of neuroaxonal damage, its specific dose-response relationship with the C9ORF72 expansion and its potential role beyond a passive bystander require systematic investigation. We performed a proteome-wide screen to identify plasma proteins linked to the C9ORF72 expansion and evaluated their predictive value for motor neuron disease (MND).

Methods: We utilized whole-genome sequencing and plasma proteomics from the UK Biobank, analyzing 106 individuals with C9ORF72 expansions (defined as >30 repeats) and 212 age- and sex-matched controls. We screened ~3,000 proteins for associations with the continuous repeat count. The top candidate was evaluated using restricted cubic splines (RCS) to assess non-linearity and threshold effects. Its ability to independently predict MND risk was tested using regression models and a machine learning approach.

Results: Our unbiased screen identified NEFL as the sole protein significantly associated with the C9ORF72 repeat count (FDR-adjusted P = 8.39 × 10−4). NEFL levels demonstrated a step-wise increase with expansion size, which followed a stable linear trajectory across the repeat spectrum (Pnon − linear = 0.4435). Elevated NEFL independently predicted MND risk (OR = 2.42; HR = 2.90), even after adjusting for the C9ORF72 repeat count. Our predictive model, combining NEFL and repeat count, achieved an AUC of 0.941 with 100% sensitivity. These findings align with emerging evidence that secreted NEFL may actively modulate neuroinflammation.

Conclusions: NEFL emerges as a robust and specific plasma biomarker for C9ORF72-related neurodegeneration. Its strong linear association with repeat burden and independent predictive power, contextualized within its potential role in immune activation, suggest that NEFL is deeply integrated into the C9ORF72 pathological landscape. These findings support NEFL-based screening and monitoring strategies for early intervention in C9ORF72 carriers.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• ukbiobank.ac.uk/learn-more-about-uk-biobank/about-us, at UK Biobank; found in the text, “Ethical considerations”

Data availability statement

Data used in this study are available from the UK Biobank (accession number 162635) through the UK Biobank Access Management System (https://www.ukbiobank.ac.uk/). Plasma proteomics data were obtained from the UK Biobank Pharma Proteomics Project (Olink platform). Derived data fields generated in this study will be returned to the UK Biobank in accordance with their data sharing policies.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Recorded: type, language, journal, volume, pages, dates, 5 authors, 5 keywords, 2 funders, 25 references.

Cite

This paper

Hu, Z., Wan, J.-j., Yan, Q.-q., Fan, Y., & Liu, J. (2026). Systematic proteomics reveals plasma NEFL as a robust predictor and pathological associate in <i>C9ORF72</i>-related neurodegeneration. Frontiers in aging neuroscience, 18, 1792887. https://doi.org/10.3389/fnagi.2026.1792887

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