Amyotrophic lateral sclerosis stratification: unveiling patterns with virome, inflammation, and metabolism molecules

Author:

Niccolai Elena,Pedone Matteo,Martinelli Ilaria,Nannini Giulia,Baldi Simone,Simonini Cecilia,Di Gloria Leandro,Zucchi Elisabetta,Ramazzotti Matteo,Spezia Pietro Giorgio,Maggi Fabrizio,Quaranta Gianluca,Masucci Luca,Bartolucci Gianluca,Stingo Francesco Claudio,Mandrioli Jessica,Amedei AmedeoORCID

Abstract

AbstractAmyotrophic lateral sclerosis (ALS) is an untreatable and clinically heterogeneous condition primarily affecting motor neurons. The ongoing quest for reliable biomarkers that mirror the disease status and progression has led to investigations that extend beyond motor neurons’ pathology, encompassing broader systemic factors such as metabolism, immunity, and the microbiome. Our study contributes to this effort by examining the potential role of microbiome-related components, including viral elements, such as torque tenovirus (TTV), and various inflammatory factors, in ALS. In our analysis of serum samples from 100 ALS patients and 34 healthy controls (HC), we evaluated 14 cytokines, TTV DNA load, and 18 free fatty acids (FFA). We found that the evaluated variables are effective in differentiating ALS patients from healthy controls. In addition, our research identifies four unique patient clusters, each characterized by distinct biological profiles. Intriguingly, no correlations were found with site of onset, sex, progression rate, phenotype, or C9ORF72 expansion. A remarkable aspect of our findings is the discovery of a gender-specific relationship between levels of 2-ethylhexanoic acid and patient survival. In addition to contributing to the growing body of evidence suggesting altered peripheral immune responses in ALS, our exploratory research underscores metabolic diversity challenging conventional clinical classifications. If our exploratory findings are validated by further research, they could significantly impact disease understanding and patient care customization. Identifying groups based on biological profiles might aid in clustering patients with varying responses to treatments. Graphical abstract

Funder

Ministero della Salute

University of Florence

Università degli Studi di Firenze

Publisher

Springer Science and Business Media LLC

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