Pharmacometabolomics applied to low-dose interleukin-2 treatment in amyotrophic lateral sclerosis.
Hugo AlarcanClément BrunoPatrick EmondCédric RaoulPatrick Vourc'hPhilippe CorciaWilliam CamuJean-Luc VeyruneCecilia GarlandaMassimo LocatiRaúl Juntas-MoralesSafaa SakerCarey SuehsChristophe MasseguinJanine KirbyPamela ShawAndrea MalaspinaJohn De VosAmmar Al-ChalabiP Nigel LeighTimothy TreeGilbert BensimonHélène BlascoPublished in: Annals of the New York Academy of Sciences (2024)
Amyotrophic lateral sclerosis (ALS) is a devastating motor neuron disease. The immunosuppressive functions of regulatory T lymphocytes (Tregs) are impaired in ALS, and correlate to disease progression. The phase 2a IMODALS trial reported an increase in Treg number in ALS patients following the administration of low-dose (ld) interleukin-2 (IL-2). We propose a pharmacometabolomics approach to decipher metabolic modifications occurring in patients treated with ld-IL-2 and its relationship with Treg response. Blood metabolomic profiles were determined on days D1, D64, and D85 from patients receiving 2 MIU of IL-2 (n = 12) and patients receiving a placebo (n = 12). We discriminated the three time points for the treatment group (average error rate of 42%). Among the important metabolites, kynurenine increased between D1 and D64, followed by a reduction at D85. The percentage increase of Treg number from D1 to D64, as predicted by the metabolome at D1, was highly correlated with the observed value. This study provided a proof of concept for metabolic characterization of the effect of ld-IL-2 in ALS. These data could present advances toward a personalized medicine approach and present pharmacometabolomics as a key tool to complement genomic and transcriptional data for drug characterization, leading to systems pharmacology.
Keyphrases
- amyotrophic lateral sclerosis
- low dose
- end stage renal disease
- high dose
- newly diagnosed
- transcription factor
- clinical trial
- electronic health record
- ejection fraction
- big data
- chronic kidney disease
- machine learning
- artificial intelligence
- copy number
- prognostic factors
- dna methylation
- deep learning
- phase ii
- heat shock
- patient reported