IAn AI-driven Multi-omics Platform integrating lipidomics, immune profiling, and inflammatory miRNA signatures to identify aCtionable therapeutic Targets in ALS
ProjectAmyotrophic lateral sclerosis (ALS) is a highly heterogeneous neurodegenerative disease for
which effective disease-modifying therapies remain limited. IMPACT-ALS aims to uncover
the fundamental biological mechanisms underlying ALS heterogeneity by integrating lipid
metabolism, immune-inflammatory pathways, and regulatory microRNA networks within a
unified AI-driven multi-omics framework. Rather than focusing on individual biomarkers, the
project seeks to identify convergent molecular mechanisms and biologically coherent patient
subgroups that can support precision medicine and therapeutic target discovery.
The project will combine deeply phenotyped discovery and validation cohorts with high-
resolution lipidomics, immune profiling, inflammation-focused miRNA analysis, and
neurodegeneration biomarkers. These complementary datasets will be integrated using
advanced artificial intelligence and systems biology approaches to reconstruct
lipid–immune–miRNA interaction networks, identify upstream regulatory hubs, and
characterize mechanistically defined ALS endotypes associated with disease progression and
motor neuron vulnerability.
By validating its findings in an independent cohort, IMPACT-ALS will deliver a robust and
scalable computational framework for the identification of reproducible, biologically
grounded, and therapeutically actionable targets. Through the integration of multi-omics and
AI, the project aims to advance the understanding of both genetic and sporadic ALS,
providing a foundation for mechanism-based patient stratification and the development of
future precision therapeutic strategies.
which effective disease-modifying therapies remain limited. IMPACT-ALS aims to uncover
the fundamental biological mechanisms underlying ALS heterogeneity by integrating lipid
metabolism, immune-inflammatory pathways, and regulatory microRNA networks within a
unified AI-driven multi-omics framework. Rather than focusing on individual biomarkers, the
project seeks to identify convergent molecular mechanisms and biologically coherent patient
subgroups that can support precision medicine and therapeutic target discovery.
The project will combine deeply phenotyped discovery and validation cohorts with high-
resolution lipidomics, immune profiling, inflammation-focused miRNA analysis, and
neurodegeneration biomarkers. These complementary datasets will be integrated using
advanced artificial intelligence and systems biology approaches to reconstruct
lipid–immune–miRNA interaction networks, identify upstream regulatory hubs, and
characterize mechanistically defined ALS endotypes associated with disease progression and
motor neuron vulnerability.
By validating its findings in an independent cohort, IMPACT-ALS will deliver a robust and
scalable computational framework for the identification of reproducible, biologically
grounded, and therapeutically actionable targets. Through the integration of multi-omics and
AI, the project aims to advance the understanding of both genetic and sporadic ALS,
providing a foundation for mechanism-based patient stratification and the development of
future precision therapeutic strategies.