Genomics Core

Our network of CROs and academic institutions generate comprehensive ALS-FTD multi-omics datasets, including whole genome (short- and long-read) sequencing, RNA sequencing, and biofluid proteomics, paired with rich clinical and longitudinal data, accessible via the Target ALS Data Engine.

What is the Target ALS Genomics Core?

Genomics Core

The Target ALS Genomics Core represents one of the most significant investments in ALS and FTD data resources to date. This core brings together the most comprehensive genomic, transcriptomic, and proteomic data from across all Target ALS collections into a single, accessible platform: the Target ALS Data Engine.

These datasets are made accessible immediately after QC analysis and with no strings attached to scientists worldwide from academia, pharma, and biotech.

How the Genomics Core works

Target ALS generates and integrates multi-omic datasets from postmortem tissue, longitudinal biofluids, and stem cell models.

Pooling these datasets into one location allows researchers to explore cross-modality insights, compare findings across biosample types, and link molecular signatures to detailed clinical, demographic, and longitudinal data.

Recent expansions include multi-omics datasets from the ALS Global Research Initiative (AGRI), with:

MS proteomics from cerebrospinal fluid and plasma using TMTpro 35-plex methodology. Data are generated by Henrik Zetterberg’s team at the University of Gothenburg.
Olink HT proteomics data from CSF and plasma, generated at Psomagen.
PacBio HiFi and short-read whole genomes from ALS, FTD, and control participants.
Standard cognitive and motor assessments paired with genomic and proteomic data.
Longitudinal digital health datasets generated on Linus Health (formerly Aural Analytics) and ModalityAI technology platforms.
Diverse patient representation to enable comparisons by genetic subtype, cognitive status, and disease trajectory.
Environmental and Occupational History data to study environmental risk and interactions with genotype.

Core leadership

The Genomics Core is advised by Dr. Matthew Harms, an international leader in neuromuscular genetics, whose work has identified multiple novel disease genes and advanced precision medicine approaches in ALS.

Empowering researchers

With a background in molecular biology and medicine, Prof Henrik Zetterberg has spent the past 15 years focusing on the development of biomarkers for Alzheimer’s disease and other brain disorders, becoming a world expert in the process. He has published more than 1100 scientific articles and has received numerous awards.

The impact of the Genomics Core

Target ALS has invested in multi-omic data generation on Postmortem Core Tissue for more than 10 years.

We invest in state-of-the-art methods to elucidate a detailed understanding of the molecular aspects of the disease, maximizing the impact of every patient donation:

The largest collection of PacBio HiFi long-read sequencing for ALS. Data are included in a larger global search engine for genomic variants across rare diseases. Learn more about HiFi Solves.
Illumina-based short-read whole genomes from ALS, FTD, and non-neurological control tissue generated by the New York Genome Center and Psomagen.
Curated tables of genetic variants and C9orf72 repeat expansion length detected using a combination of short and long-read WGS.
Illumina-based RNA sequencing files from multiple regions of the CNS including motor cortex, cerebellum, cervical, thoracic, and lumbar spinal cord generated by New York Genome Center and Psomagen.
Ready-to-analyze ‘Counts’ table curated from bulk RNA sequencing BAM files.
Visium-based spatial transcriptomic data from the motor cortex of ALS, FTD and non-neurological controls. Generated by the New York Genome Center.
Single nucseq RNA sequencing [data pending]

All datasets are accessible via the Target ALS Data Engine, powered by DNAstack’s Omics AI and integrated with Verily Workbench for streamlined analysis.

*This resource will continue to grow, with new data uploaded every 4–6 months.