Recent advances in genomic technologies have greatly enhanced our understanding of neurodegeneration. Techniques like whole-genome sequencing, long-read sequencing, and large-scale population studies have expanded the range of identified genetic risk factors, uncovering new disease mechanisms and biological pathways that could serve as therapeutic targets.
However, translating these genetic insights into clinical practice remains difficult because of challenges in interpreting variants and the limited functional validation of new discoveries. This Review highlights the key genomic technologies advancing diagnosis and research in neurodegeneration.
We focus on improvements in variant classification, detection of structural variants and repeat expansions, and combining transcriptomic, proteomic, and functional data to better determine variant pathogenicity. The ongoing integration of genomics, molecular neurobiology, and data science offers great potential for more accurate, biologically informed diagnosis and treatment of neurodegenerative disorders.