AlphaGenome identifies a deep intronic variant in a family with PLA2G6-associated neurodegeneration: Closing the diagnostic gap in rare genetic diseases
Eger, S. J.; Lopez, G.; Gomez Navarro, L. F.; Pena-Tauber, A.; Cochran, J. N.; Hiatt, S. M.; Gelvez, N.; Garcia-Garcia, M.; Lobo, S.; Greicius, M. D.; Matallana, D. L.; Acosta-Uribe, J.; Kosik, K. S.
Show abstract
A molecular diagnosis remains out of reach for a substantial subset of patients with clinically recognizable Mendelian disorders, even after comprehensive next-generation sequencing. Causal variants in non-coding regions are difficult to detect and interpret using standard pipelines. Deep intronic variants that disrupt splicing are a known but underexplored source of pathogenic alleles, and systematic tools to evaluate them at scale have only recently emerged. We aimed to resolve an incomplete genetic diagnosis in two siblings with early-onset parkinsonism, prominent neuropsychiatric features, and autonomic dysfunction consistent with PLA2G6-associated neurodegeneration (PLAN), an autosomal recessive condition. Prior clinical exome sequencing, genome sequencing, Multiplex Ligation-dependent Probe Amplification (MLPA), and long-read sequencing had identified only a single heterozygous PLA2G6 missense variant, c.2132C>G (p.Pro711Arg). We used AlphaGenome to score 91 non-coding variants shared among the affected siblings and their father within 1 megabase of the PLA2G6 locus. The deep-learning model identified an intronic variant (c.2034+355G>A) that was predicted to create a cryptic splice acceptor site that could result in inclusion of a 160-bp cryptic exon. Tissue-specific predictions indicated the aberrant splicing would be detectable in blood, confirmed by junction-spanning RNA-seq reads from an unrelated carrier. This analysis completed a compound heterozygous PLAN diagnosis nearly two decades after symptom onset and demonstrates the utility of sequence-to-function models. Systematic integration of tools like AlphaGenome into rare disease workflows offers a practical, low-barrier route to closing the diagnostic gap for patients with compelling Mendelian phenotypes and incomplete genetic diagnoses.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations 96%
- The genetic drivers of juvenile, young, and early-onset Parkinson’s Disease in India 95%
- Polygenic Parkinson’s disease genetic risk score as risk modifier of parkinsonism in Gaucher disease 93%
Similar papers in this journal
- Dominant variants in major spliceosome U4 and U5 small nuclear RNA genes cause neurodevelopmental disorders through splicing disruption 95%
- Common and rare variant association analyses in Amyotrophic Lateral Sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology 94%
- Multi-ancestry genome-wide meta-analysis in Parkinson’s disease 94%
Similar papers in this journal
- Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing 94%
- Systematic analysis of short tandem repeats in 38,095 exomes provides an additional diagnostic yield 94%
- Diagnosing missed cases of spinal muscular atrophy in genome, exome, and panel sequencing datasets 94%
Similar papers in this journal
- Association of genetic variation at the GJA5/ACP6 locus with motor progression in Parkinson’s 95%
- A 3’ UTR Deletion Is a Leading Candidate Causal Variant at the TMEM106B Locus Reducing Risk for FTLD-TDP 94%
- A fast and robust strategy to remove variant level artifacts in Alzheimer’s Disease Sequencing Project data 93%
Similar papers in this journal
- Advancing molecular, phenotypic and mechanistic insights of FGF14 pathogenic expansions (SCA27B) 95%
- Deciphering Distinct Genetic Risk Factors for FTLD-TDP Pathological Subtypes via Whole-Genome Sequencing 95%
- A human single-cell atlas of the Substantia nigra reveals novel cell-specific pathways associated with the genetic risk of Parkinson's disease and neuropsychiatric disorders. 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.