Identification of case-specific copy number variants reveals novel genetic insights into familial hemiplegic migraine pathogenesis

Familial Hemiplegic Migraine (FHM) is a rare and severe subtype of migraine characterised by transient hemiparesis and aura symptoms. While pathogenic single-nucleotide variants (SNVs) have been studied extensively, the contribution of copy number variants (CNVs) to HM pathogenesis remains underexplored. Previous studies have primarily focused on known HM gene loci. This study presents the first whole-exome-wide comprehensive investigation of CNVs in HM, employing an integrative, multi-platform approach to identify CNVs present in cases with suspected FHM and to explore their potential biological relevance. We employed three independent bioinformatic tools for CNV detection: gCNV, CNVkit, and CNVPartition. gCNV was used to detect CNVs in 182 FHM cases and 500 UKBiobank (UKBB) non-neurological controls. CNVs identified by gCNV were then cross-validated using CNVkit and CNVPartition. Variants present in controls were excluded, and cross-platform concordance defined a finalised list of case-specific CNVs. Pathway enrichment analyses were also conducted to investigate the functional context of affected genes. We identified 27 high-confidence CNVs exclusively in the FHM cases, several intersecting with known pathogenic variants catalogued in ClinVar, including loci around the ATP1A2 gene and within the PRRT2 gene. MLPA validation confirmed a few gCNV calls. Enrichment analyses highlighted involvement of the Signalling by Rho GTPases and RNA Polymerase II Transcription pathways, suggesting mechanistic links to FHM pathogenesis. The identification of high-confidence, case-specific CNVs, including those impacting well-known FHM-associated genes such as ATP1A2 and PRRT2, advances our understanding of the genetic factors contributing to FHM. The enrichment of these CNVs in pathways related to Rho GTPase signalling and RNA Polymerase II transcription suggests new biological mechanisms underlying the disorder. These insights pave the way for improved genetic diagnosis and future research into targeted therapies for FHM.