Association of Gene Expression and Tremor Network Structure

Abstract

AbstractBackgroundTranscriptomic changes in the essential tremor (ET)–associated cerebello‐thalamo‐cortical “tremor network” and their association to brain structure have not been investigated.ObjectiveThe aim was to characterize molecular changes associated with network‐level imaging‐derived phenotypes (IDP) found in ET.MethodsWe performed an imaging‐transcriptomic study in British adults using imaging‐genome‐wide association study summary statistics (UK Biobank “BIG40” cohort; n = 33,224, aged 40–69 years). We imputed imaging‐transcriptomic associations for 184 IDPs and analyzed functional enrichment of gene modules and aggregate network‐level phenotypes. Validation was performed in cerebellar‐tissue RNA‐sequencing data from ET patients and controls (n = 55).ResultsAmong 237,896 individual predicted gene expression levels for 6063 unique genes/transcripts, we detected 2269 genome‐wide significant associations (Bonferroni P < 2.102e‐7, 0.95%). These were concentrated in intracellular volume fraction measures of white matter pathways and in genes with putative links to tremor (MAPT, ARL17A, KANSL1, SPPL2C, LRRC37A4P, PLEKHM1, and FMNL1). Whole‐tremor‐network cortical thickness was associated with a gene module linked to mitochondrial organization and protein quality control (r = 0.91, P = 2e‐70), whereas white‐gray T1‐weighted magnetic resonance imaging (MRI) contrast in the tremor network was associated with a gene module linked to sphingolipid synthesis and ethanolamine metabolism (r = −0.90, P = 2e‐68). Imputed association effect sizes and RNA‐sequencing log‐fold change in the validation dataset were significantly correlated for cerebellar peduncular diffusion MRI phenotypes, and there was a close overlap of significant associations between both datasets for gray matter phenotypes (χ2 = 6.40, P = 0.006).ConclusionsThe identified genes and processes are potential treatment targets for ET, and our results help characterize molecular changes that could in future be used for patient treatment selection or prognosis prediction. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.