medRxivGenetic & Genomic MedicinePreprint
Insights into Essential Tremor and Essential Tremor-Plus from Common Variants
Miranda MedeirosiD, Dylan GharibianiD, Patrick A. DioniD, Guy Armand RouleauiD
Abstract
IntroThe heterogeneity of Essential Tremor (ET) complicates how it is diagnosed and studied. ET-Plus is a concept proposed to help explain the overlap of ET clinical features with soft signs of other neurological disorders. We aimed to better understand ET by comparing brain maps informed by ET common variant to those derived from phenotypes involved in ET-Plus. A further goal was to enhance the diagnostic precision of ET by accounting for shared neurobiological signals between ET and ET-Plus-related phenotypes. MethodsPhenotype variant association mapping to the brain was done for ET, Parkinsons disease (PD), dystonia, and cognition across adult mouse whole brain and cerebellum spatial transcriptomic data through gsMap. Separately, ET genome-wide association study (GWAS) summary statistics were conditioned on PD and cognition to account for shared genetic signals. Using both raw and conditioned GWASes, ET polygenic risk scores (PRS) were calculated across patient cohorts and controls, and their respective ability to classify ET at the 90th percentile was compared using McNemars test. ResultsSpatial mappings of GWAS signals revealed many shared associations between phenotypes. The raw ET PRS model preformed 1.33% (95% CI: [0.30% - 2.35%]; p = 0.0129) better than the conditioned ET PRS model. ConclusionWe lack the ability to decern ET from phenotypes involved in ET-Plus using existing common variant disease associations. Efforts to isolate a core genetic signal for ET by de-noising shared associations reduced the accuracy of patient classification. A more effective strategy to studying ET may be to leverage its heterogeneity rather than attempt to isolate it.
- organism: mouse
- assay: spatial transcriptomics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 0
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