Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank.
Tom ChambersValentina Escott-PriceSophie E LeggeEmily BakerKrish D SinghJames T R WaltersXavier CaserasRichard J L AnneyPublished in: Molecular psychiatry (2022)
Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h 2 SNP = 50.6%), showing moderate genetic homogeneity across lobes (h 2 SNP from 35.4% to 57.1%; mean genetic correlation between lobes r g ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.
Keyphrases
- genome wide
- copy number
- dna methylation
- bipolar disorder
- autism spectrum disorder
- gene expression
- genome wide association study
- mental health
- major depressive disorder
- resting state
- oxidative stress
- poor prognosis
- machine learning
- functional connectivity
- transcription factor
- depressive symptoms
- white matter
- high density
- genetic diversity
- genome wide identification
- deep learning
- binding protein
- big data
- brain injury