Oral Presentation 9th GeneMappers Conference 2012

Genetic and epigenetic variation in future risk of bipolar disorder: a longitudinal study in a high-risk cohort (#16)

Janice M Fullerton 1 2 , Kerrie D Pierce 1 , Gloria Roberts 3 4 , Florence Levy 3 4 , Rhoshel Lenroot 1 3 , Melissa Green 3 5 , Andrew Frankland 3 4 , Adam Wright 3 4 , Claire McCormack 3 4 , Phoebe Lau 3 4 , Peter R Schofield 1 2 , Philip B Mitchell 3 4
  1. Neuroscience Research Australia, Sydney, NSW, Australia
  2. School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
  3. School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
  4. Blackdog Institute, Sydney, NSW, Australia
  5. UNSW Research Unit for Schizophrenia Epidemiology, St Vincent's Hospital, Sydney, NSW, Australia

The molecular, biological, and neuropsychological factors associated with conversion to bipolar disorder may be dissected through longitudinal studies of high-risk individuals. We are collecting a cohort of young (12-30 year old) at-risk individuals with at least one first degree relative with BPI disorder, and controls with no family history of mental illness. Structural and functional brain imaging, peripheral blood samples, and structured clinical and neuropsychological assessments will be collected during the study. Genetic and epigenetic analysis will be conducted to identify molecular risk factors which are associated with later conversion to bipolar disorder, or modulating neuropsychological endophenotypes which may precede clinical diagnosis.

We selected 99 SNPs (70 genes) on the basis of prior evidence of association1,2 , differential mRNA expression in bipolar disorder3 or genotype effects on MRI outcomes4,5 , and compared allele frequencies between at-risk (n=135) and control groups (n=109) using PLINK. For epigenetic analysis, 47 at-risk individuals and 47 controls were analysed for methylation differences across the genome via the Illumina Methylation 450K chip.

We found significant association (p<5.0×10-4; corrected p<0.05) with SNPs in DRD2, ZMIZ1, NGF, NFIX and RASIP1. Follow-up analysis of the DRD2 signal revealed a 3 SNP haplotype which is overrepresented in at-risk individuals compared to controls (Omnibus χ2=18.45, p=9.86×10-5; Freq(CCG)= 0.839 vs 0.682; Freq(TAT)= 0.127 vs 0.281 respectively), which likely leads to increased DRD2-short splice isoform6 . We found 179 methylation sites which differed significantly between at-risk and control groups (p< 2.4×10-5; FDR<0.05), including CpG sites 480bp upstream of the CACNB2 gene on chromosome 10p12, in the 5’UTR of CSNK1D on chromosome 17, and in intron 1 of OPCML on chromosome 11.

Our results indicate that variation in both the genome and epigenome may contribute to increased risk of bipolar disorder. Further analysis will be conducted longitudinally, as at-risk individuals convert to bipolar disorder in subsequent years
  1. Piletz et al. Psychiatr Genet. 2011 Apr;21(2):57-68
  2. Sklar et al. Nat Genet 2011 Oct; 10(43):977-985
  3. Patel et al. Am J Med Genet 2010 153B(4):850-77
  4. Scharinger et al. Neuroimage. 2010 Nov 15;53(3):810-21
  5. Meyer-Lindenberg Dialogues in clinical Neuroscience 2010. 12:449-456
  6. Zhang et al. PNAS. 2007. 18:20552-20557