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Articles by I. N Ferrier
Total Records ( 2 ) for I. N Ferrier
  M. L Hamshere , E. K Green , I. R Jones , L Jones , V Moskvina , G Kirov , D Grozeva , I Nikolov , D Vukcevic , S Caesar , K Gordon Smith , C Fraser , E Russell , G Breen , D St Clair , D. A Collier , A. H Young , I. N Ferrier , A Farmer , P McGuffin , Holmans Wellcome Trust Case Control Consortium , M. J Owen , M. C O'Donovan and N. Craddock
 

Background

Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological–genetic research.

Aims

To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case–control bipolar disorder sample.

Method

We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant at P<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type.

Results

The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42x10–7). Biological systems implicated included gamma amniobutyric acid (GABA)A receptors. Genes having at least one associated polymorphism at P<10–4 included B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and CDH12.

Conclusions

Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes.

  K. A. N Macritchie , A. J Lloyd , M. E Bastin , K Vasudev , P Gallagher , R Eyre , I Marshall , J. M Wardlaw , I. N Ferrier , P. B Moore and A. H. Young
 

Background

Abnormal diffusion parameters are reported in specific brain regions and white matter tracts in bipolar disorder.

Aims

To investigate whether these abnormalities are generalised, and thus evident in large regions of white matter.

Method

Diffusion parameters were measured at several regions in the corpus callosum and in deep/periventricular white matter in 28 currently euthymic patients with bipolar disorder and controls. White matter hyperintensity loads were assessed.

Results

Comparing the whole data-sets using the sign test, in the group with bipolar disorder, mean diffusivity was greater at all 15 sites (P<0.001) and fractional anisotropy was reduced at 13 (P<0.01). The effect of diagnosis was significant for callosal mean diffusivity and fractional anisotropy and for deep/periventricular mean diffusivity (MANCOVA). Comparing individual regions (Mann–Whitney U-test), prefrontal and periventricular mean diffusivity were significantly increased; callosal and occipital fractional anisotropy were significantly reduced. Former substance use and lithium were possible confounding factors. Periventricular white matter hyperintensities were associated with significantly increased periventricular mean diffusivity in individuals with bipolar disorder.

Conclusions

Generalised white matter microstructural abnormalities may exist in bipolar disorder, possibly exacerbated by past substance use and ameliorated by lithium.

 
 
 
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