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Articles by N Craddock
Total Records ( 4 ) for N Craddock
  C. M Lewis , M. Y Ng , A. W Butler , S Cohen Woods , R Uher , K Pirlo , M. E Weale , A Schosser , U. M Paredes , M Rivera , N Craddock , M. J Owen , L Jones , I Jones , A Korszun , K. J Aitchison , J Shi , J. P Quinn , A MacKenzie , P Vollenweider , G Waeber , S Heath , M Lathrop , P Muglia , M. R Barnes , J. C Whittaker , F Tozzi , F Holsboer , M Preisig , A. E Farmer , G Breen , I. W Craig and P. McGuffin
  Objective

Studies of major depression in twins and families have shown moderate to high heritability, but extensive molecular studies have failed to identify susceptibility genes convincingly. To detect genetic variants contributing to major depression, the authors performed a genome-wide association study using 1,636 cases of depression ascertained in the U.K. and 1,594 comparison subjects screened negative for psychiatric disorders.

Method

Cases were collected from 1) a case-control study of recurrent depression (the Depression Case Control [DeCC] study; N=1346), 2) an affected sibling pair linkage study of recurrent depression (probands from the Depression Network [DeNT] study; N=332), and 3) a pharmacogenetic study (the Genome-Based Therapeutic Drugs for Depression [GENDEP] study; N=88). Depression cases and comparison subjects were genotyped at Centre National de Génotypage on the Illumina Human610-Quad BeadChip. After applying stringent quality control criteria for missing genotypes, departure from Hardy-Weinberg equilibrium, and low minor allele frequency, the authors tested for association to depression using logistic regression, correcting for population ancestry.

Results

Single nucleotide polymorphisms (SNPs) in BICC1 achieved suggestive evidence for association, which strengthened after imputation of ungenotyped markers, and in analysis of female depression cases. A meta-analysis of U.K. data with previously published results from studies in Munich and Lausanne showed some evidence for association near neuroligin 1 (NLGN1) on chromosome 3, but did not support findings at BICC1.

Conclusions

This study identifies several signals for association worthy of further investigation but, as in previous genome-wide studies, suggests that individual gene contributions to depression are likely to have only minor effects, and very large pooled analyses will be required to identify them.

  D Grozeva , G Kirov , D Ivanov , I. R Jones , L Jones , E. K Green , D. M St Clair , A. H Young , N Ferrier , A. E Farmer , P McGuffin , P. A Holmans , M. J Owen , M. C O'Donovan , N Craddock and for the Wellcome Trust Case Control Consortium
 

Context  Recent studies suggest that copy number variation in the human genome is extensive and may play an important role in susceptibility to disease, including neuropsychiatric disorders such as schizophrenia and autism. The possible involvement of copy number variants (CNVs) in bipolar disorder has received little attention to date.

Objectives  To determine whether large (>100 000 base pairs) and rare (found in <1% of the population) CNVs are associated with susceptibility to bipolar disorder and to compare with findings in schizophrenia.

Design  A genome-wide survey of large, rare CNVs in a case-control sample using a high-density microarray.

Setting  The Wellcome Trust Case Control Consortium.

Participants  There were 1697 cases of bipolar disorder and 2806 nonpsychiatric controls. All participants were white UK residents.

Main Outcome Measures  Overall load of CNVs and presence of rare CNVs.

Results  The burden of CNVs in bipolar disorder was not increased compared with controls and was significantly less than in schizophrenia cases. The CNVs previously implicated in the etiology of schizophrenia were not more common in cases with bipolar disorder.

Conclusions  Schizophrenia and bipolar disorder differ with respect to CNV burden in general and association with specific CNVs in particular. Our data are consistent with the possibility that possession of large, rare deletions may modify the phenotype in those at risk of psychosis: those possessing such events are more likely to be diagnosed as having schizophrenia, and those without them are more likely to be diagnosed as having bipolar disorder.

  N Craddock , M. C O`Donovan and M. J. Owen
 

As a result of improving technologies and greatly increased sample sizes, the last 2 years has seen unprecedented advances in identification of specific genetic risk factors for psychiatric phenotypes. Strong genetic associations have been reported at common polymorphisms within ANK3 and CACNA1C in bipolar disorder and ZNF804A in schizophrenia and a relatively specific association between common variation in GABAA receptor genes and cases with features of both bipolar disorder and schizophrenia. Further, the occurrence of rare copy number variants (CNVs) has been shown to be increased in schizophrenia compared with controls. These emerging data provide a powerful resource for exploring the relationship between psychiatric phenotypes and can, and should, be used to inform conceptualization, classification, and diagnosis in psychiatry. It is already clear that, in general, genetic associations are not specific to one of the traditional diagnostic categories. For example, variation at ZNF804A is associated with risk of both bipolar disorder and schizophrenia, and some rare CNVs are associated with risk of autism and epilepsy as well as schizophrenia. These data are not consistent with a simple dichotomous model of functional psychosis and indicate the urgent need for moves toward approaches that (a) better represent the range of phenotypic variation seen in the clinical population and (b) reflect the underlying biological variation that gives rise to the phenotypes. We consider the implications for models of psychosis and the importance of recognizing and studying illness that has prominent affective and psychotic features. We conclude that if psychiatry is to translate the opportunities offered by new research methodologies, we must finally abandon a 19th-century dichotomy and move to a classificatory approach that is worthy of the 21st century.

  L Jones , J Scott , C Cooper , L Forty , K. G Smith , P Sham , A Farmer , P McGuffin , N Craddock and I. Jones
 

Background

Only some women with recurrent major depressive disorder experience postnatal episodes. Personality and/or cognitive styles might increase the likelihood of experiencing postnatal depression.

Aims

To establish whether personality and cognitive style predicts vulnerability to postnatal episodes over and above their known relationship to depression in general.

Method

We compared personality and cognitive style in women with recurrent major depressive disorder who had experienced one or more postnatal episodes (postnatal depression (PND) group, n=143) with healthy female controls (control group, n=173). We also examined parous women with recurrent major depressive disorder who experienced no perinatal episodes (non-postnatal depression (NPND) group, n=131).

Results

The PND group had higher levels of neuroticism and dysfunctional beliefs, and lower self-esteem than the control group. However, there were no significant differences between the PND and NPND groups.

Conclusions

Established personality and cognitive vulnerabilities for depression were reported by women with a history of postnatal depression, but there was no evidence that any of these traits or styles confer a specific risk for the postnatal onset of episodes.

 
 
 
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