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Department of Psychological Medicine, Wales College of Medicine, Cardiff University, Wales, UK
Biostatistics and Bioinformatics Unit, Wales College of Medicine, Cardiff University, Wales, UK
Division of Neuroscience, University of Birmingham, Queen Elizabeth Psychiatric Hospital, Birmingham, Wales, UK
Department of Psychiatry, University of Newcastle, Wales, UK
Department of Psychological Medicine, Wales College of Medicine, Cardiff University, Wales, UK
Division of Neuroscience, University of Birmingham, Queen Elizabeth Psychiatric Hospital, Birmingham, Wales, UK
Department of Psychological Medicine, Wales College of Medicine, Cardiff University, Cardiff, Wales, UK
Correspondence: Professor Nick Craddock, Department of Psychological Medicine, Henry Wellcome Building, Wales College of Medicine, Cardiff University, Heath Park, Cardiff CF4 4XN, UK. Tel: +44 (0)2920 744663; fax: +44 (0) 22920 746554; e-mail: craddockn{at}cardiff.ac.uk
Declaration of interest N.C. and M.J.O. are consultants to GlaxoSmithKline and have received grant funding and honoraria from GlaxoSmithKline, AstraZeneca and Eli Lilly. M.C. O'D., A.H.Y., L.J. and G.K. have received honoraria from GlaxoSmithKline, AstraZeneca and Eli Lilly. G.K. has received grant funding from Janssen. Funding detailed in Acknowledgements.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Aims To replicate this finding.
Method We genotyped the Val66Met polymorphism in our UK White bipolar case-control sample (n=3062).
Results We found no overall evidence of allele or genotype association. However, we found association with disease status in the subset of 131 individuals that had experienced rapid cycling at some time (P=0.004). We found a similar association on re-analysis of our previously reported family-based association sample (P < 0.03, one-tailed test).
Conclusions Variation at the Val66Met polymorphism of BDNF does not play a major role in influencing susceptibility to bipolar disorder as a whole, but is associated with susceptibility to the rapid-cycling subset of the disorder.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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METHOD |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Probands with bipolar disorder
Individuals were recruited through mental health services in England and
Wales and met DSM-IV (American Psychiatric
Association, 1994) criteria for bipolar I disorder
(n=864, 37% male, mean age=48 years (s.d.=13)) or bipolar II disorder
(n=98, 39% male, mean age=52 years (s.d.=13)). Diagnoses were made by
the consensus lifetime best-estimate method
(Leckman et al, 1982)
on the basis of all available information, including a semi-structured
interview (Schedules for Clinical Assessment in Neuropsychiatry, SCAN;
Wing et al, 1990),
Diagnostic Interview for Genetic Studies (DIGS; Nurnburger et al,
1994) or Schedule for Affective Disorders and Schizophrenia - Lifetime Version
(SADS-L; Endicott & Spitzer,
1978) and review of psychiatric case records and an OPCRIT
checklist (McGuffin et al,
1991). Key clinical variables relating to psychosis were rated
using the Bipolar Affective Disorder Dimensional Scale (BADDS;
Craddock et al, 2004).
Our sample of people with bipolar disorder had a lifetime occurrence of one or
more psychotic features in 56% of those with bipolar I disorder and 18% of
those with bipolar II disorder. Other key clinical variables were rated
according to written operational guidelines in use by our group and available
on request from the authors. These included age at onset of impairment by
illness (those with bipolar I disorder, mean age at onset=26 years (s.d.=10);
those with bipolar II disorder, mean age at onset=30 years (s.d.=13)), family
history of psychiatric illness (history of psychiatric illness in first- or
second-degree relative: those with bipolar I disorder 71%; those with bipolar
II disorder, 76%), definite lifetime occurrence of rapid cycling (defined as
at least one period of 12 months during which four or more distinct episodes
of major mood disorder occurred; present in 13% of those with bipolar I and
18% of those with bipolar II disorder) and definite lifetime occurrence of
postpartum triggering of psychotic major affective episodes (present in 14% of
those with bipolar I and 3% those with bipolar II disorder). Team members
involved in the interview, rating and diagnostic procedures were either a
fully trained research psychologist or a psychiatrist. Interrater reliability
was high. This was formally assessed using 20 cases and resulted in a mean
kappa statistic of 0.85 for DSM-IV diagnosis. Mean kappa for the key clinical
variables ranged from 0.81 to 0.99. Formative clinical team reliability
meetings took place weekly.
Control individuals
Controls (n=2100, 47% male, mean age=42.2 years (s.d.=11.2)), all
White and of UK origin, were from three sources:
Genotyping
The Val66Met polymorphism was genotyped using a fluorescence polarisation
primer extension assay (Chen et
al, 1999), using the AcycloPrime Kit (Perkin Elmer,
Wellesley, Massachusetts, USA) according to the manufacturer's instructions
and an Analyst genotyping platform (LJL Biosystems, Sunnyvale, California,
USA).
Statistics
Case-control data
Departure from Hardy-Weinberg equilibrium was tested using
2 goodness-of-fit test. Tests for differences between allele
and genotype frequencies were performed using Pearson 2
analysis of contingency tables. Two-tailed P values are reported. In
addition to analysing data according to diagnostic group we also performed
analyses in the following subsets of patients with bipolar disorder: (a)
lifetime presence of psychotic features; (b) predominantly mood-incongruent
psychotic features; (c) age at onset of impairment by illness before 20 years;
(d) lifetime occurrence of rapid cycling; (e) lifetime occurrence of
postpartum triggering of episodes and family history of psychiatric illness
(i.e. bipolar affective puerperal psychosis); (f) family history of
psychiatric illness in a first- or second-degree relative. Adjustment for
multiple testing was made using Bonferroni correction.
Re-analysis of family-based association sample
A specific hypothesis was tested in a phenotypic subset of the previously
published UK family-based association sample
(Sklar et al, 2002) using the transmission disequilibrium test
(Spielman et al,
1993). Both one- and two-tailed P values are
provided.
Power estimation
The power of our full sample to detect an effect of a magnitude similar to
those previously reported in adult samples
(Neves-Pereira et al,
2002; Sklar et al,
2002) was estimated using the Genetic Power Calculator
(Purcell et al, 2003)
under the assumption of a multiplicative model. The power in the bipolar I
disorder sample at a critical significance level, P < 0.05,
exceeded 92% for an effect of odds ratios (ORs) > 1.3. For the effect size
estimated in our own bipolar I family-based association sample (OR=1.19;
Sklar et al, 2002)
our power to replicate this effect in the present study at this test size was
68%.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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For the subset of 131 patients with bipolar disorder who had experienced at least one period of 12 months that met DSM-IV criteria for rapid cycling, we found a significantly increased frequency of the Val allele compared with controls (88.2% v. 81.0%, OR=1.74, 95% CI 1.19-2.56, P=0.004 uncorrected for multiple testing, P=0.036 with Bonferroni correction for testing the main diagnostic categories and six subtypes, see Table 1). We found no evidence for association for any of the other subtypes examined (data not shown).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Rapid-cycling bipolar disorder
One reason for discrepancy between studies might be phenotypic
heterogeneity. Therefore we undertook a set of analyses within phenotypic
subsets of our patient sample to explore the possibility that variation at the
Val66Met polymorphism was associated with one or more specific aspects of the
range of phenotypic complexity commonly seen in bipolar disorder. We found
significant evidence that lifetime occurrence of at least one 12-month period
of rapid cycling was associated with possession of the common Val allele
(nominal significance P=0.0040), a finding that remained significant
after Bonferroni correction (P=0.036).
There was evidence for a dosage effect of the Val allele. When comparing the effect sizes, as measured by the genotypic ORs, the estimated effect size was larger for the Val/Val homozygote (OR=5.01, 95% CI 0.69-36.43) than for the Val/Met heterozygote (OR=2.99, 95% CI 0.40-22.28).
Our own UK family-based sample of 145 parent-offspring triads was included in the first of the family-based association studies to show evidence for association (Sklar et al, 2002); our sample showed a non-significant modest excess of transmission of the Val allele to affected offspring. When we tested for the presence of an effect of rapid cycling in our original family-based association sample, we found evidence for the same association of the Val allele with rapid cycling. There were only seven informative transmissions to bipolar probands with lifetime rapid cycling, but among these the Val allele was transmitted on six occasions and the Met allele on only one occasion (data not shown). Although the number of observations was small, this approached conventional levels of statistical significance (P < 0.059) under a two-tailed test. Given that a specific direction of effect was hypothesised (i.e. over-transmission of the Val allele) one can make a case for use of a one-tailed test. This was significant at P < 0.03.
It is of great interest that a similar finding has been observed in an independent sample. Müller et al (2004, 2006) have examined phenotypic subtypes within their family-based association sample in which they originally reported association (Neves-Pereira et al, 2002) and found that rapid-cycling cases explained the association originally observed. This provides confidence that our finding is robust and generalisable to other samples of European origin.
Within our study we have used the DSM-IV (American Psychiatric Association, 1994) definition of definite rapid cycling: four or more distinct episodes of major affective disorder within a 12-month period such that consecutive distinct episodes are either switches of pole or are separated by at least a 2-month period of euthymia. A participant was classified as a member of the lifetime rapid-cycling subset if they had ever experienced a 12-month period during which the DSM-IV criteria for rapid cycling were fulfilled. The DSM-IV definition is similar to the original definition of rapid cycling proposed by Dunner & Fieve (1974), but there has been a wide range of variations in definition used in the research and clinical literature (Maj et al, 1999; Mackin & Young, 2004) and there is little consistency in the literature regarding a unified core concept of rapid cycling or what features constitute the essence of rapid cycling (MacKinnon et al, 2003). An important question, therefore, arises as to what specific features of bipolar illness are captured by the definition of rapid cycling used. Observed genetic association might be strongest for one or more phenotypic variables that are components of the rapid cycling concept or that have been described to distinguish patients with rapid cycling from those with non-rapid cycling. Such possibilities include gender, episode frequency, age at onset, duration of illness or severity of episodes. However, post hoc consideration of these variables using a logistic regression model failed to demonstrate any variable that was superior to the rapid-cycling category as a predictor (data not shown). Further studies of large data-sets will be required to explore the core clinical features of rapid mood changes associated with variation at BDNF.
Methodological issues
In any case-control study spurious differences between cases and controls
that are unrelated to disease status can be caused by the presence of
so-called population structure, which may result in differential sampling of
cases and controls from genetically distinct sub-populations. However, we can
be confident that this is unlikely to be the cause of our findings because:
(a) both case and control samples were from the UK White population; (b)
allele frequencies were similar between the three control groups and genotype
distributions were consistent with Hardy-Weinberg equilibrium for the groups
separately and pooled together, suggesting absence of substantial variation in
genotype frequency across the population; (c) we observed a similar effect in
our family-based sample which is robust to population stratification;
(d) a similar effect has been observed in an independent family-based sample
(Müller et al,
2004,
2006), which again is robust
to population stratification.
In case-control studies it is important that appropriate controls are chosen for the patient sample. The ideal is to have an epidemiological design in which each control is sampled from precisely the same population as the patients, with all relevant variables being measured and allowed for in analysis. This is rarely achievable. In our study we have used three different sets of controls sampled in different ways. The different sets are similar in the distribution of BDNF alleles and genotypes, which gives confidence that the differences observed between (pooled) controls and the cases of rapid-cycling bipolar disorder are phenotype-driven rather than a spurious effect of an unusual control set. The controls may either be screened to exclude illness (‘supernormal’) or unscreened. The former is generally more powerful and the latter more useful for estimating population-level effects. In the current study control sets, blood donors and members of the 1958 birth cohort were unscreened whereas those recruited from a family practitioner clinic were screened. For bipolar disorder, which has a population lifetime risk of approximately 1%, the use of unscreened controls has a negligible effect on power (Moskvina et al, 2005).
Brain-derived neurotrophic factor and mood disorder
Brain-derived neurotrophic factor, a member of the neurotrophin
superfamily, is a highly plausible candidate for involvement in the
pathogenesis of mood disorder by virtue of its function. Neurotrophins are
synthesised in neurons as proforms that can be cleaved intra- or
extracellularly and both their synthesis and secretion depends on neuronal
activity. BDNF plays an important role in promoting and modifying growth,
development and survival of neuronal populations and, in the mature nervous
system, it is involved in activity-dependent neuronal plasticity
(Duman, 1999). These are
processes central to the synaptic plasticity hypothesis of mood disorder,
which focuses on the functional and structural changes induced by stress and
antidepressants at the synaptic level. It has been specifically hypothesised
that mania may be caused by overactivity of central BDNF function
(Tsai, 2004).
The BDNF gene lies in the chromosome 11p13 region, which has been implicated in some linkage studies of bipolar disorder but not in meta-analyses of linkage studies (reviewed in Green & Craddock, 2004). Thus there is a modest degree of genetic positional evidence to strengthen the functional support for potential BDNF involvement in bipolar disorder. Consistent with the strong evolutionary conservation of the BDNF coding sequence across species, only one common, non-conservative polymorphism in the human BDNF gene has been identified, a single-nucleotide polymorphism at nucleotide 196 within the 5' pro-BDNF sequence that causes an amino acid substitution of valine to methionine at codon 66 (Val66Met). This is the polymorphism investigated in the current study.
Implications
Our findings may help to explain some of the variability observed between
studies of the BDNF gene in bipolar disorder. Samples of individuals
with DSM-IV bipolar disorder may vary substantially in the spectrum of
severity of illness and clinical features. For any locus that influences the
clinical phenotype rather than simply the overall probability of being in the
diagnostic category, there will be variation between sample sets for the
estimated effect sizes of the locus. It is important that existing samples
that have shown no overall evidence for association between bipolar disorder
and variation at BDNF are re-analysed to search for a specific effect
with phenotypes related to rapid cycling.
Identification of allelic association is an important step towards implicating a gene within the pathogenesis of a disorder but does not constitute proof of a causal mechanism. The Val66Met polymorphism lies within the proBDNF region of the gene and is not, therefore, translated into the final mature BDNF protein product. However, there is cross-species conservation of the precursor portion of proBDNF. This is consistent with a potential functional importance for this region, perhaps as a signal peptide with an influence on intracellular trafficking and activity-dependent secretion of BDNF (Egan et al, 2003). In vitro studies demonstrated that the Met allele was associated with impaired intracellular trafficking and regulated secretion (Egan et al, 2003). This would be consistent with the hypothesis of BDNF overactivity in mania (Tsai, 2004). Alternatively the polymorphism may be in linkage disequilibrium with one or more pathogenically relevant variants lying close to this genetic location. Further genetic and biological studies are required to differentiate between these possibilities.
In summary, within the largest bipolar disorder genetic association sample studied to date we have found no evidence that variation at the common Val66Met polymorphism of the BDNF gene is associated with susceptibility to bipolar disorder as a whole. However, we obtained significant evidence that the common Val allele is associated with susceptibility to rapid cycling at some stage during illness.
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Clinical Implications and Limitations |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Received for publication February 10, 2005. Revision received April 7, 2005. Accepted for publication April 11, 2005.
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| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Psychiatric Bulletin | Advances in Psychiatric Treatment | All RCPsych Journals |
