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- Massat, Isabelle, et al.
(author)
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Positive association of dopamine D2 receptor polymorphism with bipolar affective disorder in a European Multicenter Association Study of affective disorders
- 2002
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In: American Journal of Medical Genetics. - : Wiley. - 0148-7299 .- 1096-8628. ; 114:2, s. 177-85
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Journal article (peer-reviewed)abstract
- Convincing evidence for a genetic component in the etiology of affective disorders (AD), including bipolar affective disorder (BPAD) and unipolar affective disorder (UPAD), is supported by traditional and molecular genetic studies. Most arguments lead to the complex inheritance hypothesis, suggesting that the mode of inheritance is probably not Mendelian but most likely oligogenic (or polygenic) and that the contribution of genes could be moderate or weak. The purpose of the present European multicenter study (13 centers) was to test the potential role in BPAD and UPAD of two candidate dopaminergic markers, DRD2 and DRD3, using a case-control association design. The following samples were analyzed for DRD2: 358 BPAD/358 control (C) and 133 UPAD/ 133 C subjects, and for DRD3: 325 BPAD/ 325 C and 136 UPAD/136 C subjects. Patients and controls were individually matched for sex, age ( plus minus five years) and geographical origin. Evidence for significant association between BPAD and DRD2 emerged, with an over-representation of genotype 5-5 (P=0.004) and allele 5 (P=0.002) in BPAD cases compared to controls. No association was found for DRD2 in UPAD, and for DRD3 neither in BPAD or UPAD. Our results suggest that the DRD2 microsatellite may be in linkage disequilibrium with a nearby genetic variant involved in the susceptibility to BPAD. Our large European sample allowed for replicating of some previous reported positive findings obtained in other study populations.
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2. |
- Visscher, Peter M., et al.
(author)
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Genetic survival analysis of age-at-onset of bipolar disorder : evidence for anticipation or cohort effect in families
- 2001
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In: Psychiatric Genetics. - : Lippincott Williams & Wilkins. - 0955-8829 .- 1473-5873. ; 11:3, s. 129-137
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Journal article (peer-reviewed)abstract
- Age-at-onset (AAO) in a number of extended families ascertained for bipolar disorder was analysed using survival analysis techniques, fitting proportional hazards models to estimate the fixed effects of sex, year of birth, and generation, and a random polygenic genetic effect. Data comprised the AAO (for 171 affecteds) or age when last seen (ALS) for 327 unaffecteds, on 498 individuals in 27 families. ALS was treated as the censored time in the statistical analyses. The majority of individuals classified as affected were diagnosed with bipolar I and II (n = 103) or recurrent major depressive disorder (n = 68). In addition to the significant effects of sex and year of birth, a fitted ‘generation’ effect was highly significant, which could be interpreted as evidence for an anticipation effect. The risk of developing bipolar or unipolar disorder increased twofold with each generation descended from the oldest founder. However, although information from both affected and unaffected individuals was used to estimate the relative risk of subsequent generations, it is possible that the results are biased because of the ‘Penrose effect’. Females had a twofold increased risk in developing depressive disorder relative to males. The risk of developing bipolar or unipolar disorder increased by approximately 4% per year of birth. A polygenic component of variance was estimated, resulting in a ‘heritability’ of AAO of approximately 0.52. In a family showing strong evidence of linkage to chromosome 4p (family 22), the ‘affected haplotype’ increased the relative risk of being affected by a factor of 46. In this family, there was strong evidence of a time trend in the AAO. When either year of birth or generation was fitted in the model, these effects were highly significant, but neither was significant in the presence of the other. For this family, there was no increase in trinucleotide repeats measured by the repeat expansion detection method in affected individuals compared with control subjects. Proportional hazard models appear appropriate to analyse AAO data, and the methodology will be extended to map quantitative trait loci (QTL) for AAO.
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