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. 2009 Dec;50(12):5818-27.
doi: 10.1167/iovs.09-3928. Epub 2009 Aug 6.

Plasma complement components and activation fragments: associations with age-related macular degeneration genotypes and phenotypes

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Plasma complement components and activation fragments: associations with age-related macular degeneration genotypes and phenotypes

Robyn Reynolds et al. Invest Ophthalmol Vis Sci. 2009 Dec.

Abstract

Purpose: Several genes encoding complement system components and fragments are associated with age-related macular degeneration (AMD). This study was conducted to determine whether alterations in circulating levels of these markers of complement activation and regulation are also independently associated with advanced AMD and whether they are related to AMD genotypes.

Methods: Plasma and DNA samples were selected from individuals in our AMD registry who had progressed to or developed the advanced stages of AMD, including 58 with geographic atrophy and 62 with neovascular disease. Subjects of similar age and sex, but without AMD, and who did not progress were included as controls (n = 60). Plasma complement components (C3, CFB, CFI, CFH, and factor D) and activation fragments (Bb, C3a, C5a, iC3b, and SC5b-9) were analyzed. DNA samples were genotyped for seven single-nucleotide polymorphisms in six genes previously shown to be associated with AMD: CFB, CFH, C2, C3, and CFI and the LOC387715/ARMS2 gene region. The association between AMD and each complement biomarker was assessed by using logistic regression, controlling for age, sex, and proinflammatory risk factors: smoking and body mass index (BMI). Functional genomic analyses were performed to assess the relationship between the complement markers and genotypes. Concordance, or C, statistics were calculated to assess the effect of complement components and activation fragments in an AMD gene-environment prediction model.

Results: The highest quartiles of Bb and C5a were significantly associated with advanced AMD, when compared with the lowest quartiles. In multivariate models without genetic variants, the odds ratio (OR) for Bb was 3.3 (95% confidence interval [CI] = 1.3-8.6), and the OR for C5a was 3.6 (95% CI = 1.2-10.3). With adjustment for genetic variants, these ORs were substantially higher. The alternative pathway regulator CFH was inversely associated with AMD in the model without genotypes (OR = 0.3; P = 0.01). Positive associations were found between BMI and plasma C3, CFB, CFH, iC3b, and C3a. There were also significant associations between C5a fragment and LOC387715/ARMS2 and C3 genotypes (P for trend = 0.02, 0.04), respectively. C statistics for models with behavioral and genetic factors increased to 0.94 +/- 0.20 with the addition of C3a, Bb, and C5a.

Conclusions: Increased levels of activation fragments Bb and C5a are independently associated with AMD. Higher BMI is related to increased levels of complement components. C5a is associated with AMD genotypes. C statistics are stronger with the addition of C3a, Bb, and C5a in predictive models. Results implicate ongoing activation of the alternative complement pathway in AMD pathogenesis.

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Figures

Figure 1
Figure 1
Risk scores for cases and controls based on age, sex, smoking, BMI, seven genetic variants, and C3a, Bb, and C5a fragments.

References

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