Plasma complement components and activation fragments: associations with age-related macular degeneration genotypes and phenotypes.
Plasma complement components and activation fragments: associations with age-related macular degeneration genotypes and phenotypes.
复制标题
DOI：
10.1167/iovs.09-3928
复制
发表时间：
2009-12
影响因子：
4.4
通讯作者：
Seddon JM
中科院分区：
文献类型：
--
作者：
Reynolds R;Hartnett ME;Atkinson JP;Giclas PC;Rosner B;Seddon JM
编码补体系统成分和片段的多个基因与年龄相关性黄斑变性（AMD）有关。本研究旨在确定这些补体激活和调节标志物循环水平的改变是否也与晚期 AMD 独立相关，以及它们是否与 AMD 基因型相关。血浆和 DNA 样本选自我们的 AMD 登记中已进展至或已发展为 AMD 晚期的个体，其中 58 名患有地图样萎缩，62 名患有新生血管疾病。年龄和性别相似但没有 AMD 且未进展的受试者被纳入对照 (n = 60)。分析了血浆补体成分（C3、CFB、CFI、CFH 和因子 D）和激活片段（Bb、C3a、C5a、iC3b 和 SC5b-9）。对 DNA 样本进行了基因分型，检测了先前显示与 AMD 相关的 6 个基因中的 7 个单核苷酸多态性：CFB、CFH、C2、C3 和 CFI 以及 LOC387715/ARMS2 基因区域。 AMD 与每个补体生物标志物之间的关联通过逻辑回归进行评估，控制年龄、性别和促炎危险因素：吸烟和体重指数 (BMI)。进行功能基因组分析以评估补体标记和基因型之间的关系。计算一致性或 C 统计数据以评估 AMD 基因环境预测模型中补体成分和激活片段的影响。与最低四分位数相比，Bb 和 C5a 的最高四分位数与晚期 AMD 显着相关。在没有遗传变异的多变量模型中，Bb 的优势比 (OR) 为 3.3（95% 置信区间 [CI] = 1.3-8.6），C5a 的 OR 为 3.6（95% CI = 1.2-10.3）。通过对遗传变异进行调整，这些 OR 显着提高。在无基因型的模型中，替代途径调节剂 CFH 与 AMD 呈负相关（OR = 0.3；P = 0.01）。 BMI 与血浆 C3、CFB、CFH、iC3b 和 C3a 呈正相关。 C5a 片段与 LOC387715/ARMS2 和 C3 基因型之间也分别存在显着关联（趋势 P = 0.02、0.04）。添加 C3a、Bb 和 C5a 后，具有行为和遗传因素的模型的 C 统计量增加到 0.94 ± 0.20。激活片段 Bb 和 C5a 水平的增加与 AMD 独立相关。较高的 BMI 与补体成分水平增加有关。 C5a 与 AMD 基因型相关。在预测模型中添加 C3a、Bb 和 C5a 后，C 统计量会更强。结果表明AMD发病机制中补体替代途径的持续激活。
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. 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 complment 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. 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. 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.
登录
查看更多内容
DOI：
10.1073/pnas.0501536102
发表时间：
2005-05-17
影响因子：
11.1
作者：
Hageman, GS;Anderson, DH;Allikmets, R
通讯作者：
Allikmets, R
影响因子：
5.2
作者：
Fagerness, Jesen A.;Maller, Julian B.;Seddon, Johanna M.
通讯作者：
Seddon, Johanna M.
影响因子：
82.9
作者：
Huber-Lang, Markus;Sarma, J. Vidya;Ward, Peter A.
通讯作者：
Ward, Peter A.
影响因子：
56.9
作者：
Edwards, AO;Ritter, R;Farrer, LA
通讯作者：
Farrer, LA
影响因子：
30.8
作者：
Li, Mingyao;Atmaca-Sonmez, Pelin;Abecasis, Goncalo R.
通讯作者：
Abecasis, Goncalo R.