Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936
Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936
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DOI：
10.1038/s41398-019-0576-5
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发表时间：
2019-10-07
影响因子：
6.8
通讯作者：
Deary, Ian J.
中科院分区：
文献类型：
--
作者：
Corley, Janie;Cox, Simon R.;Deary, Ian J.
吸烟行为的全基因组DNA甲基化（DNAm）分析的最新进展产生了一种新的吸烟暴露分子生物标志物。目前尚不清楚吸烟相关的DNAm（表观遗传）评分是否对年龄相关的健康结果具有预测价值，这与自我报告的（表型）吸烟措施的贡献无关。在Lothian Birth Cohort 1936（LBC 1936）研究中，使用Illumina 450 K测定法测量了895名70岁成人的血液DNA甲基化水平。使用基于230个CpG的DNA甲基化评分作为吸烟暴露的代表。使用一般线性模型（ANCOVA）和logistic回归对70岁时吸烟变量与健康结果之间的关联进行建模。对73岁（n = 532）的吸烟与脑MRI测量进行了额外的分析。吸烟-DNAm评分与自我报告的吸烟状况（P < 0.001，eta-squared eta（2）= 0.63）和吸烟包年数（r = 0.69，P < 0.001）呈正相关。较高的吸烟DNAm分数与认知功能较差、大脑结构完整性、身体健康和心理社会健康相关的变量相关。与表型吸烟相比，甲基化标记物与所有认知功能评分，特别是视觉空间能力，（P < 0.001，部分等时平方eta p（2）= 0.022）和加工速度（P < 0.001，eta p（2）= 0.030）;炎症标志物（均P< 0.001，范围为η p（2）= 0.021 ~ 0.030）;饮食模式（健康饮食组（P < 0.001）与传统饮食组（P <0.001）比较，差异有统计学意义（P <0.001）。（P < 0.001，eta p（2）= 0.032）;脑卒中（P = 0.006，OR 1.48，95% CI 1.12，1.96）;死亡率（P < 0.001，OR 1.59，95% CI 1.42，1.79），73岁; MRI体积测量（所有P < 0.001，范围从eta p（2）= 0.030至0.052）。此外，教育是一生吸烟测试的最重要的生命过程预测因子。我们的研究结果表明，与吸烟暴露的表型测量相比，吸烟相关的甲基化生物标志物通常解释了老年人某些吸烟相关疾病的更大比例的方差，其中一些解释的方差与表型吸烟状态无关。
Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared eta(2) = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial etasquared eta p(2) = 0.022) and processing speed (P < 0.001, eta p(2) = 0.030); inflammatory markers (all P< 0.001, ranges from eta p(2) = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, rip e = 0.052) and traditional diet (P < 0.001, eta p(2) = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from eta p(2) = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.