Effects of titanium dioxide nanoparticles on micrornas expression and. regulation mechanism in RAW264.7 cell

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1 纳米二氧化钛对 RAW264.7 细胞的 mirnas 调控及机制研究 梁戈玉 1, 付艳云, 张艳秋, 马书梅, 隋静, 尹立红, 浦跃朴 ( 东南大学公共卫生学院, 环境医学工程教育部重点实验室江苏南京 ) 摘要 目的 : 研究纳米二氧化钛 (TiO2) 对巨噬细胞的 mirnas 表达谱影响及调控机制 方法 : 以巨噬细胞为研究对象, 应用高通量测序技术, 检测纳米 TiO 2 暴露后产生的 mirnas 表达谱改变, 筛选免疫相关的 mirnas, 并通过生物信息学软件对差异表达 mirnas 进行调控通路分析, 在此基础上对 mir-350 的生物学功能及靶基因调控进行研究 结果 : 纳米 TiO 2 暴露后使 RAW264.7 细胞 mirnas 表达谱发生了明显改变, 共有 140 个 mirnas 发生差异表达 差异表达 mirnas 可能参与了 T cell receptor B cell receptor Natural killer cell mediated cytotoxicity 等免疫相关信号通路的调节 mir-350 可能通过对 PIK3R3 基因负向调控促进 RAW264.7 细胞的凋亡 结论 : 研究为了解纳米 TiO 2 暴露对机体免疫功能影响的可能机制提供了理论依据, 但纳米材料的表观遗传调控机制仍有待大量研究去进一步探索 关键词 纳米二氧化钛 ;RAW264.7 细胞 ;mirnas;mir-350 Effects of titanium dioxide nanoparticles on micrornas expression and regulation mechanism in RAW264.7 cell LIANG Geyu *, FU Yan-yun, ZHANG Yan-qiu, MA Shu-mei, Sui Jing, YIN Li-hong, PU Yue-pu, (School of Public Health, Southeast University, Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Nanjing , Jiangsu, China) ABSTRACT OBJECTIVE: To explore the effects of titanium dioxide (TiO2) nanoparticles on micrornas expression and regulation mechanism in RAW264.7 cell. METHODS: High-throughput sequencing technology was applied to examine the expression profile of mirnas in RAW264.7 cells after TiO 2 nanoparticles exposure. Immune-related mirnas was screened. Then, bioinformatics software was applied to analyze the related pathways of the differential expression of mirnas. In further, biological function and targets regulation of mir-350 was studied. RESULTS: The sequencing results showed that the mirnas expression profile was significantly different after TiO 2 nanoparticles exposure. In details, 140 mirnas were found to be significantly differentially expressed. Immune-related signaling pathways regulated by differential expressed mirnas were involved in T cell receptor, B cell receptor, and Natural Killer cell mediated cytotoxicity. MiR-350 may promote RAW264.7 cell apoptosis through the negative regulation of PIK3R3 gene. Conclusion: The results may provide a basis for understanding of possible immune regulation mechanisms of TiO 2 nanoparticles expourse. A lot of researches are needed to further explore the epigenetic 基金项目 : 国家自然科学基金 ( ); 国家重大科学研究计划 (2011CB933404); 江苏省青蓝工程项目 (2012); 江苏省六大人才高峰项目 (2013-WSW-053) 1 作者简介 : 梁戈玉,(1976-), 女, 教授, 研究方向 : 纳米毒理学 环境表观遗传学, lianggeyu@163.com

2 regulation mechanism of nano-material. Key words TiO 2 nanoparticles, RAW264.7 cell, mirnas;mir-350 随着纳米科技的迅速发展, 越来越多的纳米材料通过不同的途径进入人类的生活环境, 人们在应用纳米材料的同时, 也在更多地关注纳米材料对人类健康可能产生的影响 纳米二氧化钛 (titanium dioxide, TiO 2 ) 是常用的纳米材料之一, 已经被广泛应用于涂料 废水处理 杀菌 化妆品 食品添加剂和生物医用陶瓷材料等与人们日常生活紧密相关的领域 纳米 TiO 2 具有纳米材料特有的理化特征, 进入生命体后可能引起与常规尺寸 TiO 2 不一样的生物学效应, 许多研究表明纳米 TiO 2 可能产生比同剂量微米 TiO 2 更为严重的健康损害 因此, 纳米 TiO 2 对健康的潜在影响已引起广泛的关注 研究显示纳米 TiO 2 可对呼吸系统造成损伤, 对免疫系统也存在一定的影响, 如纳米 TiO 2 对动物脾脏产生氧化损伤, 还可影响大鼠淋巴细胞亚群数量 [1,2] 我们以往的研究也表明纳米 TiO 2 对可降低肺脏巨噬细胞的吞噬 趋化和抗原递呈能力, 对系统免疫产生影响 [3,4], 但纳米粒子引发组织和细胞损伤机制尚不明确, 在此过程中涉及的关键分子事件尚未得以探索 MicroRNAs(miRNAs) 是一类高度保守的非编码小 RNA, 约 个核苷酸, 广泛存在于动植物中, 在生长发育及疾病的发生发展中起着重要的作用, 目前已成为阐明环境 基因与疾病之间联系的热点研究领域之一 已有研究表明环境颗粒物暴露可引起 [5] mirnas 的变化,Jardim 等发现柴油车尾气颗粒物暴露可影响 mirnas 的表达, 其中显著性改变 mirnas(mir-513a-5p mir-494 mir-923 和 mir-96) 的靶基因大部分富 [6] [7] 集在炎症反应通道和肿瘤相关疾病中 Bollati 等和 Motta 等发现富含金属的颗粒物暴露后外周血白细胞中 mirnas 表达产生改变, 可能通过 mirnas 应答影响直接或间接的控制炎症基因表达 目前纳米材料是否可对 mirnas 调控产生影响尚不明确, 有待大量研究去探索 因此, 本研究课题拟以巨噬细胞为研究对象, 应用高通量测序技术, 检测纳米 TiO 2 暴露后产生的 mirnas 表达改变, 筛选纳米 TiO 2 暴露相关特异性 mirnas, 并针对差异表达明显 mirnas 进行生物信息学分析, 在此基础上进一步进行 mirna 调控研究, 探讨纳米二氧化钛诱发免疫系统损伤中的 mirnas 调控机制, 以期为纳米二氧化钛免疫毒理学安全性评价提供新的思路和依据 1. 材料与方法 1.1 实验材料与试剂纳米 TiO 2 购自德国 Degussa 公司, 粒径为 21nm, 比表面积为 50 m 2 /g, 纯度 >99.5% Trizol Reagent( 美国 Invitrogen 公司 ),Reverse Transcription System 试剂盒 ( 美国 Promega 公司 ),GoTaq qpcr Master Mix 试剂盒 ( 美国 Promega 公司 ),microntm mirna mimic ( 广州市锐博生物科技有限公司 ),Annexin V FITC 细胞凋亡检测试剂盒 ( 美国 BD 公司 ),SuperSignal west pico 试验试剂盒 ( 美国 Thermo 公司 ),GAPDH XP Rabbit mab ( 美国 Cell Signaling 公司 ),PI3 Kinase p55 Rabbit mab( 美国 Cell Signaling 公司 ) 1.2 细胞染毒 RAW264.7 细胞用 DMEM 高糖培养基含体积分数为 10% 的胎牛血清 (100 U/mL 青霉素 100 μg/ml 链霉素 ) 于 37 5% CO 2 培养 取生长状态良好的对数生长期细胞, 个 /ml 接种于 6 孔板, 培养 24h 后染毒 高压灭菌纳米 TiO 2 颗粒, 培养液配成浓度为 100 μg/ml 的悬液, 超声震荡 30 分钟后染毒, 对照组加入同等体积的培养液, 继续培养 24 h, 实验设两个重复 1.3 测序分析收集细胞, 纯化提取小 RNA, 应用 Hi-seq 2000 测序技术进行全基因组 mirnas 高

3 通量测序, 与目前 mirbase 数据库对比, 注释 mirnas, 对实验组和对照组 mirnas 表达进行差异比较分析, 取比值绝对值 2 为具有明显表达改变 1.4 生物信息学分析应用 DIANA.mirPath 数据库对表达上调或下调的 mirnas 进行靶基因预测和信号通路功能分析 1.5 细胞转染取对数生长期的细胞, 调整细胞浓度为 个 /ml, 进行转染 设空白对照 阴性对照组 ( 转染 Negative control) 和转染组 ( 转染 mir-350 mimic), 每组设 3 个平行 1.6 细胞增殖测定 MTT 法测定细胞增殖 转染 24h 后, 加入 10% MTT, 继续培养 4 小时后, 弃去上清, 加入 DMSO, 于 37 振荡至甲臜结晶完全溶解, 酶标仪 570 nm 测定吸光度 每组设 3 个平行 1.8 细胞周期和细胞凋亡检测采用流式细胞术进行检测 转染 24 小时后收集细胞, 制成单细胞悬液, 分别进行 PI 染色和 Annexin V/PI 双染后送流式细胞仪检测细胞周期和细胞凋亡 实验重复三次 1.9 mrna 表达检测转染 24h 后提取总 RNA, 应用 Reverse Transcription System 试剂盒进行逆转录, 应用 GoTaq qpcr Master Mix 试剂盒对 cdna 进行扩增 PIK3R3 引物序列为 :sense 5 -AAA GGA AAA TAG GGA GGT ATG GGA T-3,Antisense 5 - TTA GAG GGA GGA GTT GGT GAA GAT G- 3 GAPDH 为内参 反应条件为 :95 2 分钟,95 15 秒 ;95 15 秒,60 1 分钟,40 个循环 实验重复三次, 分析 mrna 相对表达水平 1.10 蛋白表达检测转染 24h 后提取总蛋白,Western Blot 技术检测 PIK3R3 蛋白表达水平 将蛋白样品和 2 倍浓度的 SDS 缓冲液等体积混合上样,110V 电泳后转膜,5% BSA 封闭 2h, 一抗 4 孵育过夜, 二抗继续孵育 1h, 按试剂盒加入发光液, 全自动化学发光图像分析仪检测扫描并分析结果 实验重复三次, 分析蛋白相对表达水平 1.11 统计分析数据以均数 ± 标准差 (x ±s) 表示, 应用 SPSS16.0 软件对数据进行单因素方差分析和 Dunnett s 检验, 以 p<0.05 判断为有统计学意义 2. 结果 2.1 纳米二氧化钛染毒后 RAW264.7 细胞 mirnas 表达谱分析 Fold Change mmu-mir p mmu-mir-147-3p mmu-mir-5126 mmu-mir-350-3p mmu-mir p mmu-mir p mmu-mir-19b-3p mmu-mir-27b-3p mmu-mir-1949 mmu-mir-693-3p mmu-mir-34b-5p mmu-mir-181d-5p mmu-mir-500-3p mmu-mir-450b-3p mmu-mir-2137 mmu-mir-671-5p mirna mmu-mir-5105 mmu-mir p mmu-mir-369-3p mmu-mir-491-3p mmu-mir p mmu-mir-195-5p mmu-mir-152-5p mmu-mir-326-3p mmu-mir p mmu-mir-29a-5p mmu-mir p mmu-mir-363-3p 图 1 纳米 TiO 2 染毒后 RAW264.7 细胞差异表达 mirnas

4 与对对照组相比, 实验组 RAW264.7 细胞中共有 140 个 mirnas 发生生差异表达, 其中 131 个 mirnas 表达上调, 9 个 mirnas 表达下下调 ( 见图 1) 其中上上调倍数最最大的为 mir-3089, 上调了 倍, 下调倍数数最大的为 mir-96, 下调了 倍 2.2 差异异表达 mirnas 的 RT-qPCR 验证 图 2 mirnas RT-q qpcr 分析结结果与测序结结果比较为了了验证测序序结果, 取 mir-350- 和 mir-29b 进行 RT-qPCR 分析 结果显示 : 与对照组相比, 实验组 mir-350 和 mir-29b 明显上调,RT-qPCRR 结果与测序结果一致 ( 见图 2) 2.3 与免免疫通路相相关的 mirna 调控分分析及靶基因因预测 A B C 图 3 mir-350 对免疫相关通路的调控的调调控 (A. T cell receptor signaling pathway, B. B cell receptor signaling pathway, C.Natural killer cell mediated cytotoxicity. 黄色高亮区区域表示 mir-350 潜在的的靶基因 )

5 对差异表达 mirnas 参与的信号通通路进行筛筛选, 其中与与免疫相关的的信号通路路主要有 T cell receptor signaling pathway, B cell receptor signalingg pathway, Natural killer cell mediated cytotoxicity, 通过 DIANA.mirPath 筛选出出与这些通通路相关的 mirna, 结果发现 mir-350 与这三个个通路均相关, 进一步步分析显示 mir-350 可能通过对 PIK3R3 基因的调控参与这这三个通路路的调节 ( 见图 3) 2.4 转染 mir-350 mimic 对 RAW264.7 细胞增殖的影响 mir-350 mimic 转染组与与阴性对照照组相比,OD 值差异无统计学意意义 (p>0.05), 空白对照组与阴性对对照组之间 OD 值无明明显差异 (p>0.05)( 见图 4) 图 4 转染 mir-350 mimic 对 RAW264.7 细胞增增殖的影响 2.5 转染 mir-350 mimic 对 RAW264.7 细胞周期的影响 与阴性对照组组相比,miR-350 mimic 转染组细细胞周期 G1 S 和 G2 期与阴性性对照组 差异无统计学意义 (p>0.05)( 见表 1) ) 空白对照照组与阴性性对照组之间间细胞周期 G1 S 和 G2 期无明显差差异 (p>0.05) 表 1 转染 mir-350 mimic 对 RAW264.7 细胞周期期的影响 (x x ±s) 组别 G1(%) ) S(%) G2(%) ) 转染组 ± ± ±0.035 阴性性对照组 ± ± ±0.508 空白对照组 ± ± ± 转染 mir-350 mimic 对 RAW264.7 细胞凋亡的影响 与阴性对照组组相比,miR-350 mimic 转染组细细胞凋亡率率明显上升, 与阴性对对照组相 比差别具有统计学学意义 (p< <0.05)( 见表 2) 空空白对照组组与阴性对照照组之间细细胞凋亡 率无明显差异 (p> >0.05) 表 2 转染 mir-350 mimic 对 RAW264.7 细胞凋亡亡的影响 (x x ±s) 组别 Apoptosis(%) ) 转染组 ±1.189* 阴性对照照组 4.753±0.197 空白对照照组 4.203±0.242 * 与阴阴性对照组相相比差别具有有统计学意义 (p<0.05) 2.7 mir-350 mimic 转染后 RAW264.7 细胞 PIK3R3 mrna 表达

6 图 5 转染后 RAW264.7 细胞 PIK3R3 mrna 表达以 GAPDH 为内参, 运用 2 -ΔΔCт 相对定量计算算方法得到 PIKR3 基因的相对表表达量, 转染组 PIK3R3 mrna 的表表达量是阴性性对照组的 1.05 倍, 差别无统计计学意义 (p>0.05) ( 见图 5) 2.8 mir-350 mimic 转染后 RAW264.7 细胞 PIK3R3 蛋白表达结果 * 与阴性对照组相比差差别具有统计计学意义 (p<0.05) 图 6 转染染后 RAW264.7 细胞中 PIK3R3 蛋白的的相对变化 mir-350 mimic 转染组与与阴性对照照组相比,P IK3R3 蛋白白表达量明显下降, 与阴性对照组相比差别具有有统计学意义 (p<0.05)( 见图 6) 3. 讨论 [8] mirnas 在纳纳米材料引起起健康效应应过程中的作作用目前尚尚不明确, 报道极少 Li 等研究表明碲化镉量量子点 (CdTe QDs) 暴露后 mirnas 表达达谱受到广泛泛的影响, 其中 86 个 mirnas 表达下下调,121 个 mirnas 表达上调, 部分显著著性差异表达 mirnas 的表达水平呈明显的时间 - 反应和剂剂量 - 反应关关系, 并且其其趋势和 CdTe QDs 引起的细胞胞生存抑制率相一致 此外, 研究还显示,CdTe QDs 处理理后可通过过磷酸化增加 p53 翻译译后修饰及其蛋白水平, 并可能通过此影响初级级转录本 ( pri-mirna) 转录及 mirnas 的表达 [9] Chew 等发现 mir-298 在注注射纳米金金一周后显著著上升, 它可能是纳米米材料暴露露的有效 [10] 生物标志物 Motta 等研究究表明富含含金属颗粒暴暴露可能通通过 mirnas 应答直接接或间接的控制炎症基因表表达, 提示 mirnas 表达改变可能能是介导机机体对颗粒物物及其金属属成分反 [11] 应的表观观遗传学新新机制 Nagano 等发现 70 nm 的纳米二二氧化硅染毒毒后, 的小小鼠血清 mir-122 水平升高高 本研究结结果显示, 纳米 TiO 2 暴露后 RAW264.7 细胞胞中 140 个 mirnas 表达发生改变, 其中 131 个 mirnas 表达上调, 9 个 mirnas 表达下调, 这些 mirnas 在纳米 TiO 2 暴露致致机体免疫疫应答的过程程中可能扮扮演着重要的的作用 对差异表达的 mirna 参与的信号号通路分析并并进行归类, 结果发现现与免疫相相关的信

7 号通路主要有 T cell receptor signaling pathway B cell receptor signaling pathway Natural killer cell mediated cytotoxicity, 其中 mir-350 均参与了这三个通路的调节, 因此进一步对 mir-350 参与的信号通路和靶基因调控进行了分析 分析结果显示,miR-350 可能通过对 PIK3R3 基因的调控参与免疫信号通路的调控 在 T B cell receptor signaling pathway 中,miR-350 可通过对 PIK3R3 基因的调控将信号传至 PIP3 等基因, 进而对免疫反应 细胞增殖 分化 B 细胞的发育 自身免疫 免疫球蛋白等产生影响 Natural killer cell mediated cytotoxicity 信号通路中,miR-350 也可通过 PIK3R3 基因, 影响 VaV Rac 等基因的表达, 从而影响细胞因子的释放, 进一步通过 INFγR 等基因对凋亡产生影响 现有报道显示,miRNAs 可参与调节免疫细胞的凋亡 周期 增殖等生物学功能 [12] Wu 等研究发现, 在初始 CD4 + T 细胞分化成效应细胞过程中 mir-16 mir-142-3p mir-142-5p mir-150 mir-15b 和 let-7f 全面下调, 而且这些 mirnas 都参与 T 淋巴细 [13] 胞的凋亡 Ranji 等研究发现在不同的刺激及不同的免疫细胞中参与的 mirnas 也不同, 对免疫系统的反应亦不同 mir-350 在纳米颗粒致机体损伤中的调控作用目前未见报道 本次研究结果显示 mir-350 表达升高时,RAW264.7 细胞的凋亡率明显升高, 而增殖 周期的改变并不明显 总的来说,miRNA 在纳米颗粒致免疫损伤中的作用仍需大量研究来进一步探索 目前关于 mir-350 的靶基因调控的研究极少, 有文献报道,miR-350 可通过抑制 p38 和 JNK 通路诱导病理性心脏肥大 磷脂酰肌醇 -3- 激酶 (Phosphatidylinositol,PI3K) 是一个具有羟基磷酸化功能和脂质激酶功能的酶家族, 可以促进细胞增殖 迁移和分化等 [14] 在免疫调节中同样具有重要的作用, 激活的 PI3K 可以调节 B 淋巴细胞和 T 淋巴细胞的发育 活化和分化, 也可以通过免疫受体 细胞因子受体和趋化因子等受体成为调控淋巴细胞激活的重要组成部分 [15,16] [17] PIK3R3 是 PI3K IA 类调节亚基之一 Yu 等发现 mir-193a-3p 和 -5p 可以通过 PIK3R3 信号通路的下调, 抑制人类非小细胞肺癌的转移 本研究结果显示 mir-350 可能通过转录后抑制对 PIK3R3 蛋白产生负向调控作用 目前关于 mir-350 的调控机制研究极少, 进一步筛选和确定其靶向调控蛋白, 将为明确 mir-350 参与纳米 TiO 2 引发机体免疫应答的调控机制提供依据 综上所述, 本研究对纳米 TiO 2 暴露后巨噬细胞 mirnas 表达谱进行分析, 筛选出 140 个差异表达 mirnas, 生物信息学分析结果提示 mir-350 可能参与了免疫相关信号通路的调节, 功能调控研究显示,miR-350 可能通过对 PIK3R3 基因负向调控促进 RAW264.7 细胞的凋亡 研究为进一步了解纳米 TiO 2 暴露对机体免疫功能影响的可能机制提供理论依据 参考文献 [1] Sang X, Zheng L, Sun Q, et al. The chronic spleen injury of mice following long-term exposure to titanium dioxide nanoparticles[j]. J Biomed. Mater. Res., 2012, 100: [2] Park EJ, Yoon J, Choi K, et al. Induction of chronic inflammation in mice treated with titanium dioxide nanoparticles by intratracheal instillation[j]. Toxicology, 2009, 260: [3] Liu R, Zhang X, Pu Y, et al. Small-sized titanium dioxide nanoparticles mediate immune toxicity in rat pulmonary alveolar macrophages in vivo[j]. J Nanosci Nanotechnol, 2010, 10: [4] Fu Y, Zhang Y, Chang X, et al. Systemic immune effects of titanium dioxide nanoparticles after repeated intratracheal instillation in rat [J]. Int J Mol Sci., 2014, 15: [5] Jardim MJ, Fry RC, Jaspers I, et al. Disruption of microrna expression in human airway cells by diesel exhaust particles is linked to tumorigenesis-associated pathways [J]. Environ Health Perspect, 2009, 117(11):

8 [6] Bollati V, Marinelli B, Apostoli P, et al. Exposure to metal-rich particulate matter modifies the expression of candidate micrornas in peripheral blood leukocytes [J]. Environ health perspect, 2010, 118(6): [7] Motta V, Angelici L, Nordio F, et al. Integrative analysis of mirnas and inflammatory gene expression After Acute Particulate Matter Exposure [J]. Toxicol Sci, 2013, 132(2): [8] Li S, Wang Y, Wang H, et al. MicroRNAs as participants in cytotoxicity of CdTe quantum dots in NIH/3T3 cells [J]. Biomaterials, 2011, 32(15): [9] Chew WS, Poh KW, Siddiqi NJ, et al. Short- and long-term changes in blood mirna levels after nanogold injection in rats--potential biomarkers ofnanoparticle exposure [J]. Biomarkers, 2012, 17(8): [10] Motta V, Angelici L, Nordio F, et al. Integrative analysis of mirna and inflammatory gene expression after acute particulate matter exposure [J]. Toxicol Sci, 2013, 132(2): [11] Nagano T, Higashisaka K, Kunieda A, et al. Liver-specific micrornas as biomarkers of nanomaterial-induced liver damage [J]. Nanotechnology, 2013, 24(40): [12] Wu H, Neilson JR, Kumar P, et al. mirna profiling of naïve, effector and memory CD8 T cells [J]. PLoS One, 2007, 2(10): e1020. [13] Ranji N, Sadeghizadeh M, Shokrgozar MA, et al. MiR cluster: an apoptosis inducer or proliferation enhancer [J]. Mol Cell Biochem, 2013, 380(1-2): [14] Vanhaesebroeck B, Guillermet-Guibert J, Graupera M, et al. The emerging mechanisms of isoform-specific PI3K signaling [J]. Nat Rev Mol Cell Biol, 2010, 11: [15] Lomon S, David A F. PI3K Signaling in B and T Lymphocytes: New Developments and Therapeutic Advances [J]. Biochem J. 2012, 442(3): [16] Zhang TT, Li H, Cheung SM, et al. Phosphoinositide 3-kinase-regulated adapters in lymphocyte activation [J]. Immunol Rev, 2009, 232(1): [17] Yu T, Li J, Yan M, et al. MicroRNA-193a-3p and -5p suppress the metastasis of human non-small-cell lung cancer by downregulating the ERBB4/PIK3R3/mTOR/S6K2 signaling pathway [J]. Oncogene, [Epub ahead of print]

9 编号 中国毒理学会优秀青年科技奖申请表 姓名梁戈玉 工作单位 东南大学 推荐单位东南大学公共卫生学院 中国毒理学会 制 1

10 填表说明 1. 此表在中国毒理学会网站 ( 中国毒理学会第三届中青年学者科技论坛 栏目下载后填写,A4 规格打印完成 2. 封面的编号由工作人员填写 3. 申请表中所涉及日期统一用阿拉伯数字, 如 2010 年 1 月 1 日 4. 毕业院校 工作单位填写全称, 职务等要按照国家有关规定详细填写 5. 照片为小 2 寸正面免冠彩色标准照, 可粘贴在推荐表上, 也可将照片电子版插入本表, 一并彩色打印 6. 从事科技工作经历从中专或大学毕业后填起 7. 主要事迹 500 字左右, 请勿另附页 内容应客观真实地反映候选人精神风貌 工作业绩 社会影响等情况 8. 工作单位意见由候选人所在单位填写, 推荐单位意见由负责向中国毒理学会推荐的单位填写 需负责人签字, 加盖单位公章 2

11 事科技工作经历姓 名 梁戈玉 性 别 女 出生年月日 籍 贯 江苏 党 派 中共党员 民 族 汉 学 历 博士研究生 学 位 博士 毕业院校 东南大学 所学专业 劳动卫生与环境卫生学 专业技术职称 教授 会员号 工作单位及职务东南大学公共卫生学院 通讯地址 及邮编 江苏省南京市丁家桥 87 号东南大学公共卫生学院 联系电话 手机 传真电子邮箱 是否通过毒理学资格认证考试否从2012/5- 现在东南大学, 公共卫生学院劳动卫生与环境卫生学系, 教授 2008/5-2012/5 东南大学, 公共卫生学院劳动卫生与环境卫生学系, 副教授 2011/8-2011/9 澳大利亚 monash 大学, 公共卫生学院, 访问交流 2010/3-2011/4 美国哈佛大学, 医学院, 国家公派访问学者 2005/6-2008/4 东南大学, 公共卫生学院劳动卫生与环境卫生学系, 讲师 2002/9-2005/6 东南大学, 公共卫生学院劳动卫生与环境卫生学系, 博士 1999/9-2002/6 东南大学, 公共卫生学院劳动卫生与环境卫生学系, 硕士 3

12 主要事迹 (500 字左右 ) 梁戈玉, 女, 东南大学公共卫生学院教授 博士生导师 中国环境诱变剂学会理事 中国环境诱变剂学会致癌专业委员会委员 江苏省毒理学会常务理事兼副秘书长 美国癌症研究协会 (AACR) 会员 中国毒理学学会会员,PLoS ONE 等杂志审稿人 研究方向为纳米毒理学 环境污染物健康效应和生物标志物 主要以环境化合物致健康效应的表观遗传学调控机制为切入点, 在环境卫生领域开展以生物标志物为基础的环境污染物致器官毒性和肿瘤发生的分子流行病学与机制研究, 研究涉及新型纳米材料 环境化学致癌物的接触 效应 分子机制和生物标志物等方面, 并发展进行生物监测的新指标和新技术, 为促进人群早期预警 生物监测普提供科学依据 主持完成国家自然科学基金项目 1 项, 省部级科研项目 2 项, 目前承担国家自然科学基金项目 1 项 先后参加 973 项目 国家科技重大专项等 10 余项工作 发表学术论文 60 余篇, 其中在 PloS ONE Cancer Epidemiol Biomarkers Prev Cancer Letters J Toxicol Environ Health A J Nanosci Nanotechnol 等专业杂志发表第一作者 ( 通讯作者 )SCI 论文 10 余篇 参与多本专业著作 毒理学百科全书 纳米氧化铁的毒理学与安全性 肺癌表遗传学 呼吸系统毒理学 共约 10 万字的编写 入选 2012 江苏省高校 青蓝工程 优秀青年骨干教师, 江苏省 333 工程第三层次培养对象,2013 年六大高峰人才 荣获科技奖 ( 获奖名称, 颁奖机构 ( 奖项名称 ), 奖励级别, 获奖年份, 排名顺序 ) 主持科技项目 ( 不要填写参与的项目 ) ( 项目名称, 项目来源, 执行时间, 总经费 ) 1. 纳米二氧化钛免疫毒性及表观遗传学调控研究, 项目批准号 : , 国家自然科学基金, , 59 万元, 课题负责人 ( 在研 ) 2. 特异性表达 mirna 在 BPDE 诱导人支气管上皮细胞恶性转化中的功能和调控机制研究, 项目批准号 : , 国家自然科学基金, , 20 万元, 课题 4

13 负责人 ( 已结题 ) 3. Mir-143 在肺癌发生中的作用及调控机制研究, 项目批准号 :BK , 江苏省自然科学基金, ,5 万元, 课题负责人 ( 已结题 ) 4. mirna 在 B(a)P 致 HBE 细胞恶性转化中的作用和靶基因调控研究, 项目批准号 : , 高等学校博士学科点专项科研基金资助项目, ,3.6 万元, 课题负责人 ( 已结题 ) 5. 肺癌易感基因与人群筛检技术的研究, 项目批准号 :XM 04-70, 江苏省教育厅高校研究生创新计划项目, ,2 万元, 课题负责人 ( 已结题 ) 授权专利 ( 所有发明人, 专利名称, 专利类别, 专利号, 授权时间 ) 代表性论文目录 (10 篇以内 ) ( 全部作者 < 按发表顺序 >, 论文题目, 刊物名称, 年, 卷 < 期 >, 起止页 < 英文论文请标明当年 SCI 影响因子 ; 中文内容请标明是否为核心期刊 >) 1. Fu Y, Zhang Y, Chang X, Zhang Y, Ma S, Sui J, Yin L, Pu Y, Liang G (Corresponding Author). Systemic immune effects of titanium dioxide nanoparticles after repeated intratracheal instillation in rat [J]. Int J Mol Sci., 15: , 2014 (IF=2.464) 2. Zhang Y, Wang X, Fu Y, Yin L, Pu Y, Liang G (Corresponding Author). Expression profiling and pathway analysis of microrna expression in the lungs of mice exposed to long-term, low-dose benzo(a)pyrene[j]. Mol Cell Toxicol,10:67-74, 2014 (IF=0.72) 3. Liang G, Nan H, Qureshi AA, Han J. Pre-diagnostic plasma 25-hydroxyvitamin D levels and risk of non-melanoma skin cancer in women. PLoS One, 7(4):e35211, 2012 (IF=4.351) 4. Liang G, Qureshi AA, Guo Q, De Vivo I, Han J. No association between telomere length in peripheral blood leukocytes and the risk of non-melanoma skin 5

14 cancer.cancer Epidemiol Biomarkers Prev, 20(5): , ( IF= ) 5. Liang G, Schernhammer E, Qi L, Gao X, De Vivo I, Wan J. Associations between rotating night shifts, sleep duration, and telomere length in women.plos &,6(8):e23462,2011( IF=4.35 1) 6. Liang G, Yin L, Zhang J, Liu R, Zhang T, Ye B, Pu Y. Effects of subchronic exposure to multi-walled carbon nanotubes on mice. J Toxicol Environ Health A, 73(7): , (IF~1.724) 7. Liang G, Zhang T, Liu R, Ye B, Yin L, Pu Y. Preparation and biodistribution o 1 tyrosine modified multiwall carbon nanotubes. J NanosciNanotechnol, 1 O(12): ,2010 (IF=1.435) 8. Liang G, Pu Y, Yin L, Liu R, Ye B, Su Y, Li Y. Influence of different sizes of titanium dioxide nanoparticles on hepatic and renal functions in rats with correlation to oxidative stressj Toxicol Environ Health A, 72(11-12): ,2009. (IF= 1.724) 9. Liang G, Pu Y, Yin L. Lys751Gln polymorphism in ERCC2 gene is associated with lung cancer susceptibility in the Chinese population. Progress in Natural Science, 17(7): ,2007.( IF=0.704) 10. Liang G, Pu Y, Yin L. Rapid detection of single nucleotide polymorphisms related with lung cancer susceptibility of Chinese population. Cancer Letters, 223(2): , 2005.( 1F=4.258)

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29 Int. J. Mol. Sci. 2014, 15, ; doi: /ijms Article OPEN ACCESS International Journal of Molecular Sciences ISSN Systemic Immune Effects of Titanium Dioxide Nanoparticles after Repeated Intratracheal Instillation in Rat Yanyun Fu 1, Yanqiu Zhang 1, Xuhong Chang 2, Yingjian Zhang 1, Shumei Ma 1, Jing Sui 1, Lihong Yin 1, Yuepu Pu 1 and Geyu Liang 1, * 1 2 Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing , Jiangsu, China; s: fckxxz@gmail.com (Y.F.); (Ya.Z.); zhangyingjian321@gmail.com (Yi.Z.); m @gmail.com (S.M.); sj @gmail.com (J.S.); lhyin@seu.edu.cn (L.Y.); yppu@seu.edu.cn (Y.P.) Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing , Jiangsu, China; cxhpublic@gmail.com * Author to whom correspondence should be addressed; gyliang@seu.edu.cn; Tel.: Received: 15 February 2014; in revised form: 6 April 2014 / Accepted: 9 April 2014 / Published: 22 April 2014 Abstract: The potential immune effects of titanium dioxide nanoparticles (nano-tio 2 ) are raising concern. Our previous study verified that nano-tio 2 induce local immune response in lung tissue followed by intratracheal instillation administration. In this study, we aim to evaluate the systemic immune effects of nano-tio 2. Sprague Dawley rats were treated by intratracheal instillation with nano-tio 2 at doses of 0.5, 4, and 32 mg/kg body weight, micro-tio 2 with 32 mg/kg body weight and 0.9% NaCl, respectively. The exposure was conducted twice a week, for four consecutive weeks. Histopathological immune organs from exposed animals showed slight congestion in spleen, generally brown particulate deposition in cervical and axillary lymph node. Furthermore, immune function response was characterized by increased proliferation of T cells and B cells following mitogen stimulation and enhanced natural killer (NK) cell killing activity in spleen, accompanying by increased number of B cells in blood. No significant changes of Th1-type cytokines (IL-2 and INF-γ) and Th2-type cytokines (TNF-α and IL-6) were observed. Intratracheal exposure to nano-tio 2 may be one of triggers to be responsible for the systemic immune response. Further study is needed to confirm long-lasting lymphocyte responses and the potential mechanisms.

30 Int. J. Mol. Sci. 2014, Keywords: nano-tio 2 ; systemic immune response; lymphocyte proliferation; cytokines 1. Introduction Nanomaterials are engineered structures with at least one dimension of 100 nanometers or less [1]. With the rapid development of the nanotechnology industry, more and more nanoparticles have generally come into our life through their different approaches. At the same time, safety in nanoparticles is attracting more and more attention. Because of its unusual physicochemical properties, titanium dioxide nanoparticles (nano-tio 2 ) have a wide range of applications in many fields, including cosmetics, pharmaceutical, and paint industries. Previous in vivo studies have shown that nano-tio 2 particles can easily travel throughout the body, penetrate cell membranes, lodge in mitochondria, deposit in target organs, and may cause different degrees of organ damage, including lung, liver, kidney and brain [2 10]. Some in vitro studies also have shown that nano-tio 2 can cause oxidative stress, DNA damage and enzymatic activity changes, followed by cell apoptosis or necrosis [11 13]. Recently, it has been reported that exposure to nano-tio 2 in experimental animals can damage pulmonary macrophages, induce splenocyte apoptosis, promote reactive oxygen species (ROS) accumulation, change cytokine production and decrease immune function [14 18]. However, the researches on immunotoxicity of nano-tio 2 are still rarely reported. Our previous study evaluated the local immune function of rat exposed to nano-tio 2 by intratracheal instillation [19]. The phagocytic ability of the pulmonary alveolar macrophages was increased when they were exposed to low-dose of nano-tio 2 and decreased when they were exposed to high dose of nano-tio 2. In addition, nano-tio 2 damaged the cellular structure, reduced chemotactic ability, decreased expression of both Fc receptors and major histocompatibility complex (MHC)-class II molecules and increased nitric oxide (NO) and tumor necrosis factor alpha (TNF-α) secretion of macrophages, which suggest that nano-tio 2 disrupt the functions of macrophages associated with pulmonary non-specific and specific immunity. On that basis, this study was conducted to assess systemic immune response to repeated pulmonary nano-tio 2 exposure in rats. 2. Results 2.1. Histopathological Examination Histopathological evaluation was performed in various immune organs including spleen, cervical and axillary lymph node and thymus (Figure 1). Rats from high-dose nano-tio 2 exposure showed slight congestion of the splenic sinus. In cervical and axillary lymph node, the brown particulate was generally aggregated in different sizes in rat exposed to 32 mg/kg nano-tio 2. No histopathological changes were found in thymus in all groups.

31 Int. J. Mol. Sci. 2014, Figure 1. Histopathology of the tissue in Sprague-Dawley (SD) rat caused by an intratracheal instillation with nano-tio2 for 28 days (200 ). Hematoxylin and eosin stains of spleen (a1 a5); lymph node (b1 b5) and thymus (c1 c5) tissues of rat. Black arrows point to brown particulate deposition. Spleen Lymph node Thymus Control Nano-TiO mg/kg Nano-TiO 2 4 mg/kg Nano-TiO 2 32 mg/kg Micro-TiO 2 32 mg/kg 2.2. Mitogen Stimulated Lymphocyte Proliferation Assay In this assay, lipopolysaccharide (LPS) and concanavalin A (ConA) are usually used to analyze the proliferation of B- and T-lymphocyte, respectively. The effects of treatment with nano-tio 2 particles

32 Int. J. Mol. Sci. 2014, on spleen-derived lymphocyte proliferation in the rat are shown in Figure 2. As the exposure dose of nano-tio 2 was increased, the B- and T-lymphocyte proliferation stimulated by mitogen was increased. Significant difference in the B- and T-lymphocyte proliferation ability was found in the groups exposed to 4 and 32 mg/kg nano-tio 2 compared with the control group (p < 0.05). Figure 2. Lymphocyte proliferation in the spleen from rats exposed to nano-tio 2 for 28 days by intratracheal instillation. * represents significantly different from control group (p < 0.05) Natural Killer (NK) Cell Activity Assay The effects of treatment with nano-tio 2 particles on spleen-derived natural killer (NK) cell activity in the rat are shown in Figure 3. The NK cell activity was increased with the rise of exposure dose of nano-tio 2 particles. Significant difference in the NK cell activity was found in the groups exposed to 32 mg/kg nano-tio 2 compared with the control group (p < 0.05). Figure 3. Natural killer (NK) cell activity in the spleen from rats exposed to nano-tio 2 for 28 days by intratracheal instillation. * represents significantly different from control group (p < 0.05).

33 Int. J. Mol. Sci. 2014, Lymphocyte Population of Peripheral Blood The results of lymphocyte population distribution in the peripheral blood of rat treated with nano-tio 2 are shown in Figure 4. The B-lymphocyte population distribution was increased with the rise of exposure dose of nano-tio 2. A significant increase of B-lymphocyte distribution was found in the groups exposed to 32 mg/kg nano-tio 2 compared with the control group (p < 0.05). No significant differences in distribution of T-lymphocyte populations and NK cell populations were found between exposure groups and control group (p > 0.05). Figure 4. Lymphocyte population distribution of peripheral blood from rats exposed to nano-tio 2 for 28 days by intratracheal instillation. * represents significantly different from control group (p < 0.05) Cytokine Production in Blood The effects of nano-tio 2 on the production of cytokines in blood were evaluated. No significant changes of IL-2, IL-6, IFN- γ and TNF-α expression were observed (Figure 5). 3. Discussion Increased use of artificial nanoparticles in a wide range has introduced a potential inhaled pollutant. Although the reports on toxicity of nanoparticles are now increasing, immunity-related responses of nanoparticles have not been well studied. In this study, we focused on the systemic immune response induced by repeated exposure of titanium dioxide nanoparticles, involved in immune organ formation, lymphocyte proliferation, lymphocyte distribution and cytokine induction. It has been known that the toxicological effects of nanoparticles are closely related to their specific physicochemical properties. Nano-TiO 2 seemed to be agglomerated in solution state, which might influence evaluation of biological response of nano-tio 2. In our study, we found that 0.9% NaCl buffer is a suitable solution for preparation of nano-tio 2 dispersions and subsequent biological investigation because the solution buffer with 0.9% NaCl maintained a better dispersion. Nano-TiO 2 suspension solution used for the intratracheal instillation in this study showed less aggregation.

34 Int. J. Mol. Sci. 2014, The mean diameter of the agglomerated nano-tio 2 was about 200 nm, which was not micrometer level, but nano level. Figure 5. Cytokines expression in the peripheral blood from rats exposed to nano-tio 2 for 28 days by intratracheal instillation. (A) the changes of IL-2 expression; (B) the changes of IL-6 expression; (C) the changes of IFN-γ expression; and (D) the changes of TNF-α expression. (A) (B) (C) (D) The immune organs play a vital role during the body defense progress for xenobiotic. Spleen is the largest lymphoid organ and important in both innate and adaptive immune. A few evidences have been reported that nano-tio 2 could produce spleen response. Li et al. reported that nano-tio 2 exposure at doses of 50 and 150 mg/kg by intraperitoneal injection for consecutive 45 days induced obvious congestion and lymph nodule proliferation in the mouse spleen [18]. Sang et al. showed that doses of 2.5, 5 and 10 mg/kg nano-tio 2 administrated by intragastric injection for 90 days produced congestion, white pulp rarely, disperative replication of white pulp and anemia of red pulp in the mouse spleen [17]. Chen et al. found that a large number of TiO 2 particles accumulated in spleen, and caused a mass of neutrophilic cells in spleen tissues and a severe spleen lesion after nano-tio 2 exposure with higher doses ( mg/kg) by an intraperitoneal injection for 7 days [8]. Wang et al. observed that 14 days after a large dose of 5 g/kg of nano-tio 2 was administrated by a single intragastric injection, resulted in splenic accumulation of nano-tio 2, but did not cause abnormal pathology changes in the mouse spleen [7]. The histopathological results of this study showed that the repeated intratracheal instillation administration of various doses of nano-tio 2 can induce slight congestion of spleen, consistent with above studies. We did not observe the severe injury of spleen, which may be due to the exposure dose or time of nano-tio 2 (no more than 32 mg/kg, 28 days) in our study which was lower than that in other studies. In addition, we also observed that

35 Int. J. Mol. Sci. 2014, nano-tio 2 may cause significant accumulation in the rat lymph node, while there are no abnormal pathology changes in the micro-tio 2 exposure group. Van Ravenzwaay et al. also reported nano-tio 2 (14% rutile, 86% anatase) accumulation in lymphoid tissue after inhalation exposure in the rat [20]. These results indicated that inhaled nano-tio 2 could translocate throughout the body quickly and tend to accumulate in immune organ, which possibly through uptake by migratory antigen presenting cells, because many toxicological studies have observed that macrophages or foreign-body giant cells appeared in lung tissue as exposure doses increased [21,22]. We have previously reported altered local immune cell function following intratracheal instillation of nano-tio 2. It was observed that nano-tio 2 were uptake in pulmonary macrocrophages, consistent with pulmonary macrophages as the first-line defense against inhalation of particles. Function detection showed that exposures to nano-tio 2 increased the phagocytic ability of the pulmonary macrophages [19]. In this study, immune function measurements on spleen-derived cells showed increased proliferation of T cells and B cells following mitogen stimulation and enhanced NK cell killing activity, which was accompanied by increased B cells number in blood. Lymphocyte proliferation is an important phase in the immune response. The results indicated that nano-tio 2 could trigger systemic immune responses. Recent studies have revealed that exposure to nanoparticles can stimulate immune cell. Lee et al. reported that mesoporous silica nanoparticles led to significant splenocyte proliferation to the lymphocyte mitogens when administered by intraperitoneal injection in female BALB/c mice for 4 weeks [23]. Park et al. showed an increase in numbers of B cells in splenocytes and in blood after mice were treated with nano-tio 2 by a single intratracheal instillation [24]. Wang et al. researched that increases T cells in the spleen of C57BL/6 mice dependent on nanomaterial comparison of graphene and carbon nanotubes [25]. Gustafsson et al. discussed an increase in numbers of NK cells in lung after exposure to nano-tio 2 by intratracheal installation [26]. However, Sang et al. noted lymphocytes (including T, B lymphocyte and NK cell) of whole blood in mice were significantly decreased following nano-tio 2 exposure for 90 consecutive days by intragastric administrations [17]. Differences in response may be attributed to route of administration, dose and exposure time. Cytokines are very important regulators of the immune responses and serve to maintain balance of immune system. After adaptive immune system was triggered, the activated T cells were differentiated into helper T cells and cytotoxic T cells. Then, helper T cells were differentiated into Th1 cell and Th2 cell. Th1 and Th2 cell trigger cellular and humoral immunity by secret cytokines, respectively. It was reported that IL-2 and IFN-γ levels in serum levels was significantly increased in rat treated with nano-tio 2, indicating that nano-tio 2 exposure may trigger Th1 immune response [26]. However, another recently report showed that nano-tio 2 induced a Th2 cell response in mice [27]. In this study, we analyzed the Th1-type cytokines (IL-2 and INF-γ) and Th2-type cytokines (TNF-α and IL-6). However, no significant changes of these cytokines expression were observed throughout the experimental period. The discrepancy is likely explained by species differences, nano-tio 2 particle differences, especially observation time differences. Gustafsson et al. reported that most cytokine expression at days 1 2 and a second response at day 16 of TNF-α after nano-tio 2 exposure [26]. Park et al. also noted IL-2 and IL-4 were increased in a time-dependent manner [24]. In the future, dynamic investigations will be performed to understand the mechanism between Th-related cytokines and systemic immune response with nano-tio 2 exposure.

36 Int. J. Mol. Sci. 2014, Experimental Section 4.1. Preparation of Nano-TiO 2 Manufactured nano-tio 2 (P25) was purchased from Degussa Corporation (Hanau, Germany). Micro-TiO 2 of size 1 2 μm was purchased from Beijing DK nano technology Co., Ltd. (Beijing, China). According to the information provided by the supplier, nano-tio 2 is a fine white powder with mean diameter of 21 nm (Table 1). The characteristics of the nano-tio 2 were found in our previously study [28]. Nano-TiO 2 was heated to 121 C for 20 min to reduce the risk of bacterial contamination. TiO 2 powder was dispersed into an aqueous solution buffered with 0.9% (w/v) sodium chloride (NaCl) solution. For sufficiently disperse particles, solutions containing TiO 2 particles were sonicated for 5 min at 30% amplitude by Sonicator ultrasonic processor (Model S-4000, Misonix, Inc., Farmingdale, NY, USA). Size distribution of nano-tio 2 suspension was also analyzed using Malvern Instruments Zetasizer Nano ZS90 (Malvern Instruments Ltd., Worcestershire, UK). The mean diameter of nano-tio 2 suspended in 0.9% NaCl was about 200 nm (Figure 6) Animals and Treatment Table 1. Characterization of TiO 2 particles. Particle Nano-TiO 2 Micro-TiO 2 supplier Degussa DK nano size (nm) 21 nm 1 2 μm crystalline form 80% anatase/20% rutile anatase specific surface area (m 2 /g) purity (%) >99.5 >99.9 Z-Average (d.nm) PDI * * The polydispersity index (PDI) describes the width of the particle size distribution. Male Sprague-Dawley (SD) rats, with an average body weight of g, were provided from Liaoning Chang Sheng Biotechnology Co., Ltd. (Benxi, China). The animal room was maintained at 20 ± 2 C, 60% ± 10% relative humidity and a 12 h light/dark cycle. Rats were acclimatized for 5 days before experimentation. Procedures complied with the national regulations related to animal welfare. Forty rats were randomly divided into five groups. The control group was treated with 0.9% w/w NaCl solution. The experimental groups were treated with 0.5, 4, 32 mg/kg nano-tio 2 and 32 mg/kg micro-tio 2, respectively. All groups were performed to repeated exposure (twice a week, for four consecutive weeks) by intratracheal instillation. The volume of intratracheal instillation was 0.1 ml/100 g. Four weeks later, the rats were sacrificed by exsanguination via the abdominal aorta after being anesthetized by ether. Spleen, cervical and axillary lymph node, thymus, and whole blood were collected for further assay.

37 Int. J. Mol. Sci. 2014, Figure 6. Particle size distribution of nano-tio 2 in NaCl suspension Histopathological Examination All histopathological tests were performed using standard lab-oratory procedures. The spleen, lymph node and thymus tissues were fixed in a 10% formalin solution for one week. Then, the tissues were embedded in paraffin blocks, and then sectioned into 5 μm slices and mounted on glass slides. After hematoxylin eosin (HE) staining, the slides were examined using an optical microscope (Olympus, Tokyo, Japan). The identity and analysis of the pathology slides were blind to the pathologist Preparation of Spleen-Derived Lymphocyte Populations Single-cell lymphocyte populations were prepared from the spleen of rat. Spleen was dissociated on a steel mesh in Hanks balanced salt solution (Beyotime, Nantong, China). The splenocyte that passed through the mesh were centrifuged at 2000 rpm for 5 min. The supernatant was discarded and cells were resuspended in the Hanks medium. The red blood cell lysis buffer (Beyotime, Nantong, China) was added to lyse the erythrocytes. Then, the cell suspension was filtered and washed to remove cell debris. Finally, cells were resuspended in RPMI1640 [with 10% fetal bovine serum (FBS)] (Hyclone, Victoria, Australia). Cell viability was assessed using the trypan blue exclusion test and routinely found to contain <5% dead cells. The cell density was adjusted to cells/ml for further assay Mitogen Stimulated Lymphocyte Proliferation Assay Lymphocyte proliferation responses to mitogens (lipopolysaccharide, LPS and concanavalin A, ConA) were evaluated with the CCK-8 assay. For each spleen sample, lymphocyte were placed into a U-bottom 96-well plate in triplicate at a density of cells/ ml with a total volume of 90 µl. 10 μl LPS (L2630, Sigma, St. Louis, MO, USA) or ConA (C2010, Sigma, St. Louis, MO, USA) at a concentration of 20 μg/ml was added to wells, respectively. Supplemented RPMI1640 media were added to control wells. Plates were briefly mixed on a plate shaker and then placed in a 5% CO 2, 37 C incubator for 72 h. Then, CCK-8 was added and incubated for an additional 4 h. Following incubation, spectrophotometric data were measured using an automatic microplate reader (type MRX, Dynex Technologies Company, Chantilly, VA, USA) at a wavelength of 450 nm.

38 Int. J. Mol. Sci. 2014, Natural Killer (NK) Cell Activity Assay NK cell activity was evaluated by lactate dehydrogenase (LDH) release assay. Human erythroleukemia cell line K-562 (Chinese Academy of Sciences, Shanghai, China) was used as a target cell in this assay because it is sensitive to the cytotoxicity of NK cells. K562 cells were routinely cultured in RPMI1640 medium (with 10% FBS) (Hyclone, Victoria, Australia) and were plated at a concentration of cells/ml in U-bottom 96-well plates (Corning, Shanghai, China). Splenocytes were plated at cells/ml for an effector to target ratio (E:T) of 50:1. Two controls were placed for the assay, including a spontaneous control (target cells + RPMI1640 medium) and a maximum spontaneous control (target cells + 1% NP40 lysis buffer). Plates were incubated at 5% CO 2, 37 C for 20 h and then centrifuged at 2000 rpm for 5 min. One hundred µl the supernatant was removed to the new plate, followed by 100 µl LDH matrix liquid and 30 µl 1 M HCL was added to each well. Finally, optical density (OD) was measured using an automatic microplate reader at a wavelength of 490 nm. Percentage of cytotoxicity was calculated by: Cytotoxicity % = (sample OD spontaneous OD) (maximum OD spontaneous OD) 100% (1) 4.7. Lymphocyte Population Analyses in Blood Lymphocyte population distribution in peripheral blood was examined using flow cytometry method. All monoclonal antibodies were purchased from ebioscience (San Diego, CA, USA). T cells (CD3, ebiog4.18), B cells (CD45RA, OX33), NK cells (CD161, clone 10/78) were identified using directly conjugated anti-rat antibody [29]. Erythrocytes in the blood were lysed with red blood cell lysis buffer. Then, cells were washed with PBS buffer. Finally, each sample was fixed with 0.1% paraformaldehyde and analyzed by flow cytometry (BD Biosciences, Franklin Lakes, NJ, USA) Cytokines Analyses in Blood Serum samples were obtained from peripheral blood by centrifugation at 3000 rpm for 10 min at 4 C and immediately frozen at 80 C for further detection. IL-2, IL-6, IFN-γ and TNF-α were measured by a MILLIPLEX MAP Rat Cytokine Kit (Millipore, Billerica, MA, USA) according to the manufacturers instructions Statistical Analysis Statistical analysis was done by SPSS16.0 software (SPSS Inc., Chicago, IL, USA). The differences of means among groups were analyzed by One-way analysis of variance method (ANOVA). The comparisons between experimental group and control group were made by LSD test. The results were regarded as statistical significant as p < Conclusions In summary, nano-tio2 induced pathological changes of spleen and lymph node, including slight congestion and brown particulate accumulation. Furthermore, increased proliferation of spleen-derived T cells and B cells following mitogen stimulation and enhanced NK cell killing activity were observed

39 Int. J. Mol. Sci. 2014, by repeated instillation of nano-tio 2. Number of B cell was also increased in the blood. The result suggested that nano-tio 2 may be one of triggers to be responsible for the systemic immune response. The study served to improve the overall understanding of the immune response associated with inhalable nano-tio 2 and provided new strategy for risk assessment of nano-tio 2. More work needs to be done to evaluate the potential mechanism for this response. Acknowledgments The authors thank the support from the National Natural Science Foundation (No ); State Key Program for Basic Research of China (No. 2011CB933404); Qing Lan Project (2012); 333 project of Jiangsu Province (2012); Liu Da Ren Cai Gao Feng Project of Jiangsu Province (2013-WSW-053); and the Fundamental Research Funds for the Central Universities (CXZZ13_0134). Author Contributions Conception and design: Geyu Liang, Yanyun Fu; Administrative support: Lihong Yin, Yuepu Pu; Animal experiment and data collection: Yanyun Fu, Yanqiu Zhang, Xuhong Chang, Yingjian Zhang, Shumei Ma, Jing Sui; Data analysis and drafting of manuscript: Geyu Liang, Yanyun Fu; Critical revisions/supervision: Geyu Liang, Yanyun Fu, Lihong Yin, Yuepu Pu. Conflicts of Interest The authors declare no conflict of interest. References 1. Nel, A.; Xia, T.; Madler, L.; Li, N. Toxic potential of materials at the nanolevel. Science 2006, 311, Chen, H.W.; Su, S.F.; Chien, C.T.; Lin, W.H.; Yu, S.L.; Chou, C.C.; Chen, J.J.; Yang, P.C. Titanium dioxide nanoparticles induce emphysema-like lung injury in mice. FASEB J. 2006, 20, Liu, R.; Yin, L.; Pu, Y.; Liang, G.; Zhang, J.; Su, Y.; Xiao, Z.; Ye, B. Pulmonary toxicity induced by three forms of titanium dioxide nanoparticles via intra-tracheal instillation in rats. Prog. Nat. Sci. 2009, 19, Halappanavar, S.; Jackson, P.; Williams, A.; Jensen, K.A.; Hougaard, K.S.; Vogel, U.; Yauk, C.L.; Wallin, H. Pulmonary response to surface-coated nanotitanium dioxide particles includes induction of acute phase response genes, inflammatory cascades, and changes in micrornas: A toxicogenomic study. Environ. Mol. Mutagen. 2011, 52, Cui, Y.; Liu, H.; Ze, Y.; Zengli, Z.; Hu, Y.; Cheng, Z.; Cheng, J.; Hu, R.; Gao, G.; Wang, L.; et al. Gene expression in liver injury caused by long-term exposure to titanium dioxide nanoparticles in mice. Toxicol. Sci. 2012, 128, Liu, H.; Ma, L.; Liu, J.; Zhao, J.; Yan, J.; Hong, F. Toxicity of nano-anatase TiO 2 to mice: Liver injury, oxidative stress. Toxicol. Environ. Chem. 2010, 92,

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42 Pre-Diagnostic Plasma 25-Hydroxyvitamin D Levels and Risk of Non-Melanoma Skin Cancer in Women Geyu Liang 1, Hongmei Nan 2,5, Abrar A. Qureshi 2,3, Jiali Han 2,3,4 * 1 Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China, 2 Channing Laboratory, Department of Medicine, Brigham and Women s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America, 3 Department of Dermatology, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 4 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, 5 Division of Cancer Epidemiology, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, United States of America Abstract Background: Recent reports have shown that vitamin D status was inversely associated with the risk of various cancers. However, few studies examined the association between vitamin D levels and risk of skin cancer. Methods: We prospectively evaluated the association between baseline plasma 25(OH)D levels and the risk of incident squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) among 4,641 women from the Nurses Health Study (NHS) and the NHS II with 510 incident BCC cases and 75 incident SCC cases. We used multivariate logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Results: Plasma 25(OH)D levels were positively associated with risk of BCC after adjusting for age at blood draw, season of blood draw, lab batch, hair color, burning tendency, the number of sunburns, and ultra-violet B flux of residence at blood collection. Women in the highest quartile of 25(OH)D had more than 2-fold increased risk of BCC compared with women in the lowest quartile (OR = 2.07, 95% CI = , P for trend,0.0001). We also found a significantly positive association between plasma 25(OH)D levels and SCC risk after adjusting for the same covariates (OR, highest vs. lowest quartile = 3.77, 95% CI = , P for trend = ). Conclusion: In this prospective study of women, plasma vitamin D levels were positively associated with non-melanoma skin cancer risk. Considering that most circulating vitamin D is due to sun exposure, the positive association between plasma vitamin D and non-melanoma skin cancer is confounded by sun exposure. Our data suggest that one-time measurement of plasma vitamin D levels may reasonably reflect long-term sun exposure and predict the risk of nonmelanoma skin cancer. Citation: Liang G, Nan H, Qureshi AA, Han J (2012) Pre-Diagnostic Plasma 25-Hydroxyvitamin D Levels and Risk of Non-Melanoma Skin Cancer in Women. PLoS ONE 7(4): e doi: /journal.pone Editor: Yiqing Song, Brigham & Women s Hospital, and Harvard Medical School, United States of America Received February 3, 2012; Accepted March 12, 2012; Published April 6, 2012 Copyright: ß 2012 Liang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work is supported by NIH grants CA50385, CA67262, CA87969, and CA The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * jiali.han@channing.harvard.edu Introduction Skin cancer, the most common malignancy, has been increasing rapidly over the past decades in the United States, especially in women [1 3]. Mounting epidemiologic evidence has suggested that vitamin D may be associated with reduced risk of various types of cancers, including colorectal [4], prostate [5], breast [6], pancreatic [7], and lung cancers [8]. However, few studies have examined the association between vitamin D levels and risk of skin cancer, and the data are inconsistent [9 11]. It is more difficult to study the relationship between vitamin D and skin cancer than other internal cancers because vitamin D is predominantly produced in the skin by ultraviolet B (UVB) exposure, which is the well-established risk factor for skin cancer. UVB exposure-synthesized vitamin D in the skin usually contributes 80 90% to total vitamin D in the human body [12]. Only small amount of vitamin D is derived from other sources including dietary intake. 25-hydroxyvitamin D [25(OH)D] is produced in the liver by a hydroxylation reaction [13]. Circulating plasma 25(OH)D is considered to be the best biomarker of vitamin D status because it reflects the total vitamin D levels [14]. Three epidemiologic investigations have suggested conflicting associations of skin cancer with vitamin D levels [9 11]. In an analysis of the Osteoporotic Fractures in Men Study, inverse association between plasma vitamin D levels and risk of non-melanoma skin cancer in elderly men was found [9]. However, in two other recent analyses of health maintenance organization populations, higher plasma vitamin D levels were significantly associated with increased risk of non-melanoma skin cancer [10,11]. Although experimental studies have shown that vitamin D treatment can inhibit proliferation of melanoma and basal cell carcinomas in vitro [15,16], recent evidence in a large cohort of postmenopausal women suggests that daily supplementation of vitamin D did not reduce incidence of skin cancer [17]. However, this study using PLoS ONE 1 April 2012 Volume 7 Issue 4 e35211

43 Plasma 25-Hydroxyvitamin D and Skin Cancer low dose vitamin D supplementation (400 IU/day) may not offer informative evidence regarding the potential influence of vitamin D status on skin cancer development [17]. Here we prospectively assess the association between plasma 25(OH)D levels and the risk of non-melanoma skin cancer in a nested case-control study among women from two large ongoing cohort studies: the Nurses Health Study (NHS) and NHS II. Methods Ethics Statement The institutional review board of Brigham and Women s Hospital approved this study. Participants completion and return of the self-administered questionnaire was considered to imply informed consent. NHS Nested Case-control Study In 1976, 121,700 female registered nurses between 30 and 55 years old were enrolled in the NHS. Women completed an initial questionnaire and have been followed biennially by questionnaire to update information on exposure status and to identify newly diagnosed case subjects of cancer and other medical conditions. Between 1989 and 1990, blood samples were collected from 32,826 participants for analysis. Measurements of plasma 25(OH)D levels were available from a subset of the women who served as controls in several nested case-control studies of chronic diseases conducted previously, including breast cancer, colon polyps, colon cancer and ovarian cancer [18 21]. Eligible cases in this study were Caucasian women with incident skin squamous cell carcinoma (SCC) or basal cell carcinoma (BCC) occurring after blood collection but before The rest of the subjects were controls. Participants who had previously diagnosed skin cancer before blood collection were excluded from the analysis. The nested case-control study consisted of 387 BCC cases, 67 SCC cases, and 1,641 controls. NHS II Nested Case-control Study The NHS II was established in 1989 among 116,609 female registered nurses between the ages of 25 and 42. Participants completed biennial mailed questionnaires to update exposure status and disease diagnoses. Between 1996 and 1999, 29,611 participants provided blood samples. We used all the controls from previous nested case-control studies of chronic disease within the NHS II blood cohort that had been analyzed for vitamin D, including hypertension, breast cancer and ovarian cancer [19,22,23]. The inclusive and exclusive conditions of cases and controls were the same as for the NHS. Eligible cases were Caucasian women with incident skin SCC or BCC occurring after blood collection and the rest of the subjects were controls. The follow-up ended in Participants who had previously diagnosed skin cancer before blood collection were excluded. The nested case-control study consisted of 123 BCC cases, 8 SCC cases, and 2,415 controls. Identification of BCC and SCC We have routinely identified cases of BCC and SCC in both cohorts. Participants reported new diagnoses biennially. With their permission, participants medical records were obtained and reviewed by physicians to confirm their self-reported diagnosis. Only pathologically confirmed invasive SCC cases were included in this study. Medical records were not obtained for self-reported cases of BCC, but the validity of BCC self-reports was more than 90% in validation studies in our cohorts in early years [24,25]. In this analysis, cases were diagnosed after blood collection and up to 2008 (NHS) and 2007 (NHS II). Measurement of Plasma 25(OH)D Plasma 25(OH)D concentrations were measured using radioimmunoassay or chemiluminescence immunoassay, which have been described in detail previously [26,27]. In the NHS, laboratory assays were completed in 14 batches of 4 studies from 1996 to 2004 (3 batches in 1996, 4 batches in 2000, and 7 batches in 2004). In the NHS II, blood samples were assayed in 3 batches of 3 studies (1 batch in 2003 and 2 batches in 2005). Blinded replicate quality-control samples were interspersed throughout the sets for assessing variability. The intra-assay coefficients of variation (CV) were,17.6%. Statistical Analysis In the nested case-control study of SCC or BCC, 25(OH)D measurements (continuous in ng/ml) were categorized into quartiles according to the distribution in control population of Table 1. Characteristics by quartile of plasma vitamin D concentrations in NHS and NHS II. 25-Hydroxyvitamin D concentrations, ng/ml NHS NHS II 1st quartile 2nd quartile 3rd quartile 4th quartile 1st quartile 2nd quartile 3rd quartile 4th quartile n Age at blood draw (y) 57.5(7.1) 57.6(6.7) 57.9(6.9) 58.0(6.8) 44.6(4.2) 44.0(4.2) 43.6(4.4) 43.4(4.4) Red or blonde hair color (%) Burning tendency (%) Numbers of sunburns ($5, %) Season of blood draw Summer (%) Spring and Fall (%) Winter (%) UVB flux (.113, %) Values are presented as means (Standard deviation) or percentages. doi: /journal.pone t001 PLoS ONE 2 April 2012 Volume 7 Issue 4 e35211

44 Plasma 25-Hydroxyvitamin D and Skin Cancer NHS and NHS II study separately. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated to examine the relationship between plasma 25(OH)D levels and SCC or BCC by multivariate logistic regression models. Age at blood draw (in years), season of blood draw [summer (June-August), fall (September-November), winter (December-February), and spring (March-May)], and laboratory batch were included as independent variables in all models. Hair color (1 = red, 2 = blonde, 3 = light brown, 4 = dark brown, 5 = black), burning tendency (1 = practically none, 2 = some redness only, 3 = burn, 4 = painful burn, 5 = painful burn with blisters), the number of sunburns (1 = never, 2 = 1 2, 3 = 3 5, 4 = $6), and average annual UV-B flux at residence (#113 and.113) were also adjusted for in the multivariate models. Pooled analyses of two cohort studies were conducted by merging data sets. A previous study indicated that seasonal variation may introduce biased results of 25(OH)D levels [28]. Therefore, we conducted stratified analysis to test the interaction of vitamin D and season of blood draw. We modeled season of blood draw as a three-category variable (summer, spring and fall, winter). We tested two multiplicative interaction terms by the likelihood ratio test, comparing the model with the interaction terms with the model containing just the main effects of vitamin D and season of blood draw variables, along with the same covariates. To test interaction of vitamin D and UVB flux, we modeled UVB flux as a dichotomous variable (113 as a cutoff point). We tested one multiplicative interaction term by the likelihood ratio test. Finally, to summarize multiple variables, we constructed a multivariate confounder score [29] to create a pigmentation score for BCC. Briefly, we applied the logistic regression coefficients from a multivariate model including age, hair color, burning tendency, and the number of sunburns of BCC to each individual s values for the latter three of these variables and summed the values to compute a pigmentation score. We used this score to identify participants with light and dark pigmentation phenotypes based on the median score. We tested one multiplicative interaction term between vitamin D and pigmentation by the likelihood ratio test. Statistical analyses were conducted using SAS software (version 9, SAS Institute, Cary, NC). All statistical tests were two-sided. Results The characteristics of women by quartiles of plasma 25(OH)D concentration in two cohorts are presented in Table 1. Women who provided blood samples in summer tended to have higher 25(OH)D levels than those whose blood was drawn in winter, which is consistent with previously published data [30]. In addition, women with higher 25(OH)D levels were more likely to reside in areas of higher UVB flux. The associations between plasma vitamin D levels and BCC and SCC were examined separately (Tables 2 and 3). Similar significantly positive findings were obtained between plasma 25(OH)D and risk of BCC in both cohorts in multivariate models (P for trend, and = 0.01). Women in the highest quartile of 25(OH)D had about 2-fold increased risk of BCC compared with women in the lowest quartile, both in NHS (OR = 2.28, 95% CI = ) and in NHS II (OR = 1.93, 95% CI = ). Results were similar when combining the data of NHS and NHS Table 2. Odds ratios of BCC by quartile of plasma vitamin D concentrations in NHS and NHS II. 25-Hydroxyvitamin D concentrations, ng/ml 1st quartile 2nd quartile 3rd quartile 4th quartile P for trend NHS Quartile values # n, case/control 69/406 86/ / /410 OR a 1.00(reference) 1.21( ) 1.63( ) 2.25( ),.0001 OR b 1.00(reference) 1.19( ) 1.59( ) 2.28( ),.0001 OR c 1.00(reference) 1.18( ) 1.57( ) 2.28( ),.0001 NHS II Quartile values # n, case/control 24/604 26/602 34/603 39/606 OR a 1.00(reference) 1.19( ) 1.62( ) 1.93( ) 0.01 OR b 1.00(reference) 1.20( ) 1.64( ) 1.94( ) 0.01 OR c 1.00(reference) 1.20( ) 1.63( ) 1.93( ) 0.01 Total n, case/control 93/ / / /1016 OR d 1.00(reference) 1.19( ) 1.59( ) 2.07( ),.0001 OR e 1.00(reference) 1.17( ) 1.55( ) 2.07( ),.0001 OR f 1.00(reference) 1.17( ) 1.54( ) 2.07( ),.0001 Abbreviation: OR, odds ratio. a Adjusted for age at blood draw, season of blood draw, lab batch. b Adjusted for age at blood draw, season of blood draw, lab batch, hair color, burning tendency, numbers of sunburns. c Adjusted for age at blood draw, season of blood draw, lab batch, hair color, burning tendency, numbers of sunburns, UVB flux. d Adjusted for age at blood draw, season of blood draw, lab batch, cohort. e Adjusted for age at blood draw, season of blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns. f Adjusted for age at blood draw, season of blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns, UVB flux. doi: /journal.pone t002 PLoS ONE 3 April 2012 Volume 7 Issue 4 e35211

45 Plasma 25-Hydroxyvitamin D and Skin Cancer Table 3. Odds ratios of SCC by quartile of plasma vitamin D concentrations in NHS and NHS II. 25-Hydroxyvitamin D concentrations, ng/ml 1st quartile 2nd quartile 3rd quartile 4th quartile P for trend NHS Quartile values # n, case/control 9/406 12/420 22/405 24/410 OR a 1.00(reference) 1.43( ) 2.84( ) 3.56( ) OR b 1.00(reference) 1.48( ) 2.95( ) 3.79( ) OR c 1.00(reference) 1.49( ) 3.04( ) 3.96( ) NHS II Quartile values # n, case/control 1/604 1/602 2/603 4/606 OR a 1.00(reference) 1.03( ) 1.94( ) 3.43( ) 0.20 OR b 1.00(reference) 1.33( ) 2.54( ) 4.22( ) 0.17 OR c 1.00(reference) 1.48( ) 2.62( ) 4.95( ) 0.15 Total n, case/control 10/ / / /1016 OR d 1.00(reference) 1.37( ) 2.73( ) 3.62( ) OR e 1.00(reference) 1.43( ) 2.87( ) 3.87( ) OR f 1.00(reference) 1.40( ) 2.81( ) 3.77( ) a Adjusted for age at blood draw, season of blood draw, lab batch. b Adjusted for age at blood draw, season of blood draw, lab batch, hair color, burning tendency, numbers of sunburns. c Adjusted for age at blood draw, season of blood draw, lab batch, hair color, burning tendency, numbers of sunburns, UVB flux. d Adjusted for age at blood draw, season of blood draw, lab batch, cohort. e Adjusted for age at blood draw, season of blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns. f Adjusted for age at blood draw, season of blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns, UVB flux. doi: /journal.pone t003 Table 4. Odds ratios of BCC by quartile of plasma vitamin D concentrations in NHS and NHS II (stratified by season of blood draw). season of blood draw 25-Hydroxyvitamin D concentrations, ng/ml d P for trend 1st quartile 2nd quartile 3rd quartile 4th quartile Summer n, case/control 25/138 33/224 44/259 56/333 OR a 1.00(reference) 0.73( ) 0.90( ) 0.95( ) 0.81 OR b 1.00(reference) 0.68( ) 0.88( ) 0.93( ) 0.82 OR c 1.00(reference) 0.68( ) 0.88( ) 0.93( ) 0.81 Spring and fall n, case/control 41/536 61/550 84/517 95/516 OR a 1.00(reference) 1.46( ) 2.26( ) 3.08( ),.0001 OR b 1.00(reference) 1.45( ) 2.11( ) 2.97( ),.0001 OR c 1.00(reference) 1.45( ) 2.10( ) 2.97( ),.0001 Winter n, case/control 37/331 31/243 38/229 39/162 OR a 1.00(reference) 1.38( ) 1.41( ) 2.29( ) 0.01 OR b 1.00(reference) 1.35( ) 1.47( ) 2.58( ) OR c 1.00(reference) 1.33( ) 1.44( ) 2.53( ) a Adjusted for age at blood draw, lab batch, cohort. b Adjusted for age at blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns. c Adjusted for age at blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns, UVB flux. d P for interaction between season of blood draw and 25-hydroxyvitamin D is 0.09 after adjusted for age at blood draw, lab batch, cohort. doi: /journal.pone t004 PLoS ONE 4 April 2012 Volume 7 Issue 4 e35211

46 Plasma 25-Hydroxyvitamin D and Skin Cancer Table 5. Odds ratios of BCC by quartile of plasma vitamin D concentrations in NHS and NHS II (stratified by UVB flux). UVB flux 25-Hydroxyvitamin D concentrations, ng/ml c P for trend 1st quartile 2nd quartile 3rd quartile 4th quartile #113 n, case/control 60/666 88/648 94/ /556 OR a 1.00(reference) 1.49( ) 1.82( ) 2.62( ),.0001 OR b 1.00(reference) 1.49( ) 1.81( ) 2.66( ), n, case/control 43/343 37/374 72/443 78/458 OR a 1.00(reference) 0.79( ) 1.24( ) 1.45( ) 0.04 OR b 1.00(reference) 0.80( ) 1.25( ) 1.52( ) 0.03 a Adjusted for age at blood draw, season of blood draw, lab batch, cohort. b Adjusted for age at blood draw, season of blood draw, lab batch, cohort, hair color, burning tendency, numbers of sunburns. c P for interaction between UVB flux and 25-hydroxyvitamin D is 0.07 after adjusted for age at blood draw, season of blood draw, lab batch, cohort. doi: /journal.pone t005 II (OR = 2.07, 95% CI = , P for trend,0.0001) (Table 2). We noted significantly positive associations between quartiles of 25(OH)D levels and SCC in NHS (OR = 3.96, 95% CI = , P for trend = ). In NHS II, although a similar trend was observed, the result was not statistically significant because only eight cases were identified. Overall, the positive association between 25(OH)D levels and SCC was significant after combining the two cohorts (P for trend = ). Women in the highest quartile of 25(OH)D had more than a 3-fold increased risk for SCC compared with women in the lowest quartile (OR = 3.77, 95% CI = ) (Table 3). We further examined the association between plasma 25(OH)D levels and BCC risk stratified by season of blood draw, UVB flux, and pigmentation (Tables 4, 5, 6). There was a significant positive association between 25(OH)D and risk of BCC among women with bloodcollectioninspring/fall(or = 2.97,95%CI = )orin winter (OR = 2.53, 95% CI = ), whereas no association was observed among women with blood collection in summer (OR = 0.93, 95% CI = ) (P for interaction = 0.09) (Table 4). In the stratified analysis by UVB flux, women who lived in lower UVB flux (#113) areas tended to have higher OR (2.66, 95% CI = ) when comparing the top to bottom quartile of 25(OH)D levels (P for interaction = 0.07) (Table 5). The positive association between 25(OH)D and risk of BCC appeared to be stronger among women with light pigmentation (P for interaction = 0.15) (Table 6). Discussion In this study, higher plasma 25(OH)D levels were associated with greater non-melanoma skin cancer risk among women from two large cohorts. In subgroup analysis, higher plasma 25(OH)D tended to increase risk of BCC in women whose blood was collected outside the summer season, who were from areas with less UVB flux (#113), and among those with light pigmentation. To our knowledge, the current study is one of the largest to provide important evidence on the association of prediagnostic plasma 25(OH)D levels with non-melanoma skin cancer. Vitamin D is predominantly produced in the skin by UVB exposure, which usually contributes 80 90% to total vitamin D in the human body [12]. Our data suggest that one-time measurement of plasma vitamin D levels may reasonably reflect long-term sun exposure. The validity of single 25(OH)D measures was also Table 6. Odds ratios of BCC by quartile of plasma vitamin D concentrations in NHS and NHS II (stratified by pigmentation). pigmentation 25-Hydroxyvitamin D concentrations, ng/ml c P for trend 1st quartile 2nd quartile 3rd quartile 4th quartile Light pigmentation n, case/control 46/522 53/531 81/488 97/498 OR a 1.00(reference) 1.08( ) 1.84( ) 2.35( ),.0001 OR b 1.00(reference) 1.08( ) 1.81( ) 2.31( ),.0001 Dark pigmentation n, case/control 57/488 72/491 85/520 94/518 OR a 1.00(reference) 1.26( ) 1.38( ) 1.84( ) OR b 1.00(reference) 1.26( ) 1.38( ) 1.85( ) a Adjusted for age at blood draw, season of blood draw, lab batch, cohort. b Adjusted for age at blood draw, season of blood draw, lab batch, cohort, UVB flux. c P for interaction between UVB flux and 25-hydroxyvitamin D is 0.15 after adjusted for age at blood draw, season of blood draw, lab batch, cohort. doi: /journal.pone t006 PLoS ONE 5 April 2012 Volume 7 Issue 4 e35211

47 Plasma 25-Hydroxyvitamin D and Skin Cancer evaluated in NHS. The intraclass correlation coefficients for plasma 25(OH)D measured over 3 years and over years were 0.72 and 0.50, respectively [31]. This indicates that a single 25(OH)D measurement is fairly reproducible over years and reasonably reflects long-term vitamin D status. It is well known that sun exposure is the main cause of skin cancers. Therefore, plasma 25(OH)D levels may predict the risk of non-melanoma skin cancer. Recently, Eide et al.[10] reported a positive relationship between plasma levels of 25(OH)D and non-melanoma skin cancer (adjusted OR, 1.8; 95% CI, ), including SCC and BCC, in a study of 3223 white health maintenance organization patients who sought advice about the risk of osteoporosis or low bone density. The 25(OH)D levels were similarly positively associated with non-melanoma skin cancer risk at anatomical locations less exposed to UV (adjusted OR, 2.2; 95% CI, ). In another nested case-control study, Asgari et al. [11] also found an increased risk of BCC with higher vitamin D levels among 220 BCC patients and 220 matched controls from the Kaiser Permanente Northern California Health Maintenance Organization (adjusted OR, 2.09; 95% CI, ,58). The results of this study support the findings from Eide et al. and Asgari et al., with similar risk estimated for BCC. However, Tang et al. [9] found an inverse association between higher plasma 25(OH)D levels and risk of non-melanoma skin cancer (OR, 0.6; 95% CI, ) among 930 white men from the Osteoporotic Fractures in Men Study. It should be noted that all the participants in this study and most of the patients of Eide et al. were women, but the participants in study of Tang et al. were men. Furthermore, the cohorts in our study were followed up for more than 10 years, and the Eide et al. cohort was followed for almost 10 years, but the patients of Tang et al. were followed up for only 5 years. Lastly, our study had the largest sample size. These differences may explain the variations between the results in this study and those of Tang et al. Stratified analysis on season suggests that 25(OH)D is positively associated with BCC risk among women whose blood was collected outside the summer months. In addition, we observed that the associations between plasma 25(OH)D and BCC risk were stronger among women from areas with less UVB flux. Similar to previous report [32], our data support that plasma 25(OH)D could reasonably reflect long-term vitamin D status more accurately outside the summer season or in areas of less UVB flux. In a casecontrol study, an inverse association between 25(OH)D and lung cancer was also found only among those whose blood was drawn during the darker months [33]. References 1. Miller DL, Weinstock MA (1994) Nonmelanoma skin cancer in the United States: Incidence. J Am Acad Dermatol 30: Christenson LJ, Borrowman TA, Vachon CM, Tollefson MM, Otley CC, et al. (2005) Incidence of basal cell and squamous cell carcinomas in a population younger than 40 years. JAMA 294: Linos E, Swetter SM, Cockburn MG, Colditz GA, Clarke CA (2009) Increasing burden of melanoma in the United States. J Invest Dermatol 129: Wu K, Feskanich D, Fuchs CS, Willett WC, Hollis BW, et al. (2007) A nested case control study of plasma 25-hydroxyvitamin D concentrations and risk of colorectal cancer. J Natl Cancer Inst 99: Ahonen MH, Tenkanen L, Teppo L, Hakama M, Tuohimaa P (2000) Prostate cancer risk and prediagnostic serum 25-hydroxyvitamin D levels (Finland). Cancer Causes Control11: Goodwin PJ, Ennis M, Pritchard KI, Koo J, Hood N (2009) Prognostic effects of 25- hydroxyvitamin D levels in early breast cancer. J Clin Oncol 27: Skinner HG, Michaud DS, Giovannucci E, Willett WC, Colditz GA, et al. (2006) Vitamin D intake and the risk for pancreatic cancer in two cohort studies. Cancer Epidemiol Biomarkers Prev 15: Zhou W, Suk R, Liu G, Park S, Neuberg DS, et al. (2005) Vitamin D is associated with improved survival in early-stage non small cell lung cancer patients. Cancer Epidemiol Biomarkers Prev 14: Vitamin D may be of importance in skin cancer development. Although the data from various types of cancer suggest a benefit from high vitamin D levels, they could be a marker of high sun exposure and an increased risk of skin cancer. There is in vitro evidence that vitamin D treatment decreases cell growth and metastasis [15,16], but most of the cases studied were melanoma. Evidence in vitro for the role of vitamin D in non-melanoma skin cancer is still limited. Mice with inactivated vitamin D receptor had more non-melanoma skin cancer [34]. Vitamin D3 inhibited the proliferation of basal cell carcinomas by inhibiting the hedgehog signaling pathway [16]. The evidence in humans of a positive relationship between vitamin D and non-melanoma skin cancer suggests that UV exposure may have a predominant adverse influence that exceeds any putative benefit from the higher levels of vitamin D. The strengths of the current study include its prospective design, large well-characterized study population, long follow-up duration, and data on potential confounders. The limitation is that blood samples were not assayed at the same time and in the same laboratory, although we have controlled for batch variation in the multivariate models. In conclusion, this prospective study found a positive association between plasma 25(OH)D levels and risk of non-melanoma skin cancer. Additionally, for BCC, this association was more apparent among women with blood collection outside the summer season, women from areas with less UVB flux, and light-pigmented women. Considering that most circulating vitamin D is due to sun exposure, the positive association between plasma vitamin D and non-melanoma skin cancer is confounded by sun exposure. Our results suggest that one-time measurement of plasma vitamin D may reasonably reflect long-term sun exposure and predict the risk of non-melanoma skin cancer. Acknowledgments We thank the participants in the NHS and NHS II Studies for their dedication and commitment. We also thank the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. Author Contributions Conceived and designed the experiments: JH AAQ HN. Analyzed the data: GL JH. Wrote the paper: GL JH. 9. Tang JY, Parimi N, Wu A, Boscardin WJ, Shikany JM, et al. (2010) Inverse association between serum 25(OH) vitamin D levels and non-melanoma skin cancer in elderly men. Cancer Causes Control 21: Eide MJ, Johnson DA, Jacobsen GR, Krajenta RJ, Rao DS, et al. (2011) Vitamin D and Nonmelanoma Skin Cancer in a Health Maintenance Organization Cohort. Arch Dermatol 147: Asgari MM, Tang J, Warton ME, Chren MM, Quesenberry CP Jr., et al. (2010) Association of prediagnostic serum vitamin D levels with the development of basal cell carcinoma. J Invest Dermatol 130: Garcia VC, Martini LA (2010) Vitamin d and cardiovascular disease. Nutrients 2: Holick MF (2010) Vitamin D: extraskeletal health. Endocrinol Metab Clin North Am 39: Hollis BW (1996) Assessment of vitamin D nutritional and hormonal status: what to measure and how to do it. Calcif Tissue Int 58: Seifert M, Rech M, Meineke V, Tilgen W, Reichrath J (2004) Differential biological effects of 1,25-dihydroxyVitamin D3 on melanoma cell lines in vitro. J Steroid Biochem Mol Biol 89 90: Tang JY, Xiao T, Wu A, Chang KS, Shpall E, et al. (2011) Vitamin D3 inhibits hedgehog signaling and proliferation in murine basal cell carcinomas. Cancer Prev Res (Phila) 4: PLoS ONE 6 April 2012 Volume 7 Issue 4 e35211

48 Plasma 25-Hydroxyvitamin D and Skin Cancer 17. Tang JY, Fu T, Leblanc E, Manson JE, Feldman D, et al. (2011) Calcium plus vitamin D supplementation and the risk of nonmelanoma and melanoma skin cancer: post hoc analyses of the women s health initiative randomized controlled trial. J Clin Oncol 29: Feskanich D, Ma J, Fuchs CS, Kirkner GJ, Hankinson SE, et al. (2004) Plasma vitamin D metabolites and risk of colorectal cancer in women. Cancer Epidemiol Biomarkers Prev 13: Tworoger SS, Lee IM, Buring JE, Rosner B, Hollis BW, et al. (2007) Plasma 25- hydroxyvitamin D and 1,25-dihydroxyvitamin D and risk of incident ovarian cancer. Cancer Epidemiol Biomarkers Prev16: Forman JP, Giovannucci E, Holmes MD, Bischoff-Ferrari HA, Tworoger SS, et al. (2007) Plasma 25-hydroxyvitamin D levels and risk of incident hypertension. Hypertension 49: Green AK, Hankinson SE, Bertone-Johnson ER, Tamimi RM (2010) Mammographic density, plasma vitamin D levels and risk of breast cancer in postmenopausal women. Int J Cancer 127: Eliassen AH, Spiegelman D, Hollis BW, Horst RL, Willett WC, et al. (2011) Plasma 25-hydroxyvitamin D and risk of breast cancer in the Nurses Health Study II. Breast Cancer Res 13: R Forman JP, Curhan GC, Taylor EN (2008) 25-hydroxyvitamin D levels and risk of incident hypertension among young women. Hypertension 52: Colditz GA, Martin P, Stampfer MJ, Willett WC, Sampson L, et al. (1986) Validation of questionnaire information on risk factors and disease outcomes in a prospective cohort study of women. Am J Epidemiol 123: Hunter DJ, Colditz GA, Stampfer MJ, Rosner B, Willett WC, et al. (1990) Risk factors for basal cell carcinoma in a prospective cohort of women. Annals of epidemiology 1: Hollis BW (1997) Quantitation of 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D by radioimmunoassay using radioiodinated tracers. Methods Enzymol 282: Wagner D, Hanwell HE, Vieth R (2009) An evaluation of automated methods for measurement of serum 25-hydroxyvitamin D. Clin Biochem 42: Wang Y, Jacobs EJ, McCullough ML, Rodriguez C, Thun MJ, et al. (2009) Comparing methods for accounting for seasonal variability in a biomarker when only a single sample is available: insights from simulations based on serum 25- hydroxyvitamind. Am J Epidemiol 170: Miettinen OS (1976) Stratification by a multivariate confounder score. American journal of epidemiology 104: Baraké R, Weiler H, Payette H, Gray-Donald K (2010) Vitamin D status in healthy free-living elderly men and women living in Quebec, Canada. J Am Coll Nutr 29: Kotsopoulos J, Tworoger SS, Campos H, Chung FL, Clevenger CV, et al. (2010) Reproducibility of plasma and urine biomarkers among premenopausal and postmenopausal women from the Nurses Health Studies. Cancer Epidemiol Biomarkers Prev 19: Karohl C, Su S, Kumari M, Tangpricha V, Veledar E, et al. (2010) Heritability and seasonal variability of vitamin D concentrations in male twins. Am J Clin Nutr 92: Weinstein SJ, Yu K, Horst RL, Parisi D, Virtamo J, et al. (2011) Serum 25- hydroxyvitamin D and risk of lung cancer in male smokers: a nested case-control study. PLoS One 6: e Zinser GM, Sundberg JP, Welsh J (2002) Vitamin D(3) receptor ablation sensitizes skin to chemically induced tumorigenesis. Carcinogenesis 23: PLoS ONE 7 April 2012 Volume 7 Issue 4 e35211

49 Published OnlineFirst February 25, 2011; DOI: / EPI No Association between Telomere Length in Peripheral Blood Leukocytes and the Risk of Nonmelanoma Skin Cancer Geyu Liang, Abrar A. Qureshi, Qun Guo, et al. Cancer Epidemiol Biomarkers Prev 2011;20: Published OnlineFirst February 25, Updated Version Access the most recent version of this article at: doi: / epi Cited Articles This article cites 8 articles, 4 of which you can access for free at: alerts Sign up to receive free -alerts related to this article or journal. Reprints and Subscriptions Permissions To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at pubs@aacr.org. To request permission to re-use all or part of this article, contact the AACR Publications Department at permissions@aacr.org. Downloaded from cebp.aacrjournals.org on September 16, 2011 Copyright 2011 American Association for Cancer Research

50 Published OnlineFirst February 25, 2011; DOI: / EPI Cancer Epidemiology, Biomarkers Null Results in Brief & Prevention No Association between Telomere Length in Peripheral Blood Leukocytes and the Risk of Nonmelanoma Skin Cancer Geyu Liang 1,5, Abrar A. Qureshi 2,3, Qun Guo 2, Immaculata De Vivo 2,4, and Jiali Han 2,3,4 Abstract Background: Recent reports have shown that telomere length was associated with the risk of various cancers, but the results have been inconsistent. Methods: We prospectively evaluated the association of telomere length in peripheral blood leukocytes with the risk of skin squamous cell carcinoma (SCC) in 241 cases and 241 controls within the Health Professionals Follow-up Study (HPFS), and the risk of skin basal cell carcinoma (BCC) in 623 cases and 1,943 controls within the Nurses Health Study (NHS). Results: No significant association was observed between telomere length and risk of SCC (longest quartile vs. shortest quartile, OR ¼ 1.09, 95%CI: , P ¼ 0.81). Null findings were also observed between telomere length and risk of BCC in 2 independent sets (OR ¼ 0.96, 95%CI: , P ¼ 0.83; and OR ¼ 0.91, 95%CI: , P ¼ 0.39). Conclusion: We found no evidence that telomere length in peripheral blood leukocytes was associated with risk of nonmelanoma skin cancer. Impact: Our prospective study suggests that telomere length in peripheral blood leukocytes is less likely to play a substantial role in nonmelanoma skin cancer development. Cancer Epidemiol Biomarkers Prev; 20(5); Ó2011 AACR. Introduction Telomeres are long hexameric (TTAGGG)n repetitive structures capping the ends of eukaryotic chromosomes that protect against fusion and degradation of chromosomal ends and help maintain structural integrity. Recent reports have suggested that telomere length plays an important role in cancer development (1 3). In our previous study, we found that the telomere length in peripheral blood leukocytes may be associated with risk of skin cancer (4), the most common malignancy in the United States. To confirm and extend our observations, we prospectively evaluated the association between the telomere length and risk of skin squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) within the Nurses Health Study (NHS) and Health Professionals Follow-up Study (HPFS). Authors Affiliation: 1 Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts; 2 Channing Laboratory, Department of Medicine; 3 Department of Dermatology, Brigham and Women's Hospital, Harvard Medical School; 4 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts; 5 Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of Public Heath, Southeast University, Nanjing, China Corresponding Author: Jiali Han, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston 2115, MA. Phone: ; Fax: ; jiali.han@channing.harvard.edu doi: / EPI Ó2011 American Association for Cancer Research. Materials and Methods Study population HPFS nested case control study of SCC. We conducted a nested case control study within the HPFS, which was initiated in 1986 among 51,529 U.S. male professionals, aged 40 to 75 years at study entry. Between 1993 and 1994, 18,159 study participants provided blood samples. Eligible cases consisted of men with pathologically confirmed incident SCC from the subcohort who gave a blood sample, with a diagnosis after blood collection up to Participants who had cancer previously were excluded. For each case, 1 control was matched by age (1 year) and was free of cancer up to and including the questionnaire cycle in which the case was diagnosed. In total, there are 241 Caucasian SCC cases and 241 matched Caucasian controls. NHS nested case control study of BCC 1 The NHS was established in 1976 among 121,700 female registered nurses between the ages of 30 and 55. Between 1989 and 1990, blood samples were collected from 32,826 of the cohort members. We have accrued 2,857 incident cases of BCC from the subcohort who had given a blood specimen, with a diagnosis between 1998 and We randomly selected a subset of BCC cases. Participants who had previously diagnosed cancer were excluded. One control was matched to each case by age (1 year) and was free of cancer up to and including the Downloaded from cebp.aacrjournals.org on September 16, 2011 Copyright 2011 American Association for Cancer Research

51 Published OnlineFirst February 25, 2011; DOI: / EPI Liang et al. Table 1. Characteristics of cases and controls SCC study BCC study 1 BCC study 2 Characteristic Cases Controls Cases Controls Cases Controls (n ¼ 241) (n ¼ 241) (n ¼ 260) (n ¼ 260) (n ¼ 363) (n ¼ 1,683) Age at diagnosis, mean (SD) 69.0 (8.4) 66.1 (8.0) 69.3 (7.0) Age at blood draw, mean (SD) 63.1 (8.2) 63.1 (8.2) 56.3 (6.4) 56.4 (6.4) 61.0 (5.8) 59.5 (6.6) Red or blonde hair color (%) Tanning ability, tan without burn (%) Gender Men Men Women Women Women Women questionnaire cycle in which the case was diagnosed. The nested case control study consisted of 260 Caucasian BCC cases and 260 matched Caucasian controls. NHS nested case control study of BCC 2 In addition, we had telomere length measurements in several nested case control studies within the NHS, including stroke, myocardial infarction, and endometrial cancer. We used all the controls from these studies. All cases were women diagnosed with BCC after blood collection and up to 2008 without personal history of other cancer. Controls were restricted to participants without a personal history of any cancer. We identified 363 Caucasian cases and 1,683 Caucasian controls. Information regarding skin cancer risk factors was obtained from the prospective biennial questionnaires. The study was approved by the Brigham and Women s Hospital Institutional Review Board for Human Subjects Research. Telomere length detection Genomic DNA was extracted from peripheral leukocytes using the QIAmp 96-spin blood protocol. The relative average telomere length was determined by a highthroughput 384-well real-time PCR assay with an Applied Biosystems 7900HT PCR System. The T/S ratio ( dc t ) for each sample was calculated by subtracting the average 36B4 C t value from the average telomere C t value. The relative T/S ratio ( ddc t ) was determined by subtracting the T/S ratio value of the 5 ng standard curve point from the T/S ratio of each unknown sample. The blind quality control samples were interspersed throughout the sets for assessing inter- and intraplate variability. The coefficients of variation (CV) of the telomere C t and 36B4 C t were 2.97% and 1.76%, respectively. Statistical analysis In the HPFS nested case control study of SCC and the first NHS nested case control study of BCC, relative telomere length was categorized into quartiles according to the distribution in each study-specific control population. OR and 95%CI were calculated to examine the relationship between relative telomere length and skin cancer by conditional logistic regression. In the second NHS nested case control study of BCC, we calculated a z score in each set and pooled the z scores for further analysis. The z scores were categorized into quartiles according to the distribution among BCC controls. Unconditional logistic regression was employed to calculate OR and 95%CI. All statistical tests were 2sided. Results The characteristics of cases and controls in the SCC and BCC case control study are presented in Table 1. Cases were more likely to have light pigmentary phenotypes, including lighter hair color and less tendency to tan. The association between relative telomere length and each type of skin cancer was examined separately (Table 2). No significant association was observed between telomere length and risk of SCC (P ¼ 0.81). Similar null findings were observed between telomere length and risk of BCC in both studies (P ¼ 0.83 and 0.39). Discussion Recent studies have shown that telomere length is a potential biomarker of risk of various cancers, including bladder, breast, lung, stomach, head, and neck cancers (1 3, 5, 6). However, other epidemiologic investigations suggest that the associations between telomere length and cancer risk are inconclusive (7, 8). The heterogeneity across different tumors could likely be explained by the different telomere dynamics in different types of tissue. Telomere shortening and malignant transformation in different types of cells varies in response to environmental DNA damage exposure. We previously observed that shorter telomere length was associated with a decreased risk of skin melanoma (4), and this finding was replicated in additional studies (manuscript in submission). Our previous data revealed no association between telomere length and skin SCC risk (P ¼ 0.30; ref 4). Consistently, we found no associations between the telomere length and risk of SCC in the present study. We previously observed that shorter telomere length was nonsignificantly associated with an increased risk of BCC (P ¼ 0.09; ref 4). In the present 1044 Cancer Epidemiol Biomarkers Prev; 20(5) May 2011 Downloaded from cebp.aacrjournals.org on September 16, 2011 Copyright 2011 American Association for Cancer Research Cancer Epidemiology, Biomarkers & Prevention

52 Published OnlineFirst February 25, 2011; DOI: / EPI Telomere Length and the Risk of Nonmelanoma Skin Cancer Table 2. Association between telomere length and nonmelanoma skin cancer risk 4th Quartile 3rd Quartile 2nd Quartile 1st Quartile P SCC (HPFS) a Case, n (%) 63 (26) 55 (23) 57 (24) 66 (27) Control, n (%) 60 (25) 59 (25) 63 (26) 59 (24) OR (95%CI) ( ) 0.88 ( ) 1.09 ( ) 0.81 BCC (NHS 1) a Case, n (%) 66 (25) 67 (26) 62 (24) 65 (25) Control, n (%) 66 (25) 64 (25) 64 (25) 66 (25) OR (95%CI) ( ) 0.96 ( ) 0.96 ( ) 0.83 BCC (NHS 2) b Case, n (%) 96 (26) 94 (26) 82 (23) 91 (25) Control, n (%) 421 (25) 420 (25) 426 (25) 416 (25) OR (95%CI) ( ) 0.82 ( ) 0.91 ( ) 0.39 a Conditional logistic regression. b Unconditional logistic regression adjusted for age. study of 2 prospective data sets, our results suggest that telomere length is not associated with BCC risk. The combined evidence indicates that the role of telomere length in BCC development is minimal. In conclusion, the present prospective study found no association between relative telomere length in peripheral blood leukocytes and risk of nonmelanoma skin cancer. It suggests that telomere length may not be a useful biomarker for nonmelanoma skin cancer risk assessment. Disclosure of Potential Conflicts of Interest No potential conflicts of interest were disclosed. Acknowledgments The authors thank Patrice Soule for preparing the DNA samples and Robert Farquhar for performing the telomere assays. They also thank the participants in the Nurses Health Study and the Health Professionals Follow-Up Study for their dedication and commitment; the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY Grant Support This work is supported by NIH grants CA133914, CA87969, CA055075, and CA Received January 21, 2011; accepted February 11, 2011; published OnlineFirst February 25, References 1. Broberg K, Bj ork J, Paulsson K, H oglund M, Albin M. Constitutional short telomeres are strong genetic susceptibility markers for bladder cancer. Carcinogenesis 2005;26: Jang JS, Choi YY, Lee WK, Choi JE, Cha SI, Kim YJ, et al. Telomere length and the risk of lung cancer. Cancer Sci 2008;99: Wu X, Amos CI, Zhu Y, Zhao H, Grossman BH, Shay JW, et al. Telomere dysfunction: a potential cancer predisposition factor. J Natl Cancer Inst 2003;95: Han J, Qureshi AA, Prescott J, Guo Q, Ye L, Hunter DJ, et al. A prospective study of telomere length and the risk of skin cancer. J Invest Dermatol 2009;129: Hou L, Savage SA, Blaser MJ, Perez-Perez G, Hoxha M, Dioni L, et al. Telomere length in peripheral leukocyte DNA and gastric cancer risk. Cancer Epidemiol Biomarkers Prev 2009;18: Shen J, Gammon MD, Terry MB, Wang Q, Bradshaw P, Teitelbaum SL, et al. Telomere length, oxidative damage, antioxidants and breast cancer risk. Int J Cancer 2009;124: Zee RY, Castonguay AJ, Barton NS, Buring JE. Mean telomere length and risk of incident colorectal carcinoma: a prospective, nested casecontrol approach. Cancer Epidemiol Biomarkers Prev 2009;18: Prescott J, McGrath M, Lee IM, Buring JE, De Vivo. Telomere length and genetic analyses in population-based studies of endometrial cancer risk. Cancer 2010;116: Cancer Epidemiol Biomarkers Prev; 20(5) May Downloaded from cebp.aacrjournals.org on September 16, 2011 Copyright 2011 American Association for Cancer Research

53 Associations between Rotating Night Shifts, Sleep Duration, and Telomere Length in Women Geyu Liang 1,2, Eva Schernhammer 3,4,5,LuQi 3,6, Xiang Gao 3,6, Immaculata De Vivo 3,4, Jiali Han 3,4,7 * 1 Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America, 2 Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China, 3 Channing Laboratory, Department of Medicine, Brigham and Women s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America, 4 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, 5 Ludwig Boltzmann Institute for Applied Cancer Research (LBI-ACR) and Applied Cancer Research- Institute for Translational Research (ACR-ITR) VIEnna/CEADDP, Vienna, Austria, 6 Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America, 7 Department of Dermatology, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America Abstract Background: Telomere length has been proposed as a marker of aging. However, our knowledge of lifestyle risk factors determining telomere length is limited. Methods: We evaluated the associations between years of rotating night shifts, self-reported sleep duration, and telomere length in 4,117 female participants from the Nurses Health Study. Telomere length in peripheral blood leukocytes was determined by Real-Time PCR assay. Information on rotating night shifts and sleep duration was collected via questionnaires prior to blood collection. We used multivariable linear regression to investigate the associations between rotating night shifts, sleep duration, and telomere length. Results: Compared with women in the category (9 hours), those in the lowest category of sleep duration (#6 hours) had a 0.12 unit decrease in z score after adjustment for age, BMI and cigarette smoking (equivalent to 9-year telomere attrition, P for trend = 0.05). Significant positive association between sleep duration and telomere length was seen among women under age of 50 (P for trend = 0.004), but not among those over 50 (P for trend = 0.33) (P for interaction = 0.005). In addition, we observed that women with a longer history of rotating night shifts tended to have shorter telomere length, but this relation was not statistically significant (P for trend = 0.36). Conclusion: We found that sleep duration was positively associated with telomere length among women under 50 years old. Further research is needed to confirm the observed associations. Citation: Liang G, Schernhammer E, Qi L, Gao X, De Vivo I, et al. (2011) Associations between Rotating Night Shifts, Sleep Duration, and Telomere Length in Women. PLoS ONE 6(8): e doi: /journal.pone Editor: Jose Vina, University of Valencia, Spain Received May 12, 2011; Accepted July 18, 2011; Published August 10, 2011 Copyright: ß 2011 Liang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This study was supported by National Institutes of Health grants CA133914, CA87969, and CA The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * jiali.han@channing.harvard.edu Introduction Telomere length has been reported to have important influence on various chronic diseases and aging [1], and previous data have suggested it as a potential biomarker of risk of cardiovascular disease and several cancers [2-5]. However, little is known about lifestyle factors that determine telomere length. A recent study showed that the current and long-term full-time work was associated with shorter telomere length in women of the Sister Study [6]. Another report found that telomere length was shorter in patients with sleep apnea syndrome than in controls [7]. This suggests that work schedule and sleep situation may have an effect on telomere length. Rotating night shifts work and sleep deficits disrupt circadian rhythms and have important effects on health. Increasing evidence suggests that rotating night shifts and short sleep duration are potential risk factors for various metabolic disorders, cardiovascular disease, and cancers [8 12]. It is interesting that a history of extended periods of rotating night shifts work and short telomere length in peripheral blood leukocytes (PBL) were both associated with a decreased risk of melanoma in our previous studies [13,14] and with lower risk of Parkinson s disease by us and other researchers [15,16]. Short sleep duration was also associated with a lower risk of Parkinson s disease [15]. To our knowledge, there are no epidemiologic data on the potential associations between rotating night shifts, sleep duration, and telomere length in a large general population. Here we evaluated these associations in a large ongoing US cohort of women: the Nurses Health Study (NHS). Methods Ethics Statement This study was approved by the Human Research Committee at the Brigham and Women s Hospital (Boston, MA) with written informed consent from all participants. PLoS ONE 1 August 2011 Volume 6 Issue 8 e23462

54 Night Shifts, Sleep Duration, and Telomere Length Study population The NHS was established in 1976 among 121,700 female registered nurses between the ages of 30 and 55. Participants completed biennially mailed questionnaires to update information on exposure status and newly diagnosed diseases. Between 1989 and 1990, blood samples were collected from 32,826 cohort members and were stored with liquid nitrogen. Between 2008 and 2010, several nested case-control studies were conducted within the NHS blood cohort to investigate the association between telomere length and stroke [17], myocardial infarction [18], breast cancer [19], skin cancer [14], and endometrial cancer [20]. We used all the controls from these nested case-control studies that had previously been analyzed for telomere length. The samples were limited to Caucasian women. A total of 4,117 women formed the baseline population for this study. Assessment of sleep duration, rotating night shifts and covariates Sleep duration was asked in the 1986 questionnaire, corresponding to the total hours of actual sleep in a 24-hour period. Seven options were provided (hours): 5 or less, 6, 7, 8, 9, 10, 11 or more. Information on rotating night shifts was collected from the 1988 questionnaire. Participants were asked for their total number of years of rotating night shifts, which was characterized as at least three nights per month in addition to working days or evenings in that month. Eight categories were provided (in years): never, 1 2, 3 5, 6 9, 10 14, 15 19, 20 29, 30 or more. Information on age, cigarette smoking (pack years) and body mass index (BMI) at blood draw was also collected. Telomere length measurement Genomic DNA was extracted from peripheral leukocytes using the QIAmp 96-spin blood protocol. The relative average telomere length was determined by a high-throughput 384-well Real-Time PCR assay using the Applied Biosystems 7900HT PCR System. The T/S ratio (-dct) for each sample was calculated by subtracting the average 36B4 Ct value from the average telomere Ct value. The relative T/S ratio (-ddct) was determined by subtracting the T/S ratio value of the 5 ng standard curve point from the T/S ratio of each unknown sample. Blinded qualitycontrol samples were interspersed throughout the sets to assess inter-plate and intra-plate variability. The coefficients of variation (CV) of the telomere Ct and 36B4 Ct were lower than 5% in all nested case-control studies. Statistical analysis We calculated a z score of telomere length among controls of each nested case-control study and pooled the z scores for further analysis. The z scores were categorized into quintiles. Multivariable linear regression models were used to examine the relationships between rotating night shifts or sleep duration and telomere length. Age, BMI, and cigarette smoking (pack years) were adjusted in the models. P trends across categories were calculated in the regression models. Because prolonged sleep (10+ hours) may reflect some adverse healthy conditions, we kept it as a single group and did not include it in the trend test. To test potential interaction between these sleep variables and age on telomere length, we modeled age as a dichotomous variable (50 years old as a cutoff point) and rotating night shifts or sleep duration as a continuous variable. The age of 50 years was used as a cutoff to separate pre and post-menopausal women [21]. We then tested a single multiplicative interaction term by the likelihood ratio test, comparing the model with the single interaction term with the model containing just the main effects of rotating night shifts or sleep duration and age variables, along with the same covariates. Statistical analyses were conducted using SAS software (version 9, SAS Institute, Cary, NC). All statistical tests were two-sided. Results The characteristics of women by quintiles of telomere length are presented in Table 1. A significantly inverse relationship was found between the telomere length and age (P,0.0001), which is consistent with published data [2]. Women with shorter telomere length had a slightly higher BMI; this was significant after adjusting for age (P = 0.03). Women with shorter telomere length were more likely to smoke, but this was not statistically significant (P = 0.07). There was no significant association between menopausal status and telomere length. The relationships between telomere length, nightshift work, and sleep duration are presented in Table 2. After multivariate adjustment for age, body mass index, and cigarette smoking, women with 9 hours of sleep had Z score of 0.07, whereas those with less than 6 hours of sleep had telomere length Z score of (equivalent to 9-year telomere attrition, P for trend = 0.05). Women in the top category ($10 h) had shorter telomere length (Z score, -0.10). We observed a significant interaction between sleep duration and age on telomere length (P for interaction = 0.005) (Table 3). In the stratified analyses by age, the significant association between sleep duration and telomere length was found only among women under 50 years old (P for trend = 0.004). The top category of sleep duration (9 h) was associated with a 0.75 unit increase in z score compared with the lowest category of sleep duration (#6 h). In contrast, no significant association was found between sleep duration and telomere length among women more than 50 years old (P for trend = 0.33). In addition, we found that women with the longest history of rotating night shifts work (more than 20 years) tended to have short telomere lengths compared with those with the shortest history of rotating night shifts work. This trend, while overall not statistically significant (P for trend = 0.36), appeared to be more pronounced when restricting to women less than 50 years old, but the test for interaction between rotating night shifts and age was also not statistically significant (P for interaction = 0.29). Overall, there was no association between night shifts and telomere length in this study. We examined the interactions between sleep duration and night shifts and BMI and smoking on telomere lengths, and none of the interactions were statistically significant. Discussion Telomere length has been identified as a potential biomarker of aging [1]. Our previous study examined the effect of associations between diet, body composition, and lifestyle factors on telomere length in the NHS [22]. In the present study, we examine the associations of both rotating night shifts and sleep duration with telomere length. Our results suggest that sleep duration is positively associated with telomere length, except for those with more than 10-hour sleep. Individuals with long sleep duration (10+ hours) had shortened telomere length due to two possible reasons. Long sleep duration is likely to be an indicator of poor physical condition. Previous research showed that long sleep ($9 hours) was associated with decreased physical performance in older women compared with mid-range sleepers (7 8 hours) [23]. On the other hand, people who sleep more than 10 hours can be very athletic. Our study showed that people with high level of moderate PLoS ONE 2 August 2011 Volume 6 Issue 8 e23462

55 Night Shifts, Sleep Duration, and Telomere Length Table 1. Characteristics of women by quintiles of telomere length. Quintile of telemere length (z score) Age at blood draw (years) a BMI at blood draw (kg/m 2 ) b Current smoking at blood draw (%) c Menopausal statue (%) d Premenopausal Postmenopausal Rotating night shifts (years) Sleep duration, #6 hours (%) a P, b P = 0.03 after adjusting for age. c P = 0.07 after adjusting for age. d P = 0.81 after adjusting for age. doi: /journal.pone t001 or vigorous physical activity had shorter telomere length than those with modest level (unpublished data). Short sleep duration has been associated with a decreased risk of Parkinson s and increased risks of various cancers [12,15,24]. Three cohort studies have suggested that breast cancer risk decreased with increasing sleep duration. [12,25,26], but in our own cohort we did not observe an association between sleep duration and breast cancer risk [27]. Another study also reported an association between short sleep duration and an increased risk of colorectal adenomas [20]. Individuals sleeping fewer than 6 hours per night had an almost 50% increased risk of colorectal adenomas (OR = 1.47, P for trend = 0.02) compared with individuals sleeping at least 7 hours per night [20]. Similarly, with the exception of Parkinson s disease and melanoma, short telomere length in PBL has been suggested to be associated with an increased risk of breast, bladder, lung, and stomach cancers [4,5,28,29]. Therefore, we hypothesized that there may be a positive association between sleep duration and telomere length. The current study supports the hypothesis that sleep duration is positively associated with telomere length, but the mechanisms underlying the association are still unknown. Melatonin, a hormone closely related to sleep, has been demonstrated to defend against oxidative stress, promote DNA repair and inhibit tumor development [30 32]. Some studies have shown that short telomere length is associated with high oxidative stress [33]. Recently, a link between short sleep duration and low levels of melatonin has been suggested [26,34]. In a cohort study of sleep duration and breast cancer, the levels of melatonin in urine exhibited a dose-dependent positive association with the number of hours of sleep [26]. Another study also showed that serum melatonin levels were lower in individuals with,6 hours of sleep than those with.9 hours [34]. Therefore, sleep duration probably influences telomere length via a melatonin-mediated pathway. The finding that patients with obstructive sleep apnea Table 2. The relationship between telomere length (z score), rotating night shifts, and sleep duration. n Mean±SE a (z score) P for trend a Mean±SE b (z score) P for trend b Rotating night shifts(years) Never $ Sleep duration (hours) # c c $ a Adjusted for age (continuous variable). b Adjusted for age (continuous variable), BMI (continuous variable), and cigarette smoking (pack years). c P for trend from sleep duration #6 hours to 9 hours. doi: /journal.pone t002 PLoS ONE 3 August 2011 Volume 6 Issue 8 e23462

56 Night Shifts, Sleep Duration, and Telomere Length Table 3. The relationship between telomere length (z score), rotating night shifts, and sleep duration stratified by age at blood draw. Age,50 a Age$50 a n Mean±SE (z score) P for trend n Mean±SE (z score) P for trend Nightshift (years) Never $ P for interaction, 0.29 Sleep duration (hours) # b c P for interaction, a Adjusted for age (continuous variable), BMI (continuous variable) and cigarette smoking (pack years). b The difference between #6 h and 8 h was statistically significant (P = 0.04). c The difference between #6 h and 9 h was statistically significant (P = 0.007). syndrome had both an abnormal melatonin secretion pattern [35] and short telomere length [7] was compatible with this hypothesis. More studies are needed to elucidate the possible mechanism. We observed that long sleep duration was significantly associated with long telomere length among women younger than 50 years old but not among those over 50 years old. Because telomere is shortened over age, it is possible that telomere attrition is more pronounced and more sensitive to environmental stress in early age and the attrition becomes slower over time. In addition, the effect of sleep duration on telomere length may be mediated through a melatonin-related pathway. High melatonin levels are a recognized protective factor against oxidative stress [30] and long sleep duration has been linked to high melatonin levels [26]. A significant trend of decreasing melatonin levels with increasing age was observed previously [36]. The variation of amplitude (nightday ratio of melatonin) was bigger in younger individuals than in older ones [36]. Our previous study also observed that younger women appeared to have higher urinary melatonin levels than older women, particularly in premenopausal women (#39 yr versus $49 yr) [37]. Therefore, it would be predicted that the association between sleep duration and telomere length is more apparent among younger women. Longer years of rotating night shifts work have also been associated with increased risk of various cancers, such as breast, colon, prostate, and endometrium [10,38 40]. However, in our previous study, we also suggested that both long duration of rotating night shifts work and short telomere length are associated with a decreased risk of melanoma [13,14] and Parkinson s disease [15,16]. We found that women with a longer history of rotating night shifts work tended to have shorter telomere length, but the association was not statistically significant. Consistent with our findings, a cross-sectional analysis of the Sister Study showed no association between work at night (P = 0.83), rotating nightshift work (P = 0.44) and telomere length [6]. In conclusion, in this large prospective cohort study, we found that sleep duration was positively associated with telomere length, especially in women under 50 years old. Women with longer duration of rotating night shifts tended to have short telomere length, but it was not statistically significant. To our knowledge, this is the first study to report associations between rotating night shifts, sleep duration, and telomere length in a cohort study. Further research is needed to confirm these possible associations. Acknowledgments We thank Patrice Soule for preparing the DNA samples and Robert Farquhar for performing the telomere assays. We thank Qun Guo for programming support. We thank the participants in the Nurses Health Study for their dedication and commitment. Author Contributions Conceived and designed the experiments: JH ES XG. Analyzed the data: GL LQ JH. Wrote the paper: GL JH. Reviewed the manuscript: JH ES LQ XG IV. References 1. Aubert G, Lansdorp PM (2008) Telomeres and aging. Physiol Rev 88: Fitzpatrick AL, Kronmal RA, Gardner JP, Psaty BM, Jenny NS, et al. (2007) Leukocyte telomere length and cardiovascular disease in the cardiovascular health study. Am J Epidemiol 165: Wu X, Amos CI, Zhu Y, Zhao H, Grossman BH, et al. (2003) Telomere dysfunction: a potential cancer predisposition factor. J Natl Cancer Inst 95: Shen J, Gammon MD, Terry MB, Wang Q, Bradshaw P, et al. (2009) Telomere length, oxidative damage, antioxidants and breast cancer risk. Int J Cancer 124: Broberg K, Björk J, Paulsson K, Höglund M, Albin M (2005) Constitutional short telomeres are strong genetic susceptibility markers for bladder cancer. Carcinogenesis 26: PLoS ONE 4 August 2011 Volume 6 Issue 8 e23462

57 Night Shifts, Sleep Duration, and Telomere Length 6. Parks CG, Deroo LA, Miller DB, McCanlies EC, Cawthon RM, et al. (2011) Employment and work schedule are related to telomere length in women. Occup Environ Med, [Epub ahead of print]. 7. Barceló A,Piérola J, López-Escribano H, de la Peña M, Soriano JB, et al. (2010) Telomere shortening in sleep apnea syndrome. Respir Med 104: Ha M, Park J (2005) Shiftwork and metabolic risk factors of cardiovascular disease. J Occup Health 7: Esquirol Y, Bongard V, Mabile L, Jonnier B, Soulat JM, et al. (2009) Shift work and metabolic syndrome: respective impacts of job strain, physical activity, and dietary rhythms. Chronobiol Int 26: Pronk A, Ji BT, Shu XO, Xue S, Yang G, et al. (2010) Night-shift work and breast cancer risk in a cohort of Chinese women. Am J Epidemiol 171: Knutson KL (2010) Sleep duration and cardiometabolic risk: a review of the epidemiologic evidence. 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58 This article was downloaded by: [Southeast University] On: 25 February 2010 Access details: Access Details: [subscription number ] Publisher Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Journal of Toxicology and Environmental Health, Part A Publication details, including instructions for authors and subscription information: Effects of Subchronic Exposure to Multi-Walled Carbon Nanotubes on Mice Geyu Liang a ; Lihong Yin a ; Juan Zhang a ; Ran Liu a ; Tao Zhang b ; Bing Ye a ; Yuepu Pu a a Key Laboratory of Environmental Medicine and Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China b Department of Material Science and Engineering, National Key Laboratory of Solid State Microstructures, Nanjing University, Nanjing, People's Republic of China Online publication date: 24 February 2010 To cite this Article Liang, Geyu, Yin, Lihong, Zhang, Juan, Liu, Ran, Zhang, Tao, Ye, Bing and Pu, Yuepu(2010) 'Effects of Subchronic Exposure to Multi-Walled Carbon Nanotubes on Mice', Journal of Toxicology and Environmental Health, Part A, 73: 7, To link to this Article: DOI: / URL: PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.