Jeremian Richie, Lytvyn Yuliya, Fotovati Rayyan, Li Kaiyang, Sachdeva Muskaan, Tarafdar Nawar, Georgakopoulos Jorge R, Piguet Vincent, Litvinov Ivan V, Yeung Jensen
Faculty of Medicine and Health Sciences, McGill University, 1001 Decarie Boulevard, Montréal, QC, H4A 3J1, Canada.
Research Institute of the McGill University Health Centre (RI-MUHC), Montréal, Canada.
Arch Dermatol Res. 2024 May 22;316(5):195. doi: 10.1007/s00403-024-02923-3.
Chronic arsenic exposure is a global health hazard significantly associated with the development of deleterious cutaneous changes and increased keratinocyte cancer risk. Although arsenic exposure is associated with broad-scale cellular and molecular changes, gaps exist in understanding how these changes impact the skin and facilitate malignant transformation. Recently developed epigenetic "clocks" can accurately predict chronological, biological and mitotic age, as well as telomere length, on the basis of tissue DNA methylation state. Deviations of predicted from expected age (epigenetic age dysregulation) have been associated with numerous complex diseases, increased all-cause mortality and higher cancer risk. We investigated the ability of these algorithms to detect molecular changes associated with chronic arsenic exposure in the context of associated skin lesions. To accomplish this, we utilized a multi-algorithmic approach incorporating seven "clocks" (Horvath, Skin&Blood, PhenoAge, PCPhenoAge, GrimAge, DNAmTL and epiTOC2) to analyze peripheral blood of pediatric and adult cohorts of arsenic-exposed (n = 84) and arsenic-naïve (n = 33) individuals, among whom n = 18 were affected by skin lesions. Arsenic-exposed adults with skin lesions exhibited accelerated epigenetic (Skin&Blood: + 7.0 years [95% CI 3.7; 10.2], q = 6.8 × 10), biological (PhenoAge: + 5.8 years [95% CI 0.7; 11.0], q = 7.4 × 10, p = 2.8 × 10) and mitotic age (epiTOC2: + 19.7 annual cell divisions [95% CI 1.8; 37.7], q = 7.4 × 10, p = 3.2 × 10) compared to healthy arsenic-naïve individuals; and accelerated epigenetic age (Skin&Blood: + 2.8 years [95% CI 0.2; 5.3], q = 2.4 × 10, p = 3.4 × 10) compared to lesion-free arsenic-exposed individuals. Moreover, lesion-free exposed adults exhibited accelerated Skin&Blood age (+ 4.2 [95% CI 1.3; 7.1], q = 3.8 × 10) compared to their arsenic-naïve counterparts. Compared to the pediatric group, arsenic-exposed adults exhibited accelerated epigenetic (+ 3.1 to 4.4 years (95% CI 1.2; 6.4], q = 2.4 × 10-3.1 × 10), biological (+ 7.4 to 7.8 years [95% CI 3.0; 12.1] q = 1.6 × 10-2.8 × 10) and mitotic age (+ 50.0 annual cell divisions [95% CI 15.6; 84.5], q = 7.8 × 10), as well as shortened telomere length (- 0.23 kilobases [95% CI - 0.13; - 0.33], q = 2.4 × 10), across all seven algorithms. We demonstrate that lifetime arsenic exposure and presence of arsenic-associated skin lesions are associated with accelerated epigenetic, biological and mitotic age, and shortened telomere length, reflecting altered immune signaling and genomic regulation. Our findings highlight the usefulness of DNA methylation-based algorithms in identifying deleterious molecular changes associated with chronic exposure to the heavy metal, serving as potential prognosticators of arsenic-induced cutaneous malignancy.
长期接触砷是一种全球性的健康危害,与有害的皮肤变化及角质形成细胞癌风险增加显著相关。尽管砷暴露与广泛的细胞和分子变化有关,但在理解这些变化如何影响皮肤并促进恶性转化方面仍存在差距。最近开发的表观遗传“时钟”可以根据组织DNA甲基化状态准确预测实际年龄、生物学年龄和有丝分裂年龄以及端粒长度。预测年龄与预期年龄的偏差(表观遗传年龄失调)与多种复杂疾病、全因死亡率增加和更高的癌症风险相关。我们研究了这些算法在相关皮肤病变背景下检测与长期砷暴露相关分子变化的能力。为实现这一目标,我们采用了一种多算法方法,纳入了七个“时钟”(霍瓦斯、皮肤与血液、表型年龄、PC表型年龄、格里姆年龄、DNAmTL和epiTOC2),以分析砷暴露儿童和成人群体(n = 84)以及未接触砷个体(n = 33)的外周血,其中18人患有皮肤病变。与未接触砷的健康个体相比,有皮肤病变的砷暴露成年人表现出加速的表观遗传年龄(皮肤与血液:+7.0岁[95%置信区间3.7;10.2],q = 6.8×10)、生物学年龄(表型年龄:+5.8岁[95%置信区间0.7;11.0],q = 7.4×10,p = 2.8×10)和有丝分裂年龄(epiTOC2:每年加速19.7次细胞分裂[95%置信区间1.8;37.7],q = 7.4×10,p = 3.2×10);与无病变的砷暴露个体相比,表观遗传年龄也加速(皮肤与血液:+2.8岁[95%置信区间0.2;5.3],q = 2.4×10,p = 3.4×10)。此外,与未接触砷的同龄人相比,无病变的暴露成年人表现出加速的皮肤与血液年龄(+4.2[95%置信区间1.3;7.1],q = 3.8×10)。与儿童组相比,砷暴露成年人在所有七种算法中均表现出加速的表观遗传年龄(+3.1至4.4岁(95%置信区间1.2;6.4],q = 2.4×10 - 3.1×10)、生物学年龄(+7.4至7.8岁[95%置信区间3.0;12.1],q = 1.6×10 - 2.8×10)和有丝分裂年龄(每年加速50.0次细胞分裂[95%置信区间15.6;84.5],q = 7.8×10),以及缩短的端粒长度(-0.23千碱基[95%置信区间-0.13;-0.33],q = 2.4×10)。我们证明,终生砷暴露和砷相关皮肤病变的存在与加速的表观遗传、生物学和有丝分裂年龄以及缩短的端粒长度相关,反映了免疫信号和基因组调控的改变。我们的研究结果突出了基于DNA甲基化的算法在识别与长期接触重金属相关的有害分子变化方面的有用性,可作为砷诱导皮肤恶性肿瘤的潜在预后指标。