Curtin Paul, Curtin Austen, Austin Christine, Gennings Chris, Tammimies Kristiina, Bölte Sven, Arora Manish
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York, United States of America.
Senator Frank R Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Division of Environmental Health, Icahn School of Medicine at Mount Sinai, New York City, New York, United States of America.
PLoS One. 2017 Nov 7;12(11):e0187049. doi: 10.1371/journal.pone.0187049. eCollection 2017.
Environmental exposures to essential and toxic elements may alter health trajectories, depending on the timing, intensity, and mixture of exposures. In epidemiologic studies, these factors are typically analyzed as a function of elemental concentrations in biological matrices measured at one or more points in time. Such an approach, however, fails to account for the temporal cyclicity in the metabolism of environmental chemicals, which if perturbed may lead to adverse health outcomes. Here, we conceptualize and apply a non-linear method-recurrence quantification analysis (RQA)-to quantify cyclical components of prenatal and early postnatal exposure profiles for elements essential to normal development, including Zn, Mn, Mg, and Ca, and elements associated with deleterious health effects or narrow tolerance ranges, including Pb, As, and Cr. We found robust evidence of cyclical patterns in the metabolic profiles of nutrient elements, which we validated against randomized twin-surrogate time-series, and further found that nutrient dynamical properties differ from those of Cr, As, and Pb. Furthermore, we extended this approach to provide a novel method of quantifying dynamic interactions between two environmental exposures. To achieve this, we used cross-recurrence quantification analysis (CRQA), and found that elemental nutrient-nutrient interactions differed from those involving toxicants. These rhythmic regulatory interactions, which we characterize in two geographically distinct cohorts, have not previously been uncovered using traditional regression-based approaches, and may provide a critical unit of analysis for environmental and dietary exposures in epidemiological studies.
接触环境中的必需元素和有毒元素可能会改变健康轨迹，这取决于接触的时间、强度和混合情况。在流行病学研究中，这些因素通常作为在一个或多个时间点测量的生物基质中元素浓度的函数进行分析。然而，这种方法没有考虑环境化学物质代谢中的时间周期性，而这种周期性如果受到干扰可能会导致不良健康后果。在此，我们构思并应用了一种非线性方法——递归量化分析（RQA）——来量化正常发育所必需元素（包括锌、锰、镁和钙）以及与有害健康影响或窄耐受范围相关元素（包括铅、砷和铬）的产前和产后早期接触情况的周期性成分。我们发现了营养元素代谢谱中周期性模式的有力证据，并通过随机双生子替代时间序列进行了验证，还进一步发现营养元素的动态特性与铬、砷和铅的不同。此外，我们扩展了这种方法，以提供一种量化两种环境暴露之间动态相互作用的新方法。为实现这一点，我们使用了交叉递归量化分析（CRQA），并发现元素营养元素之间的相互作用与涉及有毒物质的相互作用不同。我们在两个地理位置不同的队列中对这些有节奏的调节相互作用进行了描述，此前使用基于传统回归的方法尚未发现这些相互作用，它们可能为流行病学研究中的环境和饮食暴露提供关键的分析单元。
