Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation.

IF 3.6 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Emerging Themes in Epidemiology Pub Date : 2017-06-07 eCollection Date: 2017-01-01 DOI:10.1186/s12982-017-0061-7
Paolo Vineis, Phyllis Illari, Federica Russo
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引用次数: 32

Abstract

In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing-notably, the "sufficient-component-cause framework" and the "mark transmission" approach; (b) new acquisitions about disease pathogenesis, e.g. the "branched model" in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics research, with a large number of "signals" and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of "cancer causes". We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called "evidential pluralism". According to this view, causal reasoning is based on both "evidence of difference-making" (e.g. associations) and on "evidence of underlying biological mechanisms". We conceptualize the way scientists detect and trace signals in terms of information transmission, which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social-are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level.

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癌症研究中的因果关系:分子流行病学模型之旅及其哲学解释。
在过去的几十年里,系统生物学(包括癌症研究)一直受到技术、统计建模和生物信息学的推动。在本文中,我们试图把生物学和哲学的思考带回来。因此,我们的目标是使不同的思想传统兼容:(a)流行病学和哲学理论中的因果关系-特别是“充分成分-原因框架”和“标记传递”方法;(b)关于疾病发病机制的新发现,例如癌症的“分支模型”,以及生物标志物在这一过程中的作用;(c)组学研究蓬勃发展,有大量的“信号”和需要解释的关联。在本文中,我们首先总结了目前对致癌作用的看法,然后探讨了当前对“致癌原因”的哲学解释的相关性。我们试图提供一个统一的框架,将生物标志物和基因组数据纳入因果模型,参考一个被称为“证据多元主义”的立场。根据这一观点,因果推理是基于“差异产生的证据”(如关联)和“潜在生物机制的证据”。我们从信息传递的角度将科学家探测和追踪信号的方式概念化,这是对哲学家韦斯利·萨蒙(Wesley Salmon)提出的标记传递理论的概括。我们的方法能够帮助我们概念化诸如微观和宏观生物和心理社会等异质因素是如何因果联系的。这不仅对了解癌症病因很重要,而且对设计公共卫生政策在宏观层面上针对正确的病因也很重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Emerging Themes in Epidemiology
Emerging Themes in Epidemiology Medicine-Epidemiology
CiteScore
4.40
自引率
4.30%
发文量
9
审稿时长
28 weeks
期刊介绍: Emerging Themes in Epidemiology is an open access, peer-reviewed, online journal that aims to promote debate and discussion on practical and theoretical aspects of epidemiology. Combining statistical approaches with an understanding of the biology of disease, epidemiologists seek to elucidate the social, environmental and host factors related to adverse health outcomes. Although research findings from epidemiologic studies abound in traditional public health journals, little publication space is devoted to discussion of the practical and theoretical concepts that underpin them. Because of its immediate impact on public health, an openly accessible forum is needed in the field of epidemiology to foster such discussion.
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