Stolk Ronald P, Rosmalen Judith G M, Postma Dirkje S, de Boer Rudolf A, Navis Gerjan, Slaets Joris P J, Ormel Johan, Wolffenbuttel Bruce H R
Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Eur J Epidemiol. 2008;23(1):67-74. doi: 10.1007/s10654-007-9204-4. Epub 2007 Dec 13.
The risk for multifactorial diseases is determined by risk factors that frequently apply across disorders (universal risk factors). To investigate unresolved issues on etiology of and individual's susceptibility to multifactorial diseases, research focus should shift from single determinant-outcome relations to effect modification of universal risk factors. We present a model to investigate universal risk factors of multifactorial diseases, based on a single risk factor, a single outcome measure, and several effect modifiers. Outcome measures can be disease overriding, such as clustering of disease, frailty and quality of life. "Life course epidemiology" can be considered as a specific application of the proposed model, since risk factors and effect modifiers of multifactorial diseases typically have a chronic aspect. Risk factors are categorized into genetic, environmental, or complex factors, the latter resulting from interactions between (multiple) genetic and environmental factors (an example of a complex factor is overweight). The proposed research model of multifactorial diseases assumes that determinant-outcome relations differ between individuals because of modifiers, which can be divided into three categories. First, risk-factor modifiers that determine the effect of the determinant (such as factors that modify gene-expression in case of a genetic determinant). Second, outcome modifiers that determine the expression of the studied outcome (such as medication use). Third, generic modifiers that determine the susceptibility for multifactorial diseases (such as age). A study to assess disease risk during life requires phenotype and outcome measurements in multiple generations with a long-term follow up. Multiple generations will also enable to separate genetic and environmental factors. Traditionally, representative individuals (probands) and their first-degree relatives have been included in this type of research. We put forward that a three-generation design is the optimal approach to investigate multifactorial diseases. This design has statistical advantages (precision, multiple-informants, separation of non-genetic and genetic familial transmission, direct haplotype assessment, quantify genetic effects), enables unique possibilities to study social characteristics (socioeconomic mobility, partner preferences, between-generation similarities), and offers practical benefits (efficiency, lower non-response). LifeLines is a study based on these concepts. It will be carried out in a representative sample of 165,000 participants from the northern provinces of the Netherlands. LifeLines will contribute to the understanding of how universal risk factors are modified to influence the individual susceptibility to multifactorial diseases, not only at one stage of life but cumulatively over time: the lifeline.
多因素疾病的风险由通常适用于多种疾病的风险因素(通用风险因素)决定。为了研究多因素疾病病因及个体易感性方面尚未解决的问题,研究重点应从单一决定因素与结果的关系转向通用风险因素的效应修饰。我们提出一个基于单一风险因素、单一结果指标和多个效应修饰因素来研究多因素疾病通用风险因素的模型。结果指标可以是疾病主导的,如疾病聚集、虚弱和生活质量。“生命历程流行病学”可被视为所提出模型的一种具体应用,因为多因素疾病的风险因素和效应修饰因素通常具有慢性特征。风险因素分为遗传、环境或复杂因素,后者由(多个)遗传和环境因素之间的相互作用产生(复杂因素的一个例子是超重)。所提出的多因素疾病研究模型假定,由于效应修饰因素的存在,个体之间的决定因素与结果的关系有所不同,效应修饰因素可分为三类。第一,风险因素修饰因素,它决定决定因素的效应(例如在遗传决定因素情况下修饰基因表达的因素)。第二,结果修饰因素,它决定所研究结果的表达(例如药物使用)。第三,通用修饰因素,它决定对多因素疾病的易感性(例如年龄)。一项评估一生中疾病风险的研究需要在多代人中进行表型和结果测量,并进行长期随访。多代人研究还将有助于区分遗传和环境因素。传统上,这类研究纳入了有代表性的个体(先证者)及其一级亲属。我们提出三代设计是研究多因素疾病的最佳方法。这种设计具有统计学优势(精度、多个信息提供者、区分非遗传和遗传家族传递、直接单倍型评估、量化遗传效应),能提供研究社会特征(社会经济流动性、伴侣偏好、代际相似性)的独特可能性,并具有实际益处(效率高、无应答率低)。“生命线”研究就是基于这些概念开展的。它将在荷兰北部省份16.5万名参与者的代表性样本中进行。“生命线”研究将有助于理解通用风险因素是如何被修饰从而影响个体对多因素疾病的易感性的,这种影响不仅在生命的一个阶段存在,而且会随着时间累积:即生命历程。