Department of Psychiatry, Washington University Medical School, 660 S. Euclid, St Louis, Missouri 63110, USA
Department of Psychiatry, Washington University Medical School, 660 S. Euclid, St Louis, Missouri 63110, USA.
Philos Trans R Soc Lond B Biol Sci. 2018 Apr 19;373(1744). doi: 10.1098/rstb.2017.0163.
There is fundamental doubt about whether the natural unit of measurement for temperament and personality corresponds to single traits or to multi-trait profiles that describe the functioning of a whole person. Biogenetic researchers of temperament usually assume they need to focus on individual traits that differ individuals. Recent research indicates that a shift of emphasis to understand processes the individual is crucial for identifying the natural building blocks of temperament. Evolution and development operate on adaptation of whole organisms or persons, not on individual traits or categories. Adaptive functioning generally depends on feedback among many variable processes in ways that are characteristic of complex adaptive systems, not machines with separate parts. Advanced methods of unsupervised machine learning can now be applied to genome-wide association studies and brain imaging in order to uncover the genotypic-phenotypic architecture of traits like temperament, which are strongly influenced by complex interactions, such as genetic epistasis, pleiotropy and gene-environment interactions. We have found that the heritability of temperament can be nearly fully explained by a large number of genetic variants that are unique for multi-trait profiles, not single traits. The implications of this finding for research design and precision medicine are discussed.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.
对于气质和个性的自然测量单位是对应于单个特征，还是对应于描述整个人体功能的多特征剖面，存在根本的疑问。气质的生物遗传研究人员通常假设他们需要专注于个体差异的个体特征。最近的研究表明，强调理解个体的过程对于确定气质的自然构成块至关重要。进化和发展是在整个生物体或个体的适应上运作的，而不是在单个特征或类别上。适应功能通常取决于许多变量过程之间的反馈，这些反馈方式是复杂适应系统的特征，而不是具有独立部分的机器。现在可以将无监督机器学习的先进方法应用于全基因组关联研究和大脑成像，以揭示气质等特征的基因型-表型结构，这些特征受复杂相互作用（如遗传上位性、多效性和基因-环境相互作用）的强烈影响。我们发现，气质的遗传性可以通过大量独特的多特征剖面的遗传变异来几乎完全解释，而不是单个特征。这一发现对研究设计和精准医学的影响正在讨论中。本文是主题为“多样性的不同视角：个体差异的多学科方法”的一部分。
