What are quantitative traits and how can they be used in autism research?

被引:8
|
作者
Lyall, Kristen [1 ,2 ]
机构
[1] Drexel Univ, AJ Drexel Autism Inst, Philadelphia, PA USA
[2] Drexel Univ, AJ Drexel Autism Inst, 3020 Market St, Suite 560, Philadelphia, PA 19104 USA
关键词
autism; endophenotype; epidemiologic methods; phenotype; psychometrics; quantitative traits; GENERAL-POPULATION; SPECTRUM DISORDER; SOCIAL RESPONSIVENESS; PSYCHIATRIC-DISORDERS; BROADER PHENOTYPE; LOCUS ANALYSIS; HERITABILITY; INFANTS; BRAIN; AGE;
D O I
10.1002/aur.2937
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Quantitative traits are measurable characteristics distributed along a continuous scale thought to relate to underlying biology. There is growing interest in the use of quantitative traits in behavioral and psychiatric research, particularly in research on conditions diagnosed based on reports of behaviors, including autism. This brief commentary describes quantitative traits, including defining what they are, how we can measure them, and key considerations for their use in autism research. Examples of measures include behavioral report scales like the Social Responsiveness Scale and Broader Autism Phenotype Questionnaire, as well as biological measurements, like certain neuroimaging metrics; such measures can capture quantitative traits or constructs like the broader autism phenotype, social communication, and social cognition. Quantitative trait measures align with the Research Domain Criteria (RDoC) approach and can be used in autism research to help gain a better understanding of causal pathways and biological processes. They can also be used to aid identification of genetic and environmental factors involved in such pathways, and thereby lead to an understanding of influences on traits across the entire population. Finally, in some cases, they may be used to gauge treatment response, and assist screening and clinical characterization of phenotype. In addition, practical benefits of quantitative trait measures include improved statistical power relative to categorical classifications and (for some measures) efficiency. Ultimately, research across autism fields may benefit from incorporating quantitative trait measures as a complement to categorical diagnosis to advance understanding of autism and neurodevelopment.
引用
收藏
页码:1289 / 1298
页数:10
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