Modeling the Diagnostic Criteria for Alcohol Dependence with Genetic Animal Models

Modeling the Diagnostic Criteria for Alcohol Dependence with Genetic Animal Models
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DOI:
10.1007/7854_2011_162
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发表时间:
2013-01-01
期刊:
BEHAVIORAL NEUROBIOLOGY OF ALCOHOL ADDICTION
影响因子:
--
通讯作者:
Hitzemann, Robert J.
Hitzemann, Robert J.
中科院分区:
其他
文献类型:
--
作者:
Crabbe, John C.;Kendler, Kenneth S.;Hitzemann, Robert J.

文献摘要

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使用DSM-IV-R的酒精依赖(AD)诊断是分类的,基于个人从七个症状列表中的三个或更多症状的表现。AD风险可以追溯到遗传和环境来源。大多数AD风险的遗传学研究隐含地假设AD诊断代表单个潜在的遗传因素。我们最近发现,AD诊断的标准代表了个体风险的三种不同的遗传途径。具体来说,大量使用和耐受与戒断和继续使用,尽管问题反映了单独的遗传因素。然而,一些数据表明,AD的遗传风险用一个潜在的遗传风险因素进行了充分描述。酒精相关表型的啮齿动物模型通常针对复杂的人类AD诊断的离散方面。在这里,我们回顾了来自遗传动物模型的文献,试图确定它们是否支持单因素或多因素的遗传结构。我们的结论是,在动物文献中有适度的支持,酒精耐受性和戒断反映了不同的遗传风险因素,与我们的人类数据一致。我们建议在哪些领域进行更多的研究,以澄清这种尝试,使啮齿动物和人类的数据一致。
A diagnosis of alcohol dependence (AD) using the DSM-IV-R is categorical, based on an individual's manifestation of three or more symptoms from a list of seven. AD risk can be traced to both genetic and environmental sources. Most genetic studies of AD risk implicitly assume that an AD diagnosis represents a single underlying genetic factor. We recently found that the criteria for an AD diagnosis represent three somewhat distinct genetic paths to individual risk. Specifically, heavy use and tolerance versus withdrawal and continued use despite problems reflected separate genetic factors. However, some data suggest that genetic risk for AD is adequately described with a single underlying genetic risk factor. Rodent animal models for alcohol-related phenotypes typically target discrete aspects of the complex human AD diagnosis. Here, we review the literature derived from genetic animal models in an attempt to determine whether they support a single-factor or multiple-factor genetic structure. We conclude that there is modest support in the animal literature that alcohol tolerance and withdrawal reflect distinct genetic risk factors, in agreement with our human data. We suggest areas where more research could clarify this attempt to align the rodent and human data.