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CYP2D6 Genotype and Cognitive Deficits in Methamphetamine Users with/without HIV

CYP2D6 Genotype and Cognitive Deficits in Methamphetamine Users with/without HIV
患有/不患有艾滋病毒的甲基苯丙胺使用者的 CYP2D6 基因型和认知缺陷
批准号:
8811413
负责人:
MARIANA CHERNER
金额:
$33.34万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-04-15 至 2017-02-28

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DESCRIPTION (provided by applicant): Although cytochrome P450-2D6 (CYP2D6) is the primary enzyme responsible for methamphetamine (meth) metabolism, no work has been conducted outside of our group on its role in meth-related brain dysfunction. Our preliminary data with a small sample suggests that genetic differences coding for the activity of CYP2D6 are associated with differential vulnerability to neurocognitive problems in meth users. Individuals with genotypes corresponding to diminished metabolism seem to incur less neuropsychological impairment than those with normal metabolism. This is an intriguing finding, as it implicates the metabolic products of methamphetamine in brain injury. It also suggests that certain individuals are at increased risk of meth-related brain problems. Our group has described additive negative effects of meth, HIV, and hepatitis C (HCV) on brain function. There is evidence that liver disease, such as in HCV, as well as HIV, may alter CYP2D6 activity such that the genotype does not always correspond with the actual metabolic activity phenotype. Additionally, serotonin reuptake inhibitors for depression, which are very widely prescribed, are also substrates and inhibitors of CYP2D6 and thus may affect methamphetamine metabolism if taken concurrently. Finally, the antiretroviral ritonavir, used to boost the majority of cART regimens, is also a CYP2D6 inhibitor, and there are reports in the literature of prolonged psychoactive drug effects in HIV patients taking this medicine. As a first step in understanding whether CYP2D6 variants truly contribute to brain dysfunction associated with meth, we propose to generate CYP2D6 genotypes to replicate the small study referenced above with a large sample, and perform "deep" data analysis to understand the complexities that may mitigate the relationship between drug metabolism and cognitive outcomes. To do this, we propose to leverage an incredible resource in the form of stored samples that are accompanied by extensive clinical characterization collected from a number of projects funded by NIDA and NIMH over the past 15 years, which likely constitute the largest collection of well- characterized methamphetamine dependent cases available anywhere. Findings could lead to pharmacologic interventions to reduce brain injury as well as inform treatment choices for meth users with HIV or HCV infection.
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