Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples.,Translational Psychiatry

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Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples.
Translational Psychiatry ( IF 5.8 ) Pub Date : 2020-06-18 , DOI: 10.1038/s41398-020-00865-8
Peter B Barr ₁ , Albert Ksinan ₂ , Jinni Su ₃ , Emma C Johnson ₄ , Jacquelyn L Meyers ₅ , Leah Wetherill ₆ , Antti Latvala _{7,

8} , Fazil Aliev _{1,

9} , Grace Chan ₁₀ , Samuel Kuperman ₁₁ , John Nurnberger _{6,

12,

13} , Chella Kamarajan ₅ , Andrey Anokhin ₄ , Arpana Agrawal ₄ , Richard J Rose ₁₄ , Howard J Edenberg _{6,

15} , Marc Schuckit ₁₆ , Jaakko Kaprio _{7,

17} , Danielle M Dick _{1,

18}

Affiliation

Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.
Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA, USA.
Department of Psychology, Arizona State University, Tempe, AZ, USA.
Department of Psychiatry, School of Medicine, Washington University in St. Louis, St Louis, MO, USA.
Department of Psychiatry & Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA.
Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA.
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
Institute of Criminology and Legal Policy, University of Helsinki, Helsinki, Finland.
Faculty of Business, Karabük University, Karabük, Turkey.
Department of Psychiatry, School of Medicine, University of Connecticut, Farmington, CT, USA.
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
Department of Psychiatry, School of Medicine, Indiana University, Indianapolis, IN, USA.
Stark Neurosciences Research Institute, School of Medicine, Indiana University, Indianapolis, IN, USA.
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
Department of Biochemistry and Molecular Biology, School of Medicine, Indiana University, Indianapolis, IN, USA.
Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, USA.
Department of Public Health, University of Helsinki, Helsinki, Finland.
Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain ~2.5–3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

中文翻译：

使用多基因评分来识别临床和人群样本中物质使用障碍风险增加的个体。

全基因组多基因风险评分 (PRS) 已成为表征遗传责任的有用方法。越来越多的证据表明，PRS 可能有助于早期识别某些疾病风险增加的人。目前 PRS 治疗酒精使用障碍 (AUD) 的潜力仍然是一个悬而未决的问题。使用来自基于人群的样本 [FinnTwin12 (FT12) 研究] 和高风险样本 [酒精中毒遗传学合作研究 (COGA)] 的数据，我们检查了源自全基因组关联研究的 PRS 之间的关联(GWAS) 的 (1) 酒精依赖/酒精问题，(2) 饮酒，以及 (3) 具有 AUD 和其他物质使用障碍 (SUD) 标准的危险行为。当所有 PRS 都包含在同一模型中时，这些 PRS 解释了约 2.5-3.5% 的澳元方差（跨 FT12 和 COGA）。曲线下面积 (AUC) 的计算表明，与年龄、性别和祖先主成分作为协变量的模型相比，PRS 仅提供了轻微的改进。虽然在 COGA 和 FT12 中，PRS 分布的前 20%、10% 和 5% 的个人拥有 AUD 的几率高于连续体的低端，但每个阈值的点估计在统计上无法区分。前 5% 的人报告了更高水平的合法（酒精和尼古丁）和非法（大麻和阿片类药物）SUD 标准。PRS 与独立样本中的 SUD 风险相关。然而，以目前的形式识别风险增加的人的用处充其量是适度的。预测能力的提高可能取决于增加良好表型的发现样本的大小。

更新日期：2020-06-18

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