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精神分裂症涉及多少个基因?一个简单的模拟。

How many genes are involved in schizophrenia? A simple simulation.

机构信息

Department of Psychiatry, The Armed Forces Capital Hospital, Seongnam, Republic of Korea.

出版信息

Prog Neuropsychopharmacol Biol Psychiatry. 2012 Aug 7;38(2):302-9. doi: 10.1016/j.pnpbp.2012.04.015. Epub 2012 Apr 24.

DOI:10.1016/j.pnpbp.2012.04.015
PMID:22561393
Abstract

We attempted to estimate how many genes are involved in schizophrenia using a simulation based on the polygenic threshold model. The basic assumptions were as follows: (1) All genes involved are transmitted independently; (2) every locus is composed of two alleles - one pathogenic and the other non-pathogenic; (3) all pathogenic alleles are dominant; (4) the two alleles at any locus are in Hardy-Weinberg Equilibrium (HWE) in the general population (GP) but not within the patient (PP) or non-patient (NP) subpopulations; (5) the number of affected loci determines the disease genetically; and (6) only a fraction of genetically determined individuals actually becomes ill. A range of the total number of disease-related genes (N) and threshold genetic load (T) was set for the simulation. Assuming that the number of affected loci follows a binomial distribution, the mean gene frequencies satisfying a disease prevalence of 1.12% in the GP were sought for various N and T combinations. Based on these gene frequencies, the odds ratio and the incidence rate in relatives under random mating were calculated. These results were then compared with real genetic epidemiologic data to obtain best-fit estimates for N and T. The results indicated that a polygenic threshold model with an N greater than 100 and a T in the range of 0.3-0.8 fits the empirical data. It was estimated that at least several hundreds of study subjects are required to yield a statistically significant frequency difference for a single gene between the patient and the control groups.

摘要

我们试图通过基于多基因阈值模型的模拟来估计精神分裂症涉及多少个基因。基本假设如下:(1) 所有涉及的基因都是独立传递的;(2) 每个基因座由两个等位基因组成——一个是致病的,另一个是非致病的;(3) 所有致病等位基因都是显性的;(4) 任意基因座的两个等位基因在一般人群 (GP) 中处于哈迪-温伯格平衡 (HWE) 状态,但不在患者 (PP) 或非患者 (NP) 亚群中;(5) 受影响的基因座数量决定疾病的遗传方式;(6) 只有一部分遗传决定的个体实际上会生病。模拟设定了疾病相关基因总数 (N) 和遗传负荷阈值 (T) 的范围。假设受影响的基因座数量遵循二项式分布,那么对于各种 N 和 T 组合,我们寻求在 GP 中疾病患病率为 1.12%时满足的平均基因频率。基于这些基因频率,计算了随机交配下亲属的优势比和发病率。然后将这些结果与真实的遗传流行病学数据进行比较,以获得 N 和 T 的最佳拟合估计值。结果表明,具有 N 大于 100 和 T 在 0.3-0.8 范围内的多基因阈值模型符合经验数据。据估计,至少需要数百名研究对象才能在患者和对照组之间的单个基因的频率差异上产生统计学上的显著差异。

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