Bachmann Nadine, Turk Teja, Kadelka Claus, Marzel Alex, Shilaih Mohaned, Böni Jürg, Aubert Vincent, Klimkait Thomas, Leventhal Gabriel E, Günthard Huldrych F, Kouyos Roger
Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
Retrovirology. 2017 May 23;14(1):33. doi: 10.1186/s12977-017-0356-3.
Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission-who is the donor (parent) and who is the recipient (offspring)-is typically unknown and viral phylogenies are sparsely sampled.
We assessed the applicability of PO regression in a realistic setting using Ornstein-Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients.
We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%).
For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.
亲子回归是确定表型性状遗传力的核心工具;即这些性状受遗传因素控制的相对程度。亲子回归在病毒性状方面的适用性尚不清楚,因为病毒传播的方向——谁是供体(亲代)谁是受体(子代)——通常未知,而且病毒系统发育的样本稀少。
我们使用基于11442条瑞士HIV队列研究(SHCS)部分pol序列构建的系统发育的奥恩斯坦 - 乌伦贝克模拟数据以及来自3293名患者的设定点病毒载量(SPVL)数据,在现实环境中评估亲子回归的适用性。
我们发现供体和受体的错误识别在估计遗传力中起次要作用,并表明稀疏采样不影响亲子回归估计的平均遗传力。混合效应模型方法得出的遗传力与亲子回归相同,但可以扩展到大于2的聚类,并允许校正混杂效应。最后,我们使用这两种方法估计SHCS中的SPVL遗传力。我们采用了广泛的传播对标准来测量遗传力,发现遗传力估计值强烈依赖于这些标准。对于最保守的遗传距离标准,从概念上讲遗传力估计值预计最接近真实遗传力,我们发现在不同的自助抽样标准下估计值范围为32%至46%。对于不太保守距离标准,我们发现估计值低至8%。在混合效应模型中调整宿主人口统计学因素后,所有估计值变化不大(±2%)。
对于保守的传播对标准,亲子回归和混合效应模型都是灵活且稳健的工具,可用于估计现实环境中病毒遗传效应对病毒性状的贡献。总体而言,我们发现病毒遗传学对SPVL有很强的影响,且不受宿主人口统计学因素的混淆。