Paul H. Chook Dept. of CIS & Statistics, CUNY/Baruch College, New York, NY, USA.
Genetica. 2022 Aug;150(3-4):183-197. doi: 10.1007/s10709-021-00138-2. Epub 2021 Oct 22.
Genotype-phenotype causal modeling has evolved significantly since Johannsen's and Wright's original designs were published. The development of genomewide assays to interrogate and detect possible causal variants associated with complex traits has expanded the scope of genotype-phenotype research considerably. Clusters of causal variants discovered by genomewide assays and associated with complex traits have been used to develop polygenic risk scores to predict clinical diagnoses of multidimensional human disorders. However, genomewide investigations have met with many challenges to their research designs and statistical complexities which have hindered the reliability and validity of their predictions. Findings linked to differences in heritability estimates between causal clusters and complex traits among unrelated individuals remain a research area of some controversy. Causal models developed from case-control studies as opposed to experiments, as well as other issues concerning the genotype-phenotype causal model and the extent to which various forms of pleiotropy and the concept of the endophenotype add to its complexity, will be reviewed.
自 Johannsen 和 Wright 最初的设计发表以来,基因型-表型因果建模已经有了显著的发展。全基因组检测方法的发展,用于探究和检测与复杂性状相关的可能的因果变异,大大扩展了基因型-表型研究的范围。全基因组检测方法发现的与复杂性状相关的因果变异簇,已被用于开发多基因风险评分,以预测多维人类疾病的临床诊断。然而,全基因组研究在其研究设计和统计复杂性方面遇到了许多挑战,这阻碍了其预测的可靠性和有效性。与无关个体中因果簇与复杂性状之间遗传力估计值差异相关的发现仍然是一个存在争议的研究领域。将从病例对照研究而不是实验中开发的因果模型,以及其他与基因型-表型因果模型有关的问题,以及各种形式的表型多效性和内表型概念对其复杂性的影响,将进行回顾。