Restrepo-Lozano Jose M, Flores Cecilia, Silveira Patricia P
Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
Douglas Mental Health University Institute, Montreal, Quebec, Canada.
Biol Psychiatry Glob Open Sci. 2022 Aug 7;3(3):351-361. doi: 10.1016/j.bpsgos.2022.07.005. eCollection 2023 Jul.
The possibility of establishing a metric of individual genetic risk for a particular disease or trait has sparked the interest of the clinical and research communities, with many groups developing and validating genomic profiling methodologies for their potential application in clinical care. Current approaches for calculating genetic risk to specific psychiatric conditions consist of aggregating genome-wide association studies-derived estimates into polygenic risk scores, which broadly represent the number of inherited risk alleles for an individual. While the traditional approach for polygenic risk score calculation aggregates estimates of gene-disease associations, novel alternative approaches have started to consider functional molecular phenotypes that are closer to genetic variation and are less penalized by the multiple testing required in genome-wide association studies. Moving the focus from genotype-disease to genotype-gene regulation frameworks, these novel approaches incorporate prior knowledge regarding biological processes involved in disease and aggregate estimates for the association of genotypes and phenotypes using multi-omics data modalities. In this review, we discuss and list different functional genomics tools that can be used and integrated to inform researchers and clinicians for a better understanding and diagnosis of psychopathology. We suggest that these novel approaches can help generate biologically driven hypotheses for polygenic signals that can ultimately serve the clinical community as potential biomarkers of psychiatric disease susceptibility.
建立针对特定疾病或性状的个体遗传风险度量标准的可能性引发了临床和研究界的兴趣，许多团队正在开发和验证基因组分析方法，以便在临床护理中潜在应用。当前计算特定精神疾病遗传风险的方法包括将全基因组关联研究得出的估计值汇总为多基因风险评分，该评分大致代表个体遗传风险等位基因的数量。虽然多基因风险评分计算的传统方法汇总了基因与疾病关联的估计值，但新的替代方法已开始考虑更接近遗传变异且受全基因组关联研究所需多重检验惩罚较小的功能分子表型。这些新方法将重点从基因型与疾病的关系转向基因型与基因调控框架，纳入了有关疾病所涉及生物过程的先验知识，并使用多组学数据模式汇总基因型与表型关联的估计值。在本综述中，我们讨论并列出了不同的功能基因组学工具，这些工具可用于并整合起来，以帮助研究人员和临床医生更好地理解和诊断精神病理学。我们认为，这些新方法有助于为多基因信号生成生物学驱动的假设，最终可为临床界提供精神疾病易感性的潜在生物标志物。
