The clinical evaluation of a genetic syndrome relies upon recognition of a characteristic pattern of signs or symptoms to guide targeted genetic testing for confirmation of the diagnosis. However, individuals displaying a single phenotype of a complex syndrome may not meet criteria for clinical diagnosis or genetic testing. Here, we present a phenome-wide association study (PheWAS) approach to systematically explore the phenotypic expressivity of common and rare alleles in genes associated with four well-described syndromic diseases (Alagille (AS), Marfan (MS), DiGeorge (DS), and Noonan (NS) syndromes) in the general population.

Using human phenotype ontology (HPO) terms, we systematically mapped 60 phenotypes related to AS, MS, DS and NS in 337,198 unrelated white British from the UK Biobank (UKBB) based on their hospital admission records, self-administrated questionnaires, and physiological measurements. We performed logistic regression adjusting for age, sex, and the first 5 genetic principal components, for each phenotype and each variant in the target genes (JAG1, NOTCH2 FBN1, PTPN1 and RAS-opathy genes, and genes in the 22q11.2 locus) and performed a gene burden test.

Overall, we observed multiple phenotype-genotype correlations, such as the association between variation in JAG1, FBN1, PTPN11 and SOS2 with diastolic and systolic blood pressure; and pleiotropy among multiple variants in syndromic genes. For example, rs11066309 in PTPN11 was significantly associated with a lower body mass index, an increased risk of hypothyroidism and a smaller size for gestational age, all in concordance with NS-related phenotypes. Similarly, rs589668 in FBN1 was associated with an increase in body height and blood pressure, and a reduced body fat percentage as observed in Marfan syndrome.

Our findings suggest that the spectrum of associations of common and rare variants in genes involved in syndromic diseases can be extended to individual phenotypes within the general population.

遗传综合征的临床评估依赖于对体征或症状特征模式的识别，以指导有针对性的基因检测以确认诊断。然而，显示复杂综合征单一表型的个体可能不符合临床诊断或基因检测的标准。在这里，我们提出了一种全表型关联研究 (PheWAS) 方法，系统地探索与四种已充分描述的综合征疾病（Alagille (AS)、Marfan (MS)、DiGeorge (DS)）相关的基因中常见和稀有等位基因的表型表达。 , 和努南 (NS) 综合征) 在一般人群中。

使用人类表型本体 (HPO) 术语，我们根据入院记录、自我管理的问卷和生理测量，系统地绘制了来自英国生物银行 (UKBB) 的 337,198 名无关英国白人的 60 种与 AS、MS、DS 和 NS 相关的表型. 我们针对目标基因（ JAG1、NOTCH2 FBN1、PTPN1 和 RAS-opathy 基因，以及 22q11.2 基因座中的基因）中的每个表型和每个变体，对年龄、性别和前 5 个遗传主成分进行了逻辑回归调整并进行了基因负荷测试。

总体而言，我们观察到多种表型-基因型相关性，例如JAG1、FBN1、PTPN11和SOS2的变异与舒张压和收缩压之间的关联；和多效性在综合征基因的多个变体之间。例如，PTPN11中的 rs11066309 与较低的体重指数、甲状腺功能减退症的风险增加和胎龄较小的显着相关，所有这些都与 NS 相关表型一致。同样，FBN1中的 rs589668 与身高和血压的增加以及马凡综合征中观察到的体脂百分比降低有关。

我们的研究结果表明，涉及综合征疾病的基因中常见和罕见变异的关联范围可以扩展到一般人群中的个体表型。