A phenome-wide association study of four syndromic genes reveals pleiotropic effects of common and rare variants in the general population

Abstract

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 few phenotypes 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 pleiotropy 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, TBX1, FBN1, PTPN11, NOTCH2, and MAP2K1) and performed a gene burden testing. 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.

NETMAGE: a humaN-disEase phenoType MAp GEnerator for the Visualization of PheWAS

“…Our map correctly displays previously identified instances of potential pleiotropy from the UKBB, including rs544873’s association with pulmonary heart disease, phlebitis and thrombophlebitis, hemorrhoids, circulatory disease, and diverticulosis, and rs925488’s association with thyroid cancer, nontoxic nodular and multinodular goiter, and hypothyroidism 14 . Our map also appropriately shows associations for the SNP rs11066309 with hypertension, ischemic heart disease, myocardial infarction, coronary atherosclerosis, and hypothyroidism 15 , and associations for the SNP rs780094 with diabetes and lipid metabolism. 16…”

Impact of rare and common genetic variation in the Interleukin-1 pathway on human cytokine responses

“…Over the past decades, various studies have identified a role for common genetic variation on cytokine level and response, however a significant proportion of inter-individual variability remains to be determined [12][13][14][15]. Considering the increasing evidence that specific combinations of variants with variable frequencies can influence phenotypic variability [16][17][18], in particular for a combination of phenotypic characteristics that do not fit one specific clinical diagnosis [30], we hypothesized that the inter-individual variability in cytokine responses might be subjectable to same concept. For this purpose, we sequenced the coding regions of 48 genes related to the IL-1 pathway in almost 500 healthy individuals, and assessed IL-1ß and IL-6 levels in whole blood in response to in vitro LPS, PHA, C. albicans and S. aureus.…”