Identification of de novo variants in nonsyndromic cleft lip with/without cleft palate patients with low polygenic risk scores. Issue 3 (5th December 2022) - Ishorst, Nina; Henschel, Leonie; Thieme, Frederic; Drichel, Dmitriy; Sivalingam, Sugirthan; Mehrem, Sarah L.; Fechtner, Ariane C.; Fazaal, Julia; Welzenbach, Julia; Heimbach, André; Maj, Carlo; Borisov, Oleg; et al.
Abstract: Background: Nonsyndromic cleft lip with/without cleft palate (nsCL/P) is a congenital malformation of multifactorial etiology. Research has identified >40 genome‐wide significant risk loci, which explain less than 40% of nsCL/P heritability. Studies show that some of the hidden heritability is explained by rare penetrant variants. Methods: To identify new candidate genes, we searched for highly penetrant de novo variants (DNVs) in 50 nsCL/P patient/parent‐trios with a low polygenic risk for the phenotype (discovery). We prioritized DNV‐carrying candidate genes from the discovery for resequencing in independent cohorts of 1010 nsCL/P patients of diverse ethnicities and 1574 population‐matched controls (replication). Segregation analyses and rare variant association in the replication cohort, in combination with additional data (genome‐wide association data, expression, protein–protein‐interactions), were used for final prioritization. Conclusion: In the discovery step, 60 DNVs were identified in 60 genes, including a variant in the established nsCL/P risk gene CDH1 . Re‐sequencing of 32 prioritized genes led to the identification of 373 rare, likely pathogenic variants. Finally, MDN1 and PAXIP1 were prioritized as top candidates. Our findings demonstrate that DNV detection, including polygenic risk score analysis, is a powerful tool for identifying nsCL/P candidate genes, which can also be applied to other multifactorial congenital malformations. Abstract : In the present study, we searched for de novo variants in 50 nonsyndromic cleft lip with/without cleft palate patient/parent‐trios. A subsequent replication of prioritized candidate genes and further analyses that included genome‐wide association data, expression data from relevant tissues and protein–protein‐interactions, generated further evidence for the two top candidate genes MDN1 and PAXIP1 .