ESPE2021 ePoster Category 2 Sex differentiation, gonads and gynaecology or sex endocrinology (52 abstracts)
Combining big data science with clinics: Novel approach for understanding human sex development and its variants.
Daniel Rodríguez Gutiérrez 1 , Patrick Sproll 1 , Isabel Von der Decken 1 , Brian Stevenson 2 , Mariarosaria Lang-Muritano 3 , Daniel Konrad 3 , Dagmar L’Allemand 4 , Serge Nef 5 & Anna Biason-Lauber 1
1University of Fribourg, Fribourg, Switzerland; 2University of Lausanne, Lausanne, Switzerland; 3Kinderspital Zürich, Zürich, Switzerland; 4Kantonsspital St. Gallen, St. Gallen, Switzerland; 5University of Geneva, Geneva, Switzerland
Background/Introduction: Whole exome sequencing (WES) revolutionized clinical genetics in patients with differences of sex development (DSD). However, our ability to interpret WES data is limited by our incomplete understanding of the mechanisms involved in DSD. Thus, we created a methodology that scores potential candidates based on single cells transcriptomics of human male gonadal cells and applied it to WES data from a cohort of genetically male (46,XY) DSD patients.
Methods: For each cell type in the male gonad, genes were ranked (R score) based on two variables: Single-cell RNA-seq expression in human fetal SCs and expression in sex development-unrelated organs (heart, lung, colon). Genes with scores higher than the mean were considered as candidate players for cell-type regulation. We then applied the R score as a filter to prioritize genes with rare variants identified in our cohort of unresolved 46,XY DSD cases. An interaction network of our candidates with known sex-development genes was used to highlight those candidates with multiple connexions with sex-development pathways for further studies.
Results: From the 13,000 genes expressed in gonadal cells, we were able to create ranking lists of the most relevant genes for each male gonadal cell type (Sertoli, Leydig and germ cells). Thanks to these rankings, we filtered the thousands of variants observed in undiagnosed DSD patients, and selected high priority candidate lists of 100 genes for each cell type. Among the top-ranked candidates for further studies, we observed IGF1, KIT and IL-6, which are known to be involved in male gonadal regulation but have not been described in DSD patients.
Conclusion: This pipeline will ultimately advance basic knowledge in the regulation of human sex development. Moreover, our results highlight the value of integrating rich clinical data with cellular models and the need to generate multimodal data, serving as a proof of concept for developing powerful genetic analysis algorithms to ultimately overcome the difficulties in interpretation of next-generation data and eventually unravel the mechanisms governing human physiology.
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