A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration

Abstract

Rett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms and faster identification of variants for diagnosis. This is, however, currently hampered by the lack of interoperability between genotype-phenotype databases. Here, we demonstrate on the example of MECP2 in RTT that by making the genotype-phenotype data more Findable, Accessible, Interoperable, and Reusable (FAIR), we can facilitate prioritization and analysis of variants. In total, 10,968 MECP2 variants were successfully integrated. Among these variants 863 unique confirmed RTT causing and 209 unique confirmed benign variants were found. This dataset was used for comparison of pathogenicity predicting tools, protein consequences, and identification of ambiguous variants. Prediction tools generally recognised the RTT causing and benign variants, however, there was a broad range of overlap Nineteen variants were identified that were annotated as both disease-causing and benign, suggesting that there are additional factors in these cases contributing to disease development.

Fig. 1

Schematic drawing of the workflow of this study: data collection, preparation, FAIRification and downstream analysis.

Fig. 2

Network illustrating the number of unique and overlapping MECP2 variations within and between nine Rett syndrome databases: DECIPHER, Maastricht Rett dataset (MRD), ClinVar, Rettbase, KMD, EVS, LOVD, EVA, and ExAC. Each node (circle) represents a database. The node size correlates with the number of variants (between 30 and 4775), the edge thickness correlates with the number of overlapping/shared variants between the two databases (between 0 and 500). The colour of the charts in the nodes represent the proportion of unique variants (blue) versus variants shared with other databases (yellow).

Fig. 3

Boxplots comparing prediction score value distribution calculated by different tools from the benign, both and RTT causing MECP2 genetic variants. The effect prediction was done based on conservation score (PolyPhen), four pathogenicity scores (SIFT, CADD, MetaLR, and FATHMM.MKL), and the variant allele frequency in the GnomAD dataset.

Fig. 4

Distribution of RTT causing and benign MECP2 missense variations. Amino acid positions correspond to isoform MECP2-e2 (the result of translation initiated at exon 2). Frequency is represented as the percentage of missense variations falling in each position, from the total of missense variations in cases or controls. In a) each MECP2 domain is coloured differently, while in b) conserved deletions are coloured in yellow. Domain abbreviations: N-terminal domain (NTD), methyl-DNA binding domain (MDB), interdomain (ID), transcription repressor binding domain (TRD), C-terminal domain (CTD).