Next-generation sequencing profiling of miRNAs in individuals with 22q11.2 deletion syndrome revealed altered expression of miR-185-5p.

BACKGROUND: The 22q11.2 deletion syndrome (22q11.2DS) is a microdeletion syndrome with highly variable phenotypic manifestations, even though most patients present the typical 3 Mb microdeletion, usually affecting the same ~ 106 genes. One of the genes affected by this deletion is DGCR8, which plays a crucial role in miRNA biogenesis. Therefore, the haploinsufficiency of DGCR8 due to this microdeletion can alter the modulation of the expression of several miRNAs involved in a range of biological processes. RESULTS: In this study, we used next-generation sequencing to evaluate the miRNAs profiles in the peripheral blood of 12 individuals with typical 22q11DS compared to 12 healthy matched controls. We used the DESeq2 package for differential gene expression analysis and the DIANA-miTED dataset to verify the expression of differentially expressed miRNAs in other tissues. We used miRWalk to predict the target genes of differentially expressed miRNAs. Here, we described two differentially expressed miRNAs in patients compared to controls: hsa-miR-1304-3p, located outside the 22q11.2 region, upregulated in patients, and hsa-miR-185-5p, located in the 22q11.2 region, which showed downregulation. Expression of miR-185-5p is observed in tissues frequently affected in patients with 22q11DS, and previous studies have reported its downregulation in individuals with 22q11DS. hsa-miR-1304-3p has low expression in blood and, thus, needs more validation, though using a sensitive technology allowed us to identify differences in expression between patients and controls. CONCLUSIONS: Thus, lower expression of miR-185-5p can be related to the 22q11.2 deletion and DGCR8 haploinsufficiency, leading to phenotypic consequences in 22q11.2DS patients, while higher expression of hsa-miR-1304-3p might be related to individual genomic variances due to the heterogeneous background of the Brazilian population.

GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseases.

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.

GestaltMatcher Database - A global reference for the facial phenotypic variability of rare human diseases.

Dysmorphologists sometimes encounter challenges in recognizing disorders due to phenotypic variability influenced by factors such as age and ethnicity. Moreover, the performance of Next Generation Phenotyping Tools such as GestaltMatcher is dependent on the diversity of the training set. Therefore, we developed GestaltMatcher Database (GMDB) - a global reference for the phenotypic variability of rare diseases that complies with the FAIR-principles. We curated dysmorphic patient images and metadata from 2,224 publications, transforming GMDB into an online dynamic case report journal. To encourage clinicians worldwide to contribute, each case can receive a Digital Object Identifier (DOI), making it a citable micro-publication. This resulted in a collection of 2,312 unpublished images, partly with longitudinal data. We have compiled a collection of 10,189 frontal images from 7,695 patients representing 683 disorders. The web interface enables gene- and phenotype-centered queries for registered users (https://db.gestaltmatcher.org/). Despite the predominant European ancestry of most patients (59%), our global collaborations have facilitated the inclusion of data from frequently underrepresented ethnicities, with 17% Asian, 4% African, and 6% with other ethnic backgrounds. The analysis has revealed a significant enhancement in GestaltMatcher performance across all ethnic groups, incorporating non-European ethnicities, showcasing a remarkable increase in Top-1-Accuracy by 31.56% and Top-5-Accuracy by 12.64%. Importantly, this improvement was achieved without altering the performance metrics for European patients. GMDB addresses dysmorphology challenges by representing phenotypic variability and including underrepresented groups, enhancing global diagnostic rates and serving as a vital clinician reference database.