Standardized analysis and sharing of genome-phenome data for neuromuscular and rare disease research through the RD-Connect platform

<b>Abstract: </b><div>RD-Connect (rd-connect.eu) is an EU-funded project building an integrated platform to narrow the gaps in rare disease research, where patient populations, clinical expertise and research communities are small in number and highly fragmented. Guided by the needs of rare disease researchers and with neuromuscular and neurodegenerative researchers as its original collaborators, the RD-Connect platform securely integrates multiple types of omics data (genomics, proteomics and transcriptomics) with biosample and clinical information – at the level of an individual patient, a family or a whole cohort, providing not only a centralized data repository but also a sophisticated and user-friendly online analysis system. Whole-genome, exome or gene panel NGS datasets from individuals with rare diseases and family members are deposited at the European Genome-phenome Archive, a longstanding archiving system designed for long-term storage of these large datasets. The raw data is then processed by RD-Connect's standardised analysis and annotation pipeline to make data from different sequencing providers more comparable. The corresponding clinical information from each individual is recorded in a connected PhenoTips instance, a software solution that simplifies the capture of clinical data using the Human Phenotype Ontology, OMIM and Orpha codes. The results are made available to authorised users through the highly configurable online platform (platform.rd-connect.eu), which runs on a Hadoop cluster and uses ElasticSearch – technologies designed to handle big data at high speeds. The user-friendly interface enables filtering and prioritization of variants using the most common quality, genomic location, effect, pathogenicity and population frequency annotations, enabling users from clinical labs without extensive bioinformatics support to do their primary genomic analysis of their own patients online and compare them with other submitted cohorts. Additional tools, such as Exomiser, DiseaseCard, Alamut Functional Annotation (ALFA) and UMD Predictor (umd-predictor.eu) are integrated at several levels. The RD-Connect platform is designed to enable data sharing at various levels depending on user permissions. At the most basic level (“does this specific variant exist in any individual in this cohort?”) it has lit a Beacon within the Global Alliance for Genomics and Health’s Beacon Network (www.beacon-network.org). At the next stage of sharing – finding similarities between patients in different databases with a matching phenotype and a candidate variant in the same gene – it is actively involved in the development of Matchmaker Exchange (www.matchmakerexchange.org), allowing users of different systems to securely exchange information to find confirmatory cases. And finally, since all patients within the system have been consented for data sharing, users of the system, after validation and authorization, are able to access datasets from other centres, providing an instant means of gathering cohorts for cross-validation and further study. Although open to any rare disease, the platform is currently enriched for neuromuscular and neurodegenerative phenotypes and includes almost 1000 genomic datasets from the NeurOmics project (www.rd-neuromics.eu) with several other contributions in the pipeline, including 1000 limb-girdle muscular dystrophy index cases from the Myo-Seq project (www.myo-seq.org) and more. The platform is free of charge to use and is open for contributions of NGS and phenotypic data from research labs worldwide via [email protected] <p></p></div

Diversity of microbial communities derived from lungs of severe subtype cases and mild subtype and control individuals.

<p>(<b>a</b>) Pielou’s evenness and (<b>b</b>) Chao richness of microbial communities on genus level for severe vs mild/control samples. P-values were computed based on two-sided Wilcoxon-Mann-Whitney tests after correction for confounding effects from samples processed during winter or summer, respectively. (<b>c</b>) Phylogenetic community composition based on 16S rRNA gene fragment sequences in bronchial brushing samples. Bars represent the relative abundance of the most abundant families (>5% in one sample). The remaining families are subsumed as others.</p

Heatmap of genera showing significantly different abundances between severe versus mild subtype cases and controls.

<p>Genera showing significantly increased (<b>a</b>) or decreased (<b>b</b>) abundances in severe vs mild subtype cases and controls. Colors at the top represent COPD subtypes and controls. For each genus, samples were colored based on quartiles of non-zero abundances from light red to dark red. All Samples for which a genus was not present were colored in white.</p

Genus level community composition for COPD patients with and without abnormalities in CT and controls based on PCoA.

<p>(<b>a</b>) Lung derived microbial community composition in severe subtype COPD patients, mild subtype cases and controls were compared based on principal coordinate 1 and 2. (<b>b</b>) Boxplot comparing principal coordinate 1 between case and control samples. (<b>c</b>) Boxplot comparing principal coordinate 1 for severe subtype and mild subtype COPD patients and control samples. P-values were computed based on two-sided Wilcoxon-Mann-Whitney tests after correction for confounding effects from samples processed during winter or summer, respectively.</p

Clinical, spirometry and laboratory comparisons of patients and controls.

<p>Data presented as mean ±SD, unless otherwise indicated. Abbreviations: av. last cigarette (years): average years study participants stopped smoking before bronchoscopy procedure. BMI: body mass index. pO₂: partial pressure of oxygen. pCO₂: partial pressure of carbon dioxide. FEV₁: forced expiratory volume in 1s. FVC: forced vital capacity. LABA: long-acting beta-2 agonists.</p