The Undiagnosed Diseases Network International: Five years and more!

Undiagnosed rare diseases (URDs) account for a significant portion of the overall rare disease burden, depending upon the country. Hence, URDs represent an unmet medical need. A specific challenge posed by the ensemble of the URD patient cohort is the heterogeneity of its composition; the group, indeed, includes very rare, still unidentified conditions as well as clinical variants of recognized rare diseases. Exact disease recognition requires new approaches that cut across national and institutional boundaries, may need the implementation of methods new to diagnostics, and embrace clinical care and research. To address these issues, the Undiagnosed Diseases Network International (UDNI) was established in 2014, with the major aims of providing diagnoses to patients, implementing additional diagnostic tools, and fostering research on novel diseases, their mechanisms, and their pathways. The UDNI involves centres with internationally recognized expertise, and its scientific resources and know-how aim to fill the knowledge gaps that impede diagnosis, in particularly for ultra-rare diseases. Consequently, the UDNI fosters the translation of research into medical practice, aided by active patient involvement. The goals of the UDNI are to work collaboratively and at an international scale to: 1) provide diagnoses for individuals who have conditions that have eluded diagnosis by clinical experts; 2) gain insights into the etiology and pathogenesis of novel diseases; 3) contribute to standards of diagnosing unsolved patients; and 4) share the results of UDNI research in a timely manner and as broadly as possible.

Experimental designs for array comparative genomic hybridization technology.

Array comparative genomic hybridization (aCGH) technology is commonly used to estimate genome-wide copy-number variation and to evaluate associations between copy number and disease. Although aCGH technology is well developed and there are numerous algorithms available for estimating copy number, little attention has been paid to the important issue of the statistical experimental design. Herein, we review classical statistical experimental designs and discuss their relevance to aCGH technology as well as their importance for downstream statistical analyses. Furthermore, we provide experimental design guidance for various study objectives.