How to design a registry for undiagnosed patients in the framework of rare disease diagnosis: suggestions on software, data set and coding system

BACKGROUND

About 30 million people in the EU and USA, respectively, suffer from a rare disease. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases are being developed. To improve timely and correct diagnosis for patients with rare diseases, the development of a registry for undiagnosed patients was recommended by the German National Action Plan. In this paper we focus on the question on how such a registry for undiagnosed patients can be built and which information it should contain.

RESULTS

To develop a registry for undiagnosed patients, a software for data acquisition and storage, an appropriate data set and an applicable terminology/classification system for the data collected are needed. We have used the open-source software Open-Source Registry System for Rare Diseases (OSSE) to build the registry for undiagnosed patients. Our data set is based on the minimal data set for rare disease patient registries recommended by the European Rare Disease Registries Platform. We extended this Common Data Set to also include symptoms, clinical findings and other diagnoses. In order to ensure findability, comparability and statistical analysis, symptoms, clinical findings and diagnoses have to be encoded. We evaluated three medical ontologies (SNOMED CT, HPO and LOINC) for their usefulness. With exact matches of 98% of tested medical terms, a mean number of five deposited synonyms, SNOMED CT seemed to fit our needs best. HPO and LOINC provided 73% and 31% of exacts matches of clinical terms respectively. Allowing more generic codes for a defined symptom, with SNOMED CT 99%, with HPO 89% and with LOINC 39% of terms could be encoded.

CONCLUSIONS

With the use of the OSSE software and a data set, which, in addition to the Common Data Set, focuses on symptoms and clinical findings, a functioning and meaningful registry for undiagnosed patients can be implemented. The next step is the implementation of the registry in centres for rare diseases. With the help of medical informatics and big data analysis, case similarity analyses could be realized and aid as a decision-support tool enabling diagnosis of some undiagnosed patients.

Familial thrombocytopenia due to a complex structural variant resulting in a WAC-ANKRD26 fusion transcript

Advances in genome sequencing have resulted in the identification of the causes for numerous rare diseases. However, many cases remain unsolved with standard molecular analyses. We describe a family presenting with a phenotype resembling inherited thrombocytopenia 2 (THC2). THC2 is generally caused by single nucleotide variants that prevent silencing of ANKRD26 expression during hematopoietic differentiation. Short-read whole-exome and genome sequencing approaches were unable to identify a causal variant in this family. Using long-read whole-genome sequencing, a large complex structural variant involving a paired-duplication inversion was identified. Through functional studies, we show that this structural variant results in a pathogenic gain-of-function WAC-ANKRD26 fusion transcript. Our findings illustrate how complex structural variants that may be missed by conventional genome sequencing approaches can cause human disease.

Diagnostic Yield of Whole Genome Sequencing After Nondiagnostic Exome Sequencing or Gene Panel in Developmental and Epileptic Encephalopathies

OBJECTIVE

To assess the benefits and limitations of whole genome sequencing (WGS) compared to exome sequencing (ES) or multigene panel (MGP) in the molecular diagnosis of developmental and epileptic encephalopathies (DEE).

METHODS

We performed WGS of 30 comprehensively phenotyped DEE patient trios that were undiagnosed after first-tier testing, including chromosomal microarray and either research ES (n = 15) or diagnostic MGP (n = 15).

RESULTS

Eight diagnoses were made in the 15 individuals who received prior ES (53%): 3 individuals had complex structural variants; 5 had ES-detectable variants, which now had additional evidence for pathogenicity. Eleven diagnoses were made in the 15 MGP-negative individuals (68%); the majority (n = 10) involved genes not included in the panel, particularly in individuals with postneonatal onset of seizures and those with more complex presentations including movement disorders, dysmorphic features, or multiorgan involvement. A total of 42% of diagnoses were autosomal recessive or X-chromosome linked.

CONCLUSION

WGS was able to improve diagnostic yield over ES primarily through the detection of complex structural variants (n = 3). The higher diagnostic yield was otherwise better attributed to the power of re-analysis rather than inherent advantages of the WGS platform. Additional research is required to assist in the assessment of pathogenicity of novel noncoding and complex structural variants and further improve diagnostic yield for patients with DEE and other neurogenetic disorders.

Association between HindIII (rs320) variant in the lipoprotein lipase gene and the presence of coronary artery disease and stroke among the Saudi population

Lipoprotein Lipase (LPL) is known to be a key enzyme for lipid metabolism specifically in an enzymatic glycoprotein which provide tissues without fatty-acids and eliminates triglycerides (TG) by the circulation. Mutations in LPL were proven to cause alteration in fractions within lipoprotein, causing the development of atherosclerosis which predispose to weakening coronary artery disease (CAD) and stroke. We examined the linkage between genetic variant HindIII in LPL on lipoprotein fractions, stroke occurrences and CAD. In this case-control study, we have recruited 315 CAD cases and 205 age-matched controls. A total of 520 genomic DNA was digested with the purified PCR products for restriction fragment length polymorphism with HindIII restriction enzyme. The distribution of genotypes in a decreasing order were TT, 148 (47%), GT 135 (42.9%) and GG 32 (10.2%) in CAD groups of the study while the pattern in controls were GT 91 (44.4%), TT 86 (42%) and GG 28 (13.7%). None of all the allele or genotype frequencies were found to be significant in our study (p greater than 0.05), while the biochemical levels for both TG and LDL-c were shown to be prone in CAD patients when compare with the controls. Furthermore, the occurence of strokes were more in CAD groups vs. controls: 72 (22.9%) vs. 7 (3.4%) [p 0.000]. This could indicate the influence of HindIII variant on plasma lipid levels, and the possibility of considering it a risk factor for atherosclerosis leading to CAD and stroke occurrence.