Nationwide comprehensive epidemiological study of rare diseases in Japan using a health insurance claims database

Background

There are more than 7000 rare diseases, most of which have no specific treatment. Disease profiles, such as prevalence and natural history, among the population of a specific country are essential in determining for which disease to research and develop drugs. In Japan, disease profiles of fewer than 2000 rare diseases, called Nanbyo, have been investigated. However, non-Nanbyo rare diseases remain largely uninvestigated. Accordingly, we revealed the prevalence and natural history of rare diseases among the Japanese population. This cross-disease study is the first to analyze rare-disease epidemiology in Japan with high accuracy, disease coverage, and granularity.

Method

We applied for permission to use the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), which covered 99.9% of public health insurance claims from hospitals and 97.9% from clinics as of May 2015. Then, we obtained 10 years of data on the number of patients of approx. 4500 rare diseases, by sex and age. We translated disease names and established correspondences between rare diseases in NDB and those in Orphanet. Accordingly, we compared the prevalence and natural history between them.

Results

About 3000 diseases in NDB are included in Orphanet and other medical databases. The data indicates that even if the Nanbyo systems do not cover a rare disease, its patients survive in many cases. Regarding natural history, genetic diseases tend to be diagnosed later in Japan than in the West. The data shown in this research are available in the Additional file 1 and the website of NanbyoData.

Conclusions

Our research revealed the basic epidemiology and natural history of Japanese patients with some rare diseases using a health insurance claims database. The results imply that the coverage of the present Nanbyo systems is inadequate for rare diseases. Therefore, fundamental reform might be needed to reduce unfairness between rare diseases. Most diseases in Japan follow a tendency of natural history similar to those reported in Orphanet. However, some are detected later, partly because fewer clinical genetic tests are available in Japan than in the West. Finally, we hope that our data and analysis accelerate drug discovery for rare diseases in Japan.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02290-0.

Cross-disease analysis of depression, ataxia and dystonia highlights a role for synaptic plasticity and the cerebellum in the pathophysiology of these comorbid diseases

BACKGROUND

There is growing evidence that the neuropsychiatric and neurological disorders depression, ataxia and dystonia share common biological pathways. We therefore aimed to increase our understanding of their shared pathophysiology by investigating their shared biological pathways and molecular networks.

METHODS

We constructed gene sets for depression, ataxia, and dystonia using the Human Phenotype Ontology database and genome-wide association studies, and identified shared genes between the three diseases. We then assessed shared genes in terms of functional enrichment, pathway analysis, molecular connectivity, expression profiles and brain-tissue-specific gene co-expression networks.

RESULTS

The 33 genes shared by depression, ataxia and dystonia are enriched in shared biological pathways and connected through molecular complexes in protein-protein interaction networks. Biological processes common/shared to all three diseases were identified across different brain tissues, highlighting roles for synaptic transmission, synaptic plasticity and nervous system development. The average expression of shared genes was significantly higher in the cerebellum compared to other brain regions, suggesting these genes have distinct cerebellar functions. Several shared genes also showed high expression in the cerebellum during prenatal stages, pointing to a functional role during development.

CONCLUSIONS

The shared pathophysiology of depression, ataxia and dystonia seems to converge onto the cerebellum that maybe particularly vulnerable to changes in synaptic transmission, regulation of synaptic plasticity and nervous system development. Consequently, in addition to regulating motor coordination and motor function, the cerebellum may likely play a role in mood processing.

Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (rg  = 0.23, P = 9.3 × 10-3 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10-3 ) and concordance in effect direction (P = 2.0 × 10-3 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10-5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10-8 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.

Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite

BACKGROUND

MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics.

METHODS AND RESULTS

We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs.

CONCLUSIONS

With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.