posted on 2022-08-10, 06:34authored byMatthew T. Patrick, Redina Bardhi, Wei Zhou, James T. Elder, Johann E. Gudjonsson, Lam C. Tsoi
Additional file 2: Figure S1: Rare disease mapping and frequency of rare disease categories. Figure S2: Hexagon/scatter plot showing the mean age at recruitment and proportion of males for the diseases in each category. Figure S3: Sex of individuals with different groups of rare disease, grouped by age. Figure S4: Box/scatter plot of comorbidities for rare diseases, grouped by age. Figure S5: Heatmap showing the enrichment of comorbidities for individuals with specific groups of rare diseases compared to the full set of individuals with any rare disease. The colors represent odds ratios (OR) from Fisher exact tests, while asterisks indicate enrichments with significant p-values (after Bonferroni correction). Figure S6: Heatmap comparing the enrichment of comorbidities for individuals with specific groups of rare diseases with those from a previous study on comorbidities for individuals with common diseases1. The colors represent differences in odds ratios (OR) from Fisher exact tests. Figure S7: Heatmap showing the enrichment of complex disease comorbidities for individuals with 15 specific rare diseases included in the list of Mendelian diseases from a previous paper2. The colors represent log10 odds ratios (OR) from Fisher exact tests, while asterisks indicate enrichments with significant p-values (after Bonferroni correction). Figure S8: Histogram showing the number of ICD-10 codes mapping to different numbers of ORPHA codes in the original Orphanet mapping (in grey) as well as the number of these codes for which we were able to identify a single ORPHA code, such that individuals with the ICD-10 code should be expected to have the rare disease indicated by the ORPHA code. Some ICD-10 codes originally mapped to a large number of ORPHA codes, but across each of the bins, we were able to identify an appropriate single ORPHA code for a large proportion of ICD-10 codes, through our consensus mapping approach. Table S3: Comparing prevalence of in the UK Biobank and Optum. Table S6: Significant gene-level associations (Bonferroni adjustment). Table S9: Significant associations with loss of function variants (Bonferroni adjustment). Table S10: Shared variants between significantly comorbid rare diseases. Supplementary Note: Improvement in mapping through our consensus approach.
Funding
Rare Disease Foundation Foundation for the National Institutes of Health A. Alfred Taubman Medical Research Institute Dawn and Dudley Holmes Foundation Babcock Memorial Trust Precision Health Scholars Award Dermatology Foundation