Accurate assignment of disease liability to genetic variants using only population data.

PURPOSE: The growing size of public variant repositories prompted us to test the accuracy of pathogenicity prediction of DNA variants using population data alone. METHODS: Under the a priori assumption that the ratio of the prevalence of variants in healthy population vs that in affected populations form 2 distinct distributions (pathogenic and benign), we used a Bayesian method to assign probability to a variant belonging to either distribution. RESULTS: The approach, termed Bayesian prevalence ratio (BayPR), accurately parsed 300 of 313 expertly curated CFTR variants: 284 of 296 pathogenic/likely pathogenic variants in 1 distribution and 16 of 17 benign/likely benign variants in another. BayPR produced an area under the receiver operating characteristic curve of 0.99 for 103 functionally confirmed missense CFTR variants, which is equal to or exceeds 10 commonly used algorithms (area under the receiver operating characteristic curve range = 0.54-0.99). Application of BayPR to expertly curated variants in 8 genes associated with 7 Mendelian conditions led to the assignment of a disease-causing probability of ≥80% to 1350 of 1374 (98.3%) pathogenic/likely pathogenic variants and of ≤20% to 22 of 23 (95.7%) benign/likely benign variants. CONCLUSION: Irrespective of the variant type or functional effect, the BayPR approach provides probabilities of pathogenicity for DNA variants responsible for Mendelian disorders using only the variant counts in affected and unaffected population samples.

Integrated Transcriptomic and Proteomic Analysis of Human Eccrine Sweat Glands Identifies Missing and Novel Proteins.

The eccrine sweat gland is an exocrine gland that is involved in the secretion of sweat for control of temperature. Malfunction of the sweat glands can result in disorders such as miliaria, hyperhidrosis and bromhidrosis. Understanding the transcriptome and proteome of sweat glands is important for understanding their physiology and role in diseases. However, no systematic transcriptome or proteome analysis of sweat glands has yet been reported. Here, we isolated eccrine sweat glands from human skin by microdissection and performed RNA-seq and proteome analysis. In total, ∼138,000 transcripts and ∼6,100 proteins were identified. Comparison of the RNA-seq data of eccrine sweat glands to other human tissues revealed the closest resemblance to the cortex region of kidneys. The proteome data showed enrichment of proteins involved in secretion, reabsorption, and wound healing. Importantly, protein level identification of the calcium ion channel TRPV4 suggests the importance of eccrine sweat glands in re-epithelialization of wounds and prevention of dehydration. We also identified 2 previously missing proteins from our analysis. Using a proteogenomic approach, we identified 7 peptides from 5 novel genes, which we validated using synthetic peptides. Most of the novel proteins were from short open reading frames (sORFs) suggesting that many sORFs still remain to be annotated in the human genome. This study presents the first integrated analysis of the transcriptome and proteome of the human eccrine sweat gland and would become a valuable resource for studying sweat glands in physiology and disease.

The influence of HLA genetic variation on plasma protein expression.

Genetic variation in the human leukocyte antigen (HLA) loci is associated with risk of immune-mediated diseases, but the molecular effects of HLA polymorphism are unclear. Here we examined the effects of HLA genetic variation on the expression of 2940 plasma proteins across 45,330 Europeans in the UK Biobank, with replication analyses across multiple ancestry groups. We detected 504 proteins affected by HLA variants (HLA-pQTL), including widespread trans effects by autoimmune disease risk alleles. More than 80% of the HLA-pQTL fine-mapped to amino acid positions in the peptide binding groove. HLA-I and II affected proteins expressed in similar cell types but in different pathways of both adaptive and innate immunity. Finally, we investigated potential HLA-pQTL effects on disease by integrating HLA-pQTL with fine-mapped HLA-disease signals in the UK Biobank. Our data reveal the diverse effects of HLA genetic variation and aid the interpretation of associations between HLA alleles and immune-mediated diseases.

SLC26A9 SNP rs7512462 is not associated with lung disease severity or lung function response to ivacaftor in cystic fibrosis patients with G551D-CFTR.

BACKGROUND: The CFTR modulator ivacaftor has been variably effective in treating individuals with cystic fibrosis (CF) who harbor CFTR gating variants such as G551D, as well as other classes of CFTR variants when used with other modulators. Because CFTR genotype does not fully explain this variability, defining genetic modifiers of response to modulator therapy is of particular interest to the field of individualized CF drug therapy. Previous studies have proposed that a variant in SLC26A9 (rs7512462) is associated with lung disease severity and with response to treatment with ivacaftor in individuals with CF who carry G551D or gating variants. METHODS: Given the implications for CF treatment, we re-examined the reported associations in three cohorts; patients enrolled in the Twin and Siblings study at Johns Hopkins University, the CF modifier study at the University of North Carolina at Chapel Hill, and the prospective G551D Observational (GOAL) study. The GOAL study was specifically designed to measure lung function response to ivacaftor. RESULTS: We find no association between SLC26A9 (rs7512462) genotype and lung disease severity (n = 272) or change in lung function at one-, three-, and six-month intervals following ivacaftor treatment(n = 141) in individuals with CF who carry at least one G551D variant. CONCLUSIONS: Our inability to replicate this association indicates that rs7512462 genotype should not be used in treatment decisions.