Background: Cystic fibrosis (CF) heterozygotes with a single mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene are at significantly higher risk to develop chronic rhinosinusitis (CRS). However the reasons why remain unknown. We tested the hypothesis that CFTR heterozygotes would have smaller sinus volumes than healthy controls. To exclude sinus disease as a confounding factor we also assessed paranasal sinus volume in those with CRS, but without known CFTR mutations. Methods:A total of 131 adults of white Northern European and Latino origin were recruited: 81 diagnosed with CRS and 50 healthy controls. Subjects were genotyped for 9 common CFTR mutations covering >80% of mutation prevalence. Those with CRS were separated by CFTR mutational status and matched demographically to healthy controls. Three-dimensional sinus volume, mucosal opacification, and skull volume were quantified to obtain the percentage of pneumatization and extent of mucosal disease in each sinus. Twenty-item Sino-Nasal Outcome Test (SNOT-20) and endoscopy scores were also analyzed. Results:In individuals diagnosed with CRS we identified 7 CFTR heterozygotes (8.64%); no CFTR mutations were identified in our healthy controls. There were no significant differences between the 3 matched groups other than sinus pneumatization. The frontal and maxillary sinuses were significantly smaller in CFTR heterozygotes with CRS compared to CFTR wild-type subjects with or without disease.Conclusion: CFTR heterozygotes with CRS have significantly smaller frontal and maxillary sinus size compared to those without mutations, irrespective of disease state. This sinus hypoplasia may contribute to impaired mucus clearance and chronic sinus disease development. C 2016 ARS-AAOA, LLC. EH. Paranasal sinus size is decreased in CFTR heterozygotes with chronic rhinosinusitis. Int Forum Allergy Rhinol. 2017;7:256-260. C hronic rhinosinusitis (CRS) is a common heterogeneous condition affecting approximately 12% to 15%

BackgroundForty-two percent of patients experience disease comorbidity, contributing substantially to mortality rates and increased healthcare costs. Yet, the possibility of underlying shared mechanisms for diseases remains not well established, and few studies have confirmed their molecular predictions with clinical datasets.MethodsIn this work, we integrated genome-wide association study (GWAS) associating diseases and single nucleotide polymorphisms (SNPs) with transcript regulatory activity from expression quantitative trait loci (eQTL). This allowed novel mechanistic insights for noncoding and intergenic regions. We then analyzed pairs of SNPs across diseases to identify shared molecular effectors robust to multiple test correction (False Discovery Rate FDReRNA < 0.05). We hypothesized that disease pairs found to be molecularly convergent would also be significantly overrepresented among comorbidities in clinical datasets. To assess our hypothesis, we used clinical claims datasets from the Healthcare Cost and Utilization Project (HCUP) and calculated significant disease comorbidities (FDRcomorbidity < 0.05). We finally verified if disease pairs resulting molecularly convergent were also statistically comorbid more than by chance using the Fisher’s Exact Test.ResultsOur approach integrates: (i) 6175 SNPs associated with 238 diseases from ~ 1000 GWAS, (ii) eQTL associations from 19 tissues, and (iii) claims data for 35 million patients from HCUP. Logistic regression (controlled for age, gender, and race) identified comorbidities in HCUP, while enrichment analyses identified cis- and trans-eQTL downstream effectors of GWAS-identified variants. Among ~ 16,000 combinations of diseases, 398 disease-pairs were prioritized by both convergent eQTL-genetics (RNA overlap enrichment, FDReRNA < 0.05) and clinical comorbidities (OR > 1.5, FDRcomorbidity < 0.05). Case studies of comorbidities illustrate specific convergent noncoding regulatory elements. An intergenic architecture of disease comorbidity was unveiled due to GWAS and eQTL-derived convergent mechanisms between distinct diseases being overrepresented among observed comorbidities in clinical datasets (OR = 8.6, p-value = 6.4 × 10− 5 FET).ConclusionsThese comorbid diseases with convergent eQTL genetic mechanisms suggest clinical syndromes. While it took over a decade to confirm the genetic underpinning of the metabolic syndrome, this study is likely highlighting hundreds of new ones. Further, this knowledge may improve the clinical management of comorbidities with precision and shed light on novel approaches of drug repositioning or SNP-guided precision molecular therapy inclusive of intergenic risks.Electronic supplementary materialThe online version of this article (10.1186/s12920-018-0428-9) contains supplementary material, which is available to authorized users.

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