Genome-Wide Association Study of Susceptibility to Pseudomonas aeruginosa Infection in Cystic Fibrosis.

QUESTION: Pseudomonas aeruginosa (Pa) is a common pathogen that contributes to progressive lung disease in Cystic Fibrosis (CF). Genetic factors other than CF-causing CFTR variations contribute approximately 85% of the variation in chronic Pa infection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility to Pa infection. MATERIALS AND METHODS: We conducted a genome-wide association study (GWAS) of chronic Pa infection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronic Pa infection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bi-directional Mendelian Randomization analysis. RESULTS: Two novel genome-wide significant loci with lead SNPs rs62369766 (chr5p12; p-value= 1.98 ×10-8) and rs927553 (chr13q12.12; p-value= 1.91 × 10-8) were associated with chronic Pa infection age. The rs62369766 locus was validated using an independent French cohort (N=501). Furthermore, PRS constructed from CF lung function-associated SNPs was significantly associated with chronic Pa infection age (p-value=0.002). Finally, our analysis presented evidence for a causal effect of lung function on the chronic Pa infection age (Beta=0.782 years, p-value= 4.24 × 10-4). In the reverse direction, we observed a moderate effect (Beta=0.002, p-value=0.012). CONCLUSIONS: We identified two novel loci that are associated with chronic Pa infection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship between Pa infection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections which accounts for significant remaining morbidity in CF.

Genetic association and transcriptome integration identify contributing genes and tissues at cystic fibrosis modifier loci.

Cystic Fibrosis (CF) exhibits morbidity in several organs, including progressive lung disease in all patients and intestinal obstruction at birth (meconium ileus) in ~15%. Individuals with the same causal CFTR mutations show variable disease presentation which is partly attributed to modifier genes. With >6,500 participants from the International CF Gene Modifier Consortium, genome-wide association investigation identified a new modifier locus for meconium ileus encompassing ATP12A on chromosome 13 (min p = 3.83x10(-10)); replicated loci encompassing SLC6A14 on chromosome X and SLC26A9 on chromosome 1, (min p<2.2x10(-16), 2.81x10(-11), respectively); and replicated a suggestive locus on chromosome 7 near PRSS1 (min p = 2.55x10(-7)). PRSS1 is exclusively expressed in the exocrine pancreas and was previously associated with non-CF pancreatitis with functional characterization demonstrating impact on PRSS1 gene expression. We thus asked whether the other meconium ileus modifier loci impact gene expression and in which organ. We developed and applied a colocalization framework called the Simple Sum (SS) that integrates regulatory and genetic association information, and also contrasts colocalization evidence across tissues or genes. The associated modifier loci colocalized with expression quantitative trait loci (eQTLs) for ATP12A (p = 3.35x10(-8)), SLC6A14 (p = 1.12x10(-10)) and SLC26A9 (p = 4.48x10(-5)) in the pancreas, even though meconium ileus manifests in the intestine. The meconium ileus susceptibility locus on chromosome X appeared shifted in location from a previously identified locus for CF lung disease severity. Using the SS we integrated the lung disease association locus with eQTLs from nasal epithelia of 63 CF participants and demonstrated evidence of colocalization with airway-specific regulation of SLC6A14 (p = 2.3x10(-4)). Cystic Fibrosis is realizing the promise of personalized medicine, and identification of the contributing organ and understanding of tissue specificity for a gene modifier is essential for the next phase of personalizing therapeutic strategies.

VikNGS: a C++ variant integration kit for next generation sequencing association analysis.

SUMMARY: Integration of next generation sequencing data (NGS) across different research studies can improve the power of genetic association testing by increasing sample size and can obviate the need for sequencing controls. If differential genotype uncertainty across studies is not accounted for, combining datasets can produce spurious association results. We developed the Variant Integration Kit for NGS (VikNGS), a fast cross-platform software package, to enable aggregation of several datasets for rare and common variant genetic association analysis of quantitative and binary traits with covariate adjustment. VikNGS also includes a graphical user interface, power simulation functionality and data visualization tools. AVAILABILITY AND IMPLEMENTATION: The VikNGS package can be downloaded at http://www.tcag.ca/tools/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cystic fibrosis-related diabetes onset can be predicted using biomarkers measured at birth.

PURPOSE: Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis-related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. METHODS: Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. RESULTS: The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. CONCLUSION: We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.

LocusFocus: Web-based colocalization for the annotation and functional follow-up of GWAS.

Genome-wide association studies (GWAS) have primarily identified trait-associated loci in the non-coding genome. Colocalization analyses of SNP associations from GWAS with expression quantitative trait loci (eQTL) evidence enable the generation of hypotheses about responsible mechanism, genes and tissues of origin to guide functional characterization. Here, we present a web-based colocalization browsing and testing tool named LocusFocus (https://locusfocus.research.sickkids.ca). LocusFocus formally tests colocalization using our established Simple Sum method to identify the most relevant genes and tissues for a particular GWAS locus in the presence of high linkage disequilibrium and/or allelic heterogeneity. We demonstrate the utility of LocusFocus, following up on a genome-wide significant locus from a GWAS of meconium ileus (an intestinal obstruction in cystic fibrosis). Using LocusFocus for colocalization analysis with eQTL data suggests variation in ATP12A gene expression in the pancreas rather than intestine is responsible for the GWAS locus. LocusFocus has no operating system dependencies and may be installed in a local web server. LocusFocus is available under the MIT license, with full documentation and source code accessible on GitHub at https://github.com/naim-panjwani/LocusFocus.

Cystic fibrosis gene modifier SLC26A9 modulates airway response to CFTR-directed therapeutics.

Cystic fibrosis is realizing the promise of personalized medicine. Recent advances in drug development that target the causal CFTR directly result in lung function improvement, but variability in response is demanding better prediction of outcomes to improve management decisions. The genetic modifier SLC26A9 contributes to disease severity in the CF pancreas and intestine at birth and here we assess its relationship with disease severity and therapeutic response in the airways. SLC26A9 association with lung disease was assessed in individuals from the Canadian and French CF Gene Modifier consortia with CFTR-gating mutations and in those homozygous for the common Phe508del mutation. Variability in response to a CFTR-directed therapy attributed to SLC26A9 genotype was assessed in Canadian patients with gating mutations. A primary airway model system determined if SLC26A9 shows modification of Phe508del CFTR function upon treatment with a CFTR corrector. In those with gating mutations that retain cell surface-localized CFTR we show that SLC26A9 modifies lung function while this is not the case in individuals homozygous for Phe508del where cell surface expression is lacking. Treatment response to ivacaftor, which aims to improve CFTR-channel opening probability in patients with gating mutations, shows substantial variability in response, 28% of which can be explained by rs7512462 in SLC26A9 (P = 0.0006). When homozygous Phe508del primary bronchial cells are treated to restore surface CFTR, SLC26A9 likewise modifies treatment response (P = 0.02). Our findings indicate that SLC26A9 airway modification requires CFTR at the cell surface, and that a common variant in SLC26A9 may predict response to CFTR-directed therapeutics.

A Joint Location-Scale Test Improves Power to Detect Associated SNPs, Gene Sets, and Pathways.

Gene-based, pathway, and other multivariate association methods are motivated by the possibility of GxG and GxE interactions; however, accounting for such interactions is limited by the challenges associated with adequate modeling information. Here we propose an easy-to-implement joint location-scale (JLS) association testing framework for single-variant and multivariate analysis that accounts for interactions without explicitly modeling them. We apply the JLS method to a gene-set analysis of cystic fibrosis (CF) lung disease, which is influenced by multiple environmental and genetic factors. We identify and replicate an association between the constituents of the apical plasma membrane and CF lung disease (p = 0.0099 and p = 0.0180, respectively) and highlight a role for the SLC9A3-SLC9A3R1/2-EZR complex in contributing to CF lung disease. Many association studies could benefit from re-analysis with the JLS method that leverages complex genetic architecture for SNP, gene, and pathway identification. Analytical verification, simulation, and additional proof-of-principle applications support our approach.

Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic.

MOTIVATION: Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. RESULTS: We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. AVAILABILITY AND IMPLEMENTATION: An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. CONTACT: lisa.strug@utoronto.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Variants in Solute Carrier SLC26A9 Modify Prenatal Exocrine Pancreatic Damage in Cystic Fibrosis.

OBJECTIVES: To test the hypothesis that multiple constituents of the apical plasma membrane residing alongside the causal cystic fibrosis (CF) transmembrane conductance regulator protein, including known CF modifiers SLC26A9, SLC6A14, and SLC9A3, would be associated with prenatal exocrine pancreatic damage as measured by newborn screened (NBS) immunoreactive trypsinogen (IRT) levels. STUDY DESIGN: NBS IRT measures and genome-wide genotype data were available on 111 subjects from Colorado, 37 subjects from Wisconsin, and 80 subjects from France. Multiple linear regression was used to determine whether any of 8 single nucleotide polymorphisms (SNPs) in SLC26A9, SLC6A14, and SLC9A3 were associated with IRT and whether other constituents of the apical plasma membrane contributed to IRT. RESULTS: In the Colorado sample, 3 SLC26A9 SNPs were associated with NBS IRT (min P=1.16×10(-3); rs7512462), but no SLC6A14 or SLC9A3 SNPs were associated (P>.05). The rs7512462 association replicated in the Wisconsin sample (P=.03) but not in the French sample (P=.76). Furthermore, rs7512462 was the top-ranked apical membrane constituent in the combined Colorado and Wisconsin sample. CONCLUSIONS: NBS IRT is a biomarker of prenatal exocrine pancreatic disease in patients with CF, and a SNP in SLC26A9 accounts for significant IRT variability. This work suggests SLC26A9 as a potential therapeutic target to ameliorate exocrine pancreatic disease.

Unraveling the complex genetic model for cystic fibrosis: pleiotropic effects of modifier genes on early cystic fibrosis-related morbidities.

The existence of pleiotropy in disorders with multi-organ involvement can suggest therapeutic targets that could ameliorate overall disease severity. Here we assessed pleiotropy of modifier genes in cystic fibrosis (CF). CF, caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, affects the lungs, liver, pancreas and intestines. However, modifier genes contribute to variable disease severity across affected organs, even in individuals with the same CFTR genotype. We sought to determine whether SLC26A9, SLC9A3 and SLC6A14, that contribute to meconium ileus in CF, are pleiotropic for other early-affecting CF co-morbidities. In the Canadian CF population, we assessed evidence for pleiotropic effects on (1) pediatric lung disease severity (n = 815), (2) age at first acquisition of Pseudomonas aeruginosa (P. aeruginosa) (n = 730), and (3) prenatal pancreatic damage measured by immunoreactive trypsinogen (n = 126). A multiple-phenotype analytic strategy assessed evidence for pleiotropy in the presence of phenotypic correlation. We required the same alleles to be associated with detrimental effects. SLC26A9 was pleiotropic for meconium ileus and pancreatic damage (p = 0.002 at rs7512462), SLC9A3 for meconium ileus and lung disease (p = 1.5 × 10(-6) at rs17563161), and SLC6A14 for meconium ileus and both lung disease and age at first P. aeruginosa infection (p = 0.0002 and p = 0.006 at rs3788766, respectively). The meconium ileus risk alleles in SLC26A9, SLC9A3 and SLC6A14 are pleiotropic, increasing risk for other early CF co-morbidities. Furthermore, co-morbidities affecting the same organ tended to associate with the same genes. The existence of pleiotropy within this single disorder suggests that complementary therapeutic strategies to augment solute transport will benefit multiple CF-associated tissues.

High-quality read-based phasing of cystic fibrosis cohort informs genetic understanding of disease modification.

Phasing of heterozygous alleles is critical for interpretation of cis-effects of disease-relevant variation. We sequenced 477 individuals with cystic fibrosis (CF) using linked-read sequencing, which display an average phase block N50 of 4.39 Mb. We use these samples to construct a graph representation of CFTR haplotypes, demonstrating its utility for understanding complex CF alleles. These are visualized in a Web app, CFTbaRcodes, that enables interactive exploration of CFTR haplotypes present in this cohort. We perform fine-mapping and phasing of the chr7q35 trypsinogen locus associated with CF meconium ileus, an intestinal obstruction at birth associated with more severe CF outcomes and pancreatic disease. A 20-kb deletion polymorphism and a PRSS2 missense variant p.Thr8Ile (rs62473563) are shown to independently contribute to meconium ileus risk (p = 0.0028, p = 0.011, respectively) and are PRSS2 pancreas eQTLs (p = 9.5 × 10-7 and p = 1.4 × 10-4, respectively), suggesting the mechanism by which these polymorphisms contribute to CF. The phase information from linked reads provides a putative causal explanation for variation at a CF-relevant locus, which also has implications for the genetic basis of non-CF pancreatitis, to which this locus has been reported to contribute.

Genetic evidence supports the development of SLC26A9 targeting therapies for the treatment of lung disease.

Over 400 variants in the cystic fibrosis (CF) transmembrane conductance regulator (CFTR) are CF-causing. CFTR modulators target variants to improve lung function, but marked variability in response exists and current therapies do not address all CF-causing variants highlighting unmet needs. Alternative epithelial ion channel/transporters such as SLC26A9 could compensate for CFTR dysfunction, providing therapeutic targets that may benefit all individuals with CF. We investigate the relationship between rs7512462, a marker of SLC26A9 activity, and lung function pre- and post-treatment with CFTR modulators in Canadian and US CF cohorts, in the general population, and in those with chronic obstructive pulmonary disease (COPD). Rs7512462 CC genotype is associated with greater lung function in CF individuals with minimal function variants (for which there are currently no approved therapies; p = 0.008); and for gating (p = 0.033) and p.Phe508del/ p.Phe508del (p = 0.006) genotypes upon treatment with CFTR modulators. In parallel, human nasal epithelia with CC and p.Phe508del/p.Phe508del after Ussing chamber analysis of a combination of approved and experimental modulator treatments show greater CFTR function (p = 0.0022). Beyond CF, rs7512462 is associated with peak expiratory flow in a meta-analysis of the UK Biobank and Spirometa Consortium (p = 2.74 × 10-44) and provides p = 0.0891 in an analysis of COPD case-control status in the UK Biobank defined by spirometry. These findings support SLC26A9 as a therapeutic target to improve lung function for all people with CF and in individuals with other obstructive lung diseases.

From cell population models to tumor control probability: including cell cycle effects.

BACKGROUND: Classical expressions for the tumor control probability (TCP) are based on models for the survival fraction of cancer cells after radiation treatment. We focus on the derivation of expressions for TCP from dynamic cell population models. In particular, we derive a TCP formula for a generalized cell population model that includes the cell cycle by considering a compartment of actively proliferating cells and a compartment of quiescent cells, with the quiescent cells being less sensitive to radiation than the actively proliferating cells. METHODS: We generalize previously derived TCP formulas of Zaider and Minerbo and of Dawson and Hillen to derive a TCP formula from our cell population model. We then use six prostate cancer treatment protocols as a case study to show how our TCP formula works and how the cell cycle affects the tumor treatment. RESULTS: The TCP formulas of Zaider-Minerbo and of Dawson-Hillen are special cases of the TCP formula presented here. The former one represents the case with no quiescent cells while the latter one assumes that all newly born cells enter a quiescent cell phase before becoming active. From our case study, we observe that inclusion of the cell cycle lowers the TCP. CONCLUSION: The cell cycle can be understood as the sequestration of cells in the quiescent compartment, where they are less sensitive to radiation. We suggest that our model can be used in combination with synchronization methods to optimize treatment timing.

Improving imputation in disease-relevant regions: lessons from cystic fibrosis.

Does genotype imputation with public reference panels identify variants contributing to disease? Genotype imputation using the 1000 Genomes Project (1KG; 2504 individuals) displayed poor coverage at the causal cystic fibrosis (CF) transmembrane conductance regulator (CFTR) locus for the International CF Gene Modifier Consortium. Imputation with the larger Haplotype Reference Consortium (HRC; 32,470 individuals) displayed improved coverage but low sensitivity of variants clinically relevant for CF. A hybrid reference that combined whole genome sequencing (WGS) from 101 CF individuals with the 1KG imputed a greater number of single-nucleotide variants (SNVs) that would be analyzed in a genetic association study (r2 ≥ 0.3 and MAF ≥ 0.5%) than imputation with the HRC, while the HRC excelled in the lower frequency spectrum. Using the 1KG or HRC as reference panels missed the most common CF-causing variants or displayed low imputation accuracy. Designs that incorporate population-specific WGS can improve imputation accuracy at disease-specific loci, while imputation using public data sets can omit disease-relevant genotypes.

A stochastic model for the normal tissue complication probability (NTCP) and applicationss.

The normal tissue complication probability (NTCP) is a measure for the estimated side effects of a given radiation treatment schedule. Here we use a stochastic logistic birth-death process to define an organ-specific and patient-specific NTCP. We emphasize an asymptotic simplification which relates the NTCP to the solution of a logistic differential equation. This framework is based on simple modelling assumptions and it prepares a framework for the use of the NTCP model in clinical practice. As example, we consider side effects of prostate cancer brachytherapy such as increase in urinal frequency, urinal retention and acute rectal dysfunction.

Genome-wide association meta-analysis identifies five modifier loci of lung disease severity in cystic fibrosis.

The identification of small molecules that target specific CFTR variants has ushered in a new era of treatment for cystic fibrosis (CF), yet optimal, individualized treatment of CF will require identification and targeting of disease modifiers. Here we use genome-wide association analysis to identify genetic modifiers of CF lung disease, the primary cause of mortality. Meta-analysis of 6,365 CF patients identifies five loci that display significant association with variation in lung disease. Regions on chr3q29 (MUC4/MUC20; P=3.3 × 10(-11)), chr5p15.3 (SLC9A3; P=6.8 × 10(-12)), chr6p21.3 (HLA Class II; P=1.2 × 10(-8)) and chrXq22-q23 (AGTR2/SLC6A14; P=1.8 × 10(-9)) contain genes of high biological relevance to CF pathophysiology. The fifth locus, on chr11p12-p13 (EHF/APIP; P=1.9 × 10(-10)), was previously shown to be associated with lung disease. These results provide new insights into potential targets for modulating lung disease severity in CF.

Evidence for a causal relationship between early exocrine pancreatic disease and cystic fibrosis-related diabetes: a Mendelian randomization study.

Circulating immunoreactive trypsinogen (IRT), a biomarker of exocrine pancreatic disease in cystic fibrosis (CF), is elevated in most CF newborns. In those with severe CF transmembrane conductance regulator (CFTR) genotypes, IRT declines rapidly in the first years of life, reflecting progressive pancreatic damage. Consistent with this progression, a less elevated newborn IRT measure would reflect more severe pancreatic disease, including compromised islet compartments, and potentially increased risk of CF-related diabetes (CFRD). We show in two independent CF populations that a lower newborn IRT estimate is associated with higher CFRD risk among individuals with severe CFTR genotypes, and we provide evidence to support a causal relationship. Increased loge(IRT) at birth was associated with decreased CFRD risk in Canadian and Colorado samples (hazard ratio 0.30 [95% CI 0.15-0.61] and 0.39 [0.18-0.81], respectively). Using Mendelian randomization with the SLC26A9 rs7512462 genotype as an instrumental variable since it is known to be associated with IRT birth levels in the CF population, we provide evidence to support a causal contribution of exocrine pancreatic status on CFRD risk. Our findings suggest CFRD risk could be predicted in early life and that maintained ductal fluid flow in the exocrine pancreas could delay the onset of CFRD.

Are more complicated tumour control probability models better?

Mathematical models for the tumour control probability (TCP) are used to estimate the expected success of radiation treatment protocols of cancer. There are several TCP models in the literature, from the simplest (Poissonian TCP) to the well-advanced stochastic birth-death processes. Simple and complex models often make the same predictions. Hence, here, we present a systematic study where we compare six of these TCP models: the Poisson TCP, the Zaider-Minerbo TCP, a Monte Carlo TCP and their corresponding cell cycle (two-compartment) models. Several clinical non-uniform treatment protocols for prostate cancer are employed to evaluate these models. These include fractionated external beam radiotherapies, and high and low dose rate brachytherapies. We find that in realistic treatment scenarios, all one-compartment models and all two-compartment models give basically the same results. A difference occurs between one-compartment and two-compartment models due to reduced radiosensitivity of quiescent cells.We find that care must be taken for the right choice of parameters, such as the radiosensitivities α and ß and the hazard function h. Typically, different hazard functions are used for fractionated treatment (fractionated survival fraction) and for brachytherapies (Lea-Catcheside protraction factor). We were able to combine these two approaches into one 'effective' hazard function. Based on our results, we can recommend the use of the Poissonian TCP for everyday treatment planning. More complicated models should only be used when absolutely necessary.