Inflammation and Gut Barrier Function-Related Genes and Colorectal Cancer Risk in Western European Populations.

Gut barrier dysfunction and related inflammation are known to be associated with the development and progression of colorectal cancer (CRC). We investigated associations of 292 single-nucleotide polymorphisms (SNPs) from 27 genes related to endotoxins/lipopolysaccharide (LPS) sensing and tolerance, mucin synthesis, inflammation, and Crohn's disease with colon and rectal cancer risks. Incident CRC cases (N=1,374; colon=871, rectum=503) were matched 1:1 to controls nested within the European Prospective Investigation into Cancer and Nutrition cohort. Previously measured serum concentrations of gut barrier function and inflammation biomarkers (flagellin/LPS-specific immunoglobulins and C-reactive protein [CRP]) were available for a sub-set of participants (Ncases=1,001; Ncontrols=667). Forty-two unique SNPs from 19 different genes were associated with serum biomarkers at Punadjusted≤0.05 among controls. Among SNPs associated with a gut permeability score, 24 SNPs were in genes related to LPS sensing and mucin synthesis. Nine out of 12 SNPs associated with CRP were in genes related to inflammation or Crohn's disease. TLR4 was associated with colon cancer at the SNP level (nine SNPs, all Punadjusted≤0.04) and at the gene level (Punadjusted≤0.01). TLR4 rs10759934 was associated with rectal cancer but not colon cancer. Similarly, IL10 was associated with rectal cancer risk at a SNP and gene level (both Punadjusted ≤ 0.01), but not colon cancer. Genes and SNPs were selected a priori therefore we present unadjusted P-values. However, no association was statistically significant after multiple testing correction. This large and comprehensive study has identified gut barrier function and inflammation-related genes possibly contributing to CRC risk in European populations and is consistent with potential etiological links between host genetic background, gut barrier permeability, microbial endotoxemia and CRC development.

Investigation of common genetic risk factors between thyroid traits and breast cancer.

Breast cancer (BC) risk is suspected to be linked to thyroid disorders, however observational studies exploring the association between BC and thyroid disorders gave conflicting results. We proposed an alternative approach by investigating the shared genetic risk factors between BC and several thyroid traits. We report a positive genetic correlation between BC and thyroxine (FT4) levels (corr = 0.13, p-value = 2.0 × 10-4) and a negative genetic correlation between BC and thyroid-stimulating hormone (TSH) levels (corr = -0.09, p-value = 0.03). These associations are more striking when restricting the analysis to estrogen receptor-positive BC. Moreover, the polygenic risk scores (PRS) for FT4 and hyperthyroidism are positively associated to BC risk (OR = 1.07, 95%CI: 1.00-1.13, p-value = 2.8 × 10-2 and OR = 1.04, 95%CI: 1.00-1.08, p-value = 3.8 × 10-2, respectively), while the PRS for TSH is inversely associated to BC risk (OR = 0.93, 95%CI: 0.89-0.97, p-value = 2.0 × 10-3). Using the PLACO method, we detected 49 loci associated to both BC and thyroid traits (p-value < 5 × 10-8), in the vicinity of 130 genes. An additional colocalization and gene-set enrichment analyses showed a convincing causal role for a known pleiotropic locus at 2q35 and revealed an additional one at 8q22.1 associated to both BC and thyroid cancer. We also found two new pleiotropic loci at 14q32.33 and 17q21.31 that were associated to both TSH levels and BC risk. Enrichment analyses and evidence of regulatory signals also highlighted brain tissues and immune system as candidates for obtaining associations between BC and TSH levels. Overall, our study sheds light on the complex interplay between BC and thyroid traits and provides evidence of shared genetic risk between those conditions.

GCPBayes pipeline: a tool for exploring pleiotropy at the gene level.

Cross-phenotype association using gene-set analysis can help to detect pleiotropic genes and inform about common mechanisms between diseases. Although there are an increasing number of statistical methods for exploring pleiotropy, there is a lack of proper pipelines to apply gene-set analysis in this context and using genome-scale data in a reasonable running time. We designed a user-friendly pipeline to perform cross-phenotype gene-set analysis between two traits using GCPBayes, a method developed by our team. All analyses could be performed automatically by calling for different scripts in a simple way (using a Shiny app, Bash or R script). A Shiny application was also developed to create different plots to visualize outputs from GCPBayes. Finally, a comprehensive and step-by-step tutorial on how to use the pipeline is provided in our group's GitHub page. We illustrated the application on publicly available GWAS (genome-wide association studies) summary statistics data to identify breast cancer and ovarian cancer susceptibility genes. We have shown that the GCPBayes pipeline could extract pleiotropic genes previously mentioned in the literature, while it also provided new pleiotropic genes and regions that are worthwhile for further investigation. We have also provided some recommendations about parameter selection for decreasing computational time of GCPBayes on genome-scale data.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers.

BACKGROUND: Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. OBJECTIVE: We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. METHODS: We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. RESULTS: We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). CONCLUSIONS: We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Genome-wide Association and Meta-analysis of Age at Onset in Parkinson Disease: Evidence From the COURAGE-PD Consortium.

BACKGROUND AND OBJECTIVES: Considerable heterogeneity exists in the literature concerning genetic determinants of the age at onset (AAO) of Parkinson disease (PD), which could be attributed to a lack of well-powered replication cohorts. The previous largest genome-wide association studies (GWAS) identified SNCA and TMEM175 loci on chromosome (Chr) 4 with a significant influence on the AAO of PD; these have not been independently replicated. This study aims to conduct a meta-analysis of GWAS of PD AAO and validate previously observed findings in worldwide populations. METHODS: A meta-analysis was performed on PD AAO GWAS of 30 populations of predominantly European ancestry from the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease (COURAGE-PD) Consortium. This was followed by combining our study with the largest publicly available European ancestry dataset compiled by the International Parkinson Disease Genomics Consortium (IPDGC). RESULTS: The COURAGE-PD Consortium included a cohort of 8,535 patients with PD (91.9%: Europeans and 9.1%: East Asians). The average AAO in the COURAGE-PD dataset was 58.9 years (SD = 11.6), with an underrepresentation of females (40.2%). The heritability estimate for AAO in COURAGE-PD was 0.083 (SE = 0.057). None of the loci reached genome-wide significance (p < 5 × 10-8). Nevertheless, the COURAGE-PD dataset confirmed the role of the previously published TMEM175 variant as a genetic determinant of the AAO of PD with Bonferroni-corrected nominal levels of significance (p < 0.025): (rs34311866: ß(SE)COURAGE = 0.477(0.203), p COURAGE = 0.0185). The subsequent meta-analysis of COURAGE-PD and IPDGC datasets (Ntotal = 25,950) led to the identification of 2 genome-wide significant association signals on Chr 4, including the previously reported SNCA locus (rs983361: ß(SE)COURAGE+IPDGC = 0.720(0.122), p COURAGE+IPDGC = 3.13 × 10-9) and a novel BST1 locus (rs4698412: ß(SE)COURAGE+IPDGC = -0.526(0.096), p COURAGE+IPDGC = 4.41 × 10-8). DISCUSSION: Our study further refines the genetic architecture of Chr 4 underlying the AAO of the PD phenotype through the identification of BST1 as a novel AAO PD locus. These findings open a new direction for the development of treatments to delay the onset of PD.

The Interaction between HLA-DRB1 and Smoking in Parkinson's Disease Revisited.

BACKGROUND: Two studies that examined the interaction between HLA-DRB1 and smoking in Parkinson's disease (PD) yielded findings in opposite directions. OBJECTIVE: To perform a large-scale independent replication of the HLA-DRB1 × smoking interaction. METHODS: We genotyped 182 single nucleotide polymorphism (SNPs) associated with smoking initiation in 12 424 cases and 9480 controls to perform a Mendelian randomization (MR) analysis in strata defined by HLA-DRB1. RESULTS: At the amino acid level, a valine at position 11 (V11) in HLA-DRB1 displayed the strongest association with PD. MR showed an inverse association between genetically predicted smoking initiation and PD only in absence of V11 (odds ratio, 0.74, 95% confidence interval, 0.59-0.93, PInteraction  = 0.028). In silico predictions of the influence of V11 and smoking-induced modifications of α-synuclein on binding affinity showed findings consistent with this interaction pattern. CONCLUSIONS: Despite being one of the most robust findings in PD research, the mechanisms underlying the inverse association between smoking and PD remain unknown. Our findings may help better understand this association. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study.

BACKGROUND: Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding. OBJECTIVE: The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR). METHODS: We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry). RESULTS: Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95% confidence interval = 1.12-2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37-4.56], P = 0.003; P-difference with women = 0.029). CONCLUSIONS: Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society.

Leveraging pleiotropic association using sparse group variable selection in genomics data.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants associated with multiple complex diseases. We can leverage this phenomenon, known as pleiotropy, to integrate multiple data sources in a joint analysis. Often integrating additional information such as gene pathway knowledge can improve statistical efficiency and biological interpretation. In this article, we propose statistical methods which incorporate both gene pathway and pleiotropy knowledge to increase statistical power and identify important risk variants affecting multiple traits. METHODS: We propose novel feature selection methods for the group variable selection in multi-task regression problem. We develop penalised likelihood methods exploiting different penalties to induce structured sparsity at a gene (or pathway) and SNP level across all studies. We implement an alternating direction method of multipliers (ADMM) algorithm for our penalised regression methods. The performance of our approaches are compared to a subset based meta analysis approach on simulated data sets. A bootstrap sampling strategy is provided to explore the stability of the penalised methods. RESULTS: Our methods are applied to identify potential pleiotropy in an application considering the joint analysis of thyroid and breast cancers. The methods were able to detect eleven potential pleiotropic SNPs and six pathways. A simulation study found that our method was able to detect more true signals than a popular competing method while retaining a similar false discovery rate. CONCLUSION: We developed feature selection methods for jointly analysing multiple logistic regression tasks where prior grouping knowledge is available. Our method performed well on both simulation studies and when applied to a real data analysis of multiple cancers.

Mendelian Randomisation Study of Smoking, Alcohol, and Coffee Drinking in Relation to Parkinson's Disease.

BACKGROUND: Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson's disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. OBJECTIVE: To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. METHODS: We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). RESULTS: We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60-0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. CONCLUSION: Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

Gene network and biological pathways associated with susceptibility to differentiated thyroid carcinoma.

Variants identified in earlier genome-wide association studies (GWAS) on differentiated thyroid carcinoma (DTC) explain about 10% of the overall estimated genetic contribution and could not provide complete insights into biological mechanisms involved in DTC susceptibility. Integrating systems biology information from model organisms, genome-wide expression data from tumor and matched normal tissue and GWAS data could help identifying DTC-associated genes, and pathways or functional networks in which they are involved. We performed data mining of GWAS data of the EPITHYR consortium (1551 cases and 1957 controls) using various pathways and protein-protein interaction (PPI) annotation databases and gene expression data from The Cancer Genome Atlas. We identified eight DTC-associated genes at known loci 2q35 (DIRC3), 8p12 (NRG1), 9q22 (FOXE1, TRMO, HEMGN, ANP32B, NANS) and 14q13 (MBIP). Using the EW_dmGWAS approach we found that gene networks related to glycogenolysis, glycogen metabolism, insulin metabolism and signal transduction pathways associated with muscle contraction were overrepresented with association signals (false discovery rate adjusted p-value < 0.05). Additionally, suggestive association of 21 KEGG and 75 REACTOME pathways with DTC indicate a link between DTC susceptibility and functions related to metabolism of cholesterol, amino sugar and nucleotide sugar metabolism, steroid biosynthesis, and downregulation of ERBB2 signaling pathways. Together, our results provide novel insights into biological mechanisms contributing to DTC risk.

Replication of a Novel Parkinson's Locus in a European Ancestry Population.

BACKGROUND: A recently published East Asian genome-wide association study of Parkinson;s disease (PD) reported 2 novel risk loci, SV2C and WBSCR17. OBJECTIVES: The objective of this study were to determine whether recently reported novel SV2C and WBSCR17 loci contribute to the risk of developing PD in European and East Asian ancestry populations. METHODS: We report an association analysis of recently reported variants with PD in the COURAGE-PD cohort (9673 PD patients; 8465 controls) comprising individuals of European and East Asian ancestries. In addition, publicly available summary data (41,386 PD patients; 476,428 controls) were pooled. RESULTS: Our findings confirmed the role of the SV2C variant in PD pathogenesis (rs246814, COURAGE-PD PEuropean  = 6.64 × 10-4 , pooled PD P = 1.15 × 10-11 ). The WBSCR17 rs9638616 was observed as a significant risk marker in the East Asian pooled population only (P = 1.16 × 10-8 ). CONCLUSIONS: Our comprehensive study provides an up-to-date summary of recently detected novel loci in different PD populations and confirmed the role of SV2C locus as a novel risk factor for PD irrespective of the population or ethnic group analyzed. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fine-mapping of two differentiated thyroid carcinoma susceptibility loci at 2q35 and 8p12 in Europeans, Melanesians and Polynesians.

Differentiated thyroid carcinoma (DTC) incidence is characterized by wide ethnic and geographic variations, with high incidence rates observed in Oceanian populations. Genome-wide association studies (GWAS) identified mainly four DTC susceptibility loci at 9q22.33, 14q13.3, 2q35 and 8p12. Here we performed fine-mapping of the 2q35 and 8p12 loci in the population of the EPITHYR consortium that includes Europeans, Melanesians and Polynesians to identify likely causal variants for DTC risk. We conducted a colocalization analysis using eQTLs data to determine the SNPs with the highest probability of causality. At 2q35, we highlighted rs16857609 located in DIRC3. This SNP has a high probability of causality in the three populations, and a significant association in Europeans (OR = 1.4, p = 1.9 x 10-10). It is also associated with expression of DIRC3 and of the nearby gene IGFBP5 in thyroid tumour cells. At 8p12, we identified rs7844425 which was significantly associated with DTC in Europeans (OR = 1.32, p = 7.6 x 10-8) and rs2439304, which was highlighted by the colocalization analysis but only moderately associated with DTC in our dataset (OR = 1.2, p = 0.001). These SNPs are linked to the expression of NRG1 in thyroid tissue. Hence, our study identified novel variants at 2q35 and 8p12 to be prioritized for further functional studies.

Multiethnic genome-wide association study of differentiated thyroid cancer in the EPITHYR consortium.

Incidence of differentiated thyroid carcinoma (DTC) varies considerably between ethnic groups, with particularly high incidence rates in Pacific Islanders. DTC is one of the cancers with the highest familial risk suggesting a major role of genetic risk factors, but only few susceptibility loci were identified so far. In order to assess the contribution of known DTC susceptibility loci and to identify new ones, we conducted a multiethnic genome-wide association study (GWAS) in individuals of European ancestry and of Oceanian ancestry from Pacific Islands. Our study included 1554 cases/1973 controls of European ancestry and 301 cases/348 controls of Oceanian ancestry from seven population-based case-control studies participating to the EPITHYR consortium. All participants were genotyped using the OncoArray-500K Beadchip (Illumina). We confirmed the association with the known DTC susceptibility loci at 2q35, 8p12, 9q22.33 and 14q13.3 in the European ancestry population and suggested two novel signals at 1p31.3 and 16q23.2, which were associated with thyroid-stimulating hormone levels in previous GWAS. We additionally replicated an association with 5p15.33 reported previously in Chinese and European populations. Except at 1p31.3, all associations were in the same direction in the population of Oceanian ancestry. We also observed that the frequencies of risk alleles at 2q35, 5p15.33 and 16q23.2 were significantly higher in Oceanians than in Europeans. However, additional GWAS and epidemiological studies in Oceanian populations are needed to fully understand the highest incidence observed in these populations.

Bayesian meta-analysis models for cross cancer genomic investigation of pleiotropic effects using group structure.

An increasing number of genome-wide association studies (GWAS) summary statistics is made available to the scientific community. Exploiting these results from multiple phenotypes would permit identification of novel pleiotropic associations. In addition, incorporating prior biological information in GWAS such as group structure information (gene or pathway) has shown some success in classical GWAS approaches. However, this has not been widely explored in the context of pleiotropy. We propose a Bayesian meta-analysis approach (termed GCPBayes) that uses summary-level GWAS data across multiple phenotypes to detect pleiotropy at both group-level (gene or pathway) and within group (eg, at the SNP level). We consider both continuous and Dirac spike and slab priors for group selection. We also use a Bayesian sparse group selection approach with hierarchical spike and slab priors that enables us to select important variables both at the group level and within group. GCPBayes uses a Bayesian statistical framework based on Markov chain Monte Carlo (MCMC) Gibbs sampling. It can be applied to multiple types of phenotypes for studies with overlapping or nonoverlapping subjects, and takes into account heterogeneity in the effect size and allows for the opposite direction of the genetic effects across traits. Simulations show that the proposed methods outperform benchmark approaches such as ASSET and CPBayes in the ability to retrieve pleiotropic associations at both SNP and gene-levels. To illustrate the GCPBayes method, we investigate the shared genetic effects between thyroid cancer and breast cancer in candidate pathways.

Bidirectional Relation Between Parkinson's Disease and Glioblastoma Multiforme.

Cancer and Parkinson's disease (PD) define two disease entities that include opposite concepts. Indeed, the involved mechanisms are at different ends of a spectrum related to cell survival - one due to enhanced cellular proliferation and the other due to premature cell death. There is increasing evidence indicating that patients with neurodegenerative diseases like PD have a reduced incidence for most cancers. In support, epidemiological studies demonstrate an inverse association between PD and cancer. Both conditions apparently can involve the same set of genes, however, in affected tissues the expression was inversely regulated: genes that are down-regulated in PD were found to be up-regulated in cancer and vice versa, for example p53 or PARK7. When comparing glioblastoma multiforme (GBM), a malignant brain tumor with poor overall survival, with PD, astrocytes are dysregulated in both diseases in opposite ways. In addition, common genes, that are involved in both diseases and share common key pathways of cell proliferation and metabolism, were shown to be oppositely deregulated in PD and GBM. Here, we provide an overview of the involvement of PD- and GBM-associated genes in common pathways that are dysregulated in both conditions. Moreover, we illustrate why the simultaneous study of PD and GBM regarding the role of common pathways may lead to a deeper understanding of these still incurable conditions. Eventually, considering the inverse regulation of certain genes in PD and GBM will help to understand their mechanistic basis, and thus to define novel target-based strategies for causative treatments.

Genome-wide interaction study of early-life smoking exposure on time-to-asthma onset in childhood.

BACKGROUND: Asthma, a heterogeneous disease with variable age of onset, results from the interplay between genetic and environmental factors. Early-life tobacco smoke (ELTS) exposure is a major asthma risk factor. Only a few genetic loci have been reported to interact with ELTS exposure in asthma. OBJECTIVE: Our aim was to identify new loci interacting with ELTS exposure on time-to-asthma onset (TAO) in childhood. METHODS: We conducted genome-wide interaction analyses of ELTS exposure on time-to-asthma onset in childhood in five European-ancestry studies (totalling 8273 subjects) using Cox proportional-hazard model. The results of all five genome-wide analyses were meta-analysed. RESULTS: The 13q21 locus showed genome-wide significant interaction with ELTS exposure (P = 4.3 × 10-8 for rs7334050 within KLHL1 with consistent results across the five studies). Suggestive interactions (P < 5 × 10-6 ) were found at three other loci: 20p12 (rs13037508 within MACROD2; P = 4.9 × 10-7 ), 14q22 (rs7493885 near NIN; P = 2.9 × 10-6 ) and 2p22 (rs232542 near CYP1B1; P = 4.1 × 10-6 ). Functional annotations and the literature showed that the lead SNPs at these four loci influence DNA methylation in the blood and are located nearby CpG sites reported to be associated with exposure to tobacco smoke components, which strongly support our findings. CONCLUSIONS AND CLINICAL RELEVANCE: We identified novel candidate genes interacting with ELTS exposure on time-to-asthma onset in childhood. These genes have plausible biological relevance related to tobacco smoke exposure. Further epigenetic and functional studies are needed to confirm these findings and to shed light on the underlying mechanisms.

A novel role for ciliary function in atopy: ADGRV1 and DNAH5 interactions.

BACKGROUND: Atopy, an endotype underlying allergic diseases, has a substantial genetic component. OBJECTIVE: Our goal was to identify novel genes associated with atopy in asthma-ascertained families. METHODS: We implemented a 3-step analysis strategy in 3 data sets: the Epidemiological Study on the Genetics and Environment of Asthma (EGEA) data set (1660 subjects), the Saguenay-Lac-Saint-Jean study data set (1138 subjects), and the Medical Research Council (MRC) data set (446 subjects). This strategy included a single nucleotide polymorphism (SNP) genome-wide association study (GWAS), the selection of related gene pairs based on statistical filtering of GWAS results, and text-mining filtering using Gene Relationships Across Implicated Loci and SNP-SNP interaction analysis of selected gene pairs. RESULTS: We identified the 5q14 locus, harboring the adhesion G protein-coupled receptor V1 (ADGRV1) gene, which showed genome-wide significant association with atopy (rs4916831, meta-analysis P value = 6.8 × 10-9). Statistical filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 and 3 genes showing suggestive association with atopy (P ≤ 10-4). SNP-SNP interaction analysis between ADGRV1 and these 3 genes showed significant interaction between ADGRV1 rs17554723 and 2 correlated SNPs (rs2134256 and rs1354187) within the dynein axonemal heavy chain 5 (DNAH5) gene (Pmeta-int = 3.6 × 10-5 and 6.1 × 10-5, which met the multiple-testing corrected threshold of 7.3 × 10-5). Further conditional analysis indicated that rs2134256 alone accounted for the interaction signal with rs17554723. CONCLUSION: Because both DNAH5 and ADGRV1 contribute to ciliary function, this study suggests that ciliary dysfunction might represent a novel mechanism underlying atopy. Combining GWAS and epistasis analysis driven by statistical and knowledge-based evidence represents a promising approach for identifying new genes involved in complex traits.

Identification of a new locus at 16q12 associated with time to asthma onset.

BACKGROUND: Asthma is a heterogeneous disease in which age of onset plays an important role. OBJECTIVE: We sought to identify the genetic variants associated with time to asthma onset (TAO). METHODS: We conducted a large-scale meta-analysis of 9 genome-wide association studies of TAO (total of 5462 asthmatic patients with a broad range of age of asthma onset and 8424 control subjects of European ancestry) performed by using survival analysis techniques. RESULTS: We detected 5 regions associated with TAO at the genome-wide significant level (P < 5 × 10-8). We evidenced a new locus in the 16q12 region (near cylindromatosis turban tumor syndrome gene [CYLD]) and confirmed 4 asthma risk regions: 2q12 (IL-1 receptor-like 1 [IL1RL1]), 6p21 (HLA-DQA1), 9p24 (IL33), and 17q12-q21 (zona pellucida binding protein 2 [ZPBP2]-gasdermin A [GSDMA]). Conditional analyses identified 2 distinct signals at 9p24 (both upstream of IL33) and 17q12-q21 (near ZPBP2 and within GSDMA). Together, these 7 distinct loci explained 6.0% of the variance in TAO. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P ≤ .002), whereas the 16q12 single nucleotide polymorphism was associated with later asthma onset (P = .04). A high burden of disease risk alleles at these loci was associated with earlier age of asthma onset (4 vs 9-12 years, P = 10-4). CONCLUSION: The new susceptibility region for TAO at 16q12 harbors variants that correlate with the expression of CYLD and nucleotide-binding oligomerization domain 2 (NOD2), 2 strong candidates for asthma. This study demonstrates that incorporating the variability of age of asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes.