Identification of OCA2 as a novel locus for the co-morbidity of asthma-plus-eczema.

BACKGROUND: Numerous genes have been associated with the three most common allergic diseases (asthma, allergic rhinitis or eczema) but these genes explain only a part of the heritability. In the vast majority of genetic studies, complex phenotypes such as co-morbidity of two of these diseases, have not been considered. This may partly explain missing heritability. OBJECTIVE: To identify genetic variants specifically associated with the co-morbidity of asthma-plus-eczema. METHODS: We first conducted a meta-analysis of four GWAS (Genome-Wide Association Study) of the combined asthma-plus-eczema phenotype (total of 8807 European-ancestry subjects of whom 1208 subjects had both asthma and eczema). To assess whether the association with SNP(s) was specific to the co-morbidity, we also conducted a meta-analysis of homogeneity test of association according to disease status ("asthma-plus-eczema" vs. the presence of only one disease "asthma only or eczema only"). We then used a joint test by combining the two test statistics from the co-morbidity-SNP association and the phenotypic heterogeneity of SNP effect meta-analyses. RESULTS: Seven SNPs were detected for specific association to the asthma-plus-eczema co-morbidity, two with significant and five with suggestive evidence using the joint test after correction for multiple testing. The two significant SNPs are located in the OCA2 gene (Oculocutaneous Albinism II), a new locus never detected for significant evidence of association with any allergic disease. This gene is a promising candidate gene, because of its link to skin and lung diseases, and to epithelial barrier and immune mechanisms. CONCLUSION: Our study underlines the importance of studying sub-phenotypes as co-morbidities to detect new susceptibility genes.

Investigating the causal relationship between allergic disease and mental health.

BACKGROUND: Observational studies have reported an association between allergic disease and mental health, but a causal relationship has not been established. Here, we use Mendelian randomization (MR) to investigate a possible causal relationship between atopic disease and mental health phenotypes. METHODS: The observational relationship between allergic disease and mental health was investigated in UK Biobank. The direction of causality was investigated with bidirectional two-sample MR using summary-level data from published genome-wide association studies. A genetic instrument was derived from associated variants for a broad allergic disease phenotype to test for causal relationships with various mental health outcomes. We also investigated whether these relationships were specific to atopic dermatitis (AD), asthma or hayfever. Given the multiple testing burden, we applied a Bonferroni correction to use an individual test p-value threshold of .0016 (32 tests). RESULTS: We found strong evidence of an observational association between the broad allergic disease phenotype and depression (ORself-report =1.45, 95% CI: 1.41-1.50, p = 3.6 × 10-130 ), anxiety (OR=1.25, 95% CI: 1.18-1.33, p = 6.5 × 10-13 ), bipolar disorder (ORself-report =1.29, 95% CI: 1.12-1.47, p = 2.8 × 10-4 ) and neuroticism (ß = 0.38, 95% CI: 0.36-0.41, p = 6.8 × 10-166 ). Similar associations were found between asthma, AD, hayfever individually with the mental health phenotypes, although the associations between AD and hayfever with bipolar disorder were weaker. There was little evidence of causality in either direction (all p-values>.02). CONCLUSION: Using MR, we were unable to replicate most of the phenotypic associations between allergic disease and mental health. Any causal effects we detected were considerably attenuated compared with the phenotypic association. This suggests that most comorbidity observed clinically is unlikely to be causal.

Relationship between smoking and ALS: Mendelian randomisation interrogation of causality.

OBJECTIVE: Smoking has been widely studied as a susceptibility factor for amyotrophic lateral sclerosis (ALS), but results are conflicting and at risk of confounding bias. We used the results of recently published large genome-wide association studies and Mendelian randomisation methods to reduce confounding to assess the relationship between smoking and ALS. METHODS: Two genome-wide association studies investigating lifetime smoking (n=463 003) and ever smoking (n=1 232 091) were identified and used to define instrumental variables for smoking. A genome-wide association study of ALS (20 806 cases; 59 804 controls) was used as the outcome for inverse variance weighted Mendelian randomisation, and four other Mendelian randomisation methods, to test whether smoking is causal for ALS. Analyses were bidirectional to assess reverse causality. RESULTS: There was no strong evidence for a causal or reverse causal relationship between smoking and ALS. The results of Mendelian randomisation using the inverse variance weighted method were: lifetime smoking OR 0.94 (95% CI 0.74 to 1.19), p value 0.59; ever smoking OR 1.10 (95% CI 1 to 1.23), p value 0.05. CONCLUSIONS: Using multiple methods, large sample sizes and sensitivity analyses, we find no evidence with Mendelian randomisation techniques that smoking causes ALS. Other smoking phenotypes, such as current smoking, may be suitable for future Mendelian randomisation studies.

Evidence of a causal relationship between body mass index and psoriasis: A mendelian randomization study.

BACKGROUND: Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis. METHODS AND FINDINGS: Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied. CONCLUSIONS: Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship.

A rare coding allele in IFIH1 is protective for psoriatic arthritis.

OBJECTIVES: Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. While many common risk alleles have been reported for association with PsA as well as psoriasis, few rare coding alleles have yet been identified. METHODS: To identify rare coding variation associated with PsA risk or protection, we genotyped 41 267 variants with the exome chip and investigated association within an initial cohort of 1980 PsA cases and 5913 controls. Genotype data for an independent cohort of 2234 PsA cases and 5708 controls was also made available, allowing for a meta-analysis to be performed with the discovery dataset. RESULTS: We identified an association with the rare variant rs35667974 (p=2.39x10-6, OR=0.47), encoding an Ile923Val amino acid change in the IFIH1 gene protein product. The association was reproduced in our independent cohort, which reached a high level of significance on meta-analysis with the discovery and replication datasets (p=4.67x10-10). We identified a strong association with IFIH1 when performing multiple-variant analysis (p=6.77x10-6), and found evidence of independent effects between the rare allele and the common PsA variant at the same locus. CONCLUSION: For the first time, we report a rare coding allele in IFIH1 to be protective for PsA. This rare allele has also been identified to have the same direction of effect on type I diabetes and psoriasis. While this association further supports existing evidence for IFIH1 as a causal gene for PsA, mechanistic studies will need to be pursued to confirm that IFIH1 is indeed causal.

Identifying a novel locus for psoriatic arthritis.

A number of studies have identified genetic risk loci for PsA, the majority of which also confer risk for psoriasis. The stronger heritability of PsA in comparison with psoriasis suggests that there should be risk loci that are specific for PsA. Identifying such loci could potentially inform therapy development to provide more effective treatments for PsA patients, especially with a considerable proportion being non-responsive to current therapies. Evidence of a PsA-specific locus has been previously found at HLA-B27 within the MHC region. A recent study has provided evidence of non-HLA risk loci that are specific for PsA at IL23R, PTPN22 and on chromosome 5q31. Functional characterization of these loci will provide further understanding of the pathways underlying PsA, and enable us to apply genetic findings for patient benefit.

PTPN22 is associated with susceptibility to psoriatic arthritis but not psoriasis: evidence for a further PsA-specific risk locus.

OBJECTIVES: Psoriatic arthritis (PsA) is a chronic inflammatory arthritis associated with psoriasis; it has a higher estimated genetic component than psoriasis alone, however most genetic susceptibility loci identified for PsA to date are also shared with psoriasis. Here we attempt to validate novel single nucleotide polymorphisms selected from our recent PsA Immunochip study and determine specificity to PsA. METHODS: A total of 15 single nucleotide polymorphisms were selected (PImmunochip <1×10(-4)) for validation genotyping in 1177 cases and 2155 controls using TaqMan. Meta-analysis of Immunochip and validation data sets consisted of 3139 PsA cases and 11 078 controls. Novel PsA susceptibility loci were compared with data from two large psoriasis studies (WTCCC2 and Immunochip) to determine PsA specificity. RESULTS: We found genome-wide significant association to rs2476601, mapping to PTPN22 (p=1.49×10(-9), OR=1.32), but no evidence for association in the psoriasis cohort (p=0.34) and the effect estimates were significantly different between PsA and psoriasis (p=3.2×10(-4)). Additionally, we found genome-wide significant association to the previously reported psoriasis risk loci; NOS2 (rs4795067, p=5.27×10(-9)). CONCLUSIONS: For the first time, we report genome-wide significant association of PTPN22 (rs2476601) to PsA susceptibility, but no evidence for association to psoriasis.

Exploring the Link Between Genetic Predictors of Cardiovascular Disease and Psoriasis.

Importance: The epidemiological link between immune-mediated diseases (IMIDs) and cardiovascular disease has often been attributed to systemic inflammation. However, the direction of causality and the biological mechanisms linking cardiovascular disease with IMIDs are incompletely understood. Given the robust epidemiological association and the growing body of supportive mechanistic evidence, psoriasis is an exemplary IMID model for exploring this relationship. Objective: To assess the bidirectional relationships between genetic predictors of psoriasis and the 2 major forms of cardiovascular disease, coronary artery disease (CAD) and stroke, and to evaluate the association between genetic predictors of cardiovascular disease with 9 other IMIDs. Design, Setting, and Participants: This was a genetic association study using mendelian randomization (MR), a powerful genetic tool to help distinguish causation from associations observed in epidemiological studies, to provide supportive evidence for causality between traits. The study conducted 2-sample MR analyses using summary-level data from large-scale genome-wide association meta-analysis studies (GWAS) for each trait. The analysis focused on individuals of European descent from GWAS meta-analyses, involving CAD, stroke, psoriasis, and 9 other IMIDs. Data were analyzed from January 2023 to May 2024. Exposures: Genetic predictors of CAD, stroke, psoriasis, and 9 other IMIDs. Main Outcomes and Measures: The primary outcomes were the associations of genetic predictors of CAD and stroke with the risk of psoriasis and 9 other IMIDs, determined using inverse-variance weighted (IVW) MR estimates. Results: This study included 181 249 cases and 1 165 690 controls with CAD, 110 182 cases and 1 503 898 controls with stroke, 36 466 cases and 458 078 controls with psoriasis, for a total of approximately 3 400 000 individuals, and 9 other IMIDs. In contrast to previous assumptions, genetic predictors of psoriasis were found to have no association with CAD or stroke. In the reverse direction, genetic predictors of both CAD (MR estimate IVW odds ratio [OR], 1.07; 95% CI, 1.04-1.10; P = .003) and stroke (IVW OR, 1.22; 95% CI, 1.05-1.41; P = .01) were found to have risk-increasing associations with psoriasis. Adjusting for stroke rendered the associations of genetically predicted CAD with psoriasis risk nonsignificant (and vice versa), suggesting that a shared effect underlying genetic risk for CAD and stroke associates with increased psoriasis risk. No risk-increasing associations were observed for genetic predictors of cardiovascular disease with other common IMIDs, including rheumatoid arthritis and inflammatory bowel disease. Conclusions and Relevance: Findings of this mendelian randomization study indicate that genetic predictors of cardiovascular disease were associated with increased psoriasis risk with no reciprocal effect or association with other IMIDs. Elucidating mechanisms underpinning this association could lead to novel therapeutic approaches in both diseases.

TNS1 and NRXN1 Genes Interacting With Early-Life Smoking Exposure in Asthma-Plus-Eczema Susceptibility.

PURPOSE: Numerous genes have been associated with allergic diseases (asthma, allergic rhinitis, and eczema), but they explain only part of their heritability. This is partly because most previous studies ignored complex mechanisms such as gene-environment (G-E) interactions and complex phenotypes such as co-morbidity. However, it was recently evidenced that the co-morbidity of asthma-plus-eczema appears as a sub-entity depending on specific genetic factors. Besides, evidence also suggest that gene-by-early life environmental tobacco smoke (ETS) exposure interactions play a role in asthma, but were never investigated for asthma-plus-eczema. To identify genetic variants interacting with ETS exposure that influence asthma-plus-eczema susceptibility. METHODS: To conduct a genome-wide interaction study (GWIS) of asthma-plus-eczema according to ETS exposure, we applied a 2-stage strategy with a first selection of single nucleotide polymorphisms (SNPs) from genome-wide association meta-analysis to be tested at a second stage by interaction meta-analysis. All meta-analyses were conducted across 4 studies including a total of 5,516 European-ancestry individuals, of whom 1,164 had both asthma and eczema. RESULTS: Two SNPs showed significant interactions with ETS exposure. They were located in 2 genes, NRXN1 (2p16) and TNS1 (2q35), never reported associated and/or interacting with ETS exposure for asthma, eczema or more generally for allergic diseases. TNS1 is a promising candidate gene because of its link to lung and skin diseases with possible interactive effect with tobacco smoke exposure. CONCLUSIONS: This first GWIS of asthma-plus-eczema with ETS exposure underlines the importance of studying sub-phenotypes such as co-morbidities as well as G-E interactions to detect new susceptibility genes.

European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation.

Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

Imputation provides an opportunity to study filaggrin ( FLG) null mutations in large population cohorts that lack bespoke genotyping.

Background: Null mutations within the filaggrin ( FLG) gene are established genetic risk factors for atopic dermatitis. Studies of FLG have typically used sequencing or bespoke genotyping. Large-scale population cohorts with genome-wide imputed data offer powerful genetic analysis opportunities, but bespoke FLG genotyping is often not feasible in such studies. Therefore, we aimed to determine the quality of selected FLG null genotype data extracted from genome-wide imputed sources, focussing on UK population data. Methods: We compared the allele frequencies of three FLG null mutations that could be detected by imputation (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter; commonly referred to as R501X, R2447X and S3247X respectively) in directly genotyped and genome-wide imputed data in the ALSPAC cohort. Logistic regression analysis was used to test the association of atopic dermatitis with imputed and genotyped FLG null mutations in ALSPAC and UK Biobank to investigate the usefulness of imputed FLG data. Results: The three FLG null mutations appear to be well imputed in datasets that use the Haplotype Reference Consortium (HRC) for imputation (0.3% discordance compared with directly genotyped data). However, a greater proportion of null alleles failed imputation compared to wild-type alleles. Despite the calling of FLG mutations in imputed data being imperfect, they are still strongly associated with atopic dermatitis (p-values between 7x10 -10 and 5x10 -75 in UK Biobank). Conclusions: HRC imputed data appears to be adequate for UK population-based genetic analysis of selected FLG null mutations (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter).

Research Techniques Made Simple: Using Genetic Variants for Randomization.

Observational epidemiological studies have identified associations between a number of modifiable exposures and outcomes, including in dermatology, such as between smoking and psoriasis. However, it is challenging to determine if such relationships are causal because of the potential of confounding and reverse causation. Mendelian randomization (MR) is a statistical method that can be used to investigate the causal relationships between an exposure and outcome by using a genetic instrument that proxies the exposure. The resulting estimate (under certain assumptions) can be interpreted as the causal estimate, free of confounding and reverse causation. In this review, we provide an overview of how to undertake an MR analysis, with examples from the dermatology literature. We also discuss the challenges and future directions of this method.

Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis.

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.

Dense genotyping of immune-related susceptibility loci reveals new insights into the genetics of psoriatic arthritis.

Psoriatic arthritis (PsA) is a chronic inflammatory arthritis associated with psoriasis and, despite the larger estimated heritability for PsA, the majority of genetic susceptibility loci identified to date are shared with psoriasis. Here, we present results from a case-control association study on 1,962 PsA patients and 8,923 controls using the Immunochip genotyping array. We identify eight loci passing genome-wide significance, secondary independent effects at three loci and a distinct PsA-specific variant at the IL23R locus. We report two novel loci and evidence of a novel PsA-specific association at chromosome 5q31. Imputation of classical HLA alleles, amino acids and SNPs across the MHC region highlights three independent associations to class I genes. Finally, we find an enrichment of associated variants to markers of open chromatin in CD8(+) memory primary T cells. This study identifies key insights into the genetics of PsA that could begin to explain fundamental differences between psoriasis and PsA.