Strategies to investigate and mitigate collider bias in genetic and Mendelian randomisation studies of disease progression.

Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors that influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as "index event") bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomisation (MR) analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and MR studies using both individual- and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-Hunter and Dudbridge et al.'s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, while our second example investigates genetic associations with breast cancer mortality.

Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank.

BACKGROUND: Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. METHODS: We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; ncases=51 929; ncontrols=39 980) and subsequent arterial ischemic stroke (AIS; ncases=45 120; ncontrols=46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization. RESULTS: Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64-0.85]; P=3.69×10-8) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37-1.67]; P=3.77×10-8) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66-0.88]; adjusted P=0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24-1.60]; adjusted P=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. CONCLUSIONS: We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.

Defining disease severity in atopic dermatitis and psoriasis for the application to biomarker research: an interdisciplinary perspective.

More severe atopic dermatitis and psoriasis are associated with a higher cumulative impact on quality of life, multimorbidity and healthcare costs. Proactive, early intervention in those most at risk of severe disease may reduce this cumulative burden and modify the disease trajectory to limit progression. The lack of reliable biomarkers for this at-risk group represents a barrier to such a paradigm shift in practice. To expedite discovery and validation, the BIOMarkers in Atopic Dermatitis and Psoriasis (BIOMAP) consortium (a large-scale European, interdisciplinary research initiative) has curated clinical and molecular data across diverse study designs and sources including cross-sectional and cohort studies (small-scale studies through to large multicentre registries), clinical trials, electronic health records and large-scale population-based biobanks. We map all dataset disease severity instruments and measures to three key domains (symptoms, inflammatory activity and disease course), and describe important codependencies and relationships across variables and domains. We prioritize definitions for more severe disease with reference to international consensus, reference standards and/or expert opinion. Key factors to consider when analysing datasets across these diverse study types include explicit early consideration of biomarker purpose and clinical context, candidate biomarkers associated with disease severity at a particular point in time and over time and how they are related, taking the stage of biomarker development into account when selecting disease severity measures for analyses, and validating biomarker associations with disease severity outcomes using both physician- and patient-reported measures and across domains. The outputs from this exercise will ensure coherence and focus across the BIOMAP consortium so that mechanistic insights and biomarkers are clinically relevant, patient-centric and more generalizable to current and future research efforts.

Atopic dermatitis (AD), and psoriasis are long-term skin conditions that can significantly affect people's lives, especially when symptoms are severe. Approximately 10% of adults and 20% of children are affected by AD, while psoriasis affects around 5% of people in the UK. Both conditions are associated with debilitating physical symptoms (such as itch) and have been linked to depression and anxiety. Biomarkers are naturally occurring chemicals in the human body and have potential to enhance the longer-term management of AD and psoriasis. Currently, there are no routinely used biomarkers that can identify people who experience or will go on to develop severe AD and psoriasis. For this reason, research is under way to understand which biomarkers are linked to severity. In this study, a multidisciplinary team of skin researchers from across Europe, along with patient groups, discussed the complexities of studying severity-related biomarkers. We identified a number of severity measurement approaches and there were recommendations for future biomarker research, including (i) considering multiple measures as no single measure can encompass all aspects of severity, (ii) exploring severity measures recorded by both healthcare professionals and patients, as each may capture different aspects, and (iii) accounting for influencing factors, such as different treatment approaches, that may impact AD and psoriasis severity, which make it challenging to compare findings across studies. Overall, we anticipate that the insights gained from these discussions will increase the likelihood of biomarkers being effectively applied in real-world settings, to ultimately improve outcomes for people with AD and psoriasis.

Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function.

BACKGROUND: DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease. METHODS: We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression. RESULTS: Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression. CONCLUSIONS: Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.

Disagreement concerning atopic dermatitis subtypes between an English prospective cohort (ALSPAC) and linked electronic health records.

BACKGROUND: Subtypes of atopic dermatitis (AD) have been derived from the Avon Longitudinal Study of Parents and Children (ALSPAC) based on presence and severity of symptoms reported in questionnaires (Severe-Frequent, Moderate-Frequent, Moderate-Declining, Mild-Intermittent, Unaffected/Rare). Good agreement between ALSPAC and linked electronic health records (EHRs) would increase trust in the clinical validity of these subtypes and allow inferring subtypes from EHRs alone, which would enable their study in large primary care databases. OBJECTIVES: 1. Explore if presence and number of AD records in EHRs agrees with AD symptom and severity reports from ALSPAC; 2. Explore if EHRs agree with ALSPAC-derived AD subtypes; 3. Construct models to classify ALSPAC-derived AD subtype using EHRs. METHODS: We used data from the ALSPAC prospective cohort study from 11 timepoints until age 14 years (1991-2008), linked to local general practice EHRs. We assessed how far ALSPAC questionnaire responses and derived subtypes agreed with AD as established in EHRs using different AD definitions (e.g., diagnosis and/or prescription) and other AD-related records. We classified AD subtypes using EHRs, fitting multinomial logistic regression models tuning hyperparameters and evaluating performance in the testing set (ROC AUC, accuracy, sensitivity, and specificity). RESULTS: 8,828 individuals out of a total 13,898 had both been assigned an AD subtype and had linked EHRs. The number of AD-related codes in EHRs generally increased with severity of AD subtype, however not all with the Severe-Frequent subtypes had AD in EHRs, and many with the Unaffected/Rare subtype did have AD in EHRs. When predicting ALSPAC AD subtype using EHRs, the best tuned model had ROC AUC of 0.65, sensitivity of 0.29 and specificity of 0.83 (both macro averaged); when different sets of predictors were used, individuals with missing EHR coverage excluded, and subtypes combined, sensitivity was not considerably improved. CONCLUSIONS: ALSPAC and EHRs disagreed not just on AD subtypes, but also on whether children had AD or not. Researchers should be aware that individuals considered as having AD in one source may not be considered as having AD in another.

Age-of-onset information helps identify 76 genetic variants associated with allergic disease.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Genetic Architectures of Childhood- and Adult-Onset Asthma Are Partly Distinct.

The extent to which genetic risk factors are shared between childhood-onset (COA) and adult-onset (AOA) asthma has not been estimated. On the basis of data from the UK Biobank study (n = 447,628), we found that the variance in disease liability explained by common variants is higher for COA (onset at ages between 0 and 19 years; h2g = 25.6%) than for AOA (onset at ages between 20 and 60 years; h2g = 10.6%). The genetic correlation (rg) between COA and AOA was 0.67. Variation in age of onset among COA-affected individuals had a low heritability (h2g = 5%), which we confirmed in independent studies and also among AOA-affected individuals. To identify subtype-specific genetic associations, we performed a genome-wide association study (GWAS) in the UK Biobank for COA (13,962 affected individuals) and a separate GWAS for AOA (26,582 affected individuals) by using a common set of 300,671 controls for both studies. We identified 123 independent associations for COA and 56 for AOA (37 overlapped); of these, 98 and 34, respectively, were reproducible in an independent study (n = 262,767). Collectively, 28 associations were not previously reported. For 96 COA-associated variants, including five variants that represent COA-specific risk factors, the risk allele was more common in COA- than in AOA-affected individuals. Conversely, we identified three variants that are stronger risk factors for AOA. Variants associated with obesity and smoking had a stronger contribution to the risk of AOA than to the risk of COA. Lastly, we identified 109 likely target genes of the associated variants, primarily on the basis of correlated expression quantitative trait loci (up to n = 31,684). GWAS informed by age of onset can identify subtype-specific risk variants, which can help us understand differences in pathophysiology between COA and AOA and so can be informative for drug development.

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.

Mendelian randomization provides evidence for a causal effect of higher serum IGF-1 concentration on risk of hip and knee osteoarthritis.

OBJECTIVES: How insulin-like growth factor-1 (IGF-1) is related to OA is not well understood. We determined relationships between IGF-1 and hospital-diagnosed hand, hip and knee OA in UK Biobank, using Mendelian randomization (MR) to determine causality. METHODS: Serum IGF-1 was assessed by chemiluminescent immunoassay. OA was determined using Hospital Episode Statistics. One-sample MR (1SMR) was performed using two-stage least-squares regression, with an unweighted IGF-1 genetic risk score as an instrument. Multivariable MR included BMI as an additional exposure (instrumented by BMI genetic risk score). MR analyses were adjusted for sex, genotyping chip and principal components. We then performed two-sample MR (2SMR) using summary statistics from Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) (IGF-1, N = 30 884) and the recent genome-wide association study meta-analysis (N = 455 221) of UK Biobank and Arthritis Research UK OA Genetics (arcOGEN). RESULTS: A total of 332 092 adults in UK Biobank had complete data. Their mean (s.d.) age was 56.5 (8.0) years and 54% were female. IGF-1 was observationally related to a reduced odds of hand OA [odds ratio per doubling = 0.87 (95% CI 0.82, 0.93)], and an increased odds of hip OA [1.04 (1.01, 1.07)], but was unrelated to knee OA [0.99 (0.96, 1.01)]. Using 1SMR, we found strong evidence for an increased risk of hip [odds ratio per s.d. increase = 1.57 (1.21, 2.01)] and knee [1.30 (1.07, 1.58)] OA with increasing IGF-1 concentration. By contrast, we found no evidence for a causal effect of IGF-1 concentration on hand OA [0.98 (0.57, 1.70)]. Results were consistent when estimated using 2SMR and in multivariable MR analyses accounting for BMI. CONCLUSION: We have found evidence that increased serum IGF-1 is causally related to higher risk of hip and knee OA.

Protein-coding variants contribute to the risk of atopic dermatitis and skin-specific gene expression.

BACKGROUND: Fifteen percent of atopic dermatitis (AD) liability-scale heritability could be attributed to 31 susceptibility loci identified by using genome-wide association studies, with only 3 of them (IL13, IL-6 receptor [IL6R], and filaggrin [FLG]) resolved to protein-coding variants. OBJECTIVE: We examined whether a significant portion of unexplained AD heritability is further explained by low-frequency and rare variants in the gene-coding sequence. METHODS: We evaluated common, low-frequency, and rare protein-coding variants using exome chip and replication genotype data of 15,574 patients and 377,839 control subjects combined with whole-transcriptome data on lesional, nonlesional, and healthy skin samples of 27 patients and 38 control subjects. RESULTS: An additional 12.56% (SE, 0.74%) of AD heritability is explained by rare protein-coding variation. We identified docking protein 2 (DOK2) and CD200 receptor 1 (CD200R1) as novel genome-wide significant susceptibility genes. Rare coding variants associated with AD are further enriched in 5 genes (IL-4 receptor [IL4R], IL13, Janus kinase 1 [JAK1], JAK2, and tyrosine kinase 2 [TYK2]) of the IL13 pathway, all of which are targets for novel systemic AD therapeutics. Multiomics-based network and RNA sequencing analysis revealed DOK2 as a central hub interacting with, among others, CD200R1, IL6R, and signal transducer and activator of transcription 3 (STAT3). Multitissue gene expression profile analysis for 53 tissue types from the Genotype-Tissue Expression project showed that disease-associated protein-coding variants exert their greatest effect in skin tissues. CONCLUSION: Our discoveries highlight a major role of rare coding variants in AD acting independently of common variants. Further extensive functional studies are required to detect all potential causal variants and to specify the contribution of the novel susceptibility genes DOK2 and CD200R1 to overall disease susceptibility.

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics.

Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10-8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits.

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

Metabolomics analysis in adults with high bone mass identifies a relationship between bone resorption and circulating citrate which replicates in the general population.

OBJECTIVE: Bone turnover, which regulates bone mass, may exert metabolic consequences, particularly on markers of glucose metabolism and adiposity. To better understand these relationships, we examined cross-sectional associations between bone turnover markers (BTMs) and metabolic traits in a population with high bone mass (HBM, BMD Z-score ≥+3.2). DESIGN: ß-C-terminal telopeptide of type-I collagen (ß-CTX), procollagen type-1 amino-terminal propeptide (P1NP) and osteocalcin were assessed by electrochemiluminescence immunoassays. Metabolic traits, including lipids and glycolysis-related metabolites, were measured using nuclear magnetic resonance spectroscopy. Associations of BTMs with metabolic traits were assessed using generalized estimating equation linear regression, accounting for within-family correlation, adjusting for potential confounders (age, sex, height, weight, menopause, bisphosphonate and oral glucocorticoid use). RESULTS: A total of 198 adults with HBM had complete data, mean [SD] age 61.6 [13.7] years; 77% were female. Of 23 summary metabolic traits, citrate was positively related to all BTMs: adjusted ßß-CTX  = 0.050 (95% CI 0.024, 0.076), P = 1.71 × 10-4 , ßosteocalcin  = 6.54 × 10-4 (1.87 × 10-4 , 0.001), P = .006 and ßP1NP  = 2.40 × 10-4 (6.49 × 10-5 , 4.14 × 10-4 ), P = .007 (ß = increase in citrate (mmol/L) per 1 µg/L BTM increase). Inverse relationships of ß-CTX (ß = -0.276 [-0.434, -0.118], P = 6.03 × 10-4 ) and osteocalcin (-0.004 [-0.007, -0.001], P = .020) with triglycerides were also identified. We explored the generalizability of these associations in 3664 perimenopausal women (age 47.9 [4.4] years) from a UK family cohort. We confirmed a positive, albeit lower magnitude, association between ß-CTX and citrate (adjusted ßwomen  = 0.020 [0.013, 0.026], P = 1.95 × 10-9 ) and an inverse association of similar magnitude between ß-CTX and triglycerides (ß = -0.354 [-0.471, -0.237], P = 3.03 × 10-9 ). CONCLUSIONS: Bone resorption is positively related to circulating citrate and inversely related to triglycerides. Further studies are justified to determine whether plasma citrate or triglyceride concentrations are altered by factors known to modulate bone resorption, such as bisphosphonates.

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.

Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges.

The past decade has been proclaimed as a hugely successful era of gene discovery through the high yields of many genome-wide association studies (GWAS). However, much of the perceived benefit of such discoveries lies in the promise that the identification of genes that influence disease would directly translate into the identification of potential therapeutic targets, but this has yet to be realized at a level reflecting expectation. One reason for this, we suggest, is that GWAS, to date, have generally not focused on phenotypes that directly relate to the progression of disease and thus speak to disease treatment.

Clinical onset of atopic eczema: Results from 2 nationally representative British birth cohorts followed through midlife.

BACKGROUND: Atopic eczema onset is described primarily in early childhood, and the frequency and characteristics of adult-onset disease remain controversial. OBJECTIVE: We sought to determine the proportion of subjects who report atopic eczema symptoms between birth and midadulthood and to examine demographic, immunologic, and genetic factors associated with period of symptom onset. METHODS: We conducted a longitudinal study using data from 2 nationally representative community-based birth cohorts from the United Kingdom: the British Cohort Studies 1958 and 1970. Subjects were followed from birth through age 42 to 50 years. The primary outcome was the age period of self-reported atopic eczema symptom onset based on repeated measures of self-reported atopic eczema at each survey wave. RESULTS: The annual period prevalence of atopic eczema ranged from 5% to 15% in 2 cohorts of more than 17,000 participants each followed from birth through middle age. There was no clear trend in prevalence by age, and among adults reporting active atopic eczema during a given year, only 38% had symptom onset reported in childhood. When compared with subjects whose eczema started in childhood, those with adult-onset disease were more likely to be women, from Scotland or Northern England, of lower childhood socioeconomic group, smokers in adulthood, and less likely to have a history of asthma. In a subanalysis using data from the 1958 cohort only, genetic mutations previously associated with atopic eczema, including filaggrin-null mutations, and allergen-specific IgE were more common among those with childhood-onset disease. CONCLUSION: Rates of self-reported atopic eczema remain high after childhood, and adult-onset atopic eczema has different risk factor associations than childhood-onset eczema.

EMSY expression affects multiple components of the skin barrier with relevance to atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a common, complex, and highly heritable inflammatory skin disease. Genome-wide association studies offer opportunities to identify molecular targets for drug development. A risk locus on chromosome 11q13.5 lies between 2 candidate genes, EMSY and LRRC32 (leucine-rich repeat-containing 32) but the functional mechanisms affecting risk of AD remain unclear. OBJECTIVES: We sought to apply a combination of genomic and molecular analytic techniques to investigate which genes are responsible for genetic risk at this locus and to define mechanisms contributing to atopic skin disease. METHODS: We used interrogation of available genomic and chromosome conformation data in keratinocytes, small interfering RNA (siRNA)-mediated knockdown in skin organotypic culture and functional assessment of barrier parameters, mass spectrometric global proteomic analysis and quantitative lipid analysis, electron microscopy of organotypic skin, and immunohistochemistry of human skin samples. RESULTS: Genomic data indicate active promoters in the genome-wide association study locus and upstream of EMSY; EMSY, LRRC32, and intergenic variants all appear to be within a single topologically associating domain. siRNA-knockdown of EMSY in organotypic culture leads to enhanced development of barrier function, reflecting increased expression of structural and functional proteins, including filaggrin and filaggrin-2, as well as long-chain ceramides. Conversely, overexpression of EMSY in keratinocytes leads to a reduction in markers of barrier formation. Skin biopsy samples from patients with AD show greater EMSY staining in the nucleus, which is consistent with an increased functional effect of this transcriptional control protein. CONCLUSION: Our findings demonstrate an important role for EMSY in transcriptional regulation and skin barrier formation, supporting EMSY inhibition as a therapeutic approach.

Eleven loci with new reproducible genetic associations with allergic disease risk.

BACKGROUND: A recent genome-wide association study (GWAS) identified 99 loci that contain genetic risk variants shared between asthma, hay fever, and eczema. Many more risk loci shared between these common allergic diseases remain to be discovered, which could point to new therapeutic opportunities. OBJECTIVE: We sought to identify novel risk loci shared between asthma, hay fever, and eczema by applying a gene-based test of association to results from a published GWAS that included data from 360,838 subjects. METHODS: We used approximate conditional analysis to adjust the results from the published GWAS for the effects of the top risk variants identified in that study. We then analyzed the adjusted GWAS results with the EUGENE gene-based approach, which combines evidence for association with disease risk across regulatory variants identified in different tissues. Novel gene-based associations were followed up in an independent sample of 233,898 subjects from the UK Biobank study. RESULTS: Of the 19,432 genes tested, 30 had a significant gene-based association at a Bonferroni-corrected P value of 2.5 × 10-6. Of these, 20 were also significantly associated (P < .05/30 = .0016) with disease risk in the replication sample, including 19 that were located in 11 loci not reported to contain allergy risk variants in previous GWASs. Among these were 9 genes with a known function that is directly relevant to allergic disease: FOSL2, VPRBP, IPCEF1, PRR5L, NCF4, APOBR, IL27, ATXN2L, and LAT. For 4 genes (eg, ATXN2L), a genetically determined decrease in gene expression was associated with decreased allergy risk, and therefore drugs that inhibit gene expression or function are predicted to ameliorate disease symptoms. The opposite directional effect was observed for 14 genes, including IL27, a cytokine known to suppress TH2 responses. CONCLUSION: Using a gene-based approach, we identified 11 risk loci for allergic disease that were not reported in previous GWASs. Functional studies that investigate the contribution of the 19 associated genes to the pathophysiology of allergic disease and assess their therapeutic potential are warranted.

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.

Differential associations of allergic disease genetic variants with developmental profiles of eczema, wheeze and rhinitis.

BACKGROUND: Allergic diseases (eczema, wheeze and rhinitis) in children often present as heterogeneous phenotypes. Understanding genetic associations of specific patterns of symptoms might facilitate understanding of the underlying biological mechanisms. OBJECTIVE: To examine associations between allergic disease-related variants identified in a recent genome-wide association study and latent classes of allergic diseases (LCADs) in two population-based birth cohorts. METHODS: Eight previously defined LCADs between birth and 11 years: "No disease," "Atopic march," "Persistent eczema and wheeze," "Persistent eczema with later-onset rhinitis," "Persistent wheeze with later-onset rhinitis," "Transient wheeze," "Eczema only" and "Rhinitis only" were used as the study outcome. Weighted multinomial logistic regression was used to estimate associations between 135 SNPs (and a polygenic risk score, PRS) and LCADs among 6345 individuals from The Avon Longitudinal Study of Parents and Children (ALSPAC). Heterogeneity across LCADs was assessed before and after Bonferroni correction. Results were replicated in Manchester Asthma and Allergy Study (MAAS) (n = 896) and pooled in a meta-analysis. RESULTS: We found strong evidence for differential genetic associations across the LCADs; pooled PRS heterogeneity P-value = 3.3 × 10-14 , excluding "no disease" class. The associations between the PRS and LCADs in MAAS were remarkably similar to ALSPAC. Two SNPs (a protein-truncating variant in FLG and a SNP within an intron of GSDMB) had evidence for differential association (pooled P-values ≤ 0.006). The FLG locus was differentially associated across LCADs that included eczema, with stronger associations for LCADs with comorbid wheeze and rhinitis. The GSDMB locus in contrast was equally associated across LCADs that included wheeze. CONCLUSIONS AND CLINICAL RELEVANCE: We have shown complex, but distinct patterns of genetic associations with LCADs, suggesting that heterogeneous mechanisms underlie individual disease trajectories. Establishing the combination of allergic diseases with which each genetic variant is associated may inform therapeutic development and/or predictive modelling.