25‐Hydroxyvitamin D Concentrations and Clostridium difficile Infection: A Meta‐Analysis

Background: Well‐known risk factors for Clostridium difficile infection (CDI) are exposure to antibiotics and gastric acid suppressants. Recent studies have provided some evidence of an association between hypovitaminosis D and the risk of CDI. Therefore, this meta‐analysis aimed to pool all the existing evidence to investigate the association between 25‐hydroxyvitamin D (25[OH]D) and CDI. Methods: A systematic search was conducted in 3 databases (PubMed, Embase, and Web of Sciences) for epidemiological studies that examined the association between mean 25(OH)D concentrations and CDI as well as between 25(OH)D status and CDI severity or recurrence. 25(OH)D status was defined as “lower” or “higher” at a threshold concentration of <20 or ≥20 ng/mL, respectively. Pooled effect sizes were computed using the inverse variance heterogeneity model of meta‐analysis. Results: Eight publications (n = 4479 patients) were included in the meta‐analysis. The mean concentration of 25(OH)D in patients with CDI was 3.54 ng/mL (95% confidence interval [CI], 0.39–6.89 ng/mL) lower than in patients without CDI. Patients with lower 25(OH)D status had a higher odds (odds ratio [OR], 1.61; 95% CI, 1.02–2.53) of developing severe CDI compared with those with a higher 25(OH)D status. No significant association was found between 25(OH)D status and CDI recurrence. Conclusion: The results of this meta‐analysis suggest that lower mean concentrations of 25(OH)D were associated with CDI. A lower 25(OH)D status increased the odds of severe CDI but not of CDI recurrence.     

Plasma 25‐Hydroxyvitamin D Levels at Initiation of Care and Duration of Mechanical Ventilation in Critically Ill Surgical Patients

Objective: Limited data exist regarding the relationship between plasma 25‐hydroxyvitamin D levels and duration of respiratory support. Our goal was to explore whether vitamin D status at the time of intensive care unit (ICU) admission is associated with duration of mechanical ventilation in critically ill surgical patients. Materials and Methods: We analyzed data from a prospective cohort study involving 210 critically ill surgical patients. To explore the relationship between admission plasma 25‐hydroxyvitamin D levels and duration of mechanical ventilation, we performed a Poisson regression while controlling for clinically relevant covariates. Only patients who required ≥48 hours of mechanical ventilation and survived ≥24 hours after discontinuation of respiratory support were included in the analytic cohort. Results: Ninety‐four patients met inclusion criteria. Mean (standard deviation) plasma 25‐hydroxyvitamin D level was 16 (7) ng/mL and median (interquartile range) duration of mechanical ventilation was 4 (2–7) days. Poisson regression analysis, adjusted for age, sex, race, body mass index, primary surgical service, Acute Physiology and Chronic Health Evaluation II score, and season of ICU admission, demonstrated an inverse association of plasma 25‐hydroxyvitamin D levels with duration of mechanical ventilation (incident rate ratio per 10 ng/mL, 0.66; 95% confidence interval, 0.54–0.82). Conclusions: In our cohort of critically ill surgical patients, plasma 25‐hydroxyvitamin D levels measured on ICU admission were inversely associated with the duration of respiratory support. Randomized controlled trials are needed to assess whether vitamin D supplementation can influence duration of mechanical ventilation in surgical ICU patients.     

A Whole‐Genome Simulator Capable of Modeling High‐Order Epistasis for Complex Disease

Genome‐wide association studies (GWAS) have been successful in finding numerous new risk variants for complex diseases, but the results almost exclusively rely on single‐marker scans. Methods that can analyze joint effects of many variants in GWAS data are still being developed and trialed. To evaluate the performance of such methods it is essential to have a GWAS data simulator that can rapidly simulate a large number of samples, and capture key features of real GWAS data such as linkage disequilibrium (LD) among single‐nucleotide polymorphisms (SNPs) and joint effects of multiple loci (multilocus epistasis). In the current study, we combine techniques for specifying high‐order epistasis among risk SNPs with an existing program GWAsimulator [Li and Li, 2008] to achieve rapid whole‐genome simulation with accurate modeling of complex interactions. We considered various approaches to specifying interaction models including the following: departure from product of marginal effects for pairwise interactions, product terms in logistic regression models for low‐order interactions, and penetrance tables conforming to marginal effect constraints for high‐order interactions or prescribing known biological interactions. Methods for conversion among different model specifications are developed using penetrance table as the fundamental characterization of disease models. The new program, called simGWA, is capable of efficiently generating large samples of GWAS data with high precision. We show that data simulated by simGWA are faithful to template LD structures, and conform to prespecified diseases models with (or without) interactions.     

Pretreatment 25‐Hydroxyvitamin D Levels and Durability of Anti–Tumor Necrosis Factor–α Therapy in Inflammatory Bowel Diseases

Introduction: Emerging evidence supports an immunologic role for 25‐hydroxyvitamin D (25(OH)D) in inflammatory bowel disease (IBD). Here we examined if pretreatment vitamin D status influences durability of anti–tumor necrosis factor (TNF)–α therapy in patients with Crohn's disease (CD) or ulcerative colitis (UC). Methods: All IBD patients who had plasma 25(OH)D level checked <3 months prior to initiating anti–TNF‐α therapy were included in this retrospective single‐center cohort study. Our main predictor variable was insufficient plasma 25(OH)D (<30 ng/mL). Cox proportional hazards model adjusting for potential confounders was used to identify the independent effect of pretreatment vitamin D on biologic treatment cessation. Results: Our study included 101 IBD patients (74 CD; median disease duration 9 years). The median index 25(OH)D level was 27 ng/mL (interquartile range, 20–33 ng/mL). One‐third of the patients had prior exposure to anti–TNF‐α therapy. On multivariate analysis, patients with insufficient vitamin D demonstrated earlier cessation of anti–TNF‐α therapy (hazard ratio [HR], 2.13; 95% confidence interval [CI], 1.03–4.39; P = .04). This effect was significant in patients who stopped treatment for loss of response (HR, 3.49; 95% CI, 1.34–9.09) and stronger for CD (HR, 2.38; 95% CI, 0.95–5.99) than UC (P = NS). Conclusions: Our findings suggest that vitamin D levels may influence durability of anti–TNF‐α induction and maintenance therapy. Larger cohort studies and clinical trials of supplemental vitamin D use with disease activity as an end point may be warranted.     

Multi-ethnic analysis shows genetic risk and environmental predictors interact to influence 25(OH)D concentration and optimal vitamin D intake

25-Hydroxyvitamin D (25(OH)D) concentration is a complex trait with genetic and environmental predictors that may determine how much vitamin D exposure is required to reach optimal concentration. Interactions between continuous measures of a polygenic score (PGS) and vitamin D intake (PGS*intake) or available ultraviolet (UV) radiation (PGS*UV) were evaluated in individuals of African (n = 1,099) or European (n = 8,569) ancestries. Interaction terms and joint effects (main and interaction terms) were tested using one-degree of freedom (1-DF) and 2-DF models, respectively. Models controlled for age, sex, body mass index, cohort, and dietary intake/available UV. In addition, in participants achieving Institute of Medicine (IOM) vitamin D intake recommendations, 25(OH)D was evaluated by level PGS. The 2-DF PGS*intake, 1-DF PGS*UV, and 2-DF PGS*UV results were statistically significant in participants of European ancestry (p = 3.3 × 10⁻¹⁸, p = 2.1 × 10⁻², and p = 2.4 × 10⁻¹⁹, respectively), but not in those of African ancestry. In European-ancestry participants reaching IOM vitamin D intake guidelines, the percent of participants achieving adequate 25(OH)D ( > 20 ng/ml) increased as genetic risk decreased (72% vs. 89% in highest vs. lowest risk; p = .018). Available UV radiation and vitamin D intake interact with genetics to influence 25(OH)D. Individuals with higher genetic risk may require more vitamin D exposure to maintain optimal 25(OH)D concentrations.     

A Robust Method for Genome‐Wide Association Meta‐Analysis With the Application to Circulating Insulin‐Like Growth Factor I Concentrations

Genome‐wide association studies (GWAS) offer an excellent opportunity to identify the genetic variants underlying complex human diseases. Successful utilization of this approach requires a large sample size to identify single nucleotide polymorphisms (SNPs) with subtle effects. Meta‐analysis is a cost‐efficient means to achieve large sample size by combining data from multiple independent GWAS; however, results from studies performed on different populations can be variable due to various reasons, including varied linkage equilibrium structures as well as gene‐gene and gene‐environment interactions. Nevertheless, one should expect effects of the SNP are more similar between similar populations than those between populations with quite different genetic and environmental backgrounds. Prior information on populations of GWAS is often not considered in current meta‐analysis methods, rendering such analyses less optimal for the detecting association. This article describes a test that improves meta‐analysis to incorporate variable heterogeneity among populations. The proposed method is remarkably simple in computation and hence can be performed in a rapid fashion in the setting of GWAS. Simulation results demonstrate the validity and higher power of the proposed method over conventional methods in the presence of heterogeneity. As a demonstration, we applied the test to real GWAS data to identify SNPs associated with circulating insulin‐like growth factor I concentrations.     

Genotype‐based matching to correct for population stratification in large‐scale case‐control genetic association studies

Genome‐wide association studies are helping to dissect the etiology of complex diseases. Although case‐control association tests are generally more powerful than family‐based association tests, population stratification can lead to spurious disease‐marker association or mask a true association. Several methods have been proposed to match cases and controls prior to genotyping, using family information or epidemiological data, or using genotype data for a modest number of genetic markers. Here, we describe a genetic similarity score matching (GSM) method for efficient matched analysis of cases and controls in a genome‐wide or large‐scale candidate gene association study. GSM comprises three steps: (1) calculating similarity scores for pairs of individuals using the genotype data; (2) matching sets of cases and controls based on the similarity scores so that matched cases and controls have similar genetic background; and (3) using conditional logistic regression to perform association tests. Through computer simulation we show that GSM correctly controls false‐positive rates and improves power to detect true disease predisposing variants. We compare GSM to genomic control using computer simulations, and find improved power using GSM. We suggest that initial matching of cases and controls prior to genotyping combined with careful re‐matching after genotyping is a method of choice for genome‐wide association studies. Genet. Epidemiol. 33:508–517, 2009. © 2009 Wiley‐Liss, Inc.     

Importance of Different Types of Prior Knowledge in Selecting Genome‐Wide Findings for Follow‐Up

Biological plausibility and other prior information could help select genome‐wide association (GWA) findings for further follow‐up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts’ opinions and empirical evidence to estimate the relative importance of 15 types of information at the single‐nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two‐round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNPs established as being associated with seven disease traits through GWA meta‐analysis and independent replication, with the corresponding frequency in a randomly selected set of SNPs. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta‐analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.     

Case‐only genome‐wide interaction study of disease risk,prognosis and treatment

Case‐control genome‐wide association (GWA) studies have facilitated the identification of susceptibility loci for many complex diseases; however, these studies are often not adequately powered to detect gene‐environment (G×E) and gene‐gene (G×G) interactions. Case‐only studies are more efficient than case‐control studies for detecting interactions and require no data on control subjects. In this article, we discuss the concept and utility of the case‐only genome‐wide interaction (COGWI) study, in which common genetic variants, measured genome‐wide, are screened for association with environmental exposures or genetic variants of interest. An observed G‐E (or G‐G) association, as measured by the case‐only odds ratio (OR), suggests interaction, but only if the interacting factors are unassociated in the population from which the cases were drawn. The case‐only OR is equivalent to the interaction risk ratio. In addition to risk‐related interactions, we discuss how the COGWI design can be used to efficiently detect G×G, G×E and pharmacogenetic interactions related to disease outcomes in the context of observational clinical studies or randomized clinical trials. Such studies can be conducted using only data on individuals experiencing an outcome of interest or individuals not experiencing the outcome of interest. Sharing data among GWA and COGWI studies of disease risk and outcome can further enhance efficiency. Sample size requirements for COGWI studies, as compared to case‐control GWA studies, are provided. In the current era of genome‐wide analyses, the COGWI design is an efficient and straightforward method for detecting G×G, G×E and pharmacogenetic interactions related to disease risk, prognosis and treatment response. Genet. Epidemiol. 34:7–15, 2010. © 2009 Wiley‐Liss, Inc.     

An improved score test for genetic association studies

Large-scale genome-wide association studies (GWAS) have become feasible recently because of the development of bead and chip technology. However, the success of GWAS partially depends on the statistical methods that are able to manage and analyze this sort of large-scale data. Currently, the commonly used tests for GWAS include the Cochran-Armitage trend test, the allelic χ(2) test, the genotypic χ(2) test, the haplotypic χ(2) test, and the multi-marker genotypic χ(2) test among others. From a methodological point of view, it is a great challenge to improve the power of commonly used tests, since these tests are commonly used precisely because they are already among the most powerful tests. In this article, we propose an improved score test that is uniformly more powerful than the score test based on the generalized linear model. Since the score test based on the generalized linear model includes the aforementioned commonly used tests as its special cases, our proposed improved score test is thus uniformly more powerful than these commonly used tests. We evaluate the performance of the improved score test by simulation studies and application to a real data set. Our results show that the power increases of the improved score test over the score test cannot be neglected in most cases.     

Vitamin D and the Risks of Depression and Anxiety: An Observational Analysis and Genome-Wide Environment Interaction Study

Previous studies have suggested that vitamin D (VD) was associated with psychiatric diseases, but efforts to elucidate the functional relevance of VD with depression and anxiety from genetic perspective have been limited. Based on the UK Biobank cohort, we first calculated polygenic risk score (PRS) for VD from genome-wide association study (GWAS) data of VD. Linear and logistic regression analysis were conducted to evaluate the associations of VD traits with depression and anxiety traits, respectively. Then, using individual genotype and phenotype data from the UK Biobank, genome-wide environment interaction studies (GWEIS) were performed to identify the potential effects of gene × VD interactions on the risks of depression and anxiety traits. In the UK Biobank cohort, we observed significant associations of blood VD level with depression and anxiety traits, as well as significant associations of VD PRS and depression and anxiety traits. GWEIS identified multiple candidate loci, such as rs114086183 (p = 4.11 × 10⁻⁸, LRRTM4) for self-reported depression status and rs149760119 (p = 3.88 × 10⁻⁸, GNB5) for self-reported anxiety status. Our study results suggested that VD was negatively associated with depression and anxiety. GWEIS identified multiple candidate genes interacting with VD, providing novel clues for understanding the biological mechanism potential associations between VD and psychiatric disorders.     

Identifying candidate causal variants via trans‐population fine‐mapping

Genome‐wide association studies have discovered and confirmed a large number of loci that are implicated with disease susceptibility and severity. Polymorphisms that emerged from these studies are mostly indirectly associated to the phenotype, and the natural progression is to identify the causal variants that are functionally responsible for these association signals. Long stretches of high linkage disequilibrium (LD) benefitted the initial discovery phase in a genome‐wide scan, allowing commercial genotyping products with imperfect coverage to detect genomic regions genuinely associated with the phenotype. However, regions of high LD confound the fine‐mapping phase, as markers that are perfectly correlated to the causal variants display similar evidence of phenotypic association, hampering the process of differentiating the functional polymorphisms from neighboring surrogates. Here, we explore the potential of integrating information across different populations for narrowing the candidate region that a causal variant resides in, and compare the efficacy of this process of trans‐population fine‐mapping with the extent of variation in patterns of LD between the populations. In addition, we explore two different strategies for pooling data across multiple populations for the purpose of prioritizing the rankings of the causal variants. Our results clearly establish the benefits of trans‐population analysis in reducing the number of possible candidates for the causal variants, particularly in genomic regions displaying strong evidence of inter‐population LD variation. Directly integrating the statistical evidence by summing the test statistics outperforms the standard meta‐analytic procedure. These findings have direct relevance to the design and analysis of ongoing fine‐mapping studies. Genet. Epidemiol. 34: 653‐664, 2010.© 2010 Wiley‐Liss, Inc.     

A General Efficient and Flexible Approach for Genome‐Wide Association Analyses of Imputed Genotypes in Family‐Based Designs

Genotype imputation is a critical technique for following up genome‐wide association studies. Efficient methods are available for dealing with the probabilistic nature of imputed single nucleotide polymorphisms (SNPs) in population‐based designs, but not for family‐based studies. We have developed a new analytical approach (FBATdosage), using imputed allele dosage in the general framework of family‐based association tests to bridge this gap. Simulation studies showed that FBATdosage yielded highly consistent type I error rates, whatever the level of genotype uncertainty, and a much higher power than the best‐guess genotype approach. FBATdosage allows fast linkage and association testing of several million of imputed variants with binary or quantitative phenotypes in nuclear families of arbitrary size with arbitrary missing data for the parents. The application of this approach to a family‐based association study of leprosy susceptibility successfully refined the association signal at two candidate loci, C1orf141‐IL23R on chromosome 1 and RAB32‐C6orf103 on chromosome 6.     

Associations of 25 Hydroxyvitamin D and High Sensitivity C-reactive Protein Levels in Early Life

Vitamin D deficiency and elevated high sensitivity C-reactive protein (hs-CRP) have been associated with several health outcomes, but knowledge on early life trajectories and association between 25 hydroxyvitamin D (25(OH)D) and hs-CRP is lacking. We investigated the association between longitudinal measurements of 25(OH)D and hs-CRP, respectively, from pregnancy to childhood and throughout childhood in two Danish mother–child cohorts—the COPSAC₂₀₁₀ and COPSAC₂₀₀₀. In COPSAC₂₀₁₀, there was an association between 25(OH)D concentrations at week 24 in pregnancy and at age 6 months in childhood (n = 633): estimate (95% CI); 0.114 (0.041;0.187), p = 0.002, and between 25(OH)D at age 6 months and 6 years (n = 475): 0.155 (0.083;0.228), p < 0.001. This was also demonstrated in the COPSAC₂₀₀₀ cohort between 25(OH)D concentrations in cord blood and at age 4 years (n = 188): 0.294 (0.127;0.461), p < 0.001 and at age 6 months and 4 years (n = 264): 0.260 (0.133;0.388), p < 0.001. In COPSAC₂₀₀₀, we also found an association between hs-CRP at age 6 months and 12 years in childhood (n = 232): 0.183 (0.076;0.289), p < 0.001. Finally, we found a negative association between the cross-sectional measurements of 25(OH)D and hs-CRP at age 6 months (n = 613) in COPSAC₂₀₁₀: −0.004 (−0.008;−0.0004), p = 0.030, but this was not replicated in COPSAC₂₀₀₀. In this study, we found evidence of associations across timepoints of 25(OH)D concentrations from mid-pregnancy to infancy and through childhood and associations between hs-CRP levels during childhood, although with weak correlations. We also found a negative cross-sectional association between 25(OH)D and hs-CRP concentrations in COPSAC₂₀₁₀ proposing a role of vitamin D in systemic low-grade inflammation, though this association was not present in COPSAC₂₀₀₀.