Identification of a coagulation-related signature correlated with immune infiltration and their prognostic implications in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a fatal form of lung cancer with a poor prognosis. Coagulation system had been confirmed closely related to tumor progression and the hypercoagulable state encouraged the immune infiltration and development of tumor cells, leading to a poor prognosis in cancer patients. However, the use of the coagulation-related genes (CRGs) for prognosis in LUAD has yet to be determined. In this study, we constructed an immune-related signature (CRRS) and identified a potential coagulation-related biomarker (P2RX1). METHODS: We obtained a total of 209 CRGs based on two coagulation-related KEGG pathways, then developed the CRRS signature by using the TCGA-LUAD RNA-seq data via the procedure of LASSO-Cox regression, stepwise-Cox regression, univariate and multivariate Cox regression. Grouped by the CRRS, Kaplan-Meier survival curves and receiver operating characteristic curves were drawn for the training and validation sets, respectively. In addition, single-sample gene set enrichment analysis was exploited to explore immune infiltration level. Moreover, immunophenotypes and immunotherapy grouped by CRRS were further analyzed. RESULTS: We developed an immune-related signature (CRRS) composed of COL1A2, F2, PLAUR, C4BPA, and P2RX1 in LUAD. CRRS was an independent risk factor for overall survival and displayed stable and powerful performance. Additionally, CRRS possessed distinctly superior accuracy than traditional clinical variables and molecular features. Functional analysis indicated that the differentially high expressed genes in the low-risk group significantly enriched in T cell and B cell receptor signaling pathways. The low-risk group was sensitive to anti-PD-1/PD-L1 immunotherapy and displayed abundant immune infiltration and immune checkpoint gene expression. Finally, we identified an independent prognostic gene P2RX1. Low expression of P2RX1 associated with poor overall survival and decreased immune infiltration. CONCLUSIONS: Our study revealed a significant correlation between CRRS and immune infiltration. CRRS could serve as a promising tool to improve the clinical outcomes for individual LUAD patients.

Bi-directional causal effect between vitamin B12 and non-alcoholic fatty liver disease: Inferring from large population data.

Objectives: Many observational studies evaluate the association between vitamin B12 and non-alcoholic fatty liver disease (NAFLD). However, the causality of this association remains uncertain, especially in European populations. We conducted a bidirectional Mendelian randomization study to explore the association between vitamin B12 and NAFLD. Methods: Two-sample Mendelian randomization study was conducted. Summary statistics for vitamin B12 were acquired from a genome-wide association studies (GWAS) meta-analysis including 45,576 subjects. Summary-level data for NAFLD was obtained from a GWAS meta-analysis of 8,434 cases and 770,180 non-cases and another GWAS meta-analysis of 1,483 cases and 17,781 non-cases. Summary-level data for 4 enzymes including alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma glutamyltransferase (GGT), was available from the UK Biobank. Inverse variance weighting (as main analysis), weighted median estimate, robust adjusted profile score, MR-Egger, and MR-PRESSO (sensitivity analyses) were performed to calculate causal estimates. Results: Genetically predicted higher vitamin B12 concentrations were consistently associated with an increased NAFLD in two sources. The combined odds ratio (OR) of NAFLD was 1.30 (95% confidence interval (CI), 1.13 to 1.48; p < 0.001) per SD-increase in vitamin B12 concentrations. Genetic liability to NAFLD was also positively associated with vitamin B12 concentrations (Beta 0.08, 95%CI, 0.01 to 0.16; p = 0.034). Sensitivity analyses also revealed consistent results. Genetically predicted vitamin B12 concentrations showed no significant association with liver enzymes. Conclusion: The present study indicates that increased serum vitamin B12 concentrations may play a role in NAFLD risk. NAFLD also has a causal impact on elevated vitamin B12 concentrations in the circulation. Notably, vitamin B12 concentrations imply the levels of vitamin B12 in the circulation, and higher intake of vitamin B12 may not directly lead to higher levels of serum vitamin B12, instead the higher levels of vitamin B12 in the circulation may be caused by the dysregulation of the metabolism of this vitamin in this study. There exist bidirectional causal effects between serum vitamin B12 concentrations and risk of NAFLD in European individuals.

MR-BOIL: Causal inference in one-sample Mendelian randomization for binary outcome with integrated likelihood method.

Mendelian randomization is a statistical method for inferring the causal relationship between exposures and outcomes using an economics-derived instrumental variable approach. The research results are relatively complete when both exposures and outcomes are continuous variables. However, due to the noncollapsing nature of the logistic model, the existing methods inherited from the linear model for exploring binary outcome cannot take the effect of confounding factors into account, which leads to biased estimate of the causal effect. In this article, we propose an integrated likelihood method MR-BOIL to investigate causal relationships for binary outcomes by treating confounders as latent variables in one-sample Mendelian randomization. Under the assumption of a joint normal distribution of the confounders, we use expectation maximization algorithm to estimate the causal effect. Extensive simulations demonstrate that the estimator of MR-BOIL is asymptotically unbiased and that our method improves statistical power without inflating type I error rate. We then apply this method to analyze the data from Atherosclerosis Risk in Communications Study. The results show that MR-BOIL can better identify plausible causal relationships with high reliability, compared with the unreliable results of existing methods. MR-BOIL is implemented in R and the corresponding R code is provided for free download.

Association between homocysteine and nonalcoholic fatty liver disease: Mendelian randomisation study.

BACKGROUND: Many observational studies explore the relationship between homocysteine (Hcy) and nonalcoholic fatty liver disease (NAFLD), whereas the causality of this association remains uncertain, especially in European populations. We performed a bidirectional Mendelian randomisation study to elucidate the causal association between Hcy and NAFLD. Furthermore, we explored the relationship of Hcy with liver enzymes, including alkaline phosphatase (ALP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST). METHODS: Two-sample Mendelian randomisation study was conducted. Summary statistics for Hcy were obtained from a genome-wide association studies (GWAS) meta-analysis comprising 44,147 subjects. Summary-level data for NAFLD were acquired from a GWAS meta-analysis of 8434 cases and 770,180 noncases and another GWAS meta-analysis of 1483 cases and 17,781 noncases. Summary-level data for three liver enzymes were available from the UK Biobank. RESULTS: Genetic associations of Hcy concentrations with NAFLD and liver enzymes were observed. Genetically predicted higher Hcy concentrations were consistently associated with an increased NAFLD risk in two data sources. The combined odds ratio of NAFLD was 1.25 (95% confidence interval [CI], 1.05-1.45) per SD increase in Hcy concentrations. Genetically predicted higher Hcy concentrations showed significant association with ALP (Beta .69; 95% CI, 0.04-1.34), ALT (Beta 0.56; 95% CI, 0.15-0.97) and AST levels (Beta .57; 95% CI, 0.10-1.04). Genetic liability to NAFLD was not associated with Hcy concentrations. CONCLUSIONS: This study has clinical implications as it indicates that increased Hcy concentrations increase the relevant liver enzymes and may play a role in NAFLD risk in European populations.

Inferring causal effects of homocysteine and B-vitamin concentrations on bone mineral density and fractures: Mendelian randomization analyses.

Objectives: In the progress of bone metabolism, homocysteine (Hcy) and B vitamins play substantial roles. However, the causal associations of homocysteine, B-vitamin concentrations with bone mineral density (BMD), and fractures remain unclear. Therefore, we employed a two-sample Mendelian randomization (MR) design to infer the causal effects of Hcy and B vitamins on BMD and fractures. Methods: We selected instrumental variables from large genome-wide association studies (GWASs). Specifically, the exposures mainly included Hcy (sample size: 44,147), vitamin B12 (sample size: 45,576), folate (sample size: 37,465), and vitamin B6 (sample size: 1,864). The outcome variables included total body BMD (sample size: 66,628), heel BMD (sample size: 142,487), femoral neck BMD (sample size: 32,735), lumbar spine BMD (sample size: 28,498), and forearm BMD (sample size: 8143). Additionally, the total body BMD in several age strata was also included. Furthermore, the fractures of the forearm, femoral neck, lumbar spine, heel corresponding with the BMD regions, and femoral neck and lumbar spine BMD in men and women, separately, were added as additional outcomes. Two-sample MR approaches were utilized in this study. Inverse variance weighting (IVW) was adopted as the main analysis. MR-PRESSO, MR-Egger, the weighted median estimate, and multivariable MR were performed as sensitivity methods. Results: In the main analysis, Hcy concentrations have an inverse association with heel BMD (Beta = 0.046, 95% confidence interval (CI) -0.073 to -0.019, P = 9.59E-04) per SD unit. In addition, for one SD increase of vitamin B12, the total body BMD decreased 0.083 unit (95%CI -0.126 to -0.040, P = 1.65E-04). The trend was more obvious in age over 45 years (Beta = -0.135, 95%CI -0.203-0.067, P = 9.86E-05 for age 45-60; Beta = -0.074, 95%CI -0.141 to -0.007, P = 0.031 for age over 60 years). No association of B vitamins and Hcy levels with the risk of fractures and femoral neck and lumbar spine BMD in men and women was found in this study. Other sensitivity MR methods elucidated consistent results. Conclusions: Our findings indicated that there exist the inversely causal effects of Hcy and vitamin B12 on BMD in certain body sites and age strata. These give novel clues for intervening bone-related diseases in public health and nutrition.

Causal effects of B vitamins and homocysteine on obesity and musculoskeletal diseases: A Mendelian randomization study.

Objectives: Although homocysteine (Hcy) increases the risk of cardiovascular diseases, its effects on obesity and musculoskeletal diseases remain unclear. We performed a Mendelian randomization study to estimate the associations between Hcy and B vitamin concentrations and their effects on obesity and musculoskeletal-relevant diseases in the general population. Methods: We selected independent single nucleotide polymorphisms of Hcy (n = 44,147), vitamin B12 (n = 45,576), vitamin B6 (n = 1864), and folate (n = 37,465) at the genome-wide significance level as instruments and applied them to the studies of summary-level data for fat and musculoskeletal phenotypes from the UK Biobank study (n = 331,117), the FinnGen consortium (n = 218,792), and other consortia. Two-sample Mendelian randomization (MR) approaches were utilized in this study. The inverse variance weighting (IVW) was adopted as the main analysis. MR-PRESSO, MR-Egger, the weighted median estimate, bidirectional MR, and multivariable MR were performed as sensitivity methods. Results: Higher Hcy concentrations were robustly associated with an increased risk of knee osteoarthritis [odds ratio (OR) 1.119; 95% confidence interval (CI) 1.032-1.214; P = 0.007], hospital-diagnosed osteoarthritis (OR 1.178; 95% CI 1.012-1.37; P = 0.034), osteoporosis with pathological fracture (OR 1.597; 95% CI 1.036-2.46; P = 0.034), and soft tissue disorder (OR 1.069; 95% CI 1.001-1.141; P = 0.045) via an inverse variance weighting method and other MR approaches. Higher vitamin B12 levels were robustly associated with decreased body fat percentage and its subtypes (all P < 0.05). Bidirectional analyses showed no reverse causation. Multivariable MR analyses and other sensitivity analyses showed directionally similar results. Conclusions: There exist significant causal effects of vitamin B12 in the serum and Hcy in the blood on fat and musculoskeletal diseases, respectively. These findings may have an important insight into the pathogenesis of obesity and musculoskeletal diseases and other possible future therapies.

Plant genetic diversity affects multiple trophic levels and trophic interactions.

Intraspecific genetic diversity is an important component of biodiversity. A substantial body of evidence has demonstrated positive effects of plant genetic diversity on plant performance. However, it has remained unclear whether plant genetic diversity generally increases plant performance by reducing the pressure of plant antagonists across trophic levels for different plant life forms, ecosystems and climatic zones. Here, we analyse 4702 effect sizes reported in 413 studies that consider effects of plant genetic diversity on trophic groups and their interactions. We found that that increasing plant genetic diversity decreased the performance of plant antagonists including invertebrate herbivores, weeds, plant-feeding nematodes and plant diseases, while increasing the performance of plants and natural enemies of herbivores. Structural equation modelling indicated that plant genetic diversity increased plant performance partly by reducing plant antagonist pressure. These results reveal that plant genetic diversity often influences multiple trophic levels in ways that enhance natural pest control in managed ecosystems and consumer control of plants in natural ecosystems for sustainable plant production.

Causal Association of Thyroid Signaling with C-Reactive Protein: A Bidirectional Mendelian Randomization.

Methods: Based on the latest genome-wide association study summary data, bidirectional two-sample Mendelian randomization (MR) was employed to detect the causal relationship and effect direction between TSH, fT4, and CRP. Furthermore, in view of obesity being an important risk factor of CVD, obesity trait waist-hip ratio (WHR) and body mass index (BMI) were treated as the research objects in MR analyses for exploring the causal effects of TSH and fT4 on them, respectively. Results: Genetically increased CRP was associated with increased TSH (ß = -0.02, P = 0.011) and with increased fT4 (ß = 0.043, P = 0.001), respectively, but there was no evidence that TSH or fT4 could affect CRP. In further analyses, genetically increased TSH was associated with decreased WHR (ß = -0.02, P = 3.99e - 4). Genetically increased WHR was associated with decreased fT4 (ß = -0.081, P = 0.002). Genetically increased BMI was associated with increased TSH (ß = 0.03, P = 0.028) and with decreased fT4 (ß = -0.078, P = 1.05e - 4). Causal associations of WHR and BMI with thyroid signaling were not supported by weighted median analysis in sensitivity analyses. Conclusion: TSH and fT4 were increased due to the higher genetically predicted CRP. WHR was decreased due to the higher genetically predicted TSH. These findings will provide reference for the prevention and treatment of inflammation and metabolic syndrome.

A Novel Hierarchical Clustering Approach for Joint Analysis of Multiple Phenotypes Uncovers Obesity Variants Based on ARIC.

Genome-wide association studies (GWASs) have successfully discovered numerous variants underlying various diseases. Generally, one-phenotype one-variant association study in GWASs is not efficient in identifying variants with weak effects, indicating that more signals have not been identified yet. Nowadays, jointly analyzing multiple phenotypes has been recognized as an important approach to elevate the statistical power for identifying weak genetic variants on complex diseases, shedding new light on potential biological mechanisms. Therefore, hierarchical clustering based on different methods for calculating correlation coefficients (HCDC) is developed to synchronously analyze multiple phenotypes in association studies. There are two steps involved in HCDC. First, a clustering approach based on the similarity matrix between two groups of phenotypes is applied to choose a representative phenotype in each cluster. Then, we use existing methods to estimate the genetic associations with the representative phenotypes rather than the individual phenotypes in every cluster. A variety of simulations are conducted to demonstrate the capacity of HCDC for boosting power. As a consequence, existing methods embedding HCDC are either more powerful or comparable with those of without embedding HCDC in most scenarios. Additionally, the application of obesity-related phenotypes from Atherosclerosis Risk in Communities via existing methods with HCDC uncovered several associated variants. Among these, UQCC1-rs1570004 is reported as a significant obesity signal for the first time, whose differential expression in subcutaneous fat, visceral fat, and muscle tissue is worthy of further functional studies.

Cancer-associated dynamics and potential regulators of intronic polyadenylation revealed by IPAFinder using standard RNA-seq data.

Intronic polyadenylation (IpA) usually leads to changes in the coding region of an mRNA, and its implication in diseases has been recognized, although at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2 Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m6A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.

A Novel Approach Integrating Hierarchical Clustering and Weighted Combination for Association Study of Multiple Phenotypes and a Genetic Variant.

As a pivotal research tool, genome-wide association study has successfully identified numerous genetic variants underlying distinct diseases. However, these identified genetic variants only explain a small proportion of the phenotypic variation for certain diseases, suggesting that there are still more genetic signals to be detected. One of the reasons may be that one-phenotype one-variant association study is not so efficient in detecting variants of weak effects. Nowadays, it is increasingly worth noting that joint analysis of multiple phenotypes may boost the statistical power to detect pathogenic variants with weak genetic effects on complex diseases, providing more clues for their underlying biology mechanisms. So a Weighted Combination of multiple phenotypes following Hierarchical Clustering method (WCHC) is proposed for simultaneously analyzing multiple phenotypes in association studies. A series of simulations are conducted, and the results show that WCHC is either the most powerful method or comparable with the most powerful competitor in most of the simulation scenarios. Additionally, we evaluated the performance of WCHC in its application to the obesity-related phenotypes from Atherosclerosis Risk in Communities, and several associated variants are reported.

A Novel Method for Mendelian Randomization Analyses With Pleiotropy and Linkage Disequilibrium in Genetic Variants From Individual Data.

Mendelian randomization makes use of genetic variants as instrumental variables to eliminate the influence induced by unknown confounders on causal estimation in epidemiology studies. However, with the soaring genetic variants identified in genome-wide association studies, the pleiotropy, and linkage disequilibrium in genetic variants are unavoidable and may produce severe bias in causal inference. In this study, by modeling the pleiotropic effect as a normally distributed random effect, we propose a novel mixed-effects regression model-based method PLDMR, pleiotropy and linkage disequilibrium adaptive Mendelian randomization, which takes linkage disequilibrium into account and also corrects for the pleiotropic effect in causal effect estimation and statistical inference. We conduct voluminous simulation studies to evaluate the performance of the proposed and existing methods. Simulation results illustrate the validity and advantage of the novel method, especially in the case of linkage disequilibrium and directional pleiotropic effects, compared with other methods. In addition, by applying this novel method to the data on Atherosclerosis Risk in Communications Study, we conclude that body mass index has a significant causal effect on and thus might be a potential risk factor of systolic blood pressure. The novel method is implemented in R and the corresponding R code is provided for free download.

A novel similarity score based on gene ranks to reveal genetic relationships among diseases.

Knowledge of similarities among diseases can contribute to uncovering common genetic mechanisms. Based on ranked gene lists, a couple of similarity measures were proposed in the literature. Notice that they may suffer from the determination of cutoff or heavy computational load, we propose a novel similarity score SimSIP among diseases based on gene ranks. Simulation studies under various scenarios demonstrate that SimSIP has better performance than existing rank-based similarity measures. Application of SimSIP in gene expression data of 18 cancer types from The Cancer Genome Atlas shows that SimSIP is superior in clarifying the genetic relationships among diseases and demonstrates the tendency to cluster the histologically or anatomically related cancers together, which is analogous to the pan-cancer studies. Moreover, SimSIP with simpler form and faster computation is more robust for higher levels of noise than existing methods and provides a basis for future studies on genetic relationships among diseases. In addition, a measure MAG is developed to gauge the magnitude of association of anindividual gene with diseases. By using MAG the genes and biological processes significantly associated with colorectal cancer are detected.

Global synthesis of effects of plant species diversity on trophic groups and interactions.

Numerous studies have demonstrated that plant species diversity enhances ecosystem functioning in terrestrial ecosystems, including diversity effects on insects (herbivores, predators and parasitoids) and plants. However, the effects of increased plant diversity across trophic levels in different ecosystems and biomes have not yet been explored on a global scale. Through a global meta-analysis of 2,914 observations from 351 studies, we found that increased plant species richness reduced herbivore abundance and damage but increased predator and parasitoid abundance, predation, parasitism and overall plant performance. Moreover, increased predator/parasitoid performance was correlated with reduced herbivore abundance and enhanced plant performance. We conclude that increasing plant species diversity promotes beneficial trophic interactions between insects and plants, ultimately contributing to increased ecosystem services.

A nonparametric test for association with multiple loci in the retrospective case-control study.

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance-covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.

Evidence on the causal link between homocysteine and hypertension from a meta-analysis of 40 173 individuals implementing Mendelian randomization.

Numerous researchers have investigated the associations among methylenetetrahydrofolate reductase gene (MTHFR) C677T polymorphism, homocysteine (Hcy) concentration, and hypertension. However, the results are controversial. Thus, a meta-analysis implementing Mendelian randomization approach was conducted to examine the hypothesis that elevated Hcy concentration plausibly contributes to increased risk of hypertension. Based on several inclusion and exclusion criteria, eligible studies were selected to explore the correlation between MTHFR C677T and hypertension risk, MTHFR C677T and Hcy concentration in hypertension, and Hcy concentration and hypertension, and they were evaluated by odds ratios (ORs), effect size (ES), and standard mean difference with their corresponding 95% confidence intervals (95% CIs), respectively. Moreover, Mendelian randomization was implemented to evaluate the relationship between Hcy and hypertension. Consequently, 14 378 cases and 25 795 controls were involved in this study and the results showed that MTHFR C677T led to an elevated risk of hypertension (for T vs C: OR = 1.27, 95% CI = 1.17-1.37; for TT vs CC: OR = 1.53, 95% CI = 1.30-1.79). Additionally, in hypertensive subjects, the pooled Hcy concentration in individuals of TT genotype was 7.74 µmol/L (95% CI: 5.25-10.23) greater than that in individuals of CC genotype. Moreover, the pooled Hcy concentration in hypertensive was 0.69 µmol/L (95% CI: 0.50-0.87) greater than that in controls. The estimated causal OR associated with hypertension was 1.32 for 5 µmol/L Hcy increment. Via MTHFR C677T polymorphism, the findings in the present study demonstrated that there exists evidence on causal link between Hcy concentration and the risk of hypertension.

Plausible relationship between homocysteine and obesity risk via MTHFR gene: a meta-analysis of 38,317 individuals implementing Mendelian randomization.

OBJECTIVE: Numerous studies have explored the role of methylenetetrahydrofolate reductase gene (MTHFR) C677T polymorphism and homocysteine (Hcy) concentration in obesity, but the results are inconsistent. Hence, we performed a meta-analysis implementing Mendelian randomization approach to test the assumption that the increased Hcy concentration is plausibly related to the elevated risk of obesity. METHODS: Eligible studies were selected based on several inclusion and exclusion criteria. Correlations between MTHFR C677T and obesity risk, MTHFR C677T and Hcy concentration in obesity, Hcy concentration, and obesity were estimated by ORs, effect size and standard mean difference with their corresponding 95% CIs, respectively. Furthermore, Mendelian randomization analysis was performed to estimate the relationship between Hcy level and obesity. RESULTS: Consequently, this meta-analysis implemented with Mendelian randomization approach was conducted among 8,622 cases and 29,695 controls. The results indicated that MTHFR C677T is associated with an increased risk of obesity (for T vs C: OR=1.06, 95% CI=1.02-1.10; for TT vs CC: OR=1.13, 95% CI=1.03-1.24). Moreover, in obese subjects, the pooled Hcy concentration in individuals of TT genotype was 2.91 mmol/L (95% CI: 0.27-5.55) higher than that in individuals of CC genotype. Furthermore, the pooled Hcy concentration in subjects with obesity was 0.74 mmol/L (95% CI: 0.36-1.12) higher than that in controls. The evaluated plausible OR associated with obesity was 1.23 for 5 µmol/L Hcy level increase. CONCLUSIONS: Through this meta-analysis, we emphasize a strong relationship between Hcy level and obesity by virtue of MTHFR C677T polymorphism.

Gene-gene interactions and associations of six hypertension related single nucleotide polymorphisms with obesity risk in a Chinese children population.

Obesity is a major risk for hypertension. However, the associations between hypertension susceptibility loci and the risk of obesity as well as the effects of gene-gene interactions are unclear, especially in the Chinese children population. Six single nucleotide polymorphisms (SNPs) (ATP2B1 rs17249754, CSK rs1378942, MTHFR rs1801133, CYP17A1 rs1004467, STK39 rs3754777, FGF5 rs16998073) were genotyped for 3503 Chinese children, aged 6-18 years. Of them, 758 obese cases and 2745 controls were identified based on the International Obesity Task Force age- and sex-specific BMI references. Among the six SNPs, three were associated with obesity risk (CSK rs1378942: odds ratio (OR) = 1.20, 95% confidence interval (CI) 1.01-1.43, P = 0.042; MTHFR rs1801133: OR = 1.19, 95% CI 1.05-1.34, P = 0.006; FGF5 rs16998073: OR = 1.14, 95% CI 1.00-1.29, P = 0.047). The genetic risk score (GRS), based on these three SNPs (CSK rs1378942, MTHFR rs1801133, FGF5 rs16998073), showed a positive association with risk of obesity (OR = 1.18, 95% CI 1.09-1.28, P = 7.60 × 10-5). The same association signals were also detected in the subgroups of puberty and inactivity. In addition, interaction analyses among these loci implied a potential gene-gene interaction between MTHFR and FGF5. These findings show a significant association of hypertension susceptibility loci in Chinese children, suggesting a likely influence of genetic and environmental factors on the risk of obesity.

Indirect effect inference and application to GAW20 data.

BACKGROUND: Association studies using a single type of omics data have been successful in identifying disease-associated genetic markers, but the underlying mechanisms are unaddressed. To provide a possible explanation of how these genetic factors affect the disease phenotype, integration of multiple omics data is needed. RESULTS: We propose a novel method, LIPID (likelihood inference proposal for indirect estimation), that uses both single nucleotide polymorphism (SNP) and DNA methylation data jointly to analyze the association between a trait and SNPs. The total effect of SNPs is decomposed into direct and indirect effects, where the indirect effects are the focus of our investigation. Simulation studies show that LIPID performs better in various scenarios than existing methods. Application to the GAW20 data also leads to encouraging results, as the genes identified appear to be biologically relevant to the phenotype studied. CONCLUSIONS: The proposed LIPID method is shown to be meritorious in extensive simulations and in real-data analyses.