A versatile gene-based test for genome-wide association studies

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort

BACKGROUND

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks.

RESULTS

The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A).

CONCLUSIONS

This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer's disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington's disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses.

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia

BACKGROUND

Over the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15).

METHODS

We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls).

RESULTS

We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P = 9 × 10^-6). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23.

CONCLUSIONS

This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4.

Investigation of DNA repair-related SNPs underlying susceptibility to papillary thyroid carcinoma reveals MGMT as a novel candidate gene in Belarusian children exposed to radiation

BACKGROUND

Genetic factors may influence an individual's sensitivity to ionising radiation and therefore modify his/her risk of developing papillary thyroid carcinoma (PTC). Previously, we reported that common single nucleotide polymorphisms (SNPs) within the DNA damage recognition gene ATM contribute to PTC risk in Belarusian children exposed to fallout from the Chernobyl power plant accident. Here we explored in the same population the contribution of a panel of DNA repair-related SNPs in genes acting downstream of ATM.

METHODS

The association of 141 SNPs located in 43 DNA repair genes was examined in 75 PTC cases and 254 controls from the Gomel region in Belarus. All subjects were younger than 15 years at the time of the Chernobyl accident. Conditional logistic regressions accounting for radiation dose were performed with PLINK using the additive allelic inheritance model, and a linkage disequilibrium (LD)-based Bonferroni correction was used for correction for multiple testing.

RESULTS

The intronic SNP rs2296675 in MGMT was associated with an increased PTC risk [per minor allele odds ratio (OR) 2.54 95% CI 1.50, 4.30, P per allele = 0.0006, P corr.= 0.05], and gene-wide association testing highlighted a possible role for ERCC5 (P Gene = 0.01) and PCNA (P Gene = 0.05) in addition to MGMT (P Gene = 0.008).

CONCLUSIONS

These findings indicate that several genes acting in distinct DNA repair mechanisms contribute to PTC risk. Further investigation is needed to decipher the functional properties of the methyltransferase encoded by MGMT and to understand how alteration of such functions may lead to the development of the most common type of thyroid cancer.

A Genome-wide Association Analysis in Four Populations Reveals Strong Genetic Heterogeneity For Birth Weight

Low or high birth weight is one of the main causes for neonatal morbidity and mortality. They are also associated with adulthood chronic illness. Birth weight is a complex trait which is affected by baby's genes, maternal environments as well as the complex interactions between them. To understand the genetic basis of birth weight, we reanalyzed a genome-wide association study data set which consists of four populations, namely Thai, Afro-Caribbean, European, and Hispanic population with regular linear models. In addition to fit the data with parametric linear models, we fitted the data with a nonparametric varying-coefficient model to identify variants that are nonlinearly modulated by mother's condition to affect birth weight. For this purpose, we used baby's cord glucose level as the mother's environmental variable. At the 10^-5 genome-wide threshold, we identified 33 SNP variants in the Thai population, 26 SNPs in the Afro-Caribbean population, 18 SNPs in the European population, and 7 SNPs in the Hispanic population. Some of the variants are significantly modulated by baby's cord glucose level either linearly or nonlinearly, implying potential interactions between baby's gene and mother's glucose level to affect baby's birth weight. There is no overlap between variants identified in the four populations, indicating strong genetic heterogeneity of birth weight between the four ethnic groups. The findings of this study provide insights into the genetic basis of birth weight and reveal its genetic heterogeneity.

Genetic susceptibility to cardiovascular disease and risk of dementia

Several studies have shown cardiovascular disease (CVD) to be associated with dementia, but it is not clear whether CVD per se increases the risk of dementia or whether the association is due to shared risk factors. We tested how a genetic risk score (GRS) for coronary artery disease (CAD) affects dementia risk after CVD in 13 231 Swedish twins. We also utilized summarized genome-wide association data to study genetic overlap between CAD and Alzheimer´s disease (AD), and additionally between shared risk factors and each disease. There was no direct effect of a CAD GRS on dementia (hazard ratio 0.99, 95% confidence interval (CI): 0.98-1.01). However, the GRS for CAD modified the association between CVD and dementia within 3 years of CVD diagnosis, ranging from a hazard ratio of 1.59 (95% CI: 1.05-2.41) in the first GRS quartile to 1.91 (95% CI: 1.28-2.86) in the fourth GRS quartile. Using summary statistics, we found no genetic overlap between CAD and AD. We did, however, find that both AD and CAD share a significant genetic overlap with lipids, but that the overlap arose from clearly distinct gene clusters. In conclusion, genetic susceptibility to CAD was found to modify the association between CVD and dementia, most likely through associations with shared risk factors.

Association of atrial fibrillation susceptibility genes, atrial fibrillation phenotypes and response to catheter ablation: a gene-based analysis of GWAS data

Background

Previous studies have suggested PITX2, KCNN3 and ZFHX3 as atrial fibrillation (AF) susceptibility genes. Single common genetic polymorphisms of those genes have been linked with AF phenotypes and rhythm outcome of AF catheter ablation although their mechanisms remain elusive. New gene-based association tests may help clarifying genotype–phenotype correlations. Therefore, we hypothesized that PITX2, KCNN3 and ZFHX3 associate with left atrial enlargement and persistent AF and subsequently with ablation outcome.

Methods and results

Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing AF catheter ablation were genotyped for ~1,000,000 SNPs. Gene-based association was investigated using two different gene-based association tests (VEGAS, minSNP). Among the three candidate genes, only ZFHX3 associated with left atrial dilatation and AF recurrence after catheter ablation.

Conclusion

This study suggests a contribution of ZFHX3 to AF remodeling and response to therapy. Future and larger studies are necessary to replicate and apply these findings with an emphasis on designing AF pathophysiology-based multi-locus risk scores.

Additional Candidate Genes for Human Atherosclerotic Disease Identified Through Annotation Based on Chromatin Organization

Background—

As genome-wide association efforts, such as CARDIoGRAM and METASTROKE, are ongoing to reveal susceptibility loci for their underlying disease—atherosclerotic disease—identification of candidate genes explaining the associations of these loci has proven the main challenge. Many disease susceptibility loci colocalize with DNA regulatory elements, which influence gene expression through chromatin interactions. Therefore, the target genes of these regulatory elements can be considered candidate genes. Applying these biological principles, we used an alternative approach to annotate susceptibility loci and identify candidate genes for human atherosclerotic disease based on circular chromosome conformation capture followed by sequencing.

Methods and Results—

In human monocytes and coronary endothelial cells, we generated 63 chromatin interaction data sets for 37 active DNA regulatory elements that colocalize with known susceptibility loci for coronary artery disease (CARDIoGRAMplusC4D) and large artery stroke (METASTROKE). By circular chromosome conformation capture followed by sequencing, we identified a physical 3-dimensional interaction with 326 candidate genes expressed in at least 1 of these cell types, of which 294 have not been reported before. We highlight 16 genes based on expression quantitative trait loci.

Conclusions—

Our findings provide additional candidate-gene annotation for 37 disease susceptibility loci for human atherosclerotic disease that are of potential interest to better understand the complex pathophysiology of cardiovascular diseases.

Associations Between Genetic Variants of NADPH Oxidase-Related Genes and Blood Pressure Responses to Dietary Sodium Intervention: The GenSalt Study

BACKGROUND

The aim of this study was to comprehensively test the associations of genetic variants of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-related genes with blood pressure (BP) responses to dietary sodium intervention in a Chinese population.

METHODS

We conducted a 7-day low-sodium intervention followed by a 7-day high-sodium intervention among 1,906 participants in rural China. BP measurements were obtained at baseline and each dietary intervention using a random-zero sphygmomanometer. Linear mixed-effect models were used to assess the additive associations of 63 tag single-nucleotide polymorphisms in 11 NADPH oxidase-related genes with BP responses to dietary sodium intervention. Gene-based analyses were conducted using the truncated product method. The Bonferroni method was used to adjust for multiple testing in all analyses.

RESULTS

Systolic BP (SBP) response to high-sodium intervention significantly decreased with the number of minor T allele of marker rs6967221 in RAC1 (P = 4.51 × 10-4). SBP responses (95% confidence interval) for genotypes CC, CT, and TT were 5.03 (4.71, 5.36), 4.20 (3.54, 4.85), and 0.56 (-1.08, 2.20) mm Hg, respectively, during the high-sodium intervention. Gene-based analyses revealed that RAC1 was significantly associated with SBP response to high-sodium intervention (P = 1.00 × 10-6) and diastolic BP response to low-sodium intervention (P = 9.80 × 10-4).

CONCLUSIONS

These findings suggested that genetic variants of NADPH oxidase-related genes may contribute to the variation of BP responses to sodium intervention in Chinese population. Further replication of these findings is warranted.

Genome-wide association screens for Achilles tendon and ACL tears and tendinopathy

Achilles tendinopathy or rupture and anterior cruciate ligament (ACL) rupture are substantial injuries affecting athletes, associated with delayed recovery or inability to return to competition. To identify genetic markers that might be used to predict risk for these injuries, we performed genome-wide association screens for these injuries using data from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort consisting of 102,979 individuals. We did not find any single nucleotide polymorphisms (SNPs) associated with either of these injuries with a p-value that was genome-wide significant (p<5x10-8). We found, however, four and three polymorphisms with p-values that were borderline significant (p<10-6) for Achilles tendon injury and ACL rupture, respectively. We then tested SNPs previously reported to be associated with either Achilles tendon injury or ACL rupture. None showed an association in our cohort with a false discovery rate of less than 5%. We obtained, however, moderate to weak evidence for replication in one case; specifically, rs4919510 in MIR608 had a p-value of 5.1x10-3 for association with Achilles tendon injury, corresponding to a 7% chance of false replication. Finally, we tested 2855 SNPs in 90 candidate genes for musculoskeletal injury, but did not find any that showed a significant association below a false discovery rate of 5%. We provide data containing summary statistics for the entire genome, which will be useful for future genetic studies on these injuries.

Reporting Correct p Values in VEGAS Analyses

VEGAS (versatile gene-based association study) is a popular methodological framework to perform gene-based tests based on summary statistics from single-variant analyses. The approach incorporates linkage disequilibrium information from reference panels to account for the correlation of test statistics. The gene-based test can utilize three different types of tests. In 2015, the improved framework VEGAS2, using more detailed reference panels, was published. Both versions provide user-friendly web- and offline-based tools for the analysis. However, the implementation of the popular top-percentage test is erroneous in both versions. The p values provided by VEGAS2 are deflated/anti-conservative. Based on real data examples, we demonstrate that this can increase substantially the rate of false-positive findings and can lead to inconsistencies between different test options. We also provide code that allows the user of VEGAS to compute correct p values.

Gene-based genome-wide association study identified 19p13.3 for lean body mass

Lean body mass (LBM) is a complex trait for human health. To identify genomic loci underlying LBM, we performed a gene-based genome-wide association study of lean mass index (LMI) in 1000 unrelated Caucasian subjects, and replicated in 2283 unrelated Caucasians subjects. Gene-based association analyses highlighted the significant associations of three genes UQCR, TCF3 and MBD3 in one single locus 19p13.3 (discovery p = 6.10 × 10-5, 1.65 × 10-4 and 1.10 × 10-4; replication p = 2.21 × 10-3, 1.84 × 10-3 and 6.95 × 10-3; combined p = 2.26 × 10-6, 4.86 × 10-6 and 1.15 × 10-5, respectively). These results, together with the known functional relevance of the three genes to LMI, suggested that the 19p13.3 region containing UQCR, TCF3 and MBD3 genes was a novel locus underlying lean mass variation.

Genome-wide association study of body mass index in subjects with alcohol dependence

Outcomes related to disordered metabolism are common in alcohol dependence (AD). To investigate alterations in the regulation of body mass that occur in the context of AD, we performed a genome-wide association study (GWAS) of body mass index (BMI) in African Americans (AAs) and European Americans (EAs) with AD. Subjects were recruited for genetic studies of AD or drug dependence and evaluated using the Semi-structured Assessment for Drug Dependence and Alcoholism. We investigated a total of 2587 AAs and 2959 EAs with DSM-IV AD diagnosis. In the stage 1 sample (N = 4137), we observed three genome-wide significant (GWS) single-nucleotide polymorphism associations, rs200889048 (P = 8.98 * 10-12 ) and rs12490016 (P = 1.44 * 10-8 ) in EAs and rs1630623 (P = 5.14 * 10-9 ) in AAs and EAs meta-analyzed. In the stage 2 sample (N = 1409), we replicated 278, 253 and 168 of the stage 1 suggestive loci (P < 5*10-4 ) in AAs, EAs, and AAs and EAs meta-analyzed, respectively. A meta-analysis of stage 1 and stage 2 samples (N = 5546) identified two additional GWS signals: rs28562191 in EAs (P = 4.46 * 10-8 ) and rs56950471 in AAs (P = 1.57 * 10-9 ). Three of the GWS loci identified (rs200889048, rs12490016 and rs1630623) were not previously reported by GWAS of BMI in the general population, and two of them raise interesting hypotheses: rs12490016-a regulatory variant located within LINC00880, where there are other GWAS-identified variants associated with birth size, adiposity in newborns and bulimia symptoms, which also interact with social stress in relation to birth size; rs1630623-a regulatory variant related to ALDH1A1, a gene involved in alcohol metabolism and adipocyte plasticity. These loci offer molecular insights regarding the regulatory mechanisms of body mass in the context of AD.

Genetic variation in the endocannabinoid system and response to Cognitive Behavior Therapy for child anxiety disorders

Extinction learning is an important mechanism in the successful psychological treatment of anxiety. Individual differences in response and relapse following Cognitive Behavior Therapy may in part be explained by variability in the ease with which fears are extinguished or the vulnerability of these fears to re-emerge. Given the role of the endocannabinoid system in fear extinction, this study investigates whether genetic variation in the endocannabinoid system explains individual differences in response to CBT. Children (N = 1,309) with a primary anxiety disorder diagnosis were recruited. We investigated the relationship between variation in the CNR1, CNR2, and FAAH genes and change in primary anxiety disorder severity between pre- and post-treatment and during the follow-up period in the full sample and a subset with fear-based anxiety disorder diagnoses. Change in symptom severity during active treatment was nominally associated (P < 0.05) with two SNPs. During the follow-up period, five SNPs were nominally associated with a poorer treatment response (rs806365 [CNR1]; rs2501431 [CNR2]; rs2070956 [CNR2]; rs7769940 [CNR1]; rs2209172 [FAAH]) and one with a more favorable response (rs6928813 [CNR1]). Within the fear-based subset, the effect of rs806365 survived multiple testing corrections (P < 0.0016). We found very limited evidence for an association between variants in endocannabinoid system genes and treatment response once multiple testing corrections were applied. Larger, more homogenous cohorts are needed to allow the identification of variants of small but statistically significant effect and to estimate effect sizes for these variants with greater precision in order to determine their potential clinical utility. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

No Evidence That Genetic Variation in the Myeloid-Derived Suppressor Cell Pathway Influences Ovarian Cancer Survival

Background: The precise mechanism by which the immune system is adversely affected in cancer patients remains poorly understood, but the accumulation of immunosuppressive/protumorigenic myeloid-derived suppressor cells (MDSCs) is thought to be a prominent mechanism contributing to immunologic tolerance of malignant cells in epithelial ovarian cancer (EOC). To this end, we hypothesized genetic variation in MDSC pathway genes would be associated with survival after EOC diagnoses.Methods: We measured the hazard of death due to EOC within 10 years of diagnosis, overall and by invasive subtype, attributable to SNPs in 24 genes relevant in the MDSC pathway in 10,751 women diagnosed with invasive EOC. Versatile Gene-based Association Study and the admixture likelihood method were used to test gene and pathway associations with survival.Results: We did not identify individual SNPs that were significantly associated with survival after correction for multiple testing (P < 3.5 × 10-5), nor did we identify significant associations between the MDSC pathway overall, or the 24 individual genes and EOC survival.Conclusions: In this well-powered analysis, we observed no evidence that inherited variations in MDSC-associated SNPs, individual genes, or the collective genetic pathway contributed to EOC survival outcomes.Impact: Common inherited variation in genes relevant to MDSCs was not associated with survival in women diagnosed with invasive EOC. Cancer Epidemiol Biomarkers Prev; 26(3); 420-4. ©2016 AACR.

Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments

INTRODUCTION

We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci.

METHODS

We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions.

RESULTS

We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ toxicity, and NDUFS3, SLC25A11, ATP5H, and APP were differentially expressed in the temporal cortex.

DISCUSSION

Network analyses identified novel LOAD candidate genes. We demonstrated a functional role for four of these in a C. elegans model and found enrichment of differentially expressed genes in the temporal cortex.

Rare damaging variants in DNA repair and cell cycle pathways are associated with hippocampal and cognitive dysfunction: a combined genetic imaging study in first-episode treatment-naive patients with schizophrenia

Schizophrenia is a complex neurodevelopmental disorder where changes in both hippocampus and memory-related cognitive functions are central. However, the exact relationship between neurodevelopmental-genetic factors and hippocampal-cognitive dysfunction remains unclear. The general aim of our study is to link the occurrence of rare damaging mutations involved in susceptibility gene pathways to the structure and function of hippocampus in order to define genetically and phenotypically based subgroups in schizophrenia. In the present study, by analyzing the exome sequencing and magnetic resonance imaging data in 94 first-episode treatment-naive schizophrenia patients and 134 normal controls, we identified that a cluster of rare damaging variants (RDVs) enriched in DNA repair and cell cycle pathways was present only in a subgroup including 39 schizophrenic patients. Furthermore, we found that schizophrenic patients with this RDVs show increased resting-state functional connectivity (rsFC) between left hippocampus (especially for left dentate gyrus) and left inferior parietal cortex, as well as decreased rsFC between left hippocampus and cerebellum. Moreover, abnormal rsFC was related to the deficits of spatial working memory (SWM; that is known to recruit the hippocampus) in patients with the RDVs. Taken together, our data demonstrate for the first time, to our knowledge, that damaging rare variants of genes in DNA repair and cell cycle pathways are associated with aberrant hippocampal rsFC, which was further relative to cognitive deficits in first-episode treatment-naive schizophrenia. Therefore, our data provide some evidence for the occurrence of phenotypic alterations in hippocampal and SWM function in a genetically defined subgroup of schizophrenia.

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

BACKGROUND

The biological mechanisms by which cleaning products and disinfectants-an emerging risk factor-affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma.

OBJECTIVES

We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma.

METHODS

Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway-based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons.

RESULTS

Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking.

CONCLUSIONS

Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207-214; http://dx.doi.org/10.1289/EHP376.

Dissecting the genetics of complex traits using summary association statistics

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

Suggestive association between variants in IL1RAPL and asthma symptoms in Latin American children

Several genome-wide association studies have been conducted to investigate the influence of genetic polymorphisms in the development of allergic diseases, but few of them have included the X chromosome. The aim of present study was to perform an X chromosome-wide association study (X-WAS) for asthma symptoms. The study included 1307 children of which 294 were asthma cases. DNA was genotyped using 2.5 HumanOmni Beadchip from Illumina. Statistical analyses were performed in PLINK 1.9, MACH 1.0 and Minimac2. The variant rs12007907 (g.29483892C>A) in IL1RAPL gene was suggestively associated with asthma symptoms in discovery set (odds ratio (OR)=0.49, 95% confidence interval (CI): 0.37-0.67; P=3.33 × 10^-6). This result was replicated in the ProAr cohort in men only (OR=0.45, 95% CI: 0.21-0.95; P=0.038). Furthermore, investigating the functional role of the rs12007907 on the production a Th2-type cytokine, IL-13, we found a negative association between the minor allele A with IL-13 production in the discovery set (P=0.044). Gene-based analysis revealed that NUDT10 was the most consistently associated with asthma symptoms in discovery sample. In conclusion, the rs12007907 variant in IL1RAPL gene was negatively associated with asthma and IL-13 production in our study and a sex-specific association was observed in one of the validation samples. It suggests an effect on asthma susceptibility and may explain differences in severe asthma frequency between women and men.

Fine mapping genetic associations between the HLA region and extremely high intelligence

General cognitive ability (intelligence) is one of the most heritable behavioural traits and most predictive of socially important outcomes and health. We hypothesized that some of the missing heritability of IQ might lie hidden in the human leukocyte antigen (HLA) region, which plays a critical role in many diseases and traits but is not well tagged in conventional GWAS. Using a uniquely powered design, we investigated whether fine-mapping of the HLA region could narrow the missing heritability gap. Our case-control design included 1,393 cases with extremely high intelligence scores (top 0.0003 of the population equivalent to IQ > 147) and 3,253 unselected population controls. We imputed variants in 200 genes across the HLA region, one SNP (rs444921) reached our criterion for study-wide significance. SNP-based heritability of the HLA variants was small and not significant (h2 = 0.3%, SE = 0.2%). A polygenic score from the case-control genetic association analysis of SNPs in the HLA region did not significantly predict individual differences in intelligence in an independent unselected sample. We conclude that although genetic variation in the HLA region is important to the aetiology of many disorders, it does not appear to be hiding much of the missing heritability of intelligence.

Weighted Protein Interaction Network Analysis of Frontotemporal Dementia

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein–protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

Bayesian genome- and epigenome-wide association studies with gene level dependence

High-throughput genetic and epigenetic data are often screened for associations with an observed phenotype. For example, one may wish to test hundreds of thousands of genetic variants, or DNA methylation sites, for an association with disease status. These genomic variables can naturally be grouped by the gene they encode, among other criteria. However, standard practice in such applications is independent screening with a universal correction for multiplicity. We propose a Bayesian approach in which the prior probability of an association for a given genomic variable depends on its gene, and the gene-specific probabilities are modeled nonparametrically. This hierarchical model allows for appropriate gene and genome-wide multiplicity adjustments, and can be incorporated into a variety of Bayesian association screening methodologies with negligible increase in computational complexity. We describe an application to screening for differences in DNA methylation between lower grade glioma and glioblastoma multiforme tumor samples from The Cancer Genome Atlas. Software is available via the package BayesianScreening for R: github.com/lockEF/BayesianScreening.

A method for integrating neuroimaging into genetic models of learning performance

Specific learning disorders (SLD) are an archetypal example of how clinical neuropsychological (NP) traits can differ from underlying genetic and neurobiological risk factors. Disparate environmental influences and pathologies impact learning performance assessed through cognitive examinations and clinical evaluations, the primary diagnostic tools for SLD. We propose a neurobiological risk for SLD with neuroimaging biomarkers, which is integrated into a genome-wide association study (GWAS) of learning performance in a cohort of 479 European individuals between 8 and 21 years of age. We first identified six regions of interest (ROIs) in temporal and anterior cingulate regions where the group diagnosed with learning disability has the least overall variation, relative to the other group, in thickness, area, and volume measurements. Although we used the three imaging measures, the thickness was the leading contributor. Hence, we calculated the Euclidean distances between any two individuals based on their thickness measures in the six ROIs. Then, we defined the relative similarity of one individual according to the averaged ranking of pairwise distances from the individuals to those in the SLD group. The inverse of this relative similarity is called the neurobiological risk for the individual. Single nucleotide polymorphisms in the AGBL1 gene on chromosome 15 had a significant association with learning performance at a genome-wide level. This finding was supported in an independent cohort of 2,327 individuals of the same demographic profile. Our statistical approach for integrating genetic and neuroimaging biomarkers can be extended into studying the biological basis of other NP traits.

Genome-Wide and Gene-Based Meta-Analyses Identify Novel Loci Influencing Blood Pressure Response to Hydrochlorothiazide

This study aimed to identify novel loci influencing the antihypertensive response to hydrochlorothiazide monotherapy. A genome-wide meta-analysis of blood pressure (BP) response to hydrochlorothiazide was performed in 1739 white hypertensives from 6 clinical trials within the International Consortium for Antihypertensive Pharmacogenomics Studies, making it the largest study to date of its kind. No signals reached genome-wide significance (P<5×10-8), and the suggestive regions (P<10-5) were cross-validated in 2 black cohorts treated with hydrochlorothiazide. In addition, a gene-based analysis was performed on candidate genes with previous evidence of involvement in diuretic response, in BP regulation, or in hypertension susceptibility. Using the genome-wide meta-analysis approach, with validation in blacks, we identified 2 suggestive regulatory regions linked to gap junction protein α1 gene (GJA1) and forkhead box A1 gene (FOXA1), relevant for cardiovascular and kidney function. With the gene-based approach, we identified hydroxy-delta-5-steroid dehydrogenase, 3 β- and steroid δ-isomerase 1 gene (HSD3B1) as significantly associated with BP response (P<2.28×10-4 ). HSD3B1 encodes the 3β-hydroxysteroid dehydrogenase enzyme and plays a crucial role in the biosynthesis of aldosterone and endogenous ouabain. By amassing all of the available pharmacogenomic studies of BP response to hydrochlorothiazide, and using 2 different analytic approaches, we identified 3 novel loci influencing BP response to hydrochlorothiazide. The gene-based analysis, never before applied to pharmacogenomics of antihypertensive drugs to our knowledge, provided a powerful strategy to identify a locus of interest, which was not identified in the genome-wide meta-analysis because of high allelic heterogeneity. These data pave the way for future investigations on new pathways and drug targets to enhance the current understanding of personalized antihypertensive treatment.

Pharmacogenetic study of long-term response to interferon-β treatment in multiple sclerosis

The aim of the study is the identification of genetic factors that influence the long-term response to interferon-β (IFNβ) (4-year follow-up). We performed a genome-wide association study in 337 IFNβ-treated Italian multiple sclerosis patients at the extreme of treatment response, and we meta-analyzed association effects, integrating results with pathway analysis, gene-expression profiling of IFNβ-stimulated peripheral blood mononuclear cells from 20 healthy controls (HC) and expression quantitative locus (eQTL) analyses. From meta-analysis, 43 markers were associated at P<10-4, and two of them (rs7298096 and rs4726460) pointed to two genes, NINJ2 and TBXAS1, that were significantly downregulated after IFNβ stimulation in HC (P=3.1 × 10-9 and 5.6 × 10-10). We also observed an eQTL effect for the allele associated with favorable treatment response (rs4726460A); moreover, TBXAS1 appeared downregulated upon IFNβ administration (β=-0.39; P=0.02). Finally, we found an enrichment of pathways related to inflammatory processes and presynaptic membrane, the latter with involvement of genes related to glutamatergic system (GRM3 and GRIK2), confirming its potential role in the response to IFNβ.

Genetic architecture of age-related cognitive decline in African Americans

OBJECTIVE

To identify genetic risk factors associated with susceptibility to age-related cognitive decline in African Americans (AAs).

METHODS

We performed a genome-wide association study (GWAS) and an admixture-mapping scan in 3,964 older AAs from 5 longitudinal cohorts; for each participant, we calculated a slope of an individual's global cognitive change from neuropsychological evaluations. We also performed a pathway-based analysis of the age-related cognitive decline GWAS.

RESULTS

We found no evidence to support the existence of a genomic region which has a strongly different contribution to age-related cognitive decline in African and European genomes. Known Alzheimer disease (AD) susceptibility variants in the ABCA7 and MS4A loci do influence this trait in AAs. Of interest, our pathway-based analyses returned statistically significant results highlighting a shared risk from lipid/metabolism and protein tyrosine signaling pathways between cognitive decline and AD, but the role of inflammatory pathways is polarized, being limited to AD susceptibility.

CONCLUSIONS

The genetic architecture of aging-related cognitive in AA individuals is largely similar to that of individuals of European descent. In both populations, we note a surprising lack of enrichment for immune pathways in the genetic risk for cognitive decline, despite strong enrichment of these pathways among genetic risk factors for AD.

Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior

Caffeine is the most widely consumed psychoactive substance in the world and presents with wide interindividual variation in metabolism. This variation may modify potential adverse or beneficial effects of caffeine on health. We conducted a genome-wide association study (GWAS) of plasma caffeine, paraxanthine, theophylline, theobromine and paraxanthine/caffeine ratio among up to 9,876 individuals of European ancestry from six population-based studies. A single SNP at 6p23 (near CD83) and several SNPs at 7p21 (near AHR), 15q24 (near CYP1A2) and 19q13.2 (near CYP2A6) met GW-significance (P < 5 × 10-8) and were associated with one or more metabolites. Variants at 7p21 and 15q24 associated with higher plasma caffeine and lower plasma paraxanthine/caffeine (slow caffeine metabolism) were previously associated with lower coffee and caffeine consumption behavior in GWAS. Variants at 19q13.2 associated with higher plasma paraxanthine/caffeine (slow paraxanthine metabolism) were also associated with lower coffee consumption in the UK Biobank (n = 94 343, P < 1.0 × 10-6). Variants at 2p24 (in GCKR), 4q22 (in ABCG2) and 7q11.23 (near POR) that were previously associated with coffee consumption in GWAS were nominally associated with plasma caffeine or its metabolites. Taken together, we have identified genetic factors contributing to variation in caffeine metabolism and confirm an important modulating role of systemic caffeine levels in dietary caffeine consumption behavior. Moreover, candidate genes identified encode proteins with important clinical functions that extend beyond caffeine metabolism.

Genome-Wide Association of Heroin Dependence in Han Chinese

Drug addiction is a costly and recurring healthcare problem, necessitating a need to understand risk factors and mechanisms of addiction, and to identify new biomarkers. To date, genome-wide association studies (GWAS) for heroin addiction have been limited; moreover they have been restricted to examining samples of European and African-American origin due to difficulty of recruiting samples from other populations. This is the first study to test a Han Chinese population; we performed a GWAS on a homogeneous sample of 370 Han Chinese subjects diagnosed with heroin dependence using the DSM-IV criteria and 134 ethnically matched controls. Analysis using the diagnostic criteria of heroin dependence yielded suggestive evidence for association between variants in the genes CCDC42 (coiled coil domain 42; p = 2.8x10^-7) and BRSK2 (BR serine/threonine 2; p = 4.110⁻⁶). In addition, we found evidence for risk variants within the ARHGEF10 (Rho guanine nucleotide exchange factor 10) gene on chromosome 8 and variants in a region on chromosome 20q13, which is gene-poor but has a concentration of mRNAs and predicted miRNAs. Gene-based association analysis identified genome-wide significant association between variants in CCDC42 and heroin addiction. Additionally, when we investigated shared risk variants between heroin addiction and risk of other addiction-related and psychiatric phenotypes using polygenic risk scores, we found a suggestive relationship with variants predicting tobacco addiction, and a significant relationship with variants predicting schizophrenia. Our genome wide association study of heroin dependence provides data in a novel sample, with functionally plausible results and evidence of genetic data of value to the field.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

Gene-Based Genome-Wide Association Analysis in European and Asian Populations Identified Novel Genes for Rheumatoid Arthritis

Objective

Rheumatoid arthritis (RA) is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations.

Methods

Gene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects). For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected ‘highly verified’ genes were measured by ELISA among our in-house RA cases and controls.

Results

A total of 221 RA-associated genes were newly identified by gene-based association study, including 71‘overlapped’, 76 ‘European-specific’ and 74 ‘Asian-specific’ genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 ‘overlapped’ (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA), 5 ‘European-specific’ (PHTF1, RPS18, BAK1, TNFRSF14, SUOX) and 4 ‘Asian-specific’ (RNASET2, HFE, BTN2A2, MAPK13) genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02) and HLA-DMA (P value = 4.70E-02) in plasma were significantly different in our in-house samples.

Conclusion

Our study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA genes. The study not only greatly increases our understanding of genetic susceptibility to RA, but also provides important insights into the ethno-genetic homogeneity and heterogeneity of RA in both ethnicities.

Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle

Average daily gain (ADG) is the most economically important trait in beef cattle industry. Using genome-wide association study (GWAS) approaches, previous studies have identified several causal variants within the PLAG1, NCAPG and LCORL genes for ADG in cattle. Multi-strategy GWASs were implemented in this study to improve detection and to explore the causal genes and regions. In this study, we conducted GWASs based on the genotypes of 1,173 Simmental cattle. In the SNP-based GWAS, the most significant SNPs (rs109303784 and rs110058857, P = 1.78 × 10⁻⁷) were identified in the NCAPG intron on BTA6 and explained 4.01% of the phenotypic variance, and the independent and significant SNP (rs110406669, P = 5.18 × 10⁻⁶) explained 3.32% of the phenotypic variance. Similarly, in the haplotype-based GWAS, the most significant haplotype block, Hap-6-N1416 (P = 2.56 × 10⁻⁸), spanned 12.7 kb on BTA6 and explained 4.85% of the phenotypic variance. Also, in the gene-based GWAS, seven significant genes were obtained which included DCAF16 and NCAPG. Moreover, analysis of the transcript levels confirmed that transcripts abundance of NCAPG (P = 0.046) and DCAF16 (P = 0.046) were significantly correlated with the ADG trait. Overall, our results from the multi-strategy GWASs revealed the DCAF16-NCAPG region to be a susceptibility locus for ADG in cattle.

Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

BACKGROUND

Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other "-omics" and interaction data.

SCOPE OF REVIEW

1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other "-omics" and interaction data.

MAJOR CONCLUSIONS

To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other "-omics" data and interaction can better explain gene functions.

GENERAL SIGNIFICANCE

Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.

Bayesian variable selection for post-analytic interrogation of susceptibility loci

Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material.

What can time-frequency and phase coherence measures tell us about the genetic basis of P3 amplitude?

In a recent comprehensive investigation, we largely failed to identify significant genetic markers associated with P3 amplitude or to corroborate previous associations between P3 and specific single nucleotide polymorphisms (SNPs) or genes. In the present study we extended this line of investigation to examine time-frequency (TF) activity and intertrial phase coherence (ITPC) in the P3 time window, both of which are associated with P3 amplitude. Previous genome-wide research has reported associations between P3-related theta and delta activity and individual genetic variants. A large, population-based sample of 4211 subjects, comprising male and female adolescent twins and their parents, was genotyped for 527,828 single nucleotide polymorphisms (SNPs), from which over six million SNPs were accurately imputed. Heritability estimates were greater for TF energy than ITPC, whether based on biometric models or the combined influence of all measured SNPs (derived from genome-wide complex trait analysis). The magnitude of overlap in the specific SNPs associated with delta energy and ITPC and P3 amplitude was significant. A genome-wide analysis of all SNPs, accompanied by an analysis of approximately 17,600 genes, indicated a region of chromosome 2 around TEKT4 that was significantly associated with theta ITPC. Analysis of candidate SNPs and genes previously reported to be associated with P3 or related phenotypes yielded one association surviving correction for multiple tests: between theta energy and CRHR1. However, we did not obtain significant associations for SNPs implicated in previous genome-wide studies of TF measures. Identifying specific genetic variants associated with P3 amplitude remains a challenge.

Genotype-Phenotype Study of the Middle Gangetic Plain in India Shows Association of rs2470102 with Skin Pigmentation

Our understanding of the genetics of skin pigmentation has been largely skewed towards populations of European ancestry, imparting less attention to South Asian populations, who behold huge pigmentation diversity. Here, we investigate skin pigmentation variation in a cohort of 1,167 individuals in the Middle Gangetic Plain of the Indian subcontinent. Our data confirm the association of rs1426654 with skin pigmentation among South Asians, consistent with previous studies, and also show association for rs2470102 single nucleotide polymorphism. Our haplotype analyses further help us delineate the haplotype distribution across social categories and skin color. Taken together, our findings suggest that the social structure defined by the caste system in India has a profound influence on the skin pigmentation patterns of the subcontinent. In particular, social category and associated single nucleotide polymorphisms explain about 32% and 6.4%, respectively, of the total phenotypic variance. Phylogeography of the associated single nucleotide polymorphisms studied across 52 diverse populations of the Indian subcontinent shows wide presence of the derived alleles, although their frequencies vary across populations. Our results show that both polymorphisms (rs1426654 and rs2470102) play an important role in the skin pigmentation diversity of South Asians.

Meta-GWAS and Meta-Analysis of Exome Array Studies Do Not Reveal Genetic Determinants of Serum Hepcidin

Serum hepcidin concentration is regulated by iron status, inflammation, erythropoiesis and numerous other factors, but underlying processes are incompletely understood. We studied the association of common and rare single nucleotide variants (SNVs) with serum hepcidin in one Italian study and two large Dutch population-based studies. We genotyped common SNVs with genome-wide association study (GWAS) arrays and subsequently performed imputation using the 1000 Genomes reference panel. Cohort-specific GWAS were performed for log-transformed serum hepcidin, adjusted for age and gender, and results were combined in a fixed-effects meta-analysis (total N 6,096). Six top SNVs (p<5x10-6) were genotyped in 3,821 additional samples, but associations were not replicated. Furthermore, we meta-analyzed cohort-specific exome array association results of rare SNVs with serum hepcidin that were available for two of the three cohorts (total N 3,226), but no exome-wide significant signal (p<1.4x10-6) was identified. Gene-based meta-analyses revealed 19 genes that showed significant association with hepcidin. Our results suggest the absence of common SNVs and rare exonic SNVs explaining a large proportion of phenotypic variation in serum hepcidin. We recommend extension of our study once additional substantial cohorts with hepcidin measurements, GWAS and/or exome array data become available in order to increase power to identify variants that explain a smaller proportion of hepcidin variation. In addition, we encourage follow-up of the potentially interesting genes that resulted from the gene-based analysis of low-frequency and rare variants.

Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population

BACKGROUND

Previous studies have shown that individuals with schizophrenia have a greater risk for psoriasis than a typical person. This suggests that there might be a shared genetic etiology between the 2 conditions. We aimed to characterize the potential shared genetic susceptibility between schizophrenia and psoriasis using genome-wide marker genotype data.

METHODS

We obtained genetic data on individuals with psoriasis, schizophrenia and control individuals. We applied a marker-based coheritability estimation procedure, polygenic score analysis, a gene set enrichment test and a least absolute shrinkage and selection operator regression model to estimate the potential shared genetic etiology between the 2 diseases. We validated the results in independent schizophrenia and psoriasis cohorts from Singapore.

RESULTS

We included 1139 individuals with psoriasis, 744 with schizophrenia and 1678 controls in our analysis, and we validated the results in independent cohorts, including 441 individuals with psoriasis (and 2420 controls) and 1630 with schizophrenia (and 1860 controls). We estimated that a large fraction of schizophrenia and psoriasis risk could be attributed to common variants (h²_SNP = 29% ± 5.0%, p = 2.00 × 10^-8), with a coheritability estimate between the traits of 21%. We identified 5 variants within the human leukocyte antigen (HLA) gene region, which were most likely to be associated with both diseases and collectively conferred a significant risk effect (odds ratio of highest risk quartile = 6.03, p < 2.00 × 10^-16). We discovered that variants contributing most to the shared heritable component between psoriasis and schizophrenia were enriched in antigen processing and cell endoplasmic reticulum.

LIMITATIONS

Our sample size was relatively small. The findings of 5 HLA gene variants were complicated by the complex structure in the HLA region.

CONCLUSION

We found evidence for a shared genetic etiology between schizophrenia and psoriasis. The mechanism for this shared genetic basis likely involves immune and calcium signalling pathways.

Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis

BACKGROUND

Oesophageal adenocarcinoma represents one of the fastest rising cancers in high-income countries. Barrett's oesophagus is the premalignant precursor of oesophageal adenocarcinoma. However, only a few patients with Barrett's oesophagus develop adenocarcinoma, which complicates clinical management in the absence of valid predictors. Within an international consortium investigating the genetics of Barrett's oesophagus and oesophageal adenocarcinoma, we aimed to identify novel genetic risk variants for the development of Barrett's oesophagus and oesophageal adenocarcinoma.

METHODS

We did a meta-analysis of all genome-wide association studies of Barrett's oesophagus and oesophageal adenocarcinoma available in PubMed up to Feb 29, 2016; all patients were of European ancestry and disease was confirmed histopathologically. All participants were from four separate studies within Europe, North America, and Australia and were genotyped on high-density single nucleotide polymorphism (SNP) arrays. Meta-analysis was done with a fixed-effects inverse variance-weighting approach and with a standard genome-wide significance threshold (p<5 × 10-8). We also did an association analysis after reweighting of loci with an approach that investigates annotation enrichment among genome-wide significant loci. Furthermore, the entire dataset was analysed with bioinformatics approaches-including functional annotation databases and gene-based and pathway-based methods-to identify pathophysiologically relevant cellular mechanisms.

FINDINGS

Our sample comprised 6167 patients with Barrett's oesophagus and 4112 individuals with oesophageal adenocarcinoma, in addition to 17 159 representative controls from four genome-wide association studies in Europe, North America, and Australia. We identified eight new risk loci associated with either Barrett's oesophagus or oesophageal adenocarcinoma, within or near the genes CFTR (rs17451754; p=4·8 × 10-10), MSRA (rs17749155; p=5·2 × 10-10), LINC00208 and BLK (rs10108511; p=2·1 × 10-9), KHDRBS2 (rs62423175; p=3·0 × 10-9), TPPP and CEP72 (rs9918259; p=3·2 × 10-9), TMOD1 (rs7852462; p=1·5 × 10-8), SATB2 (rs139606545; p=2·0 × 10-8), and HTR3C and ABCC5 (rs9823696; p=1·6 × 10-8). The locus identified near HTR3C and ABCC5 (rs9823696) was associated specifically with oesophageal adenocarcinoma (p=1·6 × 10-8) and was independent of Barrett's oesophagus development (p=0·45). A ninth novel risk locus was identified within the gene LPA (rs12207195; posterior probability 0·925) after reweighting with significantly enriched annotations. The strongest disease pathways identified (p<10-6) belonged to muscle cell differentiation and to mesenchyme development and differentiation.

INTERPRETATION

Our meta-analysis of genome-wide association studies doubled the number of known risk loci for Barrett's oesophagus and oesophageal adenocarcinoma and revealed new insights into causes of these diseases. Furthermore, the specific association between oesophageal adenocarcinoma and the locus near HTR3C and ABCC5 might constitute a novel genetic marker for prediction of the transition from Barrett's oesophagus to oesophageal adenocarcinoma. Fine-mapping and functional studies of new risk loci could lead to identification of key molecules in the development of Barrett's oesophagus and oesophageal adenocarcinoma, which might encourage development of advanced prevention and intervention strategies.

FUNDING

US National Cancer Institute, US National Institutes of Health, National Health and Medical Research Council of Australia, Swedish Cancer Society, Medical Research Council UK, Cambridge NIHR Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, Else Kröner Fresenius Stiftung, Wellcome Trust, Cancer Research UK, AstraZeneca UK, University Hospitals of Leicester, University of Oxford, Australian Research Council.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

The growth hormone/insulin‐like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF‐related proteins including IGF‐I and IGF‐binding protein‐3 (IGFBP‐3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF‐I and IGFBP‐3 concentrations (IGF1, IGFBP3,GCKR,TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP‐3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF‐I and IGFBP‐3 concentrations. The IGF‐I‐decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity‐associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF‐I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF‐I‐ and IGFBP‐3‐associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF‐I and IGFBP‐3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity‐associated loci.

Gene and Network Analysis of Common Variants Reveals Novel Associations in Multiple Complex Diseases

Genome-wide association (GWA) studies typically lack power to detect genotypes significantly associated with complex diseases, where different causal mutations of small effect may be present across cases. A common, tractable approach for identifying genomic elements associated with complex traits is to evaluate combinations of variants in known pathways or gene sets with shared biological function. Such gene-set analyses require the computation of gene-level P-values or gene scores; these gene scores are also useful when generating hypotheses for experimental validation. However, commonly used methods for generating GWA gene scores are computationally inefficient, biased by gene length, imprecise, or have low true positive rate (TPR) at low false positive rates (FPR), leading to erroneous hypotheses for functional validation. Here we introduce a new method, PEGASUS, for analytically calculating gene scores. PEGASUS produces gene scores with as much as 10 orders of magnitude higher numerical precision than competing methods. In simulation, PEGASUS outperforms existing methods, achieving up to 30% higher TPR when the FPR is fixed at 1%. We use gene scores from PEGASUS as input to HotNet2 to identify networks of interacting genes associated with multiple complex diseases and traits; this is the first application of HotNet2 to common variation. In ulcerative colitis and waist-hip ratio, we discover networks that include genes previously associated with these phenotypes, as well as novel candidate genes. In contrast, existing methods fail to identify these networks. We also identify networks for attention-deficit/hyperactivity disorder, in which GWA studies have yet to identify any significant SNPs.

Fast set-based association analysis using summary data from GWAS identifies novel gene loci for human complex traits

We propose a method (fastBAT) that performs a fast set-based association analysis for human complex traits using summary-level data from genome-wide association studies (GWAS) and linkage disequilibrium (LD) data from a reference sample with individual-level genotypes. We demonstrate using simulations and analyses of real datasets that fastBAT is more accurate and orders of magnitude faster than the prevailing methods. Using fastBAT, we analyze summary data from the latest meta-analyses of GWAS on 150,064-339,224 individuals for height, body mass index (BMI), and schizophrenia. We identify 6 novel gene loci for height, 2 for BMI, and 3 for schizophrenia at PfastBAT < 5 × 10(-8). The gain of power is due to multiple small independent association signals at these loci (e.g. the THRB and FOXP1 loci for schizophrenia). The method is general and can be applied to GWAS data for all complex traits and diseases in humans and to such data in other species.

Gene-based analysis of regulatory variants identifies 4 putative novel asthma risk genes related to nucleotide synthesis and signaling

BACKGROUND

Hundreds of genetic variants are thought to contribute to variation in asthma risk by modulating gene expression. Methods that increase the power of genome-wide association studies (GWASs) to identify risk-associated variants are needed.

OBJECTIVE

We sought to develop a method that aggregates the evidence for association with disease risk across expression quantitative trait loci (eQTLs) of a gene and use this approach to identify asthma risk genes.

METHODS

We developed a gene-based test and software package called EUGENE that (1) is applicable to GWAS summary statistics; (2) considers both cis- and trans-eQTLs; (3) incorporates eQTLs identified in different tissues; and (4) uses simulations to account for multiple testing. We applied this approach to 2 published asthma GWASs (combined n = 46,044) and used mouse studies to provide initial functional insights into 2 genes with novel genetic associations.

RESULTS

We tested the association between asthma and 17,190 genes that were found to have cis- and/or trans-eQTLs across 16 published eQTL studies. At an empirical FDR of 5%, 48 genes were associated with asthma risk. Of these, for 37, the association was driven by eQTLs located in established risk loci for allergic disease, including 6 genes not previously implicated in disease cause (eg, LIMS1, TINF2, and SAFB). The remaining 11 significant genes represent potential novel genetic associations with asthma. The association with 4 of these replicated in an independent GWAS: B4GALT3, USMG5, P2RY13, and P2RY14, which are genes involved in nucleotide synthesis or nucleotide-dependent cell activation. In mouse studies, P2ry13 and P2ry14-purinergic receptors activated by adenosine 5-diphosphate and UDP-sugars, respectively-were upregulated after allergen challenge, notably in airway epithelial cells, eosinophils, and neutrophils. Intranasal exposure with receptor agonists induced the release of IL-33 and subsequent eosinophil infiltration into the lungs.

CONCLUSION

We identified novel associations between asthma and eQTLs for 4 genes related to nucleotide synthesis/signaling and demonstrated the power of gene-based analyses of GWASs.

STAMS: STRING-assisted module search for genome wide association studies and application to autism

Motivation: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association results with genetic networks to infer the key phenotype-modulating subnetworks combat these issues, but have primarily been limited to network definitions with yes/no labels for gene-gene interactions. A recent method (EW_dmGWAS) incorporates a biological network with weighted edge probability by requiring a secondary phenotype-specific expression dataset. In this article, we combine an algorithm for weighted-edge module searching and a probabilistic interaction network in order to develop a method, STAMS, for recovering modules of genes with strong associations to the phenotype and probable biologic coherence. Our method builds on EW_dmGWAS but does not require a secondary expression dataset and performs better in six test cases.

Results: We show that our algorithm improves over EW_dmGWAS and standard gene-based analysis by measuring precision and recall of each method on separately identified associations. In the Wellcome Trust Rheumatoid Arthritis study, STAMS-identified modules were more enriched for separately identified associations than EW_dmGWAS (STAMS P-value 3.0 × 10⁻⁴; EW_dmGWAS- P-value = 0.8). We demonstrate that the area under the Precision-Recall curve is 5.9 times higher with STAMS than EW_dmGWAS run on the Wellcome Trust Type 1 Diabetes data.

Availability and Implementation: STAMS is implemented as an R package and is freely available at https://simtk.org/projects/stams.

Contact:rbaltman@stanford.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Evidence of Polygenic Adaptation in the Systems Genetics of Anthropometric Traits

Many signals of natural selection have been identified in the human genome. However, except for some single-locus mechanisms, most molecular processes generating these adaptation signals are still unknown. We developed an approach that integrates datasets related to genome-wide association studies (GWAS) with information about systems biology and genetic signatures of natural selection to identify evidence of polygenic adaptation. Specifically, we focused on five anthropometric measurements: body mass index (BMI), height, waist-to-hip ratio adjusted for BMI (WHR), and waist circumference adjusted for BMI (WC), and sex differences for WHR and WC. We performed an enrichment analysis for signals of natural selection in protein interaction networks associated with anthropometric traits in European populations. The adaptation signals-enriched gene networks associated highlighted epistatic interactions in the context of polygenic selection for the investigated traits. These polygenic mechanisms indicated intriguing selective mechanisms related to the anthropometric traits: adult locomotory behavior for BMI, infection resistance for height, interplay between lipid transport and immune systems for WHR, and female-specific polygenic adaptation for WHR and WC. In conclusion, we observed evidence of polygenic adaptation in the context of systems genetics of anthropometric traits that indicates polygenic mechanisms related to the natural selection in European populations.

A multi-locus genetic association test for a dichotomous trait and its secondary phenotype

Genetic association studies often collect information on secondary phenotypes related to the primary disease status. In many situations, the secondary phenotypes are only measured in subjects with the disease condition. It would be advantageous to model the primary trait and the secondary phenotype together if they share certain level of genetic heritability. We propose a family of multi-locus testing procedures to detect the composite association between a set of genetic markers and two traits (the primary trait and a secondary phenotype), in order to identify genes influencing both traits. The proposed test is derived from a random effect model with two variance components, with each presenting the genetic effect on one trait, and incorporates a model selection procedure for seeking the optimal model to represent the two sources of genetic effects. We conduct simulation studies to evaluate performance of the proposed procedure and apply the method to a genome-wide association study of prostate cancer with the Gleason score as the secondary phenotype.

A genome-wide analysis of the response to inhaled β2-agonists in chronic obstructive pulmonary disease

Short-acting β2-agonist bronchodilators are the most common medications used in treating chronic obstructive pulmonary disease (COPD). Genetic variants determining bronchodilator responsiveness (BDR) in COPD have not been identified. We performed a genome-wide association study (GWAS) of BDR in 5789 current or former smokers with COPD in one African-American and four white populations. BDR was defined as the quantitative spirometric response to inhaled β2-agonists. We combined results in a meta-analysis. In the meta-analysis, single-nucleotide polymorphisms (SNPs) in the genes KCNK1 (P=2.02 × 10(-7)) and KCNJ2 (P=1.79 × 10(-7)) were the top associations with BDR. Among African Americans, SNPs in CDH13 were significantly associated with BDR (P=5.1 × 10(-9)). A nominal association with CDH13 was identified in a gene-based analysis in all subjects. We identified suggestive association with BDR among COPD subjects for variants near two potassium channel genes (KCNK1 and KCNJ2). SNPs in CDH13 were significantly associated with BDR in African Americans.The Pharmacogenomics Journal advance online publication, 27 October 2015; doi:10.1038/tpj.2015.65.

Genome-Wide Gene-Sodium Interaction Analyses on Blood Pressure: The Genetic Epidemiology Network of Salt-Sensitivity Study

We performed genome-wide analyses to identify genomic loci that interact with sodium to influence blood pressure (BP) using single-marker-based (1 and 2 df joint tests) and gene-based tests among 1876 Chinese participants of the Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) study. Among GenSalt participants, the average of 3 urine samples was used to estimate sodium excretion. Nine BP measurements were taken using a random zero sphygmomanometer. A total of 2.05 million single-nucleotide polymorphisms were imputed using Affymetrix 6.0 genotype data and the Chinese Han of Beijing and Japanese of Tokyo HapMap reference panel. Promising findings (P<1.00×10(-4)) from GenSalt were evaluated for replication among 775 Chinese participants of the Multi-Ethnic Study of Atherosclerosis (MESA). Single-nucleotide polymorphism and gene-based results were meta-analyzed across the GenSalt and MESA studies to determine genome-wide significance. The 1 df tests identified interactions for UST rs13211840 on diastolic BP (P=3.13×10(-9)). The 2 df tests additionally identified associations for CLGN rs2567241 (P=3.90×10(-12)) and LOC105369882 rs11104632 (P=4.51×10(-8)) with systolic BP. The CLGN variant rs2567241 was also associated with diastolic BP (P=3.11×10(-22)) and mean arterial pressure (P=2.86×10(-15)). Genome-wide gene-based analysis identified MKNK1 (P=6.70×10(-7)), C2orf80 (P<1.00×10(-12)), EPHA6 (P=2.88×10(-7)), SCOC-AS1 (P=4.35×10(-14)), SCOC (P=6.46×10(-11)), CLGN (P=3.68×10(-13)), MGAT4D (P=4.73×10(-11)), ARHGAP42 (P≤1.00×10(-12)), CASP4 (P=1.31×10(-8)), and LINC01478 (P=6.75×10(-10)) that were associated with at least 1 BP phenotype. In summary, we identified 8 novel and 1 previously reported BP loci through the examination of single-nucleotide polymorphism and gene-based interactions with sodium.

Associations of polymorphisms in TXNIP and gene-environment interactions with the risk of coronary artery disease in a Chinese Han population

Single nucleotide polymorphisms (SNPs) in thioredoxin-interacting protein (TXNIP) gene may modulate TXNIP expression, then increase the risk of coronary artery disease (CAD). In a two-stage case-control study with a total of 1818 CAD patients and 1963 controls, we genotyped three SNPs in TXNIP and found that the variant genotypes of SNPs rs7212 [odds ratio (OR) = 1.26, P = 0.001] and rs7211 (OR = 1.23, P = 0.005) were significantly associated with increased CAD risk under a dominant model. In haplotype analyses, compared with the reference haplotype, haplotype 'G-T' had a 1.22-fold increased risk of CAD (P = 0.003). We also observed the cumulative effects of SNPs rs7212 and rs7211 on CAD risk and the severity of coronary atherosclerosis. Moreover, the gene-environment interactions among the variant genotypes of SNP rs7212, smoking habit, alcohol drinking habit and history of type 2 diabetes were associated with a 3.70-fold increased risk of CAD (P < 0.001). Subsequent genotype-phenotype correlation analyses further observed the significant effects of SNP rs7212 on TXNIP mRNA expression, plasma TXNIP and malondialdehyde levels. Taken together, our data suggest that TXNIP SNPs may individually and cumulatively affect CAD risk through a possible mechanism for regulating TXNIP expression and gene-environment interactions.