SCAN: SNP and copy number annotation

Response to interferon-beta treatment in multiple sclerosis patients: a genome-wide association study

Up to 50% of multiple sclerosis (MS) patients do not respond to interferon-beta (IFN-β) treatment and determination of response requires lengthy clinical follow-up of up to 2 years. Response predictive genetic markers would significantly improve disease management. We aimed to identify IFN-β treatment response genetic marker(s) by performing a two-stage genome-wide association study (GWAS). The GWAS was carried out using data from 151 Australian MS patients from the ANZgene/WTCCC2 MS susceptibility GWAS (responder (R)=51, intermediate responders=24 and non-responders (NR)=76). Of the single-nucleotide polymorphisms (SNP) that were validated in an independent group of 479 IFN-β-treated MS patients from Australia, Spain and Italy (R=273 and NR=206), eight showed evidence of association with treatment response. Among the replicated associations, the strongest was observed for FHIT (Fragile Histidine Triad; combined P-value 6.74 × 10^-6) and followed by variants in GAPVD1 (GTPase activating protein and VPS9 domains 1; combined P-value 5.83 × 10^-5) and near ZNF697 (combined P-value 8.15 × 10^-5).

The phenotypic legacy of admixture between modern humans and Neandertals

Many modern human genomes retain DNA inherited from interbreeding with archaic hominins, such as Neandertals, yet the influence of this admixture on human traits is largely unknown. We analyzed the contribution of common Neandertal variants to over 1000 electronic health record (EHR)-derived phenotypes in ~28,000 adults of European ancestry. We discovered and replicated associations of Neandertal alleles with neurological, psychiatric, immunological, and dermatological phenotypes. Neandertal alleles together explained a significant fraction of the variation in risk for depression and skin lesions resulting from sun exposure (actinic keratosis), and individual Neandertal alleles were significantly associated with specific human phenotypes, including hypercoagulation and tobacco use. Our results establish that archaic admixture influences disease risk in modern humans, provide hypotheses about the effects of hundreds of Neandertal haplotypes, and demonstrate the utility of EHR data in evolutionary analyses.

Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs

We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals, and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2, ZNF259/APOA5, KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5, LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol, and GCKR, TRIB1, ZNF259/APOA5 and NCAN/MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol (FN1 and SAMM50), two for HDL cholesterol (LOC100996634 and COPB1) and one for LDL cholesterol (LINC00324/CTC1/PFAS). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.

Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma

Primary open angle glaucoma (POAG) is a leading cause of blindness world-wide. To identify new susceptibility loci, we meta-analyzed GWAS results from 8 independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significant SNPs in two Australian studies (1,252 cases and 2,592 controls), 3 European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of top SNPs identified three novel loci: rs35934224[T] within TXNRD2 (odds ratio (OR) = 0.78, P = 4.05×10⁻¹¹ encoding a mitochondrial protein required for redox homeostasis; rs7137828[T] within ATXN2 (OR = 1.17, P = 8.73×10⁻¹⁰), and rs2745572[A] upstream of FOXC1 (OR = 1.17, P = 1.76×10⁻¹⁰). Using RT-PCR and immunohistochemistry, we show TXNRD2 and ATXN2 expression in retinal ganglion cells and the optic nerve head. These results identify new pathways underlying POAG susceptibility and suggest novel targets for preventative therapies.

Genome-wide association study identifies variation at 6q25.1 associated with survival in multiple myeloma

Survival following a diagnosis of multiple myeloma (MM) varies between patients and some of these differences may be a consequence of inherited genetic variation. In this study, to identify genetic markers associated with MM overall survival (MM-OS), we conduct a meta-analysis of four patient series of European ancestry, totalling 3,256 patients with 1,200 MM-associated deaths. Each series is genotyped for ∼600,000 single nucleotide polymorphisms across the genome; genotypes for six million common variants are imputed using 1000 Genomes Project and UK10K as the reference. The association between genotype and OS is assessed by Cox proportional hazards model adjusting for age, sex, International staging system and treatment. We identify a locus at 6q25.1 marked by rs12374648 associated with MM-OS (hazard ratio=1.34, 95% confidence interval=1.22-1.48, P=4.69 × 10(-9)). Our findings have potential clinical implications since they demonstrate that inherited genotypes can provide prognostic information in addition to conventional tumor acquired prognostic factors.

RBP-Var: a database of functional variants involved in regulation mediated by RNA-binding proteins

Transcription factors bind to the genome by forming specific contacts with the primary DNA sequence; however, RNA-binding proteins (RBPs) have greater scope to achieve binding specificity through the RNA secondary structure. It has been revealed that single nucleotide variants (SNVs) that alter RNA structure, also known as RiboSNitches, exhibit 3-fold greater local structure changes than replicates of the same DNA sequence, demonstrated by the fact that depletion of RiboSNitches could result in the alteration of specific RNA shapes at thousands of sites, including 3' UTRs, binding sites of microRNAs and RBPs. However, the network between SNVs and post-transcriptional regulation remains unclear. Here, we developed RBP-Var, a database freely available at http://www.rbp-var.biols.ac.cn/, which provides annotation of functional variants involved in post-transcriptional interaction and regulation. RBP-Var provides an easy-to-use web interface that allows users to rapidly find whether SNVs of interest can transform the secondary structure of RNA and identify RBPs whose binding may be subsequently disrupted. RBP-Var integrates DNA and RNA biology to understand how various genetic variants and post-transcriptional mechanisms cooperate to orchestrate gene expression. In summary, RBP-Var is useful in selecting candidate SNVs for further functional studies and exploring causal SNVs underlying human diseases.

Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional Human Longevity

We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived humans. In a standard GWAS analysis, only one locus in these studies is significant (APOE/TOMM40) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional human longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included APOE/TOMM40 (associated with Alzheimer’s disease), CDKN2B/ANRIL (implicated in the regulation of cellular senescence), ABO (tags the O blood group), and SH2B3/ATXN2 (a signaling gene that extends lifespan in Drosophila and a gene involved in neurological disease). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including coronary artery disease and Alzheimer’s disease. iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes.

Longevity is a complex phenotype, and few genetic variants that affect lifespan have been identified. However, aging and disease are closely related, and a great deal is known about the genetic basis of disease risk. Here, we show using genome-wide association studies (GWAS) of longevity and disease that there is an overlap between loci involved in longevity and loci involved in several diseases, such as Alzheimer’s disease and coronary artery disease. We then develop a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from 14 large studies of disease and disease-related traits in order to narrow the search for SNPs associated with longevity. Using iGWAS, we found eight SNPs that are significant in our discovery cohorts, and we were able to validate four of these in replication studies of long-lived subjects. Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits. Beyond the study of human longevity, iGWAS can be applied to boost statistical power in any GWAS of a target phenotype by using larger GWAS of genetically-related conditions.

Genetic risk factors for decreased bone mineral accretion in children with asthma receiving multiple oral corticosteroid bursts

BACKGROUND

Long-term intermittent oral corticosteroid (OCS) use in children with asthma leads to significant decreases in bone mineral accretion (BMA).

OBJECTIVE

We aimed to identify genetic factors influencing OCS dose effects on BMA in children with asthma.

METHODS

We first performed a gene-by-OCS interaction genome-wide association study (GWAS) of BMA in 489 white participants in the Childhood Asthma Management Program trial who took short-term oral prednisone bursts when they experienced acute asthma exacerbations. We selected the top-ranked 2000 single nucleotide polymorphisms (SNPs) in the GWAS and determined whether these SNPs also had cis-regulatory effects on dexamethasone-induced gene expression in osteoblasts.

RESULTS

We identified 2 SNPs (rs9896933 and rs2074439) associated with decreased BMA and related to the tubulin γ pathway. The rs9896933 variant met the criteria for genome-wide significance (P = 3.15 × 10(-8) in the GWAS) and is located on the intron of tubulin folding cofactor D (TBCD) gene. The rs2074439 variant (P = 2.74 × 10(-4) in the GWAS) showed strong cis-regulatory effects on dexamethasone-induced tubulin γ gene expression in osteoblasts (P = 8.64 × 10(-4)). Interestingly, we found that BMA worsened with increasing prednisone dose as the number of mutant alleles of the 2 SNPs increased.

CONCLUSIONS

We have identified 2 novel tubulin γ pathway SNPs, rs9896933 and rs2074439, showing independent interactive effects with cumulative corticosteroid dose on BMA in children with asthma receiving multiple OCS bursts.

eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs

The causal and interplay mechanisms of Single Nucleotide Polymorphisms (SNPs) associated with complex diseases (complex disease SNPs) investigated in genome-wide association studies (GWAS) at the transcriptional level (mRNA) are poorly understood despite recent advancements such as discoveries reported in the Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTex). Protein interaction network analyses have successfully improved our understanding of both single gene diseases (Mendelian diseases) and complex diseases. Whether the mRNAs downstream of complex disease genes are central or peripheral in the genetic information flow relating DNA to mRNA remains unclear and may be disease-specific. Using expression Quantitative Trait Loci (eQTL) that provide DNA to mRNA associations and network centrality metrics, we hypothesize that we can unveil the systems properties of information flow between SNPs and the transcriptomes of complex diseases. We compare different conditions such as naïve SNP assignments and stringent linkage disequilibrium (LD) free assignments for transcripts to remove confounders from LD. Additionally, we compare the results from eQTL networks between lymphoblastoid cell lines and liver tissue. Empirical permutation resampling (p<0.001) and theoretic Mann-Whitney U test (p<10(-30)) statistics indicate that mRNAs corresponding to complex disease SNPs via eQTL associations are likely to be regulated by a larger number of SNPs than expected. We name this novel property mRNA hubness in eQTL networks, and further term mRNAs with high hubness as master integrators. mRNA master integrators receive and coordinate the perturbation signals from large numbers of polymorphisms and respond to the personal genetic architecture integratively. This genetic signal integration contrasts with the mechanism underlying some Mendelian diseases, where a genetic polymorphism affecting a single protein hub produces a divergent signal that affects a large number of downstream proteins. Indeed, we verify that this property is independent of the hubness in protein networks for which these mRNAs are transcribed. Our findings provide novel insights into the pleiotropy of mRNAs targeted by complex disease polymorphisms and the architecture of the information flow between the genetic polymorphisms and transcriptomes of complex diseases.

Genetic evidence for common pathways in human age-related diseases

Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age-related diseases, suggesting that common pathways of aging may influence age-related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age-related diseases, we analyzed the genes and pathways found to be associated with five major categories of age-related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age-related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age-related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient-sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age-related diseases in humans as has been demonstrated in model organisms.

Genetic basis of interindividual susceptibility to cancer cachexia: selection of potential candidate gene polymorphisms for association studies

Cancer cachexia is a complex and multifactorial disease. Evolving definitions highlight the fact that a diverse range of biological processes contribute to cancer cachexia. Part of the variation in who will and who will not develop cancer cachexia may be genetically determined. As new definitions, classifications and biological targets continue to evolve, there is a need for reappraisal of the literature for future candidate association studies. This review summarizes genes identified or implicated as well as putative candidate genes contributing to cachexia, identified through diverse technology platforms and model systems to further guide association studies. A systematic search covering 1986-2012 was performed for potential candidate genes / genetic polymorphisms relating to cancer cachexia. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Pathway analysis software was used to reveal possible network associations between genes. Functionality of SNPs/genes was explored based on published literature, algorithms for detecting putative deleterious SNPs and interrogating the database for expression of quantitative trait loci (eQTLs). A total of 154 genes associated with cancer cachexia were identified and explored for functional polymorphisms. Of these 154 genes, 119 had a combined total of 281 polymorphisms with functional and/or clinical significance in terms of cachexia associated with them. Of these, 80 polymorphisms (in 51 genes) were replicated in more than one study with 24 polymorphisms found to influence two or more hallmarks of cachexia (i.e., inflammation, loss of fat mass and/or lean mass and reduced survival). Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides a contemporary basis to select genes and/or polymorphisms for further association studies in cancer cachexia, and to develop their potential as susceptibility biomarkers of cachexia.

Verification of the Chromosome Region 9q21 Association with Pelvic Organ Prolapse Using RegulomeDB Annotations

Pelvic organ prolapse (POP) is a common highly disabling disorder with a large hereditary component. It is characterized by a loss of pelvic floor support that leads to the herniation of the uterus in or outside the vagina. Genome-wide linkage studies have shown an evidence of POP association with the region 9q21 and six other loci in European pedigrees. The aim of our study was to test the above associations in a case-control study in Russian population. Twelve SNPs including SNPs cited in the above studies and those selected using the RegulomeDB annotations for the region 9q21 were genotyped in 210 patients with POP (stages III-IV) and 292 controls with no even minimal POP. Genotyping was performed using the polymerase chain reaction with confronting two-pair primers (PCR–CTPP). Association analyses were conducted for individual SNPs, 9q21 haplotypes, and SNP-SNP interactions. SNP rs12237222 with the highest RegulomeDB score 1a appeared to be the key SNP in haplotypes associated with POP. Other RegulomeDB Category 1 SNPs, rs12551710 and rs2236479 (scores 1d and 1f, resp.), exhibited epistatic effects. In this study, we verified the region 9q21 association with POP in Russians, using RegulomeDB annotations.

Phenome-Wide Association Studies: Embracing Complexity for Discovery

The inherent complexity of biological systems can be leveraged for a greater understanding of the impact of genetic architecture on outcomes, traits, and pharmacological response. The genome-wide association study (GWAS) approach has well-developed methods and relatively straight-forward methodologies; however, the bigger picture of the impact of genetic architecture on phenotypic outcome still remains to be elucidated even with an ever-growing number of GWAS performed. Greater consideration of the complexity of biological processes, using more data from the phenome, exposome, and diverse -omic resources, including considering the interplay of pleiotropy and genetic interactions, may provide additional leverage for making the most of the incredible wealth of information available for study. Here, we describe how incorporating greater complexity into analyses through the use of additional phenotypic data and widespread deployment of phenome-wide association studies may provide new insights into genetic factors influencing diseases, traits, and pharmacological response.

Genome-Wide Association Study Identifies Novel Pharmacogenomic Loci For Therapeutic Response to Montelukast in Asthma

Background

Genome-wide association study (GWAS) is a powerful tool to identify novel pharmacogenetic single nucleotide polymorphisms (SNPs). Leukotriene receptor antagonists (LTRAs) are a major class of asthma medications, and genetic factors contribute to variable responses to these drugs. We used GWAS to identify novel SNPs associated with the response to the LTRA, montelukast, in asthmatics.

Methods

Using genome-wide genotype and phenotypic data available from American Lung Association - Asthma Clinical Research Center (ALA-ACRC) cohorts, we evaluated 8-week change in FEV₁ related to montelukast administration in a discovery population of 133 asthmatics. The top 200 SNPs from the discovery GWAS were then tested in 184 additional samples from two independent cohorts.

Results

Twenty-eight SNP associations from the discovery GWAS were replicated. Of these, rs6475448 achieved genome-wide significance (combined P = 1.97 x 10^-09), and subjects from all four studies who were homozygous for rs6475448 showed increased ΔFEV₁ from baseline in response to montelukast.

Conclusions

Through GWAS, we identified a novel pharmacogenomic locus related to improved montelukast response in asthmatics.

Pharmacoethnicity in Paclitaxel-Induced Sensory Peripheral Neuropathy

PURPOSE

Paclitaxel is used worldwide in the treatment of breast, lung, ovarian, and other cancers. Sensory peripheral neuropathy is an associated adverse effect that cannot be predicted, prevented, or mitigated. To better understand the contribution of germline genetic variation to paclitaxel-induced peripheral neuropathy, we undertook an integrative approach that combines genome-wide association study (GWAS) data generated from HapMap lymphoblastoid cell lines (LCL) and Asian patients.

METHODS

GWAS was performed with paclitaxel-induced cytotoxicity generated in 363 LCLs and with paclitaxel-induced neuropathy from 145 Asian patients. A gene-based approach was used to identify overlapping genes and compare with a European clinical cohort of paclitaxel-induced neuropathy. Neurons derived from human-induced pluripotent stem cells were used for functional validation of candidate genes.

RESULTS

SNPs near AIPL1 were significantly associated with paclitaxel-induced cytotoxicity in Asian LCLs (P < 10(-6)). Decreased expression of AIPL1 resulted in decreased sensitivity of neurons to paclitaxel by inducing neurite morphologic changes as measured by increased relative total outgrowth, number of processes and mean process length. Using a gene-based analysis, there were 32 genes that overlapped between Asian LCL cytotoxicity and Asian patient neuropathy (P < 0.05), including BCR. Upon BCR knockdown, there was an increase in neuronal sensitivity to paclitaxel as measured by neurite morphologic characteristics.

CONCLUSIONS

We identified genetic variants associated with Asian paclitaxel-induced cytotoxicity and functionally validated the AIPL1 and BCR in a neuronal cell model. Furthermore, the integrative pharmacogenomics approach of LCL/patient GWAS may help prioritize target genes associated with chemotherapeutic-induced peripheral neuropathy.

A candidate gene study reveals association between a variant of the Peroxisome Proliferator-Activated Receptor Gamma (PPAR-γ) gene and systemic sclerosis

Introduction

The multifunctional nuclear receptor peroxisome proliferator-activated receptor gamma (PPAR-γ) has potent anti-fibrotic effects, and its expression and activity are impaired in patients with systemic sclerosis (SSc). We investigated PPAR-γ gene (PPARG) single nucleotide polymorphisms (SNPs) associated with SSc.

Methods

Tag SNPs spanning PPARG were genotyped in a European ancestry US discovery cohort comprising 152 SSc patients and 450 controls, with replication of our top signal in a European cohort (1031 SSc patients and 1014 controls from France). Clinical parameters and disease severity were analyzed to evaluate clinical associations with PPARG variants.

Results

In the discovery cohort, a single PPARG intronic SNP (rs10865710) was associated with SSc (p = 0.010; odds ratio = 1.52 per C allele, 95% confidence interval 1.10-2.08). This association was replicated in the French validation cohort (p = 0.052; odds ratio = 1.16 per C allele, 95% confidence interval 1.00-1.35). Meta-analysis of both cohorts indicated stronger evidence for association (p = 0.002; odds ratio = 1.22 per C allele, 95% confidence interval 1.07-1.40). The rs10865710 C allele was also associated with pulmonary arterial hypertension in the French SSc cohort (p = 0.002; odds ratio = 2.33 per C allele, 95% confidence interval 1.34-4.03).

Conclusions

A PPARG variant is associated with susceptibility to SSc, consistent with a role of PPAR-γ in the pathogenesis of SSc.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0641-2) contains supplementary material, which is available to authorized users.

Beyond the usual suspects: a multidimensional genetic exploration of infant attachment disorganization and security

Although the environmental influences on infant attachment disorganization and security are well-studied, little is known about their heritability. Candidate gene studies have shown small, often non-replicable effects. In this study, we gathered the largest sample (N = 657) of ethnically homogenous, 14-month-old children with both observed attachment and genome-wide data. First, we used a Genome-Wide Association Study (GWAS) approach to identify single nucleotide polymorphisms (SNPs) associated with attachment disorganization and security. Second, we annotated them into genes (Versatile Gene-based Association Study) and functional pathways. Our analyses provide evidence of novel genes (HDAC1, ZNF675, BSCD1) and pathways (synaptic transmission, cation transport) associated with attachment disorganization. Similar analyses identified a novel gene (BECN1) but no distinct pathways associated with attachment security. The results of this first extensive, exploratory study on the molecular-genetic basis of infant attachment await replication in large, independent samples.

The variation game: Cracking complex genetic disorders with NGS and omics data

Tremendous advances in Next Generation Sequencing (NGS) and high-throughput omics methods have brought us one step closer towards mechanistic understanding of the complex disease at the molecular level. In this review, we discuss four basic regulatory mechanisms implicated in complex genetic diseases, such as cancer, neurological disorders, heart disease, diabetes, and many others. The mechanisms, including genetic variations, copy-number variations, posttranscriptional variations, and epigenetic variations, can be detected using a variety of NGS methods. We propose that malfunctions detected in these mechanisms are not necessarily independent, since these malfunctions are often found associated with the same disease and targeting the same gene, group of genes, or functional pathway. As an example, we discuss possible rewiring effects of the cancer-associated genetic, structural, and posttranscriptional variations on the protein-protein interaction (PPI) network centered around P53 protein. The review highlights multi-layered complexity of common genetic disorders and suggests that integration of NGS and omics data is a critical step in developing new computational methods capable of deciphering this complexity.

A genome-wide association study of autism using the Simons Simplex Collection: Does reducing phenotypic heterogeneity in autism increase genetic homogeneity?

BACKGROUND

Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD.

METHODS

Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup.

RESULTS

Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups.

CONCLUSIONS

In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.

SCAN database: facilitating integrative analyses of cytosine modification and expression QTL

Functional annotation of genetic variants including single nucleotide polymorphisms (SNPs) and copy number variations (CNV) promises to greatly improve our understanding of human complex traits. Previous transcriptomic studies involving individuals from different global populations have investigated the genetic architecture of gene expression variation by mapping expression quantitative trait loci (eQTL). Functional interpretation of genome-wide association studies (GWAS) has identified enrichment of eQTL in top signals from GWAS of human complex traits. The SCAN (SNP and CNV Annotation) database was developed as a web-based resource of genetical genomic studies including eQTL detected in the HapMap lymphoblastoid cell line samples derived from apparently healthy individuals of European and African ancestry. Considering the critical roles of epigenetic gene regulation, cytosine modification quantitative trait loci (mQTL) are expected to add a crucial layer of annotation to existing functional genomic information. Here, we describe the new features of the SCAN database that integrate comprehensive mQTL mapping results generated in the HapMap CEU (Caucasian residents from Utah, USA) and YRI (Yoruba people from Ibadan, Nigeria) LCL samples and demonstrate the utility of the enhanced functional annotation system.

Database URL:http://www.scandb.org/

A meta-analysis strategy for gene prioritization using gene expression, SNP genotype, and eQTL data

In order to understand disease pathogenesis, improve medical diagnosis, or discover effective drug targets, it is important to identify significant genes deeply involved in human disease. For this purpose, many earlier approaches attempted to prioritize candidate genes using gene expression profiles or SNP genotype data, but they often suffer from producing many false-positive results. To address this issue, in this paper, we propose a meta-analysis strategy for gene prioritization that employs three different genetic resources—gene expression data, single nucleotide polymorphism (SNP) genotype data, and expression quantitative trait loci (eQTL) data—in an integrative manner. For integration, we utilized an improved technique for the order of preference by similarity to ideal solution (TOPSIS) to combine scores from distinct resources. This method was evaluated on two publicly available datasets regarding prostate cancer and lung cancer to identify disease-related genes. Consequently, our proposed strategy for gene prioritization showed its superiority to conventional methods in discovering significant disease-related genes with several types of genetic resources, while making good use of potential complementarities among available resources.

Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease--without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER.

Sequence and analysis of a whole genome from Kuwaiti population subgroup of Persian ancestry

Background

The 1000 Genome project paved the way for sequencing diverse human populations. New genome projects are being established to sequence underrepresented populations helping in understanding human genetic diversity. The Kuwait Genome Project an initiative to sequence individual genomes from the three subgroups of Kuwaiti population namely, Saudi Arabian tribe; “tent-dwelling” Bedouin; and Persian, attributing their ancestry to different regions in Arabian Peninsula and to modern-day Iran (West Asia). These subgroups were in line with settlement history and are confirmed by genetic studies. In this work, we report whole genome sequence of a Kuwaiti native from Persian subgroup at >37X coverage.

Results

We document 3,573,824 SNPs, 404,090 insertions/deletions, and 11,138 structural variations. Out of the reported SNPs and indels, 85,939 are novel. We identify 295 ‘loss-of-function’ and 2,314 ’deleterious’ coding variants, some of which carry homozygous genotypes in the sequenced genome; the associated phenotypes include pharmacogenomic traits such as greater triglyceride lowering ability with fenofibrate treatment, and requirement of high warfarin dosage to elicit anticoagulation response. 6,328 non-coding SNPs associate with 811 phenotype traits: in congruence with medical history of the participant for Type 2 diabetes and β-Thalassemia, and of participant’s family for migraine, 72 (of 159 known) Type 2 diabetes, 3 (of 4) β-Thalassemia, and 76 (of 169) migraine variants are seen in the genome. Intergenome comparisons based on shared disease-causing variants, positions the sequenced genome between Asian and European genomes in congruence with geographical location of the region. On comparison, bead arrays perform better than sequencing platforms in correctly calling genotypes in low-coverage sequenced genome regions however in the event of novel SNP or indel near genotype calling position can lead to false calls using bead arrays.

Conclusions

We report, for the first time, reference genome resource for the population of Persian ancestry. The resource provides a starting point for designing large-scale genetic studies in Peninsula including Kuwait, and Persian population. Such efforts on populations under-represented in global genome variation surveys help augment current knowledge on human genome diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1233-x) contains supplementary material, which is available to authorized users.

The genetic basis of quality of life in healthy Swedish women: a candidate gene approach

BACKGROUND

Quality of life (QoL) is an increasingly important parameter in clinical practice as it predicts mortality and poor health outcomes. It is hypothesized that one may have a genetic predisposition for QoL. We therefore related 139 candidate genes, selected through a literature search, to QoL in healthy females.

METHODS

In 5,142 healthy females, background characteristics (i.e. demographic, clinical, lifestyle, and psychological factors) were assessed. QoL was measured by the EORTC QLQ-C30, which consists of 15 domains. For all women genotype information was available. For each candidate gene, single nucleotide polymorphisms (SNPs) were identified based on their functional (n = 2,663) and physical annotation (n = 10,649). SNPs were related to each QoL-domain, while controlling for background characteristics and population stratification. Finally, gene-based analyses were performed relating the combined effect of 10,649 SNPs (selected based on physical annotation) for each gene, to QoL using the statistical software package VEGAS.

RESULTS

Overall, we found no relation between genetic variations (SNPs and genes) and 14 out of 15 QoL-domains. The strongest association was found between cognitive functioning and the top SNP rs1468951 (p = 1.21E-05) in the GSTZ1 gene. Furthermore, results of the gene-based test showed that the combined effect of 11 SNPs within the GSTZ1 gene is significantly associated with cognitive functioning (p = 2.60E-05).

CONCLUSION

If validated, the involvement of GSTZ1 in cognitive functioning underscores its heritability which is likely the result of differences in the dopamine pathway, as GSTZ1 contributes to the equilibrium between dopamine and its neurotoxic metabolites via the glutathione redox cycle.

A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis

OBJECTIVE

Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset.

METHODS

To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10(-8) was used to determine significance. Replication was performed in 1523 additional patients from the POSH study.

RESULTS

Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10(-6). These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27-1.75, P = 1.1×10(-6)), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67-0.85, P = 1.8×10(-6)), and rs1728400 which is between LINC00917 and FOXF1.

CONCLUSIONS

In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.

Identification of genetic variants associated with capecitabine-induced hand-foot syndrome through integration of patient and cell line genomic analyses

OBJECTIVE

A primary challenge in identifying replicable pharmacogenomic markers from clinical genomewide association study (GWAS) trials in oncology is the difficulty in performing a second large clinical trial with the same drugs and dosage regimen. We sought to overcome this challenge by incorporating GWAS results from cell-based studies using the same chemotherapy as a clinical cohort.

METHODS

In this study, we test whether the overlap between genetic variants identified in a preclinical study and a clinical study on capecitabine is more than expected by chance. A GWAS of capecitabine-induced cytotoxicity was performed in 164 lymphoblastoid cell lines derived from the CEU HapMap population and compared with a GWAS of hand-foot syndrome (HFS), the most frequent capecitabine-induced adverse drug reaction, in Spanish breast and colorectal cancer patients (n=160) treated with capecitabine.

RESULTS

We observed an overlap of 16 single nucleotide polymorphisms associated with capecitabine-induced cytotoxicity (P<0.001) in lymphoblastoid cell lines and HFS (P<0.05) in patients, which is a greater overlap than expected by chance (genotype-phenotype permutation empirical P=0.015). Ten tag single nucleotide polymorphisms, which cover the overlap loci, were genotyped in a second patient cohort (n=85) and one of them, rs9936750, was associated with capecitabine-induced HFS (P=0.0076).

CONCLUSION

The enrichment results imply that cellular models of capecitabine-induced cytotoxicity may capture components of the underlying polygenic architecture of related toxicities in patients.

Family-based association study of common variants, rare mutation study and epistatic interaction detection in HDAC genes in schizophrenia

BACKGROUND

Histone deacetylases (HDACs) are key enzymes of histone acetylation, and abnormalities in histone modifications and in the level of HDAC proteins have been reported in schizophrenia. The objective of the present study was to systematically test the HDAC genes for its association with schizophrenia.

METHODS

A family-based genetic association study (951 Caucasian subjects in 313 nuclear families) using 601 tag-single nucleotide polymorphisms in HDAC genes was conducted followed by a replication study of top-ranked markers in a sample of 1427 Caucasian subjects from 241 multiplex families and 176 trios. Epistasis interaction was tested by using the pedigree-based generalized multifactor dimensionality reduction (GMDR). Furthermore, we analyzed exome sequencing data of 1134 subjects for detection of rare mutations in HDAC genomic regions.

RESULTS

In the exploratory study, ten markers were in significant association with schizophrenia (P<0.01). One maker rs14251 (HDAC3) was replicated (P=0.04) and remained significant in the whole sample (P=0.004). GMDR identified that a significant three-locus interaction model was detected involving rs17265596 (HDAC9), rs7290710 (HDAC10) and rs7634112 (HDAC11) with a good testing accuracy (0.58). No rare mutations were found associated with schizophrenia.

CONCLUSION

This first exploratory systematic study of the HDAC genes provides consistent support for the involvement of the HDAC3 gene in the etiology of schizophrenia. A statistical epistatic interaction between HDAC9, HDAC10, and HDAC11 was detected and seems biologically plausible.

Genomic architecture of pharmacological efficacy and adverse events

The pharmacokinetic and pharmacodynamic disciplines address pharmacological traits, including efficacy and adverse events. Pharmacogenomics studies have identified pervasive genetic effects on treatment outcomes, resulting in the development of genetic biomarkers for optimization of drug therapy. Pharmacogenomics-based tests are already being applied in clinical decision making. However, despite substantial progress in identifying the genetic etiology of pharmacological response, current biomarker panels still largely rely on single gene tests with a large portion of the genetic effects remaining to be discovered. Future research must account for the combined effects of multiple genetic variants, incorporate pathway-based approaches, explore gene-gene interactions and nonprotein coding functional genetic variants, extend studies across ancestral populations, and prioritize laboratory characterization of molecular mechanisms. Because genetic factors can play a key role in drug response, accurate biomarker tests capturing the main genetic factors determining treatment outcomes have substantial potential for improving individual clinical care.

Identification of a variant in KDR associated with serum VEGFR2 and pharmacodynamics of Pazopanib

PURPOSE

VEGF receptor (VEGFR) kinases are important drug targets in oncology that affect function of systemic endothelial cells. To discover genetic markers that affect VEGFR inhibitor pharmacodynamics, we performed a genome-wide association study of serum soluble vascular VEGFR2 concentrations [sVEGFR2], a pharmacodynamic biomarker for VEGFR2 inhibitors.

EXPERIMENTAL DESIGN

We conducted a genome-wide association study (GWAS) of [sVEGFR2] in 736 healthy Old Order Amish volunteers. Gene variants identified from the GWAS were genotyped serially in a cohort of 128 patients with advanced solid tumor with baseline [sVEGFR2] measurements, and in 121 patients with renal carcinoma with [sVEGFR2] measured before and during pazopanib therapy.

RESULTS

rs34231037 (C482R) in KDR, the gene encoding sVEGFR2 was found to be highly associated with [sVEGFR2], explaining 23% of the variance (P = 2.7 × 10(-37)). Association of rs34231037 with [sVEGFR2] was replicated in 128 patients with cancer with comparable effect size (P = 0.025). Furthermore, rs34231037 was a significant predictor of changes in [sVEGFR2] in response to pazopanib (P = 0.01).

CONCLUSION

Our findings suggest that genome-wide analysis of phenotypes in healthy populations can expedite identification of candidate pharmacogenetic markers. Genotyping for germline variants in KDR may have clinical utility in identifying patients with cancer with unusual sensitivity to effects of VEGFR2 kinase inhibitors.

Structural architecture of SNP effects on complex traits

Despite the discovery of copy-number variation (CNV) across the genome nearly 10 years ago, current SNP-based analysis methodologies continue to collapse the homozygous (i.e., A/A), hemizygous (i.e., A/0), and duplicative (i.e., A/A/A) genotype states, treating the genotype variable as irreducible or unaltered by other colocalizing forms of genetic (e.g., structural) variation. Our understanding of common, genome-wide CNVs suggests that the canonical genotype construct might belie the enormous complexity of the genome. Here we present multiple analyses of several phenotypes and provide methods supporting a conceptual shift that embraces the structural dimension of genotype. We comprehensively investigate the impact of the structural dimension of genotype on (1) GWAS methods, (2) interpretation of rare LOF variants, (3) characterization of genomic architecture, and (4) implications for mapping loci involved in complex disease. Taken together, these results argue for the inclusion of a structural dimension and suggest that some portion of the "missing" heritability might be recovered through integration of the structural dimension of SNP effects on complex traits.

Cross-tissue and tissue-specific eQTLs: partitioning the heritability of a complex trait

Top signals from genome-wide association studies (GWASs) of type 2 diabetes (T2D) are enriched with expression quantitative trait loci (eQTLs) identified in skeletal muscle and adipose tissue. We therefore hypothesized that such eQTLs might account for a disproportionate share of the heritability estimated from all SNPs interrogated through GWASs. To test this hypothesis, we applied linear mixed models to the Wellcome Trust Case Control Consortium (WTCCC) T2D data set and to data sets representing Mexican Americans from Starr County, TX, and Mexicans from Mexico City. We estimated the proportion of phenotypic variance attributable to the additive effect of all variants interrogated in these GWASs, as well as a much smaller set of variants identified as eQTLs in human adipose tissue, skeletal muscle, and lymphoblastoid cell lines. The narrow-sense heritability explained by all interrogated SNPs in each of these data sets was substantially greater than the heritability accounted for by genome-wide-significant SNPs (∼10%); GWAS SNPs explained over 50% of phenotypic variance in the WTCCC, Starr County, and Mexico City data sets. The estimate of heritability attributable to cross-tissue eQTLs was greater in the WTCCC data set and among lean Hispanics, whereas adipose eQTLs significantly explained heritability among Hispanics with a body mass index ≥ 30. These results support an important role for regulatory variants in the genetic component of T2D susceptibility, particularly for eQTLs that elicit effects across insulin-responsive peripheral tissues.

Inherited variability in a master regulator polymorphism (rs4846126) associates with survival in 5-FU treated colorectal cancer patients

BACKGROUND

Treatment with 5-fluorouracil (5-FU) is known to improve survival in many cancers including colorectal cancer. Response to the treatment, overall survival and recurrence show inter-individual variation.

METHODS

In this study we employed a strategy to search eQTL variants influencing the expression of a large number of genes. We identified four single nucleotide polymorphisms, defined as master regulators of transcription, and genotyped them in a set of 218 colorectal cancer patients undergoing adjuvant 5-FU based therapy.

RESULTS

Our results showed that the minor allele variant of the rs4846126 polymorphism was associated with poor overall and progression-free survival. Patients that were homozygous for the variant allele showed an over two fold increased risk of death (HR 2.20 95%CI 1.05-4.60) and progression (HR 2.88, 95% 1.47-5.63). The integration of external information from publicly available gene expression repositories suggested that the rs4846126 polymorphism deserves further investigation. This variant potentially regulates the gene expression of 273 genes with some of them possibly associated to the patient's response to 5-FU treatment or colorectal cancer.

CONCLUSIONS

Present results show that mining of public data repositories in combination with own data can be a fruitful approach to identify markers that affect therapy outcome. In particular, a genetic screen of master regulators may help in order to search for the polymorphisms involved in treatment response in cancer patients.

Gene-age interactions in blood pressure regulation: a large-scale investigation with the CHARGE, Global BPgen, and ICBP Consortia

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.

Linking the genetic architecture of cytosine modifications with human complex traits

Interindividual variation in cytosine modifications could contribute to heterogeneity in disease risks and other complex traits. We assessed the genetic architecture of cytosine modifications at 283,540 CpG sites in lymphoblastoid cell lines (LCLs) derived from independent samples of European and African descent. Our study suggests that cytosine modification variation was primarily controlled in local by single major modification quantitative trait locus (mQTL) and additional minor loci. Local genetic epistasis was detectable for a small proportion of CpG sites, which were enriched by more than 9-fold for CpG sites mapped to population-specific mQTL. Genetically dependent CpG sites whose modification levels negatively (repressive sites) or positively (facilitative sites) correlated with gene expression levels significantly co-localized with transcription factor binding, with the repressive sites predominantly associated with active promoters whereas the facilitative sites rarely at active promoters. Genetically independent repressive or facilitative sites preferentially modulated gene expression variation by influencing local chromatin accessibility, with the facilitative sites primarily antagonizing H3K27me3 and H3K9me3 deposition. In comparison with expression quantitative trait loci (eQTL), mQTL detected from LCLs were enriched in associations for a broader range of disease categories including chronic inflammatory, autoimmune and psychiatric disorders, suggesting that cytosine modification variation, while possesses a degree of cell linage specificity, is more stably inherited over development than gene expression variation. About 11% of unique single-nucleotide polymorphisms reported in the Genome-Wide Association Study Catalog were annotated, 78% as mQTL and 31% as eQTL in LCLs, which covered 37% of the investigated diseases/traits and provided insights to the biological mechanisms.

Germline genetic variants in ABCB1, ABCC1 and ALDH1A1, and risk of hematological and gastrointestinal toxicities in a SWOG Phase III trial S0221 for breast cancer

Hematological and gastrointestinal toxicities are common among patients treated with cyclophosphamide and doxorubicin for breast cancer. To examine whether single-nucleotide polymorphisms (SNPs) in key pharmacokinetic genes were associated with risk of hematological or gastrointestinal toxicity, we analyzed 78 SNPs in ABCB1, ABCC1 and ALDH1A1 in 882 breast cancer patients enrolled in the SWOG trial S0221 and treated with cyclophosphamide and doxorubicin. A two-SNP haplotype in ALDH1A1 was associated with an increased risk of grade 3 and 4 hematological toxicity (odds ratio=1.44, 95% confidence interval=1.16-1.78), which remained significant after correction for multiple comparisons. In addition, four SNPs in ABCC1 were associated with gastrointestinal toxicity. Our findings provide evidence that SNPs in pharmacokinetic genes may have an impact on the development of chemotherapy-related toxicities. This is a necessary first step toward building a clinical tool that will help assess risk of adverse outcomes before undergoing chemotherapy.

Shared and independent colorectal cancer risk alleles in TGFβ-related genes in African and European Americans

Genome-wide association studies (GWAS) in colorectal cancer (CRC) identified five regions near transforming growth factor β-related genes BMP4, GREM1, CDH1, SMAD7 and RPHN2. The true risk alleles remain to be identified in these regions, and their role in CRC risk in non-European populations has been understudied. Our previous work noted significant genetic heterogeneity between African Americans (AAs) and European Americans (EAs) for single nucleotide polymorphisms (SNPs) identified in GWAS. We hypothesized that associations may not have been replicated in AAs due to differential or independent genetic structures. In order to test this hypothesis, we genotyped 195 tagging SNPs across these five gene regions in 1194 CRC cases (795 AAs and 399 EAs) and 1352 controls (985 AAs and 367 EAs). Imputation was performed, and association testing of genotyped and imputed SNPs included ancestry, age and sex as covariates. In two of the five genes originally associated with CRC, we found evidence for association in AAs including rs1862748 in CDH1 (OR(Add) = 0.82, P = 0.02) and in GREM1 the SNPs rs10318 (OR(Rec) = 60.1, P = 0.01), rs11632715 (OR(Rec) = 2.36; P = 0.004) and rs12902616 (OR(Rec) = 1.28, P = 0.005), the latter which is in linkage disequilibrium with the previously identified SNP rs4779584. Testing more broadly for associations in these gene regions in AAs, we noted three statistically significant association peaks in GREM1 and RHPN2 that were not identified in EAs. We conclude that some CRC risk alleles are shared between EAs and AAs and others are population specific.

Integrative analyses of genetic variation, epigenetic regulation, and the transcriptome to elucidate the biology of platinum sensitivity

BACKGROUND

Using genome-wide genetic, gene expression, and microRNA expression (miRNA) data, we developed an integrative approach to investigate the genetic and epigenetic basis of chemotherapeutic sensitivity.

RESULTS

Through a sequential multi-stage framework, we identified genes and miRNAs whose expression correlated with platinum sensitivity, mapped these to genomic loci as quantitative trait loci (QTLs), and evaluated the associations between these QTLs and platinum sensitivity. A permutation analysis showed that top findings from our approach have a much lower false discovery rate compared to those from a traditional GWAS of drug sensitivity. Our approach identified five SNPs associated with 10 miRNAs and the expression level of 15 genes, all of which were associated with carboplatin sensitivity. Of particular interest was one SNP (rs11138019), which was associated with the expression of both miR-30d and the gene ABCD2, which were themselves correlated with both carboplatin and cisplatin drug-specific phenotype in the HapMap samples. Functional study found that knocking down ABCD2 in vitro led to increased apoptosis in ovarian cancer cell line SKOV3 after cisplatin treatment. Over-expression of miR-30d in vitro caused a decrease in ABCD2 expression, suggesting a functional relationship between the two.

CONCLUSIONS

We developed an integrative approach to the investigation of the genetic and epigenetic basis of human complex traits. Our approach outperformed standard GWAS and provided hints at potential biological function. The relationships between ABCD2 and miR-30d, and ABCD2 and platin sensitivity were experimentally validated, suggesting a functional role of ABCD2 and miR-30d in sensitivity to platinating agents.

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

Integrative "omic" analysis for tamoxifen sensitivity through cell based models

It has long been observed that tamoxifen sensitivity varies among breast cancer patients. Further, ethnic differences of tamoxifen therapy between Caucasian and African American have also been reported. Since most studies have been focused on Caucasian people, we sought to comprehensively evaluate genetic variants related to tamoxifen therapy in African-derived samples. An integrative "omic" approach developed by our group was used to investigate relationships among endoxifen (an active metabolite of tamoxifen) sensitivity, SNP genotype, mRNA and microRNA expressions in 58 HapMap YRI lymphoblastoid cell lines. We identified 50 SNPs that associate with cellular sensitivity to endoxifen through their effects on 34 genes and 30 microRNA expression. Some of these findings are shared in both Caucasian and African samples, while others are unique in the African samples. Among gene/microRNA that were identified in both ethnic groups, the expression of TRAF1 is also correlated with tamoxifen sensitivity in a collection of 44 breast cancer cell lines. Further, knock-down TRAF1 and over-expression of hsa-let-7i confirmed the roles of hsa-let-7i and TRAF1 in increasing tamoxifen sensitivity in the ZR-75-1 breast cancer cell line. Our integrative omic analysis facilitated the discovery of pharmacogenomic biomarkers that potentially affect tamoxifen sensitivity.

CDKAL1-related single nucleotide polymorphisms are associated with insulin resistance in a cross-sectional cohort of Greek children

Five novel loci recently found to be associated with body mass in two GWAS of East Asian populations were evaluated in two cohorts of Swedish and Greek children and adolescents. These loci are located within, or in the proximity of: CDKAL1, PCSK1, GP2, PAX6 and KLF9. No association with body mass has previously been reported for these loci in GWAS performed on European populations. The single nucleotide polymorphisms (SNPs) with the strongest association at each loci in the East Asian GWAS were genotyped in two cohorts, one obesity case control cohort of Swedish children and adolescents consisting of 496 cases and 520 controls and one cross-sectional cohort of 2293 nine-to-thirteen year old Greek children and adolescents. SNPs were surveyed for association with body mass and other phenotypic traits commonly associated with obesity, including adipose tissue distribution, insulin resistance and daily caloric intake. No association with body mass was found in either cohort. However, among the Greek children, association with insulin resistance could be observed for the two CDKAL1-related SNPs: rs9356744 (β = 0.018, p = 0.014) and rs2206734 (β = 0.024, p = 0.001). CDKAL1-related variants have previously been associated with type 2 diabetes and insulin response. This study reports association of CDKAL1-related SNPs with insulin resistance, a clinical marker related to type 2 diabetes in a cross-sectional cohort of Greek children and adolescents of European descent.

A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10(-8)) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10(-4)) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10(-6). In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.

Genome-wide association analyses of child genotype effects and parent-of-origin effects in specific language impairment

Specific language impairment (SLI) is a neurodevelopmental disorder that affects linguistic abilities when development is otherwise normal. We report the results of a genome-wide association study of SLI which included parent-of-origin effects and child genotype effects and used 278 families of language-impaired children. The child genotype effects analysis did not identify significant associations. We found genome-wide significant paternal parent-of-origin effects on chromosome 14q12 (P = 3.74 × 10(-8)) and suggestive maternal parent-of-origin effects on chromosome 5p13 (P = 1.16 × 10(-7)). A subsequent targeted association of six single-nucleotide-polymorphisms (SNPs) on chromosome 5 in 313 language-impaired individuals and their mothers from the ALSPAC cohort replicated the maternal effects, albeit in the opposite direction (P = 0.001); as fathers' genotypes were not available in the ALSPAC study, the replication analysis did not include paternal parent-of-origin effects. The paternally-associated SNP on chromosome 14 yields a non-synonymous coding change within the NOP9 gene. This gene encodes an RNA-binding protein that has been reported to be significantly dysregulated in individuals with schizophrenia. The region of maternal association on chromosome 5 falls between the PTGER4 and DAB2 genes, in a region previously implicated in autism and ADHD. The top SNP in this association locus is a potential expression QTL of ARHGEF19 (also called WGEF) on chromosome 1. Members of this protein family have been implicated in intellectual disability. In summary, this study implicates parent-of-origin effects in language impairment, and adds an interesting new dimension to the emerging picture of shared genetic etiology across various neurodevelopmental disorders.

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

Background

Alzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling.

Results

Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (S_R) based method followed by prioritization using clusters derived from PPI network. S_R for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes.

Conclusions

With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-199) contains supplementary material, which is available to authorized users.

Integrating cell-based and clinical genome-wide studies to identify genetic variants contributing to treatment failure in neuroblastoma patients

High-risk neuroblastoma is an aggressive malignancy with high rates of treatment failure. We evaluated genetic variants associated with in vitro sensitivity to two derivatives of cyclophosphamide for association with clinical response in a separate replication cohort of neuroblastoma patients (n=2,709). Lymphoblastoid cell lines (LCLs) were exposed to increasing concentrations of 4-hydroperoxycyclophosphamide [4HC n=422] and phosphoramide mustard [PM n=428] to determine sensitivity. Genome-wide association studies (GWAS) were performed to identify single nucleotide polymorphisms (SNPs) associated with 4HC and PM sensitivity. SNPs consistently associated with LCL sensitivity were analyzed for associations with event-free survival in patients. Two linked SNPs, rs9908694 and rs1453560, were found to be associated with PM sensitivity in LCLs across populations and were associated with event-free survival in all patients (P=0.01) and within the high-risk subset (P=0.05). Our study highlights the value of cell-based models to identify candidate variants that may predict response to treatment in patients with cancer.

rSNPBase: a database for curated regulatory SNPs

In recent years, human regulatory SNPs (rSNPs) have been widely studied. Here, we present database rSNPBase, freely available at http://rsnp.psych.ac.cn/, to provide curated rSNPs that analyses the regulatory features of all SNPs in the human genome with reference to experimentally supported regulatory elements. In contrast with previous SNP functional annotation databases, rSNPBase is characterized by several unique features. (i) To improve reliability, all SNPs in rSNPBase are annotated with reference to experimentally supported regulatory elements. (ii) rSNPBase focuses on rSNPs involved in a wide range of regulation types, including proximal and distal transcriptional regulation and post-transcriptional regulation, and identifies their potentially regulated genes. (iii) Linkage disequilibrium (LD) correlations between SNPs were analysed so that the regulatory feature is annotated to SNP-set rather than a single SNP. (iv) rSNPBase provides the spatio-temporal labels and experimental eQTL labels for SNPs. In summary, rSNPBase provides more reliable, comprehensive and user-friendly regulatory annotations on rSNPs and will assist researchers in selecting candidate SNPs for further genetic studies and in exploring causal SNPs for in-depth molecular mechanisms of complex phenotypes.

Post genome-wide association studies functional characterization of prostate cancer risk loci

Background

Over the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa.

Results

In this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR).

Conclusions

A comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.