Identify Candidate Single Nucleotide Polymorphisms Research Articles

Genome-Wide Pathway Analysis in Major Depressive Disorder

The aims of this study were: (1) to identify candidate single-nucleotide polymorphisms (SNPs) and mechanisms of major depressive disorder (MDD) and (2) to generate SNP-to-gene-to-pathway hypotheses. An MDD genome-wide association study (GWAS) data set that included 365,419 SNPs in 1,821 MDD cases and 1,822 controls of European descent was used in this study. Identify Candidate Causal SNPs and Pathway (ICSNPathway) analysis was applied to the GWAS dataset. ICSNPathway analysis identified 21 candidate SNPs, 16 genes, and 5 pathways, which provided 16 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs3213764 alters the role of ATF7IP in the context of the pathways of negative regulation of transcription, negative regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolic processes and negative regulation of gene expression (nominal p < 0.001, FDR = 0.043, 0.044, and 0.046, respectively). Five of 16 candidate genes are known to be associated with inflammatory or immune response that may be associated with MDD: ANPEP, PRDM1, ZBTB32, MMP8, and ENPEP. By applying the ICSNPathway analysis to the MDD GWAS data, 21 candidate SNPs, 16 genes that included ATF7IP, ANPEP, PRDM1, ZBTB32, MMP8, and ENPEP, and 5 pathways that involved negative regulation of transcription and nucleic acid metabolism were identified that may contribute to MDD susceptibility.

Association of germ-line single nucleotide polymorphisms (SNPs) with pathologic response to neoadjuvant cisplatin-based chemotherapy in patients with resectable non-small cell lung cancers.

7558 Background: Pathologic response to neoadjuvant chemotherapy correlates with survival in resected lung cancers. Predictive biomarkers of response are needed. Tumor-specific biomarkers have been hindered by reproducibility and specimen adequacy. Genome-wide association studies (most in SE Asia) have identified candidate SNPs that correlate with clinical outcomes after cisplatin-based chemotherapy. We evaluated whether these candidate SNPs are predictive of pathologic response to neoadjuvant chemotherapy in a US population. Methods: We aimed to correlate SNPs with near complete PR (ncPR) to neoadjuvant cisplatin + docetaxel in patients with resectable lung cancers. ncPR was defined as 90% necrosis, inflammation and fibrosis across serial 1cm sections of the resected tumor. Germline DNA was extracted and 50 candidate SNPs were genotyped by Sequenom Mass ARRAY iPLEX. SNPs were analyzed for correlation with ncPR using recessive (aa vs AA/aA) , dominant (AA vs aa/aA) and log-additive (linear increase in risk with each additional allele) genetic models. In this exploratory dataset, a p-value &lt;0.1 was considered worthy of further study. Results: 60 patients were treated and had sufficient DNA for analysis. Nine patients had a ncPR. 7 of 50 SNPs (table) correlated with pathologic response in one of the three models. Conclusions: Of the candidate SNPs identified from the literature, 7 showed a promising correlation to ncPR to neoadjuvant chemotherapy. This expands upon the experience evaluating SNPs and chemotherapy sensitivity into a North American population. Study of these 7 SNPs is ongoing in our current multimodality trial as a validation cohort. This study was funded by the Lung Cancer Research Foundation. [Table: see text]

Pathway analysis of a genome-wide association study in schizophrenia

ObjectiveThe aim of this study was to identify the candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms that contribute to schizophrenia susceptibility and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach. MethodsWe used schizophrenia GWAS data of the genotypes of 660,259 SNPs in 1378 controls and 1351 cases of European descent after quality control filtering. ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the schizophrenia GWAS dataset. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate SNPs using improved-gene set enrichment analysis. ResultsICSNPathway analysis identified fifteen candidate SNPs, ten candidate pathways, and nine hypothetical biological mechanisms. The most strongly associated potential pathways were as follows. First, rs1644731 and rs1644730 to RDH8 to estrogen biosynthetic process (p<0.001, FDR<0.001). The genes involved in this pathway are RDH8 and HSD3B1 (p<0.05). All-trans-retinol dehydrogenase (RDH8) is a visual cycle enzyme that reduces all-trans-retinal to all-trans-retinol in the presence of NADPH. The chemical reactions and pathways involved result in the formation of estrogens, which are C18 steroid hormones that can stimulate the development of female sexual characteristics. Second, rs1146031 to ACVR1 to mesoderm formation and activin binding (p<0.001, FDR=0.032, 0.034). Two of 15 candidate genes are known genes associated with schizophrenia: KCNQ2 and APOL2. One of the 10 candidate pathways, estrogen biosynthetic process, is known to be associated with schizophrenia (p<0.001, FDR<0.001). However, 13 of candidate genes (RDH8, ACVR1, PSMD9, KCNAB1, SLC17A3, ARCN1, COG7, STAB2, LRPAP1, STAB1, CXCL16, COL4A4, EXOSC3) and 9 of candidate pathways were novel. ConclusionBy applying ICSNPathway analysis to schizophrenia GWAS data, we identified candidate SNPs, genes like KCNQ2 and APOL2 and pathways involving the estrogen biosynthetic process may contribute to schizophrenia susceptibility. Further analyses are needed to validate the results of this analysis.

A genome-wide association study of survival in small-cell lung cancer patients treated with irinotecan plus cisplatin chemotherapy

We conducted a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) influencing overall survival (OS) of small-cell lung cancer (SCLC) patients. We prospectively collected blood samples from 139 SCLC patients who participated in phase II studies of irinotecan and cisplatin (IP) chemotherapy as first-line therapy. Among 334 127 SNPs, which passed quality control, seven showed significant association with OS. The rs16950650CT, rs7186128AG or GG, rs17574269AG, rs8020368CC, rs4655567CC, rs2166219TT or rs2018683TT showed shorter OS compared with control alleles. Among the seven SNPs, rs4655567, rs8020368 and rs2018683 were significantly associated with a resistant relapse (RR). In the multivariate analysis, rs8020368CC was significantly associated with higher risk of RR (odds ratio=16.7, P=0.007). In vitro and in silico analysis showed that SNPs in C14orf49 might be associated with epithelial-to-mesenchymal transition. This exploratory GWAS identified candidate SNPs that may be predictive of the clinical outcome of SCLC patients receiving IP.

Associations between single nucleotide polymorphisms (SNPs) in inflammation-related genes and quality of life after radiation therapy (RT) for prostate cancer.

2 Background: Prostate-directed RT results in local inflammation that may contribute to short-term toxicity and subsequently effects on long-term quality of life (QOL). We sought to explore the hypothesis that SNPs in inflammation-related genes may influence QOL sequelae following definitive prostate cancer RT. Methods: We studied Caucasian participants in the prospective US Physicians’ Health Study diagnosed and treated with RT for non-metastatic prostate cancer between 1982 and 2006. Forty-three SNPs in 10 inflammation-related genes were genotyped and analyzed using the additive model. Men were followed for cancer-specific QOL outcomes with regularly administered questionnaires. We dichotomized the maximum score for four parameters (decreased urinary stream, increased urinary frequency, rectal urgency and impotence) relevant to RT reported at least one year following RT and analyzed associations between scores and SNPs using Fisher’s exact tests and logistic regression. Results: We identified 264 men with QOL data who previously provided blood for genotype analysis and received RT at a median age of 72 years (IQR 68 – 76 years). Features at diagnosis included: 67% PSA&lt;10, 61% Gleason&lt;7, 95% T1/T2 disease and 71% Charlson co-morbidity index 0-1. QOL questions were completed a median of 6 years following RT. Without adjusting for multiple testing, 13 SNPs had nominally significant associations (p &lt; 0.05) with QOL parameters; 7 remained significant after adjusting for age, features at diagnosis, and use of brachytherapy (Table). Conclusions: We identify candidate SNPs in inflammation-related genes that can be further explored in regards to their associations with long-term effects of prostate-directed RT. [Table: see text]

Genome-wide association study of sleep in Drosophila melanogaster.

BackgroundSleep is a highly conserved behavior, yet its duration and pattern vary extensively among species and between individuals within species. The genetic basis of natural variation in sleep remains unknown.ResultsWe used the Drosophila Genetic Reference Panel (DGRP) to perform a genome-wide association (GWA) study of sleep in D. melanogaster. We identified candidate single nucleotide polymorphisms (SNPs) associated with differences in the mean as well as the environmental sensitivity of sleep traits; these SNPs typically had sex-specific or sex-biased effects, and were generally located in non-coding regions. The majority of SNPs (80.3%) affecting sleep were at low frequency and had moderately large effects. Additive models incorporating multiple SNPs explained as much as 55% of the genetic variance for sleep in males and females. Many of these loci are known to interact physically and/or genetically, enabling us to place them in candidate genetic networks. We confirmed the role of seven novel loci on sleep using insertional mutagenesis and RNA interference.ConclusionsWe identified many SNPs in novel loci that are potentially associated with natural variation in sleep, as well as SNPs within genes previously known to affect Drosophila sleep. Several of the candidate genes have human homologues that were identified in studies of human sleep, suggesting that genes affecting variation in sleep are conserved across species. Our discovery of genetic variants that influence environmental sensitivity to sleep may have a wider application to all GWA studies, because individuals with highly plastic genotypes will not have consistent phenotypes.

Genome-wide pathway analysis of a genome-wide association study on multiple sclerosis

The aims of this study were to identify candidate single nucleotide polymorphisms (SNPs) and mechanisms of multiple sclerosis (MS) and to generate SNP to gene to pathway hypotheses. A MS genome-wide association study (GWAS) dataset that included 505,763 SNPs in 500 cases and 500 controls of European descent was used in this study. Identify candidate Causal SNPs and Pathway (ICSNPathway) analysis was applied to the GWAS dataset. ICSNPathway analysis identified 9 candidate SNPs and 5 pathways, which provided 5 hypothetical biological mechanisms. The candidate SNPs, namely, rs1802127 (MSH5), rs9277471 (human leukocyte antigen [HLA]-DPB1), rs8084 (HLA-DRA), rs7192 (HLA-DRA), rs2072895 (HLA-F), rs2735059 (HLA-F), rs915669 (HLA-G), rs915668 (HLA-G), and rs1063320 (HLA-G) were all at HLA loci (-log10(P) = 3.301-4.000). The most strongly associated pathway was rs1802127 to MSH5 to meiotic recombination and meiotic cell cycle (nominal P < 0.001, false discovery rate [FDR] < 0.001). When HLA loci were excluded, ICSNPathway analysis identified seven candidate non-HLA SNPs (rs5896 [F2], rs8181979 [SHC1], rs9297605 [TAF2], rs669 [A2 M], rs2228043 [IL6ST], rs1061622 [TNFRSF1B], rs1801516 [ATM]) and ten candidate causal pathways, which provided seven hypothetical biological mechanisms (nominal P ≤ 0.001, FDR ≤ 0.047). The most strongly associated pathway was SNP rs5896 to F2 to the transcriptional activation DNA-binding protein B from mRNA (nominal P < 0.001, FDR = 0.006). The application of ICSNPathway analysis to the MS GWAS dataset resulted in the identification of candidate SNPs, pathways, and biological mechanisms that might contribute to MS susceptibility.

Pathway Analysis of a Genome-Wide Association Study of Ileal Crohn's Disease

The aim of this study was to identify the candidate single-nucleotide polymorphisms (SNPs) and candidate mechanisms of Crohn's disease (CD) and to generate a SNP to gene to pathway hypothesis using a pathway-based approach, ICSNPathway (Identify candidate Causal SNPs and Pathways) of genome-wide association studies (GWAS). An ileal CD GWAS dataset downloaded from NCBI dbGap was used in this study, which was conducted using 297,857 SNPs in 968 CD cases and 995 controls after quality control filtering. ICSNPathway analysis was applied to the CD GWAS dataset. ICSNPathway analysis identified seven candidate SNPs, nine pathways, which provided five hypothetical biological mechanisms. First, rs4077515 to caspase recruitment domain-containing protein 9 (CARD9) to response to peptidoglycan, positive regulation of tumor necrosis factor production, response to exogenous dsRNA, positive regulation of interleukin-6 production, and positive regulation of innate immune response (nominal p≤0.002, false discovery rate [FDR]=0.027). Second, rs2066842, rs3135500, and rs5743291 to NOD2 to response to pepditoglycan, innate immune response activating signal transduction, and positive regulation of innate immune response (nominal p≤0.001, FDR=0.027). Third, rs8172678 to PPARGC1A to cellular glucose homeostasis (nominal p<0.001, FDR=0.031). Fourth, rs1050152 to SLC22A4 to cofactor transporter activity and vitamin transport (nominal p<0.001, FDR=0.044). Fifth, rs9621049 to TCN2 to vitamin transport (nominal p<0.001, FDR=0.046). In conclusion, by applying ICSNPathway analysis to CD GWAS, we identified candidate SNPs, genes involving CARD9, NOD2, PPARGC1A, SLC22A4, and TCN2, pathways, and hypothetical mechanisms, which may contribute to ileal CD susceptibility.

Neuropathy Is Not Associated With Clinical Outcomes in Patients Receiving Adjuvant Taxane-Containing Therapy for Operable Breast Cancer

Neuropathy is a common and potentially disabling complication of adjuvant taxane therapy. Recent studies have identified candidate single nucleotide polymorphisms associated with taxane-induced neuropathy. Therefore, we sought to determine whether neuropathy was associated with breast cancer recurrence in a clinical trial population who received adjuvant taxane therapy. Trial E1199 included 4,554 eligible women with operable breast cancer who received up to four cycles of doxorubicin and cyclophosphamide every 3 weeks followed by paclitaxel 175 mg/m(2) every 3 weeks for four cycles (P3), paclitaxel 80 mg/m(2) weekly for 12 cycles (P1), docetaxel 100 mg/m(2) every 3 weeks for four cycles (D3), or docetaxel 35 mg/m(2) weekly for 12 cycles (D1). A Cox proportional hazards model was used to determine the relationship between neuropathy and disease-free survival (DFS), overall survival (OS), and recurrence-free survival (RFS) by treating neuropathy status as a time dependent covariate and using a landmark analysis. Of 4,554 patients who received at least one taxane dose, grade 2 to 4 neuropathy developed in 18%, 22%, 15%, and 13% of patients in the P3, P1, D3, and D1 arms, respectively. In a model that included age, race, obesity, menopausal status, tumor size, nodal status, treatment arm, neuropathy, and hyperglycemia, no significant relationship was found between neuropathy and DFS, OS, or RFS. There was no association between taxane-induced neuropathy and outcome.

Maximal conditional chi-square importance in random forests

High-dimensional data are frequently generated in genome-wide association studies (GWAS) and other studies. It is important to identify features such as single nucleotide polymorphisms (SNPs) in GWAS that are associated with a disease. Random forests represent a very useful approach for this purpose, using a variable importance score. This importance score has several shortcomings. We propose an alternative importance measure to overcome those shortcomings. We characterized the effect of multiple SNPs under various models using our proposed importance measure in random forests, which uses maximal conditional chi-square (MCC) as a measure of association between a SNP and the trait conditional on other SNPs. Based on this importance measure, we employed a permutation test to estimate empirical P-values of SNPs. Our method was compared to a univariate test and the permutation test using the Gini and permutation importance. In simulation, the proposed method performed consistently superior to the other methods in identifying of risk SNPs. In a GWAS of age-related macular degeneration, the proposed method confirmed two significant SNPs (at the genome-wide adjusted level of 0.05). Further analysis showed that these two SNPs conformed with a heterogeneity model. Compared with the existing importance measures, the MCC importance measure is more sensitive to complex effects of risk SNPs by utilizing conditional information on different SNPs. The permutation test with the MCC importance measure provides an efficient way to identify candidate SNPs in GWAS and facilitates the understanding of the etiology between genetic variants and complex diseases. heping.zhang@yale.edu Supplementary data are available at Bioinformatics online.

Genome‐wide SNP genotyping study using pooled DNA to identify candidate markers mediating susceptibility to end‐stage renal disease attributed to Type 1 diabetes

Genetic factors play a major role in the progression of kidney disease in diabetes. To identify candidate single nucleotide polymorphisms (SNPs) with potential effects on susceptibility to end-stage renal disease (ESRD), we performed a whole genome association scan using pooled DNA from Caucasian individuals with Type 1 diabetes. We utilized the Illumina Infinium II HumanHap 550 beadchip platform to genotype 555 352 SNPs in DNA pools comprised of 547 cases with ESRD and 549 control subjects with Type 1 diabetes duration > 20 years and no ESRD. Pooled probe intensity was used to predict mean allele frequency (MAF) for each locus. Individual genotyping was performed using the iPLEX assay in conjunction with the MassARRAY platform (Sequenom). We identified 2870 markers showing substantial differences in MAF (5.0-10.7%) between pools. To initiate validation of these findings, we genotyped 22 high-ranking markers in 462 individuals with ESRD and 470 unaffected control subjects selected from the genome-wide SNP genotyping study sample. We observed the strongest evidence for association between ESRD and rs1749824, located in the ZMIZ1 gene [OR = 1.47 (1.21-1.78) per copy of T allele; P = 8.1 x 10(-5)] and rs9298190, located in the musculin gene [OR = 1.56 (1.28-1.91) per copy of C allele; P = 1.6 x 10(-5)]. Evidence for nominal association with markers in or near the IRS2, TMPO, BID, KLRA1, ELMO1 and CNDP1 genes was also observed (P < or = 0.0006). These findings identify several novel loci which may contribute to ESRD susceptibility in individuals with Type 1 diabetes.

Taste receptor polymorphisms in the Old Order Amish: Associations with obesity and related traits

Nutritional intake contributes to the development of human disease mainly by influencing the development of obesity-related conditions such as diabetes and cardiovascular disease. Orosensory variation strongly affects ingestive behavior and nutrient intake, while genetic variation in taste receptors (TRs) strongly affects taste sensitivity and food preference. Moreover, the expression of TRs in the gastrointestinal tract suggests that they may be involved in the nutrient-dependent regulation of metabolism. Therefore, we hypothesized that genetic variation in TRs may impact the development of obesity-related disease. To investigate these possibilities, we genotyped >60 haplotype-tagging single-nucleotide polymorphisms (SNPs) within 2 kB of all TAS1R and TAS2R genes in DNA samples from the Amish Family Diabetes Study. We identified candidate SNPs from the dbSNP and HapMap databases, and prioritized those with a minor allele frequency of ⩾0.2 in the CEU cohort (Utah residents with ancestry from northern and western Europe). We then evaluated the effects of genotype on 39 obesity-related traits (with adjustments for age, sex, and BMI). Several SNPs were significantly associated with obesity-related traits, including diabetes, glucose and insulin levels during oral glucose-tolerance tests, weight, and eating behaviors. We conclude that common variation in taste receptor genes may influence food preference, metabolism and/or risk factors associated with obesity. Support: NIDCD, NHLBI, NIDDK, UMSOM.

Mouse SNP Miner: an annotated database of mouse functional single nucleotide polymorphisms

BackgroundThe mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci (<10 Mb) the identification of candidate functional DNA sequence changes remains challenging due to the high density of sequence variation between strains.DescriptionTo help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at ). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function.ConclusionWe have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.

Mining for Single Nucleotide Polymorphisms and Insertions/Deletions in Maize Expressed Sequence Tag Data

We have developed a computer based method to identify candidate single nucleotide polymorphisms (SNPs) and small insertions/deletions from expressed sequence tag data. Using a redundancy-based approach, valid SNPs are distinguished from erroneous sequence by their representation multiple times in an alignment of sequence reads. A second measure of validity was also calculated based on the cosegregation of the SNP pattern between multiple SNP loci in an alignment. The utility of this method was demonstrated by applying it to 102,551 maize (Zea mays) expressed sequence tag sequences. A total of 14,832 candidate polymorphisms were identified with an SNP redundancy score of two or greater. Segregation of these SNPs with haplotype indicates that candidate SNPs with high redundancy and cosegregation confidence scores are likely to represent true SNPs. This was confirmed by validation of 264 candidate SNPs from 27 loci, with a range of redundancy and cosegregation scores, in four inbred maize lines. The SNP transition/transversion ratio and insertion/deletion size frequencies correspond to those observed by direct sequencing methods of SNP discovery and suggest that the majority of predicted SNPs and insertion/deletions identified using this approach represent true genetic variation in maize.