Displaying publications 41 - 60 of 198 in total

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  1. Fulltext Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
    Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2018 07;50(7):928-936.
    PMID: 29892016 DOI: 10.1038/s41588-018-0142-8
    Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
    Matched MeSH terms: Genome-Wide Association Study/methods
  2. Fulltext Genome wide comprehensive analysis and web resource development on cell wall degrading enzymes from phyto-parasitic nematodes
    Rai KM, Balasubramanian VK, Welker CM, Pang M, Hii MM, Mendu V
    BMC Plant Biol, 2015;15:187.
    PMID: 26232118 DOI: 10.1186/s12870-015-0576-4
    The plant cell wall serves as a primary barrier against pathogen invasion. The success of a plant pathogen largely depends on its ability to overcome this barrier. During the infection process, plant parasitic nematodes secrete cell wall degrading enzymes (CWDEs) apart from piercing with their stylet, a sharp and hard mouthpart used for successful infection. CWDEs typically consist of cellulases, hemicellulases, and pectinases, which help the nematode to infect and establish the feeding structure or form a cyst. The study of nematode cell wall degrading enzymes not only enhance our understanding of the interaction between nematodes and their host, but also provides information on a novel source of enzymes for their potential use in biomass based biofuel/bioproduct industries. Although there is comprehensive information available on genome wide analysis of CWDEs for bacteria, fungi, termites and plants, but no comprehensive information available for plant pathogenic nematodes. Herein we have performed a genome wide analysis of CWDEs from the genome sequenced phyto pathogenic nematode species and developed a comprehensive publicly available database.
    Matched MeSH terms: Genome-Wide Association Study*
  3. Fulltext Germline variants are associated with increased primary melanoma tumor thickness at diagnosis
    Mangantig E, MacGregor S, Iles MM, Scolyer RA, Cust AE, Hayward NK, et al.
    Hum Mol Genet, 2021 01 06;29(21):3578-3587.
    PMID: 33410475 DOI: 10.1093/hmg/ddaa222
    Germline genetic variants have been identified, which predispose individuals and families to develop melanoma. Tumor thickness is the strongest predictor of outcome for clinically localized primary melanoma patients. We sought to determine whether there is a heritable genetic contribution to variation in tumor thickness. If confirmed, this will justify the search for specific genetic variants influencing tumor thickness. To address this, we estimated the proportion of variation in tumor thickness attributable to genome-wide genetic variation (variant-based heritability) using unrelated patients with measured primary cutaneous melanoma thickness. As a secondary analysis, we conducted a genome-wide association study (GWAS) of tumor thickness. The analyses utilized 10 604 individuals with primary cutaneous melanoma drawn from nine GWAS datasets from eight cohorts recruited from the general population, primary care and melanoma treatment centers. Following quality control and filtering to unrelated individuals with study phenotypes, 8125 patients were used in the primary analysis to test whether tumor thickness is heritable. An expanded set of 8505 individuals (47.6% female) were analyzed for the secondary GWAS meta-analysis. Analyses were adjusted for participant age, sex, cohort and ancestry. We found that 26.6% (SE 11.9%, P = 0.0128) of variation in tumor thickness is attributable to genome-wide genetic variation. While requiring replication, a chromosome 11 locus was associated (P 
    Matched MeSH terms: Genome-Wide Association Study*
  4. Fulltext Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
    Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium
    Nat Neurosci, 2015 Feb;18(2):199-209.
    PMID: 25599223 DOI: 10.1038/nn.3922
    Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.
    Matched MeSH terms: Genome-Wide Association Study/methods*
  5. Fulltext Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses
    Zhang H, Ahearn TU, Lecarpentier J, Barnes D, Beesley J, Qi G, et al.
    Nat Genet, 2020 06;52(6):572-581.
    PMID: 32424353 DOI: 10.1038/s41588-020-0609-2
    Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
    Matched MeSH terms: Genome-Wide Association Study*
  6. Fulltext Gene-environment Interaction: The Causes of High Obesity Incidence
    Ellulu MS, Jalambo MO
    Kathmandu Univ Med J (KUMJ), 2018 2 16;15(57):91-93.
    PMID: 29446373
    Urbanization has provided experimental settings for testing the interactive relationship between genetic background and changes in lifestyle and dietary patterns. The concept of gene-environment interaction was described by epidemic of obesity along with urbanization. Genome-wide association has identified several genes such as melanocortin-4 receptor that associates with environmental influences of obesity. Gene environment (GxE) interaction refers to modification by an environmental factor of the effect of a genetic variant on a phenotypic trait. GxE interactions can serve to modulate the adverse effects of a risk allele, or can exacerbate the genotype-phenotype relationship and increase risk.
    Matched MeSH terms: Genome-Wide Association Study/methods*
  7. Fulltext Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
    Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Jan;53(1):65-75.
    PMID: 33398198 DOI: 10.1038/s41588-020-00748-0
    Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
    Matched MeSH terms: Genome-Wide Association Study*
  8. Moving into a new era of periodontal genetic studies: relevance of large case-control samples using severe phenotypes for genome-wide association studies
    Vaithilingam RD, Safii SH, Baharuddin NA, Ng CC, Cheong SC, Bartold PM, et al.
    J Periodontal Res, 2014 Dec;49(6):683-95.
    PMID: 24528298 DOI: 10.1111/jre.12167
    Studies to elucidate the role of genetics as a risk factor for periodontal disease have gone through various phases. In the majority of cases, the initial 'hypothesis-dependent' candidate-gene polymorphism studies did not report valid genetic risk loci. Following a large-scale replication study, these initially positive results are believed to be caused by type 1 errors. However, susceptibility genes, such as CDKN2BAS (Cyclin Dependend KiNase 2B AntiSense RNA; alias ANRIL [ANtisense Rna In the Ink locus]), glycosyltransferase 6 domain containing 1 (GLT6D1) and cyclooxygenase 2 (COX2), have been reported as conclusive risk loci of periodontitis. The search for genetic risk factors accelerated with the advent of 'hypothesis-free' genome-wide association studies (GWAS). However, despite many different GWAS being performed for almost all human diseases, only three GWAS on periodontitis have been published - one reported genome-wide association of GLT6D1 with aggressive periodontitis (a severe phenotype of periodontitis), whereas the remaining two, which were performed on patients with chronic periodontitis, were not able to find significant associations. This review discusses the problems faced and the lessons learned from the search for genetic risk variants of periodontitis. Current and future strategies for identifying genetic variance in periodontitis, and the importance of planning a well-designed genetic study with large and sufficiently powered case-control samples of severe phenotypes, are also discussed.
    Matched MeSH terms: Genome-Wide Association Study*
  9. Fulltext The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study
    Giannakopoulou O, Lin K, Meng X, Su MH, Kuo PH, Peterson RE, et al.
    JAMA Psychiatry, 2021 Nov 01;78(11):1258-1269.
    PMID: 34586374 DOI: 10.1001/jamapsychiatry.2021.2099
    IMPORTANCE: Most previous genome-wide association studies (GWAS) of depression have used data from individuals of European descent. This limits the understanding of the underlying biology of depression and raises questions about the transferability of findings between populations.

    OBJECTIVE: To investigate the genetics of depression among individuals of East Asian and European descent living in different geographic locations, and with different outcome definitions for depression.

    DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association analyses followed by meta-analysis, which included data from 9 cohort and case-control data sets comprising individuals with depression and control individuals of East Asian descent. This study was conducted between January 2019 and May 2021.

    EXPOSURES: Associations of genetic variants with depression risk were assessed using generalized linear mixed models and logistic regression. The results were combined across studies using fixed-effects meta-analyses. These were subsequently also meta-analyzed with the largest published GWAS for depression among individuals of European descent. Additional meta-analyses were carried out separately by outcome definition (clinical depression vs symptom-based depression) and region (East Asian countries vs Western countries) for East Asian ancestry cohorts.

    MAIN OUTCOMES AND MEASURES: Depression status was defined based on health records and self-report questionnaires.

    RESULTS: There were a total of 194 548 study participants (approximate mean age, 51.3 years; 62.8% women). Participants included 15 771 individuals with depression and 178 777 control individuals of East Asian descent. Five novel associations were identified, including 1 in the meta-analysis for broad depression among those of East Asian descent: rs4656484 (β = -0.018, SE = 0.003, P = 4.43x10-8) at 1q24.1. Another locus at 7p21.2 was associated in a meta-analysis restricted to geographically East Asian studies (β = 0.028, SE = 0.005, P = 6.48x10-9 for rs10240457). The lead variants of these 2 novel loci were not associated with depression risk in European ancestry cohorts (β = -0.003, SE = 0.005, P = .53 for rs4656484 and β = -0.005, SE = 0.004, P = .28 for rs10240457). Only 11% of depression loci previously identified in individuals of European descent reached nominal significance levels in the individuals of East Asian descent. The transancestry genetic correlation between cohorts of East Asian and European descent for clinical depression was r = 0.413 (SE = 0.159). Clinical depression risk was negatively genetically correlated with body mass index in individuals of East Asian descent (r = -0.212, SE = 0.084), contrary to findings for individuals of European descent.

    CONCLUSIONS AND RELEVANCE: These results support caution against generalizing findings about depression risk factors across populations and highlight the need to increase the ancestral and geographic diversity of samples with consistent phenotyping.

    Matched MeSH terms: Genome-Wide Association Study*
  10. Fulltext A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk
    Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, et al.
    Cancer Res, 2018 Sep 15;78(18):5419-5430.
    PMID: 30054336 DOI: 10.1158/0008-5472.CAN-18-0951
    Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.
    Matched MeSH terms: Genome-Wide Association Study*
  11. Fulltext Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes
    Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Electronic address: douglas.ruderfer@vanderbilt.edu, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium
    Cell, 2018 Jun 14;173(7):1705-1715.e16.
    PMID: 29906448 DOI: 10.1016/j.cell.2018.05.046
    Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.
    Matched MeSH terms: Genome-Wide Association Study*
  12. Fulltext Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis
    Ishigaki K, Sakaue S, Terao C, Luo Y, Sonehara K, Yamaguchi K, et al.
    Nat Genet, 2022 Nov;54(11):1640-1651.
    PMID: 36333501 DOI: 10.1038/s41588-022-01213-w
    Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P 
    Matched MeSH terms: Genome-Wide Association Study*
  13. Fulltext Whole-genome noncoding sequence analysis in T-cell acute lymphoblastic leukemia identifies oncogene enhancer mutations
    Hu S, Qian M, Zhang H, Guo Y, Yang J, Zhao X, et al.
    Blood, 2017 Jun 15;129(24):3264-3268.
    PMID: 28408461 DOI: 10.1182/blood-2017-03-771162
    Publisher's Note: There is an Inside Blood Commentary on this article in this issue.
    Matched MeSH terms: Genome-Wide Association Study*
  14. Fulltext Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions
    Dareng EO, Coetzee SG, Tyrer JP, Peng PC, Rosenow W, Chen S, et al.
    Am J Hum Genet, 2024 Jun 06;111(6):1061-1083.
    PMID: 38723632 DOI: 10.1016/j.ajhg.2024.04.011
    To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.
    Matched MeSH terms: Genome-Wide Association Study*
  15. Fulltext Association of ESR1 Germline Variants with TP53 Somatic Variants in Breast Tumors in a Genome-wide Study
    Tjader NP, Beer AJ, Ramroop J, Tai MC, Ping J, Gandhi T, et al.
    Cancer Res Commun, 2024 Jun 27;4(6):1597-1608.
    PMID: 38836758 DOI: 10.1158/2767-9764.CRC-24-0026
    In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

    SIGNIFICANCE: Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

    Matched MeSH terms: Genome-Wide Association Study*
  16. Fulltext Walking pace is a protective factor for rheumatoid arthritis: a mendelian randomization study
    Zhang Q, Huang X, Zhang Y, Chao Z, Zhou R, Hamid RA, et al.
    Sci Rep, 2024 Oct 22;14(1):24886.
    PMID: 39438628 DOI: 10.1038/s41598-024-76666-6
    Walking pace is a simple and functional form of exercise and a strong predictor of health, but little is known about its causal association with rheumatoid arthritis. This study aimed to investigate the causal effect of WP on the developing RA using Mendelian randomization analysis. The genetic variation associated with WP was selected as an instrumental variable from the latest genome-wide association studies. Summary-level data for the outcomes were obtained from the corresponding GWAS. The inverse-variance weighted method was used as the primary MR analysis. The results were further tested using a multivariable MR approach based on Bayesian model averaging. Confounders (BMI, SMK, HBP, TD) with close associations with RA were included in the analysis. An observational study with individual data from UK Biobank was performed to reinforce our findings. The MR results indicated the significant inverse associations of WP with the risk of RA (odds ratio (OR), 0.31; 95% confidence interval (CI), 0.15, 0.62; p = 1.05 × 10 -3). After adjusting for the risk factors, the associations for WP and RA did not change substantially. Observational study results demonstrated the same effect of WP on reducing the risk of RA. The Mendelian randomization analysis and observational study provide evidence suggesting that walking pace is a protective factor for rheumatoid arthritis. Given its simple measurement, walking pace may be a pragmatic target for interventions.
    Matched MeSH terms: Genome-Wide Association Study*
  17. Fulltext Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
    Walsh N, Zhang H, Hyland PL, Yang Q, Mocci E, Zhang M, et al.
    J Natl Cancer Inst, 2019 Jun 01;111(6):557-567.
    PMID: 30541042 DOI: 10.1093/jnci/djy155
    BACKGROUND: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.

    METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.

    RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.

    CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  18. Exome sequencing and array-based comparative genomic hybridisation analysis of preferential 6-methylmercaptopurine producers
    Chua EW, Cree S, Barclay ML, Doudney K, Lehnert K, Aitchison A, et al.
    Pharmacogenomics J, 2015 Oct;15(5):414-21.
    PMID: 25752523 DOI: 10.1038/tpj.2015.9
    Preferential conversion of azathioprine or 6-mercaptopurine into methylated metabolites is a major cause of thiopurine resistance. To seek potentially Mendelian causes of thiopurine hypermethylation, we recruited 12 individuals who exhibited extreme therapeutic resistance while taking azathioprine or 6-mercaptopurine and performed whole-exome sequencing (WES) and copy-number variant analysis by array-based comparative genomic hybridisation (aCGH). Exome-wide variant filtering highlighted four genes potentially associated with thiopurine metabolism (ENOSF1 and NFS1), transport (SLC17A4) or therapeutic action (RCC2). However, variants of each gene were found only in two or three patients, and it is unclear whether these genes could influence thiopurine hypermethylation. Analysis by aCGH did not identify any unusual or pathogenic copy-number variants. This suggests that if causative mutations for the hypermethylation phenotype exist they may be heterogeneous, occurring in several different genes, or they may lie within regulatory regions not captured by WES. Alternatively, hypermethylation may arise from the involvement of multiple genes with small effects. To test this hypothesis would require recruitment of large patient samples and application of genome-wide association studies.
    Matched MeSH terms: Genome-Wide Association Study
  19. Fulltext An Improved Oil Palm Genome Assembly as a Valuable Resource for Crop Improvement and Comparative Genomics in the Arecoideae Subfamily
    Ong AL, Teh CK, Mayes S, Massawe F, Appleton DR, Kulaveerasingam H
    Plants (Basel), 2020 Nov 03;9(11).
    PMID: 33152992 DOI: 10.3390/plants9111476
    Oil palm (Elaeis guineensis Jacq.) is the most traded crop among the economically important palm species. Here, we report an extended version genome of E. guineensis that is 1.2 Gb in length, an improvement of the physical genome coverage to 79% from the previous 43%. The improvement was made by assigning an additional 1968 originally unplaced scaffolds that were available publicly into the physical genome. By integrating three ultra-dense linkage maps and using them to place genomic scaffolds, the 16 pseudomolecules were extended. As we show, the improved genome has enhanced the mapping resolution for genome-wide association studies (GWAS) and permitted further identification of candidate genes/protein-coding regions (CDSs) and any non-coding RNA that may be associated with them for further studies. We then employed the new physical map in a comparative genomics study against two other agriculturally and economically important palm species-date palm (Phoenix dactylifera L.) and coconut palm (Cocos nucifera L.)-confirming the high level of conserved synteny among these palm species. We also used the improved oil palm genome assembly version as a palm genome reference to extend the date palm physical map. The improved genome of oil palm will enable molecular breeding approaches to expedite crop improvement, especially in the largest subfamily of Arecoideae, which consists of 107 species belonging to Arecaceae.
    Matched MeSH terms: Genome-Wide Association Study
  20. Fulltext Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution
    Plissonneau C, Benevenuto J, Mohd-Assaad N, Fouché S, Hartmann FE, Croll D
    Front Plant Sci, 2017;8:119.
    PMID: 28217138 DOI: 10.3389/fpls.2017.00119
    Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution.
    Matched MeSH terms: Genome-Wide Association Study
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