Displaying publications 1 - 20 of 27 in total

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  1. Zhang M, Wang Z, Obazee O, Jia J, Childs EJ, Hoskins J, et al.
    Oncotarget, 2016 Oct 11;7(41):66328-66343.
    PMID: 27579533 DOI: 10.18632/oncotarget.11041
    Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.
    Matched MeSH terms: Genome-Wide Association Study/methods
  2. Yu CY, Ang GY, Subramaniam V, Johari James R, Ahmad A, Abdul Rahman T, et al.
    Genet Test Mol Biomarkers, 2017 Jul;21(7):409-415.
    PMID: 28525288 DOI: 10.1089/gtmb.2016.0235
    AIMS: CYP2D6 is one of the major enzymes in the cytochrome P450 monooxygenase system. It metabolizes ∼25% of prescribed drugs and hence, the genetic diversity of a CYP2D6 gene has continued to be of great interest to the medical and pharmaceutical industries. This study was designed to perform a systematic analysis of the CYP2D6 gene in six subtribes of the Malaysian Orang Asli.

    METHODS: Genomic DNAs were extracted from the blood samples followed by whole-genome sequencing. The reads were aligned to the reference human genome hg19 and variants in the CYP2D6 gene were analyzed. CYP2D6*5 and duplication of CYP2D6 were analyzed using previously established methods.

    RESULTS: A total of 72 single nucleotide polymorphisms were identified. CYP2D6*1, *2, *4, *5, *10,*41, and duplication of the gene were found in the Orang Asli, whereby CYP2D6*2 and *41 alleles are reported for the first time in the Malaysian population.

    CONCLUSION: The findings in this study provide insights into the genetic polymorphisms of CYP2D6 in the Orang Asli of Peninsular Malaysia.

    Matched MeSH terms: Genome-Wide Association Study/methods
  3. 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*
  4. Vincent-Chong VK, Anwar A, Karen-Ng LP, Cheong SC, Yang YH, Pradeep PJ, et al.
    PLoS One, 2013;8(2):e54705.
    PMID: 23405089 DOI: 10.1371/journal.pone.0054705
    Despite the advances in diagnosis and treatment of oral squamous cell carcinoma (OSCC), mortality and morbidity rates have not improved over the past decade. A major drawback in diagnosis and treatment of OSCC is the lack of knowledge relating to how genetic instability in oral cancer genomes affects oral carcinogenesis. Hence, the key aim of this study was to identify copy number alterations (CNAs) that may be cancer associated in OSCC using high-resolution array comparative genomic hybridization (aCGH). To our knowledge this is the first study to use ultra-high density aCGH microarrays to profile a large number of OSCC genomes (n = 46). The most frequently amplified CNAs were located on chromosome 11q11(52%), 2p22.3(52%), 1q21.3-q22(54%), 6p21.32(59%), 20p13(61%), 7q34(52% and 72%),8p11.23-p11.22(80%), 8q11.1-q24.4(54%), 9q13-q34.3(54%), 11q23.3-q25(57%); 14q21.3-q31.1(54%); 14q31.3-q32.33(57%), 20p13-p12.3(54%) and 20q11.21-q13.33(52%). The most frequently deleted chromosome region was located on 3q26.1 (54%). In order to verify the CNAs from aCGH using quantitative polymerase chain reaction (qPCR), the three top most amplified regions and their associated genes, namely ADAM5P (8p11.23-p11.22), MGAM (7q34) and SIRPB1 (20p13.1), were selected in this study. The ADAM5P locus was found to be amplified in 39 samples and deleted in one; MGAM (24 amplifications and 3 deletions); and SIRPB1 (12 amplifications, others undetermined). On the basis of putative cancer-related annotations, two genes, namely ADAM metallopeptidase domain 9 (ADAM9) and maltase-glucoamylase alpha-glucosidase (MGAM), that mapped to CNA regions were selected for further evaluation of their mRNA expression using reverse transcriptase qPCR. The over-expression of MGAM was confirmed with a 6.6 fold increase in expression at the mRNA level whereas the fold change in ADAM9 demonstrated a 1.6 fold increase. This study has identified significant regions in the OSCC genome that were amplified and resulted in consequent over-expression of the MGAM and ADAM9 genes that may be utilized as biological markers for OSCC.
    Matched MeSH terms: Genome-Wide Association Study/methods
  5. Teo YY, Sim X, Ong RT, Tan AK, Chen J, Tantoso E, et al.
    Genome Res, 2009 Nov;19(11):2154-62.
    PMID: 19700652 DOI: 10.1101/gr.095000.109
    The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.
    Matched MeSH terms: Genome-Wide Association Study/methods
  6. Tang H, Jiang L, Stolzenberg-Solomon RZ, Arslan AA, Beane Freeman LE, Bracci PM, et al.
    Cancer Epidemiol Biomarkers Prev, 2020 Sep;29(9):1784-1791.
    PMID: 32546605 DOI: 10.1158/1055-9965.EPI-20-0275
    BACKGROUND: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level.

    METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.

    RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).

    CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.

    IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  7. 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
  8. Poniah P, Mohd Zain S, Abdul Razack AH, Kuppusamy S, Karuppayah S, Sian Eng H, et al.
    Urol Oncol, 2017 09;35(9):545.e1-545.e11.
    PMID: 28527622 DOI: 10.1016/j.urolonc.2017.04.017
    BACKGROUND: Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease.

    METHODS: To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method.

    RESULTS: A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation.

    CONCLUSION: In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  9. Panagiotou OA, Travis RC, Campa D, Berndt SI, Lindstrom S, Kraft P, et al.
    Eur Urol, 2015 Apr;67(4):649-57.
    PMID: 25277271 DOI: 10.1016/j.eururo.2014.09.020
    BACKGROUND: No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).

    OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.

    DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

    OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.

    RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.

    CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.

    PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  10. 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*
  11. Mueller SH, Lai AG, Valkovskaya M, Michailidou K, Bolla MK, Wang Q, et al.
    Genome Med, 2023 Jan 26;15(1):7.
    PMID: 36703164 DOI: 10.1186/s13073-022-01152-5
    BACKGROUND: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.

    METHODS: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.

    RESULTS: In European ancestry samples, 14 genes were significantly associated (q 

    Matched MeSH terms: Genome-Wide Association Study/methods
  12. Morales Berstein F, McCartney DL, Lu AT, Tsilidis KK, Bouras E, Haycock P, et al.
    Elife, 2022 Mar 29;11.
    PMID: 35346416 DOI: 10.7554/eLife.75374
    BACKGROUND: Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

    METHODS: We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

    RESULTS: Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

    CONCLUSIONS: GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

    FUNDING: FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

    Matched MeSH terms: Genome-Wide Association Study/methods
  13. Milne RL, Kuchenbaecker KB, Michailidou K, Beesley J, Kar S, Lindström S, et al.
    Nat Genet, 2017 Dec;49(12):1767-1778.
    PMID: 29058716 DOI: 10.1038/ng.3785
    Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
    Matched MeSH terms: Genome-Wide Association Study/methods
  14. Low JS, Chin YM, Mushiroda T, Kubo M, Govindasamy GK, Pua KC, et al.
    PLoS One, 2016;11(1):e0145774.
    PMID: 26730743 DOI: 10.1371/journal.pone.0145774
    BACKGROUND: Nasopharyngeal carcinoma (NPC) is a neoplasm of the epithelial lining of the nasopharynx. Despite various reports linking genomic variants to NPC predisposition, very few reports were done on copy number variations (CNV). CNV is an inherent structural variation that has been found to be involved in cancer predisposition.

    METHODS: A discovery cohort of Malaysian Chinese descent (NPC patients, n = 140; Healthy controls, n = 256) were genotyped using Illumina® HumanOmniExpress BeadChip. PennCNV and cnvPartition calling algorithms were applied for CNV calling. Taqman CNV assays and digital PCR were used to validate CNV calls and replicate candidate copy number variant region (CNVR) associations in a follow-up Malaysian Chinese (NPC cases, n = 465; and Healthy controls, n = 677) and Malay cohort (NPC cases, n = 114; Healthy controls, n = 124).

    RESULTS: Six putative CNVRs overlapping GRM5, MICA/HCP5/HCG26, LILRB3/LILRA6, DPY19L2, RNase3/RNase2 and GOLPH3 genes were jointly identified by PennCNV and cnvPartition. CNVs overlapping GRM5 and MICA/HCP5/HCG26 were subjected to further validation by Taqman CNV assays and digital PCR. Combined analysis in Malaysian Chinese cohort revealed a strong association at CNVR on chromosome 11q14.3 (Pcombined = 1.54x10-5; odds ratio (OR) = 7.27; 95% CI = 2.96-17.88) overlapping GRM5 and a suggestive association at CNVR on chromosome 6p21.3 (Pcombined = 1.29x10-3; OR = 4.21; 95% CI = 1.75-10.11) overlapping MICA/HCP5/HCG26 genes.

    CONCLUSION: Our results demonstrated the association of CNVs towards NPC susceptibility, implicating a possible role of CNVs in NPC development.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  15. Lau YY, Yin WF, Chan KG
    Sensors (Basel), 2014;14(8):13913-24.
    PMID: 25196111 DOI: 10.3390/s140813913
    Enterobacter asburiae L1 is a quorum sensing bacterium isolated from lettuce leaves. In this study, for the first time, the complete genome of E. asburiae L1 was sequenced using the single molecule real time sequencer (PacBio RSII) and the whole genome sequence was verified by using optical genome mapping (OpGen) technology. In our previous study, E. asburiae L1 has been reported to produce AHLs, suggesting the possibility of virulence factor regulation which is quorum sensing dependent. This evoked our interest to study the genome of this bacterium and here we present the complete genome of E. asburiae L1, which carries the virulence factor gene virK, the N-acyl homoserine lactone-based QS transcriptional regulator gene luxR and the N-acyl homoserine lactone synthase gene which we firstly named easI. The availability of the whole genome sequence of E. asburiae L1 will pave the way for the study of the QS-mediated gene expression in this bacterium. Hence, the importance and functions of these signaling molecules can be further studied in the hope of elucidating the mechanisms of QS-regulation in E. asburiae. To the best of our knowledge, this is the first documentation of both a complete genome sequence and the establishment of the molecular basis of QS properties of E. asburiae.
    Matched MeSH terms: Genome-Wide Association Study/methods
  16. Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al.
    Nat Genet, 2015 Feb;47(2):164-71.
    PMID: 25581431 DOI: 10.1038/ng.3185
    Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
    Matched MeSH terms: Genome-Wide Association Study/methods*
  17. Ku CS, Teo SM, Naidoo N, Sim X, Teo YY, Pawitan Y, et al.
    J Hum Genet, 2011 Aug;56(8):552-60.
    PMID: 21677662 DOI: 10.1038/jhg.2011.54
    Copy number variations can be identified using newer genotyping arrays with higher single nucleotide polymorphisms (SNPs) density and copy number probes accompanied by newer algorithms. McCarroll et al. (2008) applied these to the HapMap II samples and identified 1316 copy number polymorphisms (CNPs). In our study, we applied the same approach to 859 samples from three Singapore populations and seven HapMap III populations. Approximately 50% of the 1291 autosomal CNPs were found to be polymorphic only in populations of non-African ancestry. Pairwise comparisons among the 10 populations showed substantial differences in the CNPs frequencies. Additionally, 698 CNPs showed significant differences with false discovery rate (FDR)<0.01 among the 10 populations and these loci overlap with known disease-associated or pharmacogenetic-related genes such as CFHR3 and CFHR1 (age related macular degeneration), GSTTI (metabolism of various carcinogenic compounds and cancers) and UGT2B17 (prostate cancer and graft-versus-host disease). The correlations between CNPs and genome-wide association studies-SNPs were investigated and several loci, which were previously unreported, that may potentially be implicated in complex diseases and traits were found; for example, childhood acute lymphoblastic leukaemia, age-related macular degeneration, breast cancer, response to antipsychotic treatment, rheumatoid arthritis and type-1 diabetes. Additionally, we also found 5014 novel copy number loci that have not been reported previously by McCarroll et al. (2008) in the 10 populations.
    Matched MeSH terms: Genome-Wide Association Study/methods*
  18. Haerian BS, Lim KS, Tan CT, Raymond AA, Mohamed Z
    Pharmacogenomics, 2011 May;12(5):713-25.
    PMID: 21391884 DOI: 10.2217/pgs.10.212
    Several studies demonstrated a link between ABCB1 gene variants and the response to treatment in epilepsy, but the results have been inconclusive. Here, we performed the first haplotype meta-analysis to examine the association of haplotypes of ABCB1 common variants with the response to treatment in epilepsy.
    Matched MeSH terms: Genome-Wide Association Study/methods*
  19. Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al.
    Nat Genet, 2019 03;51(3):431-444.
    PMID: 30804558 DOI: 10.1038/s41588-019-0344-8
    Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.
    Matched MeSH terms: Genome-Wide Association Study/methods
  20. 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*
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