Displaying publications 21 - 27 of 27 in total

Abstract:
Sort:
  1. 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
  2. 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
  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. 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*
  5. 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*
  6. 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
  7. Cai Q, Zhang B, Sung H, Low SK, Kweon SS, Lu W, et al.
    Nat Genet, 2014 Aug;46(8):886-90.
    PMID: 25038754 DOI: 10.1038/ng.3041
    In a three-stage genome-wide association study among East Asian women including 22,780 cases and 24,181 controls, we identified 3 genetic loci newly associated with breast cancer risk, including rs4951011 at 1q32.1 (in intron 2 of the ZC3H11A gene; P=8.82×10(-9)), rs10474352 at 5q14.3 (near the ARRDC3 gene; P=1.67×10(-9)) and rs2290203 at 15q26.1 (in intron 14 of the PRC1 gene; P=4.25×10(-8)). We replicated these associations in 16,003 cases and 41,335 controls of European ancestry (P=0.030, 0.004 and 0.010, respectively). Data from the ENCODE Project suggest that variants rs4951011 and rs10474352 might be located in an enhancer region and transcription factor binding sites, respectively. This study provides additional insights into the genetics and biology of breast cancer.
    Matched MeSH terms: Genome-Wide Association Study/methods
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links