Displaying publications 61 - 80 of 500 in total

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  1. Nagaya D, Zahari Z, Saleem M, Yahaya BH, Tan SC, Yusoff NM
    J Clin Pharm Ther, 2018 Feb;43(1):80-86.
    PMID: 28656735 DOI: 10.1111/jcpt.12585
    WHAT IS KNOWN: Drug addiction is a novelty-seeking personality trait that is associated with the candidate genes OPRD1 (opioid delta receptors), OPRK1 (opioid kappa receptors) and PDYN (prodynorphin). However, associations between single nucleotide polymorphisms (SNPs) rs1042114 (80G>T) of the OPRD1 gene, rs702764 (843 A>G) of the OPRK1 gene, and rs910080 (3' UTR _743T>C), rs1997794 (5' UTR -381A>G) and rs1022563 (3' UTR) of the PDYN gene and novelty seeking remain controversial as reported results have not been reproducible.

    OBJECTIVE: The goal of this study was to determine the frequencies of SNPs rs1042114, rs702764, rs1997794, rs1022563 and rs910080 in the Malaysian population and to study their association with opioid dependence in Malaysian Malays.

    METHODS: A total of 459 Malay male with opioid dependence and 543 healthy male (controls) subjects were included in this study. SNPs were genotyped using the TaqMan SNP genotyping assay. Statistical analysis was performed using Golden Helix SVS software suite to identify the distribution of allele and genotype frequencies, and SNP-SNP interactions were also analysed in this study.

    RESULTS AND DISCUSSION: SNP rs1042114 in the OPRD1 gene is strongly associated with opiate addiction (P=.0001). In individuals homozygous for this risk allele, the likelihood of opiate addiction is increased by a factor 1.62 (95% confidence interval (CI) 1.412-1.875). Polymorphic alleles at SNP rs702764 of OPRK1 were not associated with opioid dependence. A significant association between opioid dependence and SNP rs910080 of PDYN (P=.0217) was detected, but there was no association for SNPs rs199774 and rs1022563. A significant interaction was also identified between homozygous wild-type genotype TT of rs702764 with the risk genotypes TG/GG of rs1042114 (odds ratio (OR)=2.111 (95% CI 1.227-3.631), P=.0069) and with the risk genotypes GA/AA of rs910080 (OR=1.415 (95% CI 1.04-1.912), P=.0239).

    WHAT IS NEW AND CONCLUSION: The results indicate that SNPs rs1042114 and rs910080 contribute to vulnerability to opioid dependence in the Malaysian Malay population. These results will help us to understand the effect of the SNPs and the SNP-SNP interaction on opioid dependence and may assist in efforts to screen vulnerable individuals and match them with individually tailored prevention and treatment strategies.

    Matched MeSH terms: Genetic Predisposition to Disease/genetics*
  2. Wong HC, Ooi Y, Pulikkotil SJ, Naing C
    BMC Oral Health, 2018 10 22;18(1):171.
    PMID: 30348144 DOI: 10.1186/s12903-018-0637-9
    BACKGROUND: Periodontitis is a major oral health problem and it is considered as one of the reasons for tooth loss in developing and developed nations. The objective of the current review was to investigate the association between IL10 polymorphisms - 1082 A > G (rs1800896), -819C > T (rs1800871), - 592 A > C (rs1800872) and the risk of either chronic periodontitis or aggressive periodontitis.

    METHODS: This is a meta- analysis study, following the preferred reporting items for systematic reviews and meta- analyses (PRISMA). Relevant studies were searched in the health related electronic databases. Methodological quality of the included studies were assessed using the Newcastle-Ottawa Scale. For individual studies, odds ratio (OR) and its 95%confidence interval (CI) were calculated to assess the strength of association between IL10 polymorphisms (- 1082 A > G, -819C > T, - 592 A > C) and the risk of periodontitis. For pooling of the estimates across studies included, the summary OR and its 95% CIs were calculated with random-effects model. The pooled estimates were done under four genetic models such as the allelic contrast model, the recessive model, the dominant model and the additive model. Trial sequential analysis (TSA) was done for estimation of the required information size for this meta-analysis study.

    RESULTS: Sixteen studies were identified for this review. The included studies were assessed to be of moderate to good methodological quality. A significant association between polymorphism of IL10-1082 A > G polymorphism and the risk of chronic periodontitis in the non-Asian populations was observed only in the recessive model (OR,1.42; 95% CI:1.11, 1.8,I2: 43%). The significant associations between - 592 A > C polymorphism and the risk of aggressive periodontitis in the non-Asian populations were observed in particular genetic models such as allele contrast (OR, 4.34; 95%CI:1.87,10.07,I2: 65%) and recessive models (OR, 2.1; 95% CI:1.16, 3.82,I2: 0%). The TSA plot revealed that the required information size for evidence of effect was sufficient to draw a conclusion.

    CONCLUSIONS: This meta-analysis suggested that the IL10-1082 A > G polymorphism was associated with chronic periodontitis CP risk in non-Asians. Thus, in order to further establish the associations between IL10 (- 819 C > T, - 592 A > C) in Asian populations, future studies should include larger sample sizes with multi-ethnic groups.

    Matched MeSH terms: Genetic Predisposition to Disease*
  3. Sim EU, Ting SH
    Biomed Res Int, 2018;2018:4682431.
    PMID: 30112391 DOI: 10.1155/2018/4682431
    Genetic risk to cancer is a knowledge largely confined to experts and the more educated sectors of the developed western countries. The perception of genetic susceptibility to cancer among the masses is fragmented, particularly in developing countries. As cancer diseases affect developing countries as much as developed nations, it is imperative to study perception and reception of genetic risk to cancer in Southeast Asia. Here, we report on a novel case study to gauge the awareness and attitudes towards genetic determination of cancer among the undergraduates of a Malaysian public university. A total of 272 university undergraduate students completed an online questionnaire. On causes of cancer, the respondents believed that cancer is caused by lifestyle and environmental factors, but those with science background were more likely to associate it with genetic factors. The results on awareness of genetic profiling of cancer risk showed that there are significant differences between those with science and nonscience background but there are no significant differences for gender and socioeconomic background. As for attitudes towards cancer risk, female respondents, those from middle socioeconomic status and science background, are more likely to believe in genetic determinism of cancer. The findings have implications on target population segmentation in strategic health communication on cancer.
    Matched MeSH terms: Genetic Predisposition to Disease*
  4. Chua KH, Puah SM, Chew CH, Tan SY, Lian LH
    Ann Hum Biol, 2010 Apr;37(2):274-80.
    PMID: 19951233 DOI: 10.3109/03014460903325185
    In this study, we investigated the polymorphisms of the exon 1 (+49A/G), promoter sites (-1722T/C, -1661A/G, -318C/T), and 3'-untranslated region (3'-UTR) (+6230 A/G) of the CTLA-4 gene in systemic lupus erythematosus (SLE) affected patients. Polymerase chain reaction-restriction fragment length polymorphism was used to determine genotypes of these five markers in 130 SLE patients and 130 healthy controls. Of the five tested polymorphisms, there was no statistical significant difference between the genotypic and allelic frequencies of patients with SLE and controls. Hence, we propose that the CTLA-4 gene does not play a major role in the genetic susceptibility to the development of SLE in the Malaysian population.
    Matched MeSH terms: Genetic Predisposition to Disease*
  5. Hatmal MM, Alshaer W, Mahmoud IS, Al-Hatamleh MAI, Al-Ameer HJ, Abuyaman O, et al.
    PLoS One, 2021;16(10):e0257857.
    PMID: 34648514 DOI: 10.1371/journal.pone.0257857
    CD36 (cluster of differentiation 36) is a membrane protein involved in lipid metabolism and has been linked to pathological conditions associated with metabolic disorders, such as diabetes and dyslipidemia. A case-control study was conducted and included 177 patients with type-2 diabetes mellitus (T2DM) and 173 control subjects to study the involvement of CD36 gene rs1761667 (G>A) and rs1527483 (C>T) polymorphisms in the pathogenesis of T2DM and dyslipidemia among Jordanian population. Lipid profile, blood sugar, gender and age were measured and recorded. Also, genotyping analysis for both polymorphisms was performed. Following statistical analysis, 10 different neural networks and machine learning (ML) tools were used to predict subjects with diabetes or dyslipidemia. Towards further understanding of the role of CD36 protein and gene in T2DM and dyslipidemia, a protein-protein interaction network and meta-analysis were carried out. For both polymorphisms, the genotypic frequencies were not significantly different between the two groups (p > 0.05). On the other hand, some ML tools like multilayer perceptron gave high prediction accuracy (≥ 0.75) and Cohen's kappa (κ) (≥ 0.5). Interestingly, in K-star tool, the accuracy and Cohen's κ values were enhanced by including the genotyping results as inputs (0.73 and 0.46, respectively, compared to 0.67 and 0.34 without including them). This study confirmed, for the first time, that there is no association between CD36 polymorphisms and T2DM or dyslipidemia among Jordanian population. Prediction of T2DM and dyslipidemia, using these extensive ML tools and based on such input data, is a promising approach for developing diagnostic and prognostic prediction models for a wide spectrum of diseases, especially based on large medical databases.
    Matched MeSH terms: Genetic Predisposition to Disease*
  6. 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: Genetic Predisposition to Disease/genetics*
  7. Zuber SH, Yahya N
    J Cancer Res Ther, 2021 6 15;17(2):477-483.
    PMID: 34121695 DOI: 10.4103/jcrt.JCRT_896_18
    Purpose: This study systematically reviews the distribution of racial/ancestral features and their inclusion as covariates in genetic-toxicity association studies following radiation therapy.

    Materials and Methods: Original research studies associating genetic features and normal tissue complications following radiation therapy were identified from PubMed. The distribution of radiogenomic studies was determined by mining the statement of country of origin and racial/ancestrial distribution and the inclusion in analyses. Descriptive analyses were performed to determine the distribution of studies across races/ancestries, countries, and continents and the inclusion in analyses.

    Results: Among 174 studies, only 23 with a population of more one race/ancestry which were predominantly conducted in the United States. Across the continents, most studies were performed in Europe (77 studies averaging at 30.6 patients/million population [pt/mil]), North America (46 studies, 20.8 pt/mil), Asia (46 studies, 2.4 pt/mil), South America (3 studies, 0.4 pt/mil), Oceania (2 studies, 2.1 pt/mil), and none from Africa. All 23 studies with more than one race/ancestry considered race/ancestry as a covariate, and three studies showed race/ancestry to be significantly associated with endpoints.

    Conclusion: Most toxicity-related radiogenomic studies involved a single race/ancestry. Individual Participant Data meta-analyses or multinational studies need to be encouraged.

    Matched MeSH terms: Genetic Predisposition to Disease*
  8. Breast Cancer Association Consortium, Dorling L, Carvalho S, Allen J, González-Neira A, Luccarini C, et al.
    N Engl J Med, 2021 02 04;384(5):428-439.
    PMID: 33471991 DOI: 10.1056/NEJMoa1913948
    BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

    METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

    RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

    CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

    Matched MeSH terms: Genetic Predisposition to Disease/genetics*
  9. Liu J, Prager-van der Smissen WJC, Collée JM, Bolla MK, Wang Q, Michailidou K, et al.
    Sci Rep, 2020 Jun 16;10(1):9688.
    PMID: 32546843 DOI: 10.1038/s41598-020-65665-y
    In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.
    Matched MeSH terms: Genetic Predisposition to Disease/genetics
  10. 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: Genetic Predisposition to Disease*
  11. 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: Genetic Predisposition to Disease/genetics
  12. Tan SC, Low TY, Mohamad Hanif EA, Sharzehan MAK, Kord-Varkaneh H, Islam MA
    Sci Rep, 2021 Sep 20;11(1):18619.
    PMID: 34545128 DOI: 10.1038/s41598-021-97935-8
    The ESR1 rs9340799 polymorphism has been frequently investigated with regard to its association with breast cancer (BC) susceptibility, but the findings have been inconclusive. In this work, we aimed to address the inconsistencies in study findings by performing a systematic review and meta-analysis. Eligible studies were identified from the Web of Science, PubMed, Scopus, China National Knowledge Infrastructure, VIP and Wanfang databases based on the predefined inclusion and exclusion criteria. The pooled odds ratio (OR) was then calculated under five genetic models: homozygous (GG vs. AA), heterozygous (AG vs. AA), dominant (AG + GG vs. AA), recessive (GG vs. AA + AG) and allele (G vs. A). Combined results from 23 studies involving 34,721 subjects indicated a lack of significant association between the polymorphism and BC susceptibility (homozygous model, OR = 1.045, 95% CI 0.887-1.231, P = 0.601; heterozygous model, OR = 0.941, 95% CI 0.861-1.030, P = 0.186; dominant model, OR = 0.957, 95% CI 0.875-1.045, P = 0.327; recessive model, OR = 1.053, 95% CI 0.908-1.222, P = 0.495; allele model, OR = 0.987, 95% CI 0.919-1.059, P = 0.709). Subgroup analyses by ethnicity, menopausal status and study quality also revealed no statistically significant association (P > 0.05). In conclusion, our results showed that the ESR1 rs9340799 polymorphism was not associated with BC susceptibility, suggesting its limited potential as a genetic marker for BC.
    Matched MeSH terms: Genetic Predisposition to Disease*
  13. Yang Y, Shu X, Shu XO, Bolla MK, Kweon SS, Cai Q, et al.
    EBioMedicine, 2019 Oct;48:203-211.
    PMID: 31629678 DOI: 10.1016/j.ebiom.2019.09.006
    BACKGROUND: We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.

    METHODS: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.

    FINDINGS: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P 

    Matched MeSH terms: Genetic Predisposition to Disease*
  14. Yarmolinsky J, Relton CL, Lophatananon A, Muir K, Menon U, Gentry-Maharaj A, et al.
    PLoS Med, 2019 Aug;16(8):e1002893.
    PMID: 31390370 DOI: 10.1371/journal.pmed.1002893
    BACKGROUND: Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours.

    METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.

    CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.

    Matched MeSH terms: Genetic Predisposition to Disease/genetics
  15. Hung KL, Wang JS, Keng WT, Chen HJ, Liang JS, Ngu LH, et al.
    Pediatr Neurol, 2013 Sep;49(3):185-90.
    PMID: 23835273 DOI: 10.1016/j.pediatrneurol.2013.04.021
    X-linked adrenoleukodystrophy is caused by a defective peroxisomal membrane transporter, ABCD1, responsible for transporting very-long-chain fatty acid substrate into peroxisomes for degradation. The main biochemical defect, which is also one of the major diagnostic hallmarks, of X-linked adrenoleukodystrophy is the accumulation of saturated very-long-chain fatty acids in all tissues and body fluids.
    Matched MeSH terms: Genetic Predisposition to Disease/genetics*
  16. Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.
    Nat Genet, 2023 Dec;55(12):2065-2074.
    PMID: 37945903 DOI: 10.1038/s41588-023-01534-4
    The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
    Matched MeSH terms: Genetic Predisposition to Disease*
  17. Sakaue S, Hirata J, Kanai M, Suzuki K, Akiyama M, Lai Too C, et al.
    Nat Commun, 2020 03 26;11(1):1569.
    PMID: 32218440 DOI: 10.1038/s41467-020-15194-z
    The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex traits. Here we apply dimensionality reduction methods (PCA, t-SNE, PCA-t-SNE, UMAP, and PCA-UMAP) to biobank-derived genomic data of a Japanese population (n = 169,719). Dimensionality reduction reveals fine-scale population structure, conspicuously differentiating adjacent insular subpopulations. We further enluciate the demographic landscape of these Japanese subpopulations using population genetics analyses. Finally, we perform phenome-wide polygenic risk score (PRS) analyses on 67 complex traits. Differences in PRS between the deconvoluted subpopulations are not always concordant with those in the observed phenotypes, suggesting that the PRS differences might reflect biases from the uncorrected structure, in a trait-dependent manner. This study suggests that such an uncorrected structure can be a potential pitfall in the clinical application of PRS.
    Matched MeSH terms: Genetic Predisposition to Disease*
  18. 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: Genetic Predisposition to Disease*
  19. Papadimitriou N, Dimou N, Tsilidis KK, Banbury B, Martin RM, Lewis SJ, et al.
    Nat Commun, 2020 01 30;11(1):597.
    PMID: 32001714 DOI: 10.1038/s41467-020-14389-8
    Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomisation analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.51, 95% confidence interval [CI]: 0.27 to 0.98, P-value = 0.04) and colorectal cancer (OR: 0.66, 95% CI: 0.48 to 0.90, P-value = 0.01). We found similar magnitude inverse associations for estrogen positive (ER+ve) breast cancer and for colon cancer. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.
    Matched MeSH terms: Genetic Predisposition to Disease*
  20. Michailidou K, Beesley J, Lindstrom S, Canisius S, Dennis J, Lush MJ, et al.
    Nat Genet, 2015 Apr;47(4):373-80.
    PMID: 25751625 DOI: 10.1038/ng.3242
    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
    Matched MeSH terms: Genetic Predisposition to Disease*
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