24 resultados para Case-Control
Resumo:
Alcohol and tobacco consumption are well-recognized risk factors for head and neck cancer (HNC). Evidence suggests that genetic predisposition may also play a role. Only a few epidemiologic studies, however, have considered the relation between HNC risk and family history of HNC and other cancers. We pooled individual-level data across 12 case-control studies including 8,967 HNC cases and 13,627 controls. We obtained pooled odds ratios (OR) using fixed and random effect models and adjusting for potential confounding factors. All statistical tests were two-sided. A family history of HNC in first-degree relatives increased the risk of HNC (OR=1.7, 95% confidence interval, CI, 1.2-2.3). The risk was higher when the affected relative was a sibling (OR=2.2, 95% CI 1.6-3.1) rather than a parent (OR=1.5, 95% CI 1.1-1.8) and for more distal HNC anatomic sites (hypopharynx and larynx). The risk was also higher, or limited to, in subjects exposed to tobacco. The OR rose to 7.2 (95% CI 5.5-9.5) among subjects with family history, who were alcohol and tobacco users. A weak but significant association (OR=1.1, 95% CI 1.0-1.2) emerged for family history of other tobacco-related neoplasms, particularly with laryngeal cancer (OR=1.3, 95% CI 1.1-1.5). No association was observed for family history of nontobacco-related neoplasms and the risk of HNC (OR=1.0, 95% CI 0.9-1.1). Familial factors play a role in the etiology of HNC. In both subjects with and without family history of HNC, avoidance of tobacco and alcohol exposure may be the best way to avoid HNC.
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Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.
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OBJECTIVE: A distinct subset of proinflammatory CD4+ T cells that produce interleukin-17 was recently identified. These cells are implicated in different autoimmune disease models, such as experimental autoimmune encephalomyelitis and collagen-induced arthritis, but their involvement in human autoimmune disease has not yet been clearly established. The purpose of this study was to assess the frequency and functional properties of Th17 cells in healthy donors and in patients with different autoimmune diseases. METHODS: Peripheral blood was obtained from 10 psoriatic arthritis (PsA), 10 ankylosing spondylitis (AS), 10 rheumatoid arthritis (RA), and 5 vitiligo patients, as well as from 25 healthy donors. Synovial tissue samples from a separate group of patients were also evaluated (obtained as paraffin-embedded sections). Peripheral blood cells were analyzed by multiparameter flow cytometry and immunohistochemistry. Cytokine production was examined by enzyme-linked immunosorbent assay and intracellular cytokine staining using specific monoclonal antibodies. Synovial tissue was examined for infiltrating T cells by immunohistochemical analysis. RESULTS: We found increased numbers of circulating Th17 cells in the peripheral blood of patients with seronegative spondylarthritides (PsA and AS), but not in patients with RA or vitiligo. In addition, Th17 cells from the spondylarthritis patients showed advanced differentiation and were polyfunctional in terms of T cell receptor-driven cytokine production. CONCLUSION: These observations suggest a role of Th17 cells in the pathogenesis of certain human autoimmune disorders, in particular the seronegative spondylarthritides.
Resumo:
BACKGROUND: The magnitude of risk conferred by the interaction between tobacco and alcohol use on the risk of head and neck cancers is not clear because studies have used various methods to quantify the excess head and neck cancer burden. METHODS: We analyzed individual-level pooled data from 17 European and American case-control studies (11,221 cases and 16,168 controls) participating in the International Head and Neck Cancer Epidemiology consortium. We estimated the multiplicative interaction parameter (psi) and population attributable risks (PAR). RESULTS: A greater than multiplicative joint effect between ever tobacco and alcohol use was observed for head and neck cancer risk (psi = 2.15; 95% confidence interval, 1.53-3.04). The PAR for tobacco or alcohol was 72% (95% confidence interval, 61-79%) for head and neck cancer, of which 4% was due to alcohol alone, 33% was due to tobacco alone, and 35% was due to tobacco and alcohol combined. The total PAR differed by subsite (64% for oral cavity cancer, 72% for pharyngeal cancer, 89% for laryngeal cancer), by sex (74% for men, 57% for women), by age (33% for cases <45 years, 73% for cases >60 years), and by region (84% in Europe, 51% in North America, 83% in Latin America). CONCLUSIONS: Our results confirm that the joint effect between tobacco and alcohol use is greater than multiplicative on head and neck cancer risk. However, a substantial proportion of head and neck cancers cannot be attributed to tobacco or alcohol use, particularly for oral cavity cancer and for head and neck cancer among women and among young-onset cases.
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To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.
Resumo:
OBJECTIVE: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.
Resumo:
Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
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BACKGROUND: Increasing incidence of head and neck cancer (HNC) in young adults has been reported. We aimed to compare the role of major risk factors and family history of cancer in HNC in young adults and older patients. METHODS: We pooled data from 25 case-control studies and conducted separate analyses for adults ≤45 years old ('young adults', 2010 cases and 4042 controls) and >45 years old ('older adults', 17 700 cases and 22 704 controls). Using logistic regression with studies treated as random effects, we estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: The young group of cases had a higher proportion of oral tongue cancer (16.0% in women; 11.0% in men) and unspecified oral cavity / oropharynx cancer (16.2%; 11.1%) and a lower proportion of larynx cancer (12.1%; 16.6%) than older adult cases. The proportions of never smokers or never drinkers among female cases were higher than among male cases in both age groups. Positive associations with HNC and duration or pack-years of smoking and drinking were similar across age groups. However, the attributable fractions (AFs) for smoking and drinking were lower in young when compared with older adults (AFs for smoking in young women, older women, young men and older men, respectively, = 19.9% (95% CI = 9.8%, 27.9%), 48.9% (46.6%, 50.8%), 46.2% (38.5%, 52.5%), 64.3% (62.2%, 66.4%); AFs for drinking = 5.3% (-11.2%, 18.0%), 20.0% (14.5%, 25.0%), 21.5% (5.0%, 34.9%) and 50.4% (46.1%, 54.3%). A family history of early-onset cancer was associated with HNC risk in the young [OR = 2.27 (95% CI = 1.26, 4.10)], but not in the older adults [OR = 1.10 (0.91, 1.31)]. The attributable fraction for family history of early-onset cancer was 23.2% (8.60% to 31.4%) in young compared with 2.20% (-2.41%, 5.80%) in older adults. CONCLUSIONS: Differences in HNC aetiology according to age group may exist. The lower AF of cigarette smoking and alcohol drinking in young adults may be due to the reduced length of exposure due to the lower age. Other characteristics, such as those that are inherited, may play a more important role in HNC in young adults compared with older adults.
Resumo:
UNLABELLED: Trabecular bone score (TBS) seems to provide additive value on BMD to identify individuals with prevalent fractures in T1D. TBS did not significantly differ between T1D patients and healthy controls, but TBS and HbA1c were independently associated with prevalent fractures in T1D. A TBS cutoff <1.42 reflected prevalent fractures with 91.7 % sensitivity and 43.2 % specificity. INTRODUCTION: Type 1 diabetes (T1D) increases the risk of osteoporotic fractures. TBS was recently proposed as an indirect measure of bone microarchitecture. This study aimed at investigating the TBS in T1D patients and healthy controls. Associations with prevalent fractures were tested. METHODS: One hundred nineteen T1D patients (59 males, 60 premenopausal females; mean age 43.4 ± 8.9 years) and 68 healthy controls matched for gender, age, and body mass index (BMI) were analyzed. The TBS was calculated in the lumbar region, based on two-dimensional (2D) projections of DXA assessments. RESULTS: TBS was 1.357 ± 0.129 in T1D patients and 1.389 ± 0.085 in controls (p = 0.075). T1D patients with prevalent fractures (n = 24) had a significantly lower TBS than T1D patients without fractures (1.309 ± 0.125 versus 1.370 ± 0.127, p = 0.04). The presence of fractures in T1D was associated with lower TBS (odds ratio = 0.024, 95 % confidence interval (CI) = 0.001-0.875; p = 0.042) but not with age or BMI. TBS and HbA1c were independently associated with fractures. The area-under-the curve (AUC) of TBS was similar to that of total hip BMD in discriminating T1D patients with or without prevalent fractures. In this set-up, a TBS cutoff <1.42 discriminated the presence of fractures with a sensitivity of 91.7 % and a specificity of 43.2 %. CONCLUSIONS: TBS values are lower in T1D patients with prevalent fractures, suggesting an alteration of bone strength in this subgroup of patients. Reliable TBS cutoffs for the prediction of fracture risk in T1D need to be determined in larger prospective studies.