4 resultados para MEN 1 syndrome

em DigitalCommons@The Texas Medical Center


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Prostate cancer (PrCa) is a leading cause of morbidity and mortality, yet the etiology remains uncertain. Meta-analyses show that PrCa risk is reduced by 16% in men with type 2 diabetes (T2D), but the mechanism is unknown. Recent genome-wide association studies and meta-analyses have found single nucleotide polymorphisms (SNPs) that consistently predict T2D risk. We evaluated associations of incident PrCa with 14 T2D SNPs in the Atherosclerosis Risk in Communities (ARIC) study. From 1987-2000, there were 397 incident PrCa cases ascertained from state or local cancer registries among 6,642 men (1,560 blacks and 5,082 whites) aged 45-64 years at baseline. Genotypes were determined by TaqMan assay. Cox proportional hazards models were used to assess the association between PrCa and increasing number of T2D risk-raising alleles for individual SNPs and for genetic risk scores (GRS) comprised of the number of T2D risk-raising alleles across SNPs. Two-way gene-gene interactions were evaluated with likelihood ratio tests. Using additive genetic models, the T2D risk-raising allele was associated with significantly reduced risk of PrCa for IGF2BP2 rs4402960 (hazard ratio [HR]=0.79; P=0.07 among blacks only), SLC2A2 rs5400 (race-adjusted HR=0.85; P=0.05) and UCP2 rs660339 (race-adjusted HR=0.84; P=0.02), but significantly increased risk of PrCa for CAPN10 rs3792267 (race-adjusted HR=1.20; P=0.05). No other SNPs were associated with PrCa using an additive genetic model. However, at least one copy of the T2D risk-raising allele for TCF7L2 rs7903146 was associated with reduced PrCa risk using a dominant genetic model (race-adjusted HR=0.79; P=0.03). These results imply that the T2D-PrCa association may be partly due to shared genetic variation, but these results should be verified since multiple tests were performed. When the combined, additive effects of these SNPs were tested using a GRS, there was nearly a 10% reduction in risk of PrCa per T2D risk-raising allele (race-adjusted HR=0.92; P=0.02). SNPs in IGF2BP2, KCNJ11 and SLC2A2 were also involved in multiple synergistic gene-gene interactions on a multiplicative scale. In conclusion, it appears that the T2D-PrCa association may be due, in part, to common genetic variation. Further knowledge of T2D gene-PrCa mechanisms may improve understanding of PrCa etiology and may inform PrCa prevention and treatment.^

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Little is known about epidemiological markers that are associated with survival of patients with myelodysplastic syndromes (MDS). We conducted a secondary case-based analysis of 465 de novo MDS patients from the University of Texas MD Anderson Cancer Center (UTMDACC). We investigated the association between demographic as well as occupational exposure markers and survival while incorporating known clinical markers of prognosis. In our patient population, 60.6% were men and the majority were white (93.1%). The distribution of MDS subtypes by the French–American–British (FAB) classification was 81 (19%) refractory anemia (RA), 46 (9.9%) refractory anemia with ringed sideroblasts (RARS), 57 (12.3%) chronic myelomonocytic leukemia (CMML), 173 (37.2%) RA with excess blasts (RAEB), and 86 (18.5%) RAEB in transformation (RAEBT). We found that those older at diagnosis (> 60 years of age) (HR = 1.68, CI = 1.26-2.25) were at a higher risk of dying compared to younger patients. Similarly, high pack years of smoking (>= 30 pack years of smoking) (HR = 1.34, CI = 1.02-1.74), and agricultural chemical exposure (HR = 1.61, CI = 1.05-2.46) were significantly associated with overall lower survival when compared to patients with none or medium exposures. Among clinical markers, greater than 5% bone marrow blasts (HR = 1.81 CI = 1.27-2.56), poor cytogenetics (HR = 3.20, CI = 2.37-4.33)), and platelet cytopenias (<100000/ul) (HR = 1.46, CI = 1.11-1.92) were also significantly associated with overall MDS survival.^ The identification of epidemiological markers could help physicians stratify patients and customize treatment strategies to improve the outcome of MDS based on patient lifestyle information such as smoking exposure and agrochemical exposure. We hope that this study highlights the impact of these exposures in MDS prognosis.^

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Metabolic Syndrome (MetS) is a clustering of cardiovascular (CV) risk factors that includes obesity, dyslipidemia, hyperglycemia, and elevated blood pressure. Applying the criteria for MetS can serve as a clinically feasible tool for identifying patients at high risk for CV morbidity and mortality, particularly those who do not fall into traditional risk categories. The objective of this study was to examine the association between MetS and CV mortality among 10,940 American hypertensive adults, ages 30-69 years, participating in a large randomized controlled trial of hypertension treatment (HDFP 1973-1983). MetS was defined as the presence of hypertension and at least two of the following risk factors: obesity, dyslipidemia, or hyperglycemia. Of the 10,763 individuals with sufficient data available for analysis, 33.2% met criteria for MetS at baseline. The baseline prevalence of MetS was significantly higher among women (46%) than men (22%) and among non-blacks (37%) versus blacks (30%). All-cause and CV mortality was assessed for 10,763 individuals. Over a median follow-up of 7.8 years, 1,425 deaths were observed. Approximately 53% of these deaths were attributed to CV causes. Compared to individuals without MetS at baseline, those with MetS had higher rates of all-cause mortality (14.5% v. 12.6%) and CV mortality (8.2% versus 6.4%). The unadjusted risk of CV mortality among those with MetS was 1.31 (95% confidence interval [CI], 1.12-1.52) times that for those without MetS at baseline. After multiple adjustment for traditional risk factors of age, race, gender, history of cardiovascular disease (CVD), and smoking status, individuals with MetS, compared to those without MetS, were 1.42 (95% CI, 1.20-1.67) times more likely to die of CV causes. Of the individual components of MetS, hyperglycemia/diabetes conferred the strongest risk of CV mortality (OR 1.73; 95% CI, 1.39-2.15). Results of the present study suggest MetS defined as the presence of hypertension and 2 additional cardiometabolic risk factors (obesity, dyslipidemia, or hyperglycemia/diabetes) can be used with some success to predict CV mortality in middle-aged hypertensive adults. Ongoing and future prospective studies are vital to examine the association between MetS and cardiovascular morbidity and mortality in select high-risk subpopulations, and to continue evaluating the public health impact of aggressive, targeted screening, prevention, and treatment efforts to prevent future cardiovascular disability and death.^

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Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^