4 resultados para sonda FDR

em DigitalCommons@The Texas Medical Center


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This study aimed to develop and validate The Cancer Family Impact Scale (CFIS), an instrument for use in studies investigating relationships among family factors and colorectal cancer (CRC) screening when family history is a risk factor. We used existing data to develop the measure from 1,285 participants (637 families) across the United States who were in the Johns Hopkins Colon Cancer Genetic Testing study. Participants were 94% white with an average age of 50.1 years, and 60% were women. None had a personal CRC history, and eighty percent had 1 FDR with CRC and 20% had more than one FDR with CRC. The study had three aims: (1) to identify the latent factors underlying the CFIS via exploratory factor analysis (EFA); (2) to confirm the findings of the EFA via confirmatory factor analysis (CFA); and (3) to assess the reliability of the scale via Cronbach's alpha. Exploratory analyses were performed on a split half of the sample, and the final model was confirmed on the other half. The EFA suggested the CFIS was an 18-item measure with 5 latent constructs: (1) NEGATIVE: negative effects of cancer on the family; (2) POSITIVE: positive effects of cancer on the family; (3) COMMUNICATE: how families communicate about cancer; (4) FLOW: how information about cancer is conveyed in families; and (5) NORM: how individuals react to family norms about cancer. CFA on the holdout sample showed the CFIS to have a reasonably good fit (Chi-square = 389.977, df = 122, RMSEA= 0.058 (.052-.065), CFI=.902, TLI=.877, GF1=.939). The overall reliability of the scale was α=0.65. The reliability of the subscales was: (1) NEGATIVE α = 0.682; (2) POSITIVE α = 0.686; (3) COMMUNICATE α = 0.723; (4) FLOW α = 0.467; and (5) NORM α = 0.732. ^ We concluded the CFIS to be a good measure with most fit levels over 0.90. The CFIS could be used to compare theoretically driven hypotheses about the pathways through which family factors could influence health behavior among unaffected individuals at risk due to family history, and also aid in the development and evaluation of cancer prevention interventions including a family component. ^

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Atherosclerosis is a complex disease resulting from interactions of genetic and environmental risk factors leading to heart failure and stroke. Using an atherosclerotic mouse model (ldlr-/-, apobec1-/- designated as LDb), we performed microarray analysis to identify candidate genes and pathways, which are most perturbed in changes in the following risk factors: genetics (control C57BL/6 vs. LDb mice), shearstress (lesion-prone vs. lesion-resistant regions in LDb mice), diet (chow vs. high fat fed LDb mice) and age (2-month-old vs. 8-month old LDb mice). ^ Atherosclerotic lesion quantification and lipid profile studies were performed to assess the disease phenotype. A microarray study was performed on lesion-prone and lesion-resistant regions of each aorta. Briefly, 32 male C57BL/6 and LDb mice (n =16/each) were fed on either chow or high fat diet, sacrificed at 2- and 8-months old, and RNA isolated from the aortic lesion-prone and aortic lesion-resistant segments. Using 64 Affymetrix Murine 430 2.0 chips, we profiled differentially expressed genes with the cut off value of FDR ≤ 0.15 for t-test, and q <0.0001 for the ANOVA. The data were normalized using two normalization methods---invariant probe sets (Loess) and Quantile normalization, the statistical analysis was performed using t-tests and ANOVA, and pathway characterization was done using Pathway Express (Wayne State). The result identified the calcium signaling pathway as the most significant overrepresented pathway, followed by focal adhesion. In the calcium signaling pathway, 56 genes were found to be significantly differentially expressed out of 180 genes listed in the KEGG calcium signaling pathway. Nineteen of these genes were consistently identified by both statistical tests, 11 of which were unique to the test, and 26 were unique to the ANOVA test, using the cutoffs noted above. ^ In conclusion, this finding suggested that hypercholesterolemia drives the disease progression by altering the expression of calcium channels and regulators which subsequently results in cell differentiation, growth, adhesion, cytoskeletal change and death. Clinically, this pathway may serve as an important target for future therapeutic intervention, and thus the calcium signaling pathway may serve as an important target for future diagnostic and therapeutic intervention. ^

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The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^

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Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^