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1.
Biomed Rep ; 2(5): 737-742, 2014 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-25054020

RESUMO

Lung cancer is one of the main causes of cancer-related mortality. The identification of early diagnostic biomarkers improved outcomes for lung cancer patients. Serum fibrin-fibrinogen degradation products (FDP) levels are elevated in numerous malignancies due to hemostatic alterations. The serum FDP levels were compared to the levels of cytokeratin 19 fragment antigen (CYFRA 21-1), another well-established biomarker. The serum samples from 193 lung cancer patients, 84 healthy controls and 106 patients with benign respiratory diseases were obtained. The serum FDP level was measured using the DR-70 immunoassay and the CYFRA 21-1 level was measured by electrochemiluminescence using the Roche Analytics E170. Receiver operating characteristics curves were used to assess the predictive sensitivity and specificity. The mean serum FDP level in lung cancer patients (35.01±229.02 µg/ml) was significantly higher compared to the 190 non-cancerous subjects (0.60±0.75 µg/ml; P=0.039). The mean serum CYFRA 21-1 level in lung cancer patients (4.50±6.67 ng/ml) was also significantly higher compared to the non-cancerous subjects (1.40±0.83 ng/ml; P<0.05). FDP exhibited clinical sensitivity and specificity of 86 and 75%, respectively, at an optimal cut-off at 0.67 µg/ml. CYFRA 21-1 exhibited clinical sensitivity and specificity of 77 and 74%, respectively, at a cut-off of 1.65 ng/ml. The serum FDP area under the curve (0.87) was slightly higher compared to CYFRA 21-1 (0.83). Therefore, it is apparent that serum FDP is comparable to CYFRA 21-1 as a lung cancer biomarker and can be used for clinical practice.

2.
BMC Proc ; 5 Suppl 9: S66, 2011 Nov 29.
Artigo em Inglês | MEDLINE | ID: mdl-22373457

RESUMO

Statistical tests on rare variant data may well have type I error rates that differ from their nominal levels. Here, we use the Genetic Analysis Workshop 17 data to estimate type I error rates and powers of three models for identifying rare variants associated with a phenotype: (1) by using the number of minor alleles, age, and smoking status as predictor variables; (2) by using the number of minor alleles, age, smoking status, and the identity of the population of the subject as predictor variables; and (3) by using the number of minor alleles, age, smoking status, and ancestry adjustment using 10 principal component scores. We studied both quantitative phenotype and a dichotomized phenotype. The model with principal component adjustment has type I error rates that are closer to the nominal level of significance of 0.05 for single-nucleotide polymorphisms (SNPs) in noncausal genes for the selected phenotype than the model directly adjusting for population. The principal component adjustment model type I error rates are also closer to the nominal level of 0.05 for noncausal SNPs located in causal genes for the phenotype. The power for causal SNPs with the principal component adjustment model is comparable to the power of the other methods. The power using the underlying quantitative phenotype is greater than the power using the dichotomized phenotype.

3.
BMC Proc ; 3 Suppl 7: S107, 2009 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-20017971

RESUMO

BACKGROUND: To account for population stratification in association studies, principal-components analysis is often performed on single-nucleotide polymorphisms (SNPs) across the genome. Here, we use Framingham Heart Study (FHS) Genetic Analysis Workshop 16 data to compare the performance of local ancestry adjustment for population stratification based on principal components (PCs) estimated from SNPs in a local chromosomal region with global ancestry adjustment based on PCs estimated from genome-wide SNPs. METHODS: Standardized height residuals from unrelated adults from the FHS Offspring Cohort were averaged from longitudinal data. PCs of SNP genotype data were calculated to represent individual's ancestry either 1) globally using all SNPs across the genome or 2) locally using SNPs in adjacent 20-Mbp regions within each chromosome. We assessed the extent to which there were differences in association studies of height depending on whether PCs for global, local, or both global and local ancestry were included as covariates. RESULTS: The correlations between local and global PCs were low (r < 0.12), suggesting variability between local and global ancestry estimates. Genome-wide association tests without any ancestry adjustment demonstrated an inflated type I error rate that decreased with adjustment for local ancestry, global ancestry, or both. A known spurious association was replicated for SNPs within the lactase gene, and this false-positive association was abolished by adjustment with local or global ancestry PCs. CONCLUSION: Population stratification is a potential source of bias in this seemingly homogenous FHS population. However, local and global PCs derived from SNPs appear to provide adequate information about ancestry.

4.
J Nanosci Nanotechnol ; 7(11): 3727-30, 2007 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-18047046

RESUMO

We have investigated the degree of dispersion of single-walled carbon nanotubes (SWNTs) in solution using laser spectroscopic techniques. SWNTs were suspended in aqueous media using a sodium dodecyl sulfate (SDS) surfactant. SWNTs with different dispersion states were prepared by controlling the intensity and duration of sonication and centrifugation. The absorption and fluorescence spectroscopic techniques were employed to characterize the different dispersion state of the prepared samples. Nanotube suspensions with better dispersion showed higher fluorescence and sharper absorption peaks. The fluorescence data were characterized as a function of the nanotube chirality, and absorption peak shifts were analyzed depending on the first and second van Hove singularities (vHs) of semiconducting nanotubes.


Assuntos
Coloides/química , Cristalização/métodos , Nanotecnologia/métodos , Nanotubos de Carbono/química , Nanotubos de Carbono/ultraestrutura , Espectrometria de Fluorescência/métodos , Absorção , Teste de Materiais , Conformação Molecular , Tamanho da Partícula
5.
Genet Epidemiol ; 26(2): 132-41, 2004 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-14748013

RESUMO

Which genotype misclassification errors are most costly, in terms of increased sample size necessary (SSN) to maintain constant asymptotic power and significance level, when performing case/control studies of genetic association? We answer this question for single-nucleotide polymorphisms (SNPs), using the 2x3 chi(2) test of independence. Our strategy is to expand the noncentrality parameter of the asymptotic distribution of the chi(2) test under a specified alternative hypothesis to approximate SSN, using a linear Taylor series in the error parameters. We consider two scenarios: the first assumes Hardy-Weinberg equilibrium (HWE) for the true genotypes in both cases and controls, and the second assumes HWE only in controls. The Taylor series approximation has a relative error of less than 1% when each error rate is less than 2%. The most costly error is recording the more common homozygote as the less common homozygote, with indefinitely increasing cost coefficient as minor SNP allele frequencies approach 0 in both scenarios. The cost of misclassifying the more common homozygote to the heterozygote also becomes indefinitely large as the minor SNP allele frequency goes to 0 under both scenarios. For the violation of HWE modeled here, the cost of misclassifying a heterozygote to the less common homozygote becomes large, although bounded. Therefore, the use of SNPs with a small minor allele frequency requires careful attention to the frequency of genotyping errors to ensure that power specifications are met. Furthermore, the design of automated genotyping should minimize those errors whose cost coefficients can become indefinitely large.


Assuntos
Mapeamento Cromossômico/estatística & dados numéricos , Frequência do Gene/genética , Genótipo , Polimorfismo de Nucleotídeo Único/genética , Alelos , Estudos de Casos e Controles , Humanos , Desequilíbrio de Ligação/genética , Computação Matemática , Fenótipo , Reprodutibilidade dos Testes , Tamanho da Amostra , Viés de Seleção , Software
6.
Hum Hered ; 58(3-4): 139-44, 2004.
Artigo em Inglês | MEDLINE | ID: mdl-15812170

RESUMO

Kang et al. [Genet Epidemiol 2004;26:132-141] addressed the question of which genotype misclassification errors are most costly, in terms of minimum percentage increase in sample size necessary (%MSSN) to maintain constant asymptotic power and significance level, when performing case/control studies of genetic association in a genetic model-free setting. They answered the question for single nucleotide polymorphisms (SNPs) using the 2 x 3 chi2 test of independence. We address the same question here for a genetic model-based framework. The genetic model parameters considered are: disease model (dominant, recessive), genotypic relative risk, SNP (marker) and disease allele frequency, and linkage disequilibrium. %MSSN coefficients of each of the six possible error rates are determined by expanding the non-centrality parameter of the asymptotic distribution of the 2 x 3 chi2 test under a specified alternative hypothesis to approximate %MSSN using a linear Taylor series in the error rates. In this work we assume errors misclassifying one homozygote as another homozygote are 0, since these errors are thought to rarely occur in practice. Our findings are that there are settings of the genetic model parameters that lead to large total %MSSN for both dominant and recessive models. As SNP minor allele approaches 0, total %MSSN increases without bound, independent of other genetic model parameters. In general, %MSSN is a complex function of the genetic model parameters. Use of SNPs with small minor allele frequency requires careful attention to frequency of genotyping errors to insure that power specifications are met. Software to perform these calculations for study design is available, and an example of its use to study a disease is given.


Assuntos
Doenças Genéticas Inatas/genética , Genótipo , Polimorfismo de Nucleotídeo Único , Projetos de Pesquisa , Alelos , Frequência do Gene , Genes Dominantes , Genes Recessivos , Heterozigoto , Homozigoto , Humanos , Desequilíbrio de Ligação , Modelos Genéticos , Reprodutibilidade dos Testes , Tamanho da Amostra , Software
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