Biomedical subjects

Helen Lyon

Publications and source records attributed to Helen Lyon.

6 recordsLinked to original sources

PubMed2006

A common genetic variant is associated with adult and childhood obesity.

Obesity is a heritable trait and a risk factor for many common diseases such as type 2 diabetes, heart disease, and hypertension. We used a dense whole-genome scan of DNA samples from the Framingham Heart Study participants to identify a common genetic variant near the INSIG2 gene associated with obesity. We have replicated the finding in four separate samples composed of individuals of Western European ancestry, African Americans, and children. The obesity-predisposing genotype is present in 10% of individuals. Our study suggests that common genetic polymorphisms are important determinants of obesity.

Adult↗

PubMed2005

Genomic screening and replication using the same data set in family-based association testing.

The Human Genome Project and its spin-offs are making it increasingly feasible to determine the genetic basis of complex traits using genome-wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome-wide family-based association studies, using single SNPs or haplotypes, can identify associations that achieve genome-wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease-susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease-susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype-tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome-wide significance, as population-based designs do.

Asthma↗

PubMed2004

A family-based association test for repeatedly measured quantitative traits adjusting for unknown environmental and/or polygenic effects.

We propose a family-based association test, FBAT-PC, for studies with quantitative traits that are measured repeatedly. The traits may be influenced by partially or completely unknown factors that may vary for each measurement. Using generalized principal component analysis, FBAT-PC amplifies the genetic effects of each measurement by constructing an overall phenotype with maximal heritability. Analytically, and in the simulation studies, we compare FBAT-PC with standard methodology and assess both the heritability of the overall phenotype and the power of FBAT-PC. Compared to univariate analysis, FBAT-PC achieves power gains of up to 200%. Applications of FBAT-PC to an osteoporosis study and to an asthma study show the practical relevance of FBAT-PC. FBAT-PC has been implemented in the software package PBAT and is freely available at http://www.biostat.harvard.edu/~clange/default.htm.

Journal Article↗

PubMed2004

IL10 gene polymorphisms are associated with asthma phenotypes in children.

IL10 is an anti-inflammatory cytokine that has been found to have lower production in macrophages and mononuclear cells from asthmatics. Since reduced IL10 levels may influence the severity of asthma phenotypes, we examined IL10 single-nucleotide polymorphisms (SNPs) for association with asthma severity and allergy phenotypes as quantitative traits. Utilizing DNA samples from 518 Caucasian asthmatic children from the Childhood Asthma Management Program (CAMP) and their parents, we genotyped six IL10 SNPs: 3 in the promoter, 2 in introns, and one in the 3' UTR. Using family-based association tests, each SNP was tested for association with asthma and allergy phenotypes individually. Population-based association analysis was performed with each SNP locus, the promoter haplotypes and the 6-loci haplotypes. The 3' UTR SNP was significantly associated with FEV(1) as a percent of predicted (FEV(1)PP) (P=0.0002) in both the family and population analyses. The promoter haplotype GCC was positively associated with IgE levels and FEV(1)PP (P=0.007 and 0.012, respectively). The promoter haplotype ATA was negatively associated with lnPC(20) and FEV(1)PP (P=0.008 and 0.043, respectively). Polymorphisms in IL10 are associated with asthma phenotypes in this cohort. Further studies of variation in the IL10 gene may help elucidate the mechanism of asthma development in children.

3' Untranslated Regions↗

PubMed2003

Gene expression profile after cardiopulmonary bypass and cardioplegic arrest.

OBJECTIVE: This study examines the cardiac and peripheral gene expression responses to cardiopulmonary bypass and cardioplegic arrest. METHODS: Atrial myocardium and skeletal muscle were harvested from 16 patients who underwent coronary artery bypass grafting before and after cardiopulmonary bypass and cardioplegic arrest. Ten sample pairs were selected for patient similarity, and oligonucleotide microarray analyses of 12,625 genes were performed using matched precardiopulmonary bypass tissues as controls. Array results were validated with Northern blotting, real-time polymerase chain reaction, in situ hybridization, and immunoblotting. Statistical analyses were nonparametric. RESULTS: Median durations of cardiopulmonary bypass and cardioplegic arrest were 74 and 60 minutes, respectively. Compared with precardiopulmonary bypass, postcardiopulmonary bypass myocardial tissues revealed 480 up-regulated and 626 down-regulated genes with a threshold P value of.025 or less (signal-to-noise ratio: 3.46); skeletal muscle tissues showed 560 and 348 such genes, respectively (signal-to-noise ratio: 3.04). Up-regulated genes in cardiac tissues included inflammatory and transcription activators FOS; jun B proto-oncogene; nuclear receptor subfamily 4, group A, member 3; MYC; transcription factor-8; endothelial leukocyte adhesion molecule-1; and cysteine-rich 61; apoptotic genes nuclear receptor subfamily 4, group A, member 1 and cyclin-dependent kinase inhibitor 1A; and stress genes dual-specificity phosphatase-1, dual-specificity phosphatase-5, and B-cell translocation gene 2. Up-regulated skeletal muscle genes included interleukin 6; interleukin 8; tumor necrosis factor receptor superfamily, member 11B; nuclear receptor subfamily 4, group A, member 3; transcription factor-8; interleukin 13; jun B proto-oncogene; interleukin 1B; glycoprotein Ib, platelet, alpha polypeptide; and Ras-associated protein RAB27A. Down-regulated genes included haptoglobin and numerous immunoglobulins in the heart, and factor H-related gene 2, protein phosphatase 1, regulatory subunit 3A, and growth differentiation factor-8 in skeletal muscle. CONCLUSIONS: By establishing a profile of the gene-expression responses to cardiopulmonary bypass and cardioplegia, this study allows a better understanding of their effects and provides a framework for the evaluation of new cardiac surgical modalities directly at the genome level.

Aged↗

PubMed2003

A new powerful non-parametric two-stage approach for testing multiple phenotypes in family-based association studies.

We introduce a new powerful nonparametric testing strategy for family-based association studies in which multiple quantitative traits are recorded and the phenotype with the strongest genetic component is not known prior to the analysis. In the first stage, using a population-based test based on the generalized estimating equation approach, we test all recorded phenotypes for association with the marker locus without biasing the nominal significance level of the later family-based analysis. In the second stage the phenotype with the smallest p value is selected and tested by a family-based association test for association with the marker locus. This strategy is robust against population admixture and stratification and does not require any adjustment for multiple testing. We demonstrate the advantages of this testing strategy over standard methodology in a simulation study. The practical importance of our testing strategy is illustrated by applications to the Childhood Asthma Management Program asthma data sets.

Asthma↗