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Replication of TCF4 through Association and Linkage Studies in Late-Onset Fuchs Endothelial Corneal Dystrophy

Fuchs endothelial corneal dystrophy (FECD) is a common, late-onset disorder of the corneal endothelium. Although progress has been made in understanding the genetic basis of FECD by studying large families in which the phenotype is transmitted in an autosomal dominant fashion, a recently reported genome-wide association study identified common alleles at a locus on chromosome 18 near TCF4 which confer susceptibility to FECD. Here, we report the findings of our independent validation study for TCF4 using the largest FECD dataset to date (450 FECD cases and 340 normal controls). Logistic regression with sex as a covariate was performed for three genetic models: dominant (DOM), additive (ADD), and recessive (REC). We found significant association with rs613872, the target marker reported by Baratz et al.(2010), for all three genetic models (DOM: P = 9.33×10−35; ADD: P = 7.48×10−30; REC: P = 5.27×10−6). To strengthen the association study, we also conducted a genome-wide linkage scan on 64 multiplex families, composed primarily of affected sibling pairs (ASPs), using both parametric and non-parametric two-point and multipoint analyses. The most significant linkage region localizes to chromosome 18 from 69.94cM to 85.29cM, with a peak multipoint HLOD = 2.5 at rs1145315 (75.58cM) under the DOM model, mapping 1.5 Mb proximal to rs613872. In summary, our study presents evidence to support the role of the intronic TCF4 single nucleotide polymorphism rs613872 in late-onset FECD through both association and linkage studies

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice. Methods. We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers’ use of genetic and genomic testing options and indications in clinical practice, providers’ awareness of pharmacogenetic applications, and providers’ opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice. Methods. We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers’ use of genetic and genomic testing options and indications in clinical practice, providers’ awareness of pharmacogenetic applications, and providers’ opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

UnlabelledIn this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice.MethodsWe surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers' use of genetic and genomic testing options and indications in clinical practice, providers' awareness of pharmacogenetic applications, and providers' opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships

Polymorphic variants in tenascin-C (TNC) are associated with atherosclerosis and coronary artery disease

Tenascin-C ( TNC ) is an extracellular matrix protein implicated in biological processes important for atherosclerotic plaque development and progression, including smooth muscle cell migration and proliferation. Previously, we observed differential expression of TNC in atherosclerotic aortas compared with healthy aortas. The goal of this study was to investigate whether common genetic variation within TNC is associated with risk of atherosclerosis and coronary artery disease (CAD) in three independent datasets. We genotyped 35 single nucleotide polymorphisms (SNPs), including 21 haplotype tagging SNPs, in two of these datasets: human aorta tissue samples ( n = 205) and the CATHGEN cardiovascular study ( n = 1,325). Eleven of these 35 SNPs were then genotyped in a third dataset, the GENECARD family study of early-onset CAD ( n = 879 families). Three SNPs representing a block of linkage disequilibrium, rs3789875, rs12347433, and rs4552883, were significantly associated with athero sclerosis in multiple datasets and demonstrated consistent, but suggestive, genetic effects in all analyses. In combined analysis rs3789875 and rs12347433 were statistically significant after Bonferroni correction for 35 comparisons, p = 2 × 10 −6 and 5 × 10 −6 , respectively. The SNP rs12347433 is a synonymous coding SNP and may be biologically relevant to the mechanism by which tenascin-C influences the pathophysiology of CAD and atherosclerosis. This is the first report of genetic association between polymorphisms in TNC and atherosclerosis or CAD

Results of the multipoint linkage analysis using MERLIN.

<p>Note: All linkage regions with a LOD score >1.5 at the peak marker in at least one of the multipoint analyses, nonparametric (NPL), dominant (DOM), or recessive (REC), are presented. The upper and lower bounds of each linkage peak interval presented were selected based on covering all markers with a LOD or HLOD score within one LOD score unit of the peak marker's LOD score. The peak LOD scores are indicated with <b>bold text</b>. Chr, chromosome; SNP, single nucleotide polymorphism; LOD, logarithm of the odds; HLOD, heterogeneity logarithm of the odds.</p

Worldwide distribution of the minor (risk) allele, G, of rs613872 in <i>TCF4.</i>

<p>Data from the Human Genome Diversity Project, available online through the UCSC genome browser at <a href="http://genome.ucsc.edu/" target="_blank">http://genome.ucsc.edu/</a>. Note the higher prevalence of the risk allele in sample populations from Europe, the Middle East, and Southern Asia and the absence of the risk allele in sample populations from Africa, Eastern Asia, and Central and South America.</p

Comparison of genotype frequencies between Duke dataset and dataset used in Baratz et al. (2010), and between male and female in Duke dataset for rs613872.

<p>*<b>N: total sample size.</b></p><p>**<b>Heterozygous frequencies are elevated in all datasets and are highlighted in bold.</b></p

Plot of the top multipoint linkage peak on chromosome 18.

<p>SNP markers are plotted along the x-axis by their deCODE map position, and the LOD/HLOD scores for each marker are plotted along the y-axis. The results of the FASTLINK/HOMOG dominant two-point analysis are indicated with black circles, and the results of the MERLIN dominant multipoint analysis are indicated with a black line. The SNP rs4941043 is the peak marker from the two-point analysis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0018044#pone-0018044-t003" target="_blank"><b>Table 3</b></a>). The location of the <i>FCD2</i> peak (Sundin <i>et al.</i>, 2006) and the most significantly associated SNP, rs613872, from the FECD GWAS performed by Baratz <i>et al.</i> (2010) are indicated by arrows. The location of the <i>TCF4</i> gene is also indicated for reference. 2PT, two-point results; MPT, multipoint results; cM, centiMorgans; LOD, logarithm of the odds; HLOD, heterogeneity logarithm of the odds.</p