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Dive into the research topics where Sharon L.R. Kardia is active.

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Featured researches published by Sharon L.R. Kardia.


Molecular & Cellular Proteomics | 2002

Discordant Protein and mRNA Expression in Lung Adenocarcinomas

Guoan Chen; Tarek G. Gharib; Chiang Ching Huang; Jeremy M. G. Taylor; David E. Misek; Sharon L.R. Kardia; Thomas J. Giordano; Mark D. Iannettoni; Mark B. Orringer; Samir M. Hanash; David G. Beer

The relationship between gene expression measured at the mRNA level and the corresponding protein level is not well characterized in human cancer. In this study, we compared mRNA and protein expression for a cohort of genes in the same lung adenocarcinomas. The abundance of 165 protein spots representing 98 individual genes was analyzed in 76 lung adenocarcinomas and nine non-neoplastic lung tissues using two-dimensional polyacrylamide gel electrophoresis. Specific polypeptides were identified using matrix-assisted laser desorption/ionization mass spectrometry. For the same 85 samples, mRNA levels were determined using oligonucleotide microarrays, allowing a comparative analysis of mRNA and protein expression among the 165 protein spots. Twenty-eight of the 165 protein spots (17%) or 21 of 98 genes (21.4%) had a statistically significant correlation between protein and mRNA expression (r > 0.2445; p < 0.05); however, among all 165 proteins the correlation coefficient values (r) ranged from −0.467 to 0.442. Correlation coefficient values were not related to protein abundance. Further, no significant correlation between mRNA and protein expression was found (r = −0.025) if the average levels of mRNA or protein among all samples were applied across the 165 protein spots (98 genes). The mRNA/protein correlation coefficient also varied among proteins with multiple isoforms, indicating potentially separate isoform-specific mechanisms for the regulation of protein abundance. Among the 21 genes with a significant correlation between mRNA and protein, five genes differed significantly between stage I and stage III lung adenocarcinomas. Using a quantitative analysis of mRNA and protein expression within the same lung adenocarcinomas, we showed that only a subset of the proteins exhibited a significant correlation with mRNA abundance.


American Journal of Human Genetics | 2005

Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies

Hua Tang; Thomas Quertermous; Beatriz L. Rodriguez; Sharon L.R. Kardia; Xiaofeng Zhu; Andrew Brown; James S. Pankow; Michael A. Province; Steven C. Hunt; Eric Boerwinkle; Nicholas J. Schork; Neil Risch

We have analyzed genetic data for 326 microsatellite markers that were typed uniformly in a large multiethnic population-based sample of individuals as part of a study of the genetics of hypertension (Family Blood Pressure Program). Subjects identified themselves as belonging to one of four major racial/ethnic groups (white, African American, East Asian, and Hispanic) and were recruited from 15 different geographic locales within the United States and Taiwan. Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed near-perfect correspondence with the four self-reported race/ethnicity categories. Of 3,636 subjects of varying race/ethnicity, only 5 (0.14%) showed genetic cluster membership different from their self-identified race/ethnicity. On the other hand, we detected only modest genetic differentiation between different current geographic locales within each race/ethnicity group. Thus, ancient geographic ancestry, which is highly correlated with self-identified race/ethnicity--as opposed to current residence--is the major determinant of genetic structure in the U.S. population. Implications of this genetic structure for case-control association studies are discussed.


Proceedings of the National Academy of Sciences of the United States of America | 2003

Protein profiles associated with survival in lung adenocarcinoma

Guoan Chen; Tarek G. Gharib; Hong Wang; Chiang Ching Huang; Rork Kuick; Dafydd G. Thomas; Kerby Shedden; David E. Misek; Jeremy M. G. Taylor; Thomas J. Giordano; Sharon L.R. Kardia; Mark D. Iannettoni; John Yee; Philip J. Hogg; Mark B. Orringer; Samir M. Hanash; David G. Beer

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer.


Circulation | 1998

Variation in the Region of the Angiotensin-Converting Enzyme Gene Influences Interindividual Differences in Blood Pressure Levels in Young White Males

Myriam Fornage; Christopher I. Amos; Sharon L.R. Kardia; Charles F. Sing; Stephen T. Turner; Eric Boerwinkle

BACKGROUND The renin-angiotensin system regulates blood pressure through its effects on vascular tone, renal hemodynamics, and renal sodium and fluid balance. METHODS AND RESULTS Using data from a large population-based sample of 1488 siblings having a mean age of 14.8 years and belonging to the youngest generation of 583 randomly ascertained three-generation pedigrees from Rochester, Minn, we carried out variance components-based linkage analyses to evaluate the contribution of variation in four renin-angiotensin system gene regions (angiotensinogen, renin, angiotensin I-converting enzyme, and angiotensin II receptor type 1) to interindividual variation in systolic, diastolic, and mean arterial pressure. We rejected the null hypothesis that allelic variation in the region of the angiotensin-converting enzyme (ACE) gene does not contribute to interindividual blood pressure variability. After conditioning on measured covariates, variation in this region accounted for 0%, 13% (P=0.04), and 16% (P=0.04) of the interindividual variance in systolic, diastolic, and mean arterial pressures, respectively. These estimates were even greater in a subset of subjects with a positive family history of hypertension (0%, 29% [P=0.005], and 32% [P<0.005], respectively). In sex-specific analyses, genetic variation in the region of the ACE gene significantly influenced interindividual blood pressure variation in males (37% for SBP [P=0.03], 38% for DBP [P=0.04], and 53% for MAP [P<0.005]) but not in females. CONCLUSIONS Although it is possible that variation in a gene near the ACE gene may explain the observed results, knowledge about the physiological involvement of ACE in blood pressure regulation supports the proposition that the ACE gene itself influences blood pressure variability in a sex-specific manner.


American Journal of Pathology | 2001

Organ-Specific Molecular Classification of Primary Lung, Colon, and Ovarian Adenocarcinomas Using Gene Expression Profiles

Thomas J. Giordano; Kerby Shedden; Donald R. Schwartz; Rork Kuick; Jeremy M. G. Taylor; Nana Lee; David E. Misek; Joel K. Greenson; Sharon L.R. Kardia; David G. Beer; Gad Rennert; Kathleen R. Cho; Stephen B. Gruber; Eric R. Fearon; Samir M. Hanash

Molecular classification of tumors based on their gene expression profiles promises to significantly refine diagnosis and management of cancer patients. The establishment of organ-specific gene expression patterns represents a crucial first step in the clinical application of the molecular approach. Here, we report on the gene expression profiles of 154 primary adenocarcinomas of the lung, colon, and ovary. Using high-density oligonucleotide arrays with 7129 gene probe sets, comprehensive gene expression profiles of 57 lung, 51 colon, and 46 ovary adenocarcinomas were generated and subjected to principle component analysis and to a cross-validated prediction analysis using nearest neighbor classification. These statistical analyses resulted in the classification of 152 of 154 of the adenocarcinomas in an organ-specific manner and identified genes expressed in a putative tissue-specific manner for each tumor type. Furthermore, two tumors were identified, one in the colon group and another in the ovarian group, that did not conform to their respective organ-specific cohorts. Investigation of these outlier tumors by immunohistochemical profiling revealed the ovarian tumor was consistent with a metastatic adenocarcinoma of colonic origin and the colonic tumor was a pleomorphic mesenchymal tumor, probably a leiomyosarcoma, rather than an epithelial tumor. Our results demonstrate the ability of gene expression profiles to classify tumors and suggest that determination of organ-specific gene expression profiles will play a significant role in a wide variety of clinical settings, including molecular diagnosis and classification.


Journal of Genetic Counseling | 2004

Exploring the Public Understanding of Basic Genetic Concepts

Angela D. Lanie; Toby Epstein Jayaratne; Jane P. Sheldon; Sharon L.R. Kardia; Elizabeth Anderson; Merle Feldbaum; Elizabeth M. Petty

It is predicted that the rapid acquisition of new genetic knowledge and related applications during the next decade will have significant implications for virtually all members of society. Currently, most people get exposed to information about genes and genetics only through stories publicized in the media. We sought to understand how individuals in the general population used and understood the concepts of “genetics” and “genes.” During in-depth one-on-one telephone interviews with adults in the United States, we asked questions exploring their basic understanding of these terms, as well as their belief as to the location of genes in the human body. A wide range of responses was received. Despite conversational familiarity with genetic terminology, many noted frustration or were hesitant when trying to answer these questions. In addition, some responses reflected a lack of understanding about basic genetic science that may have significant implications for broader public education measures in genetic literacy, genetic counseling, public health practices, and even routine health care.


Genetics in Medicine | 2009

The Scientific Foundation for Personal Genomics: Recommendations from a National Institutes of Health–Centers for Disease Control and Prevention Multidisciplinary Workshop

Muin J. Khoury; Colleen M. McBride; Sheri D. Schully; John P. A. Ioannidis; W. Gregory Feero; A. Cecile J. W. Janssens; Marta Gwinn; Denise G. Simons-Morton; Jay M. Bernhardt; Michele Cargill; Stephen J. Chanock; George M. Church; Ralph J. Coates; Francis S. Collins; Robert T. Croyle; Barry R. Davis; Gregory J. Downing; Amy Duross; Susan Friedman; Mitchell H. Gail; Geoffrey S. Ginsburg; Robert C. Green; Mark H. Greene; Philip Greenland; Jeffrey R. Gulcher; Andro Hsu; Kathy Hudson; Sharon L.R. Kardia; Paul L. Kimmel; Michael S. Lauer

The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.


Circulation | 2000

Positional Genomic Analysis Identifies the β2-Adrenergic Receptor Gene as a Susceptibility Locus for Human Hypertension

Molly S. Bray; Julia Krushkal; Li Li; Robert E. Ferrell; Sharon L.R. Kardia; Charles F. Sing; Stephen T. Turner; Eric Boerwinkle

BACKGROUND -After genome-wide linkage analyses of blood pressure levels, we resequenced 5 positional candidate genes in a linkage region on chromosome 5 and genotyped selected variants in several family samples from Rochester, Minn. METHODS AND RESULTS In a sample of 55 pedigrees containing >/=1 sibling-pair(s) discordant for systolic blood pressure, polymorphisms within the beta(2)-adrenergic receptor gene (Arg16Gly, P=0.009) and the glutathione peroxidase 3 gene (-302G-->A, P=0.037; -623A-->C, P=0.013) were significantly related to blood pressure levels. In a second sample of 298 nuclear families (n=1283 individuals), the Arg16Gly polymorphism was significantly associated with diastolic blood pressure in family-based analyses (P=0.016) and with both diastolic (P=0.009) and mean arterial blood pressure (P=0.038) in analyses of the parental generation only. Neither polymorphism in the glutathione peroxidase 3 gene was associated with blood pressure levels in this sample. An additional 291 families (n=1240 individuals) were added to the nuclear family sample, and the Gln27Glu polymorphism in the beta(2)-adrenergic receptor gene was significantly associated with both systolic (P=0.034) and mean arterial blood pressure (P=0.035) in the parental generation of the combined 589 families. The frequencies of both the Gly16 and Glu27 alleles were higher in hypertensives than in normotensives (0.649 versus 0.604 and 0.490 versus 0.429, respectively), and the odds ratio for the occurrence of hypertension was 1.80 (95% confidence interval, 1.08 to 3.00; P=0. 023) for the Glu27 allele. CONCLUSIONS The results of this study provide support for further detailed investigations of the mechanistic pathways by which variations in the beta(2)-adrenergic receptor gene may influence blood pressure levels.


Diabetes | 2011

A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium

Aldi T. Kraja; Dhananjay Vaidya; James S. Pankow; Mark O. Goodarzi; Themistocles L. Assimes; Iftikhar J. Kullo; Ulla Sovio; Rasika A. Mathias; Yan V. Sun; Nora Franceschini; Devin Absher; Guo Li; Qunyuan Zhang; Mary F. Feitosa; Nicole L. Glazer; Talin Haritunians; Anna Liisa Hartikainen; Joshua W. Knowles; Kari E. North; Carlos Iribarren; Brian G. Kral; Lisa R. Yanek; Paul F. O'Reilly; Mark McCarthy; David Couper; Aravinda Chakravarti; Bruce M. Psaty; Lewis C. Becker; Michael A. Province; Eric Boerwinkle

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.


Human Molecular Genetics | 2011

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

Ervin R. Fox; J. Hunter Young; Yali Li; Albert W. Dreisbach; Brendan J. Keating; Solomon K. Musani; Kiang Liu; Alanna C. Morrison; Santhi K. Ganesh; Abdullah Kutlar; Josef F. Polak; Richard R. Fabsitz; Daniel L. Dries; Deborah N. Farlow; Susan Redline; Adebowale Adeyemo; Joel N. Hirschorn; Yan V. Sun; Sharon B. Wyatt; Alan D. Penman; Walter Palmas; Jerome I. Rotter; Raymond R. Townsend; Ayo Doumatey; Bamidele O. Tayo; Thomas H. Mosley; Helen N. Lyon; Sun J. Kang; Charles N. Rotimi; Richard S. Cooper

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.

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Eric Boerwinkle

University of Texas Health Science Center at Houston

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Thomas H. Mosley

University of Mississippi Medical Center

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Wei Zhao

University of Michigan

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