Top Advances in Functional Genomics and Translational Biology for 2009

HomeCirculation: Cardiovascular GeneticsVol. 3, No. 1Top Advances in Functional Genomics and Translational Biology for 2009 Free AccessResearch ArticlePDF/EPUBAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessResearch ArticlePDF/EPUBTop Advances in Functional Genomics and Translational Biology for 2009 Patrick T. Ellinor and Jennifer E. Van Eyk Patrick T. EllinorPatrick T. Ellinor From the Cardiovascular Research Center and Cardiac Arrhythmia Service (P.T.E.), Massachusetts General Hospital, Boston, Mass; and Departments of Medicine, Biological Chemistry, Biomedical Engineering (J.V.E.), Johns Hopkins University, Baltimore, Md. and Jennifer E. Van EykJennifer E. Van Eyk From the Cardiovascular Research Center and Cardiac Arrhythmia Service (P.T.E.), Massachusetts General Hospital, Boston, Mass; and Departments of Medicine, Biological Chemistry, Biomedical Engineering (J.V.E.), Johns Hopkins University, Baltimore, Md. Originally published1 Feb 2010https://doi.org/10.1161/CIRCGENETICS.110.937367Circulation: Cardiovascular Genetics. 2010;3:106–108During the past years vast strides have been made in population genetics and proteomics. Genome-wide association studies (GWAS) have become large, collaborative, multicenter efforts often involving in excess of 50 000 subjects with dramatically increased power compared with previous efforts. Rapid evolution in sequencing technology has made comprehensive sequencing of the exome feasible and enabled a unique approach toward the identification of rare disease-causing variants. This year, several key proteomic articles have been published on the discovery and verification of new protein biomarkers that mark a new stage in this field, specifically in our efforts to move these emerging markers toward clinical application.The American Heart Association Functional Genomics and Translational Biology Interdisciplinary Council provides a forum for a multidisciplinary group of volunteers committed to making a substantial contribution to reduce the burden of heart disease and stroke through genetics, genomics, proteomics, and metabolomics research and translational science. On behalf of the Council on Functional Genomics and Translational Biology, we have selected 4 manuscripts published in 2009 that reflect these advances.Genome Wide Association Study of Premature Myocardial Infarction Identifies 9 Genetic Loci1. Myocardial Infarction Genetics Consortium. Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants. Nat Genet. 2009;41:334–341. PMID: 19198609.Principal FindingsMost patients who have a myocardial infarction (MI) are elderly; however, a minority of patients with a MI present at an early age have a higher heritability of MI and are thus more likely to have a genetic basis for their condition. Investigators from the Myocardial Infarction Genetics Consortium1 performed a multistage case-control GWAS in subjects with early-onset MI. In an initial stage, a GWAS for single-nucleotide polymorphisms (SNPs) and copy number variants was undertaken using 2967 cases and 3075 controls. The top hits from the initial analysis and from the previously published studies were analyzed in 3 successive replication stages consisting of an additional 12 800 cases and controls. A total of 9 loci were significantly associated with premature MI, in which 6 were previously reported and 3 were novel. None of the common or rare copy number variants were associated with premature MI.ImplicationsThis manuscript highlights some of the great strengths and inherent weaknesses of GWAS. As for the strengths, the investigators are to be commended for the large, multistage replication strategy used because they have convincingly identified many common genetic variants associated with premature MI. Second, as an unbiased and genome-wide analysis, GWAS offers the potential to discover new pathways for disease pathogenesis. The limitations of this manuscript are similar to other GWAS studies. Considerable future work will be necessary to elucidate the precise mechanisms by which genetic variants identified in this GWAS, and in other association studies, lead to disease. Furthermore, the majority of GWAS have been performed in individuals of European ancestry, and future work will be necessary to determine whether the results can be generalized to other races and ethnicities. Finally, despite the tremendous efforts of the investigators, the overall effect sizes remain small, with odds ratios ranging from 1.12 to 1.29. Even when combined, the top variants at each of the 9 loci account for <3% of variance in MI risk. Thus, despite the heritability of premature MI, a large part of the genetic basis of the disease remains unexplained.Rapid Sequencing of the Human Exome2. Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J. Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 2009;461:272–276. PMID: 19684571.Principal FindingsAs illustrated in the preceding manuscript, despite the ever increasing scale of genome-wide studies, the common variants identified have typically only accounted for a small percentage of the heritability of a condition. Therefore, other disease mechanisms including the role of rare genetic variants have continued to be explored. Although the costs for sequencing the entire genome are falling quickly, genome-wide sequencing is likely to continue to remain too expensive for individual investigators for at least a few more years. Based on these constraints, a recent focus on sequencing all of the protein coding regions, or exomes, that comprise ≈1% of the human genome, has emerged.2Ng et al sequenced the exomes of 12 individuals. Of these, 8 were referent subjects, and 4 had Freeman-Sheldon syndrome, a rare, autosomal dominant craniocarpotarsal dystrophy due to mutations in MYH3. Starting with genomic DNA, they used 2 microarrays to enrich the exome in each individual, and then shotgun sequenced the enriched library. They obtained an average of 6.4 gigabases of sequence or ≈50-fold coverage of the exomes for each individual. Use of referent subjects from the HapMap and Human Genome Structural variation projects enabled a detailed comparison of the call rates of coding SNPs (cSNPs) between the current exome sequencing and traditional sequencing or genotyping techniques. Overall, exomic sequencing was highly sensitive at cSNP detection with concordance rates in excess of 99%. There were an average of 17,272 cSNPs identified in each individual, and as expected more cSNPs were identified in Africans than in non-Africans. Polymorphisms that disrupt splice-site junctions or alter protein coding are typically assumed to be pathological, and a striking number of such variants were identified; among all of the subjects studied, there were a total of 225 nonsynonymous SNPs, 102 splice-site disruptions, and 664 small insertions or deletions. Finally, in a proof of concept study, the investigators used exomic sequencing and filtering of common cSNPs to identify multiple mutations in MYH3 among the 4 subjects with Freeman-Sheldon syndrome.ImplicationsIn the near future, exomic sequencing will offer the potential to screen the entire coding region of the genome. Particularly promising are the applications of this technique for the identification of causative genes in diseases that seem to have a genetic basis, but in which the families are too small for traditional linkage analysis.3 Limitations at the moment include cost, the vast amount of genotypic data generated, the need for expertise in data processing, and the large sample sizes necessary to detect rare variants for more common diseases.Mass Spectrometry for Multiplexed Biomarker Detection4. Kuhn E, Addona T, Keshishian H, Burgess M, Mani DR, Lee RT, Sabatine MS, Gerszten RE, Carr SA. Developing multiplexed assays for troponin I and interleukin-33 in plasma by peptide immunoaffinity enrichment and targeted mass spectrometry. Clin Chem. 2009;55:1108–1117. PMID: 19372185.Principal FindingsBiomarkers have a vital role in promoting innovation in diagnostics and treatments. The application of proteomic technology in the area of circulating biomarkers has been technically challenging with respect to discovery of new markers and their verification. Kuhn and coworkers5 use a mass spectrometry method called selective reaction monitoring (or multiple reaction monitoring) to obtain absolute quantification of 2 known biomarkers in serum. This method is based on quantification of signature peptides that are unique to a particular protein and can even be used to track selective peptides with disease-induced modifications (eg, phosphorylation or proteolytic fragments), single/multiple amino acid changes due to polymorphism or unique to specific protein isoforms. The use of selective reaction monitoring was coupled with immuno-affinity enrichment of the representative low abundant proteins including cardiac troponin I and interleukin 33. The latter was selected to represent a candidate biomarker for which an ELISA does not exist. Selective reaction monitoring completely removes the need for antibodies or as in this case, the need for 2 high affinity specific antibodies while allowing one to obtain quantitative data that is comparable with the data (with similar reproducibility and coefficient of variation) obtained by classic methods such as ELISA or radioimmunoassay.6 Thus, the selective reaction monitoring technique described in this manuscript provides a novel approach for the targeted discovery and verification of biomarkers in cardiovascular disease.ImplicationsThis technology opens the door to absolute quantification of candidate proteins in hundreds of patient samples without the need for development of expensive antibodies and immunoassays. This will improve the diversity of protein targets that can be tested as biomarkers and should ultimately increase the probability of identifying robust diagnostic and prognostic proteins.Transforming Growth Factor Beta in Marfan Syndrome7. Matt P, Schoenhoff F, Habashi J, Holm T, Van Erp C, Loch D, Carlson OD, Griswold BF, Fu Q, De Backer J, Loeys B, Huso DL, McDonnell NB, Van Eyk JE, Dietz HC; GenTAC Consortium. Circulating transforming growth factor-beta in Marfan syndrome. Circulation. 2009;120:526–532. PMID: 19635970.Principal FindingsTransforming growth factor beta (TGF-β) is a ubiquitous cytokine present in virtually all mammalian cells that controls cell differentiation and proliferation.7 Circulating TGF-β levels (bound and free [active]) were elevated in a mouse model, Fbn1C1039G/+ that mimics many clinical features of individuals with Marfan syndrome, including the progressive dilation of the aorta. TGF-β levels were also found to be elevated in a large cohort of patients with Marfan syndrome obtained through the multicenter GenTAC (National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions) consortium. Importantly, TGF-β levels are sensitive to therapeutic intervention and are lower in both the Fbn1C1039G/+ mouse model and in patients treated with the AT1-antagonist losartan, which has been shown to reduce aortic root growth and dimensions in the mouse model of Marfan syndrome.ImplicationsThis manuscript provides an elegant example of the ability to directly translate the findings from an animal model of a disease rapidly into patients. As pointed out in the accompanying editorial,8 measuring circulating levels of TGF-β may serve as a prognostic and therapeutic marker that can ultimately be integrated into the clinical management of patients with Marfan syndrome.Sources of FundingThis work was supported National Institute of Health grants HL092577 and DA027021 (to P.T.E.), NO1-HV28180 and 1U54RR023561 (to J.V.E).DisclosuresNone.FootnotesCorrespondence to Patrick T. Ellinor, MD, PhD, Massachusetts General Hospital, 149 13th St, Charlestown, MA 02129. E-mail [email protected] References 1 Kathiresan S, Voight BF, Purcell S, Musunuru K, Ardissino D, Mannucci PM, Anand S, Engert JC, Samani NJ, Schunkert H, Erdmann J, Reilly MP, Rader DJ, Morgan T, Spertus JA, Stoll M, Girelli D, McKeown PP, Patterson CC, Siscovick DS, O'Donnell CJ, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Melander O, Altshuler D, Merlini PA, Berzuini C, Bernardinelli L, Peyvandi F, Tubaro M, Celli P, Ferrario M, Fetiveau R, Marziliano N, Casari G, Galli M, Ribichini F, Rossi M, Bernardi F, Zonzin P, Piazza A, Yee J, Friedlander Y, Marrugat J, Lucas G, Subirana I, Sala J, Ramos R, Meigs JB, Williams G, Nathan DM, MacRae CA, Havulinna AS, Berglund G, Hirschhorn JN, Asselta R, Duga S, Spreafico M, Daly MJ, Nemesh J, Korn JM, McCarroll SA, Surti A, Guiducci C, Gianniny L, Mirel D, Parkin M, Burtt N, Gabriel SB, Thompson JR, Braund PS, Wright BJ, Balmforth AJ, Ball SG, Hall AS, Linsel-Nitschke P, Lieb W, Ziegler A, Konig I, Hengstenberg C, Fischer M, Stark K, Grosshennig A, Preuss M, Wichmann HE, Schreiber S, Ouwehand W, Deloukas P, Scholz M, Cambien F, Li M, Chen Z, Wilensky R, Matthai W, Qasim A, Hakonarson HH, Devaney J, Burnett MS, Pichard AD, Kent KM, Satler L, Lindsay JM, Waksman R, Epstein SE, Scheffold T, Berger K, Huge A, Martinelli N, Olivieri O, Corrocher R, McKeown P, Erdmann E, Konig IR, Holm H, Thorleifsson G, Thorsteinsdottir U, Stefansson K, Do R, Xie C, Siscovick D. Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants. Nat Genet. 2009; 41: 334–341.CrossrefMedlineGoogle Scholar2 Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J. Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 2009; 461: 272–276.CrossrefMedlineGoogle Scholar3 Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK, Dent KM, Huff CD, Shannon PT, Jabs EW, Nickerson DA, Shendure J, Bamshad MJ. Exome sequencing identifies the cause of a mendelian disorder. Nat Genet. 2010; 42: 30–35.CrossrefMedlineGoogle Scholar4 Kuhn E, Addona T, Keshishian H, Burgess M, Mani DR, Lee RT, Sabatine MS, Gerszten RE, Carr SA. Developing multiplexed assays for troponin I and interleukin-33 in plasma by peptide immunoaffinity enrichment and targeted mass spectrometry. Clin Chem. 2009; 55: 1108–1117.PMID: 19372185.CrossrefMedlineGoogle Scholar5 Keshishian H, Addona T, Burgess M, Mani DR, Shi X, Kuhn E, Sabatine MS, Gerszten RE, Carr SA. Quantification of cardiovascular biomarkers in patient plasma by targeted mass spectrometry and stable isotope dilution. Mol Cell Proteomics. 2009; 8: 2339–2349.CrossrefMedlineGoogle Scholar6 Gerszten RE, Carr SA, Sabatine M. Integration of proteomic-based tools for improved biomarkers of myocardial injury. Clin Chem. 2009 [Epub ahead of print].Google Scholar7 Matt P, Schoenhoff F, Habashi J, Holm T, Van Erp C, Loch D, Carlson OD, Griswold BF, Fu Q, De Backer J, Loeys B, Huso DL, McDonnell NB, Van Eyk JE, Dietz HC; GenTAC Consortium. Circulating transforming growth factor-beta in Marfan syndrome. Circulation. 2009; 120: 526–532.LinkGoogle Scholar8 Braverman AC. Transforming growth factor-beta: a biomarker in Marfan syndrome? Circulation. 2009; 120: 464–466.LinkGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails February 2010Vol 3, Issue 1 Advertisement Article InformationMetrics https://doi.org/10.1161/CIRCGENETICS.110.937367 Originally publishedFebruary 1, 2010 Keywordssignal transductionaortadiagnosisgeneticsPDF download Advertisement SubjectsGeneticsOmics