Translational Genomics Research Research Articles

IntheNews: A ROUNDUP OF NEWS AND INFORMATION FROM OUR COMMUNITY

In<i>the</i>News: A ROUNDUP OF NEWS AND INFORMATION FROM OUR COMMUNITY

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of cerebrotendinous xanthomatosis

BackgroundSemantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction.MethodsDue to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies.ResultsA framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption.ConclusionsThis work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research.

Translational genomic research: protocol development and initial outcomes following SNP testing for colon cancer risk

Although single nucleotide polymorphism (SNP) testing for disease susceptibility is commercially available, translational studies are necessary to understand how to communicate genomic information and potential implications for public health. We explored attitudes about and initial responses to genomic testing for colon cancer risk. Following development of the educational materials, we offered testing for three colon cancer SNPs in a pilot study with primary care patients. Participants completed pre- and post-test sessions and interviews. We analyzed interview transcripts with qualitative software using thematic analysis. All 20 participants opted for SNP testing. Qualitative analysis identified several themes: Motivations for SNP Testing, Before/After: Meaning of Results, Emotional Responses to SNP Results and Genomic Literacy/ Information Delivery. Results demonstrate that individuals will pursue SNP testing in the context of pre and post-test education. SNP results may influence health behaviors like healthy eating and exercise yet did not appear to impact colon cancer screening intentions.

Establishing a Framework for Improving the Quality of Clinical and Translational Research

TO THEEDITOR: The discovery of serious problems with research conducted in a laboratory at Duke University 1 has had a profound effect on our approach to translational research. We believe that this experience provides a number of salient, broadly applicable lessons— not just for the field of cancer genomics, but for scientific endeavors and institutions across the spectrum of biomedical research. As part of our initial response, we have developed a set of principles for translational research. 2 This Translational Medicine Quality Framework (TMQF) Principles document reflects the work of a multidisciplinary faculty leadership group and a panel of external experts who represent clinical, laboratory, and genomic research, including quantitative sciences. These principles have been formulated to ensure that research efforts at Duke University are guided by clear and consistent standards for quality. In particular, this framework will enhance the degree to which both the public and the scientific community can be confident that basic and translational research resulting in human applications has been conducted and validated in a manner consistent with current knowledge of the issues, the necessary scope of expertise, an awareness of the potential pitfalls of translational genomic research, and the relevant regulatory requirements. Key points of the TMQF document include creating accountability for research quality and fostering a culture of open discussion and challenge of research beyond the individual laboratory and investigator; guaranteeing robust data provenance and reproducible data management; ensuring adequate quantitative collaboration as a standard in the research environment; and enacting heightened scrutiny of human research that involves conflicts of interest, whether individual or institutional. We are currently finalizing a document that will detail our specific plans for implementing improvements to research quality throughout the institution. As part of the corrective actions taken, we have conducted an intensive review of all publications that resulted from Anil Potti’s work at Duke University (including five that appeared inJournal of Clinical Oncology) 3-7 and for which Potti appears as an author or coauthor. After we excluded opinion pieces and reviews without original data, we were left with 32 articles that included more than 150 coauthors. In each case, we asked the coauthors to attest once again to the conditions of authorship and to collaborate to determine whether they could vouch for the reproducibility of the results. This effort led to the full retraction of 10 articles (nine published;

Rogue MRSA: Antibiotics in Livestock Linked To Pathogen in Humans

Antibiotic use in livestock is linked to the recent emergence of a particular strain of methicillin-resistant Staphylococcus aureus (MRSA), according to Lance B. Price from the Translational Genomics Research Institute (TGEN) in Flagstaff, Ariz., leader of a consortium of scientists from 20 research centers in 19 countries, who analyzed 89 separate core MRSA genomes. “Our findings exemplify a bidirectional zoonotic exchange, underscoring the potential public health risks of widespread antibiotic use in food animal production,” the scientists conclude. Details appear in the January/February 2012 mBio (doi:10.1128/mBio00305–11).

Personalized medicine: a patient - centered paradigm

Personalized medicine: a patient - centered paradigm

Population Sciences, Translational Research, and the Opportunities and Challenges for Genomics to Reduce the Burden of Cancer in the 21st Century

Advances in genomics and related fields are promising tools for risk assessment, early detection, and targeted therapies across the entire cancer care continuum. In this commentary, we submit that this promise cannot be fulfilled without an enhanced translational genomics research agenda firmly rooted in the population sciences. Population sciences include multiple disciplines that are needed throughout the translational research continuum. For example, epidemiologic studies are needed not only to accelerate genomic discoveries and new biological insights into cancer etiology and pathogenesis, but to characterize and critically evaluate these discoveries in well-defined populations for their potential for cancer prediction, prevention and response to treatment. Behavioral, social, and communication sciences are needed to explore genomic-modulated responses to old and new behavioral interventions, adherence to therapies, decision making across the continuum, and effective use in health care. Implementation science, health services, outcomes research, comparative effectiveness research, and regulatory science are needed for moving validated genomic applications into practice and for measuring their effectiveness, cost-effectiveness, and unintended consequences. Knowledge synthesis, evidence reviews, and economic modeling of the effects of promising genomic applications will facilitate policy decisions and evidence-based recommendations. Several independent and multidisciplinary panels have recently made specific recommendations for enhanced research and policy infrastructure to inform clinical and population research for moving genomic innovations into the cancer care continuum. An enhanced translational genomics and population sciences agenda is urgently needed to fulfill the promise of genomics in reducing the burden of cancer.

Motivators for participation in a whole-genome sequencing study: implications for translational genomics research

The promise of personalized medicine depends on the ability to integrate genetic sequencing information into disease risk assessment for individuals. As genomic sequencing technology enters the realm of clinical care, its scale necessitates answers to key social and behavioral research questions about the complexities of understanding, communicating, and ultimately using sequence information to improve health. Our study captured the motivations and expectations of research participants who consented to participate in a research protocol, ClinSeq, which offers to return a subset of the data generated through high-throughput sequencing. We present findings from an exploratory study of 322 participants, most of whom identified themselves as white, non-Hispanic, and coming from higher socio-economic groups. Participants aged 45-65 years answered open-ended questions about the reasons they consented to ClinSeq and about what they anticipated would come of genomic sequencing. Two main reasons for participating were as follows: a conviction to altruism in promoting research, and a desire to learn more about genetic factors that contribute to one's own health risk. Overall, participants expected genomic research to help improve understanding of disease causes and treatments. Our findings offer a first glimpse into the motivations and expectations of individuals seeking their own genomic information, and provide initial insights into the value these early adopters of technology place on information generated by high-throughput sequencing studies.

Genetic association of complement receptor 1 polymorphism rs3818361 in Alzheimer's disease

Complement receptor 1 gene polymorphism rs3818361 was recently shown to increase the risk of Alzheimer's disease (AD). We performed an independent replication study of this genetic variant in 2,470 individuals from Spain. By applying an allelic model, we observed a trend toward an association between this marker and late-onset AD susceptibility in our case-control study (odds ratio = 1.114, 95% confidence interval: 0.958-1.296, P = .16). Meta-analysis of available studies (n = 31,771 individuals), including previous studies and public genome-wide association study resources (Alzheimer's Disease Neuroimaging Initiative, Translational Genomics Research Institute, and Multi-site Collaborative Study for Genotype-Phenotype Associations in Alzheimer's Disease), strongly supports the effect of rs3818361 (odds ratio = 1.180, 95% confidence interval: 1.113-1.252, P < 2.99E-8) and suggests the existence of between-study heterogeneity (P < .05). We concluded that the complement receptor 1 gene may contribute to AD risk, although its effect size could be smaller than previously estimated.

The personalised medicine. A paradigm of evidence-based medicine.

The practice of "evidence-based medicine" aims at the conscientious, explicit and judicious use of the current best evidence in making decisions about the individualised patient care. The clinical genetics evolved from translational genetics research and contributes to the clinical care of patients and families through evidence-based health care in managing inherited disorders through accurate diagnosis, molecular pathology and assessing phenotypic correlations. Translational genetics and genomics research has led to the development of powerful tools for clinical diagnosis, assessing individual's genomic profile for disease prediction/prevention, high-throughput genome-wide screening for predisposition and/or protection to complex medical conditions, and discovery and development of new drugs and vaccines. Gene mapping and deciphering pathogenic mutations have helped in unravelling the basic biological mechanisms leading to new drug discovery and development. Targeted pharmacotherapy is now possible for managing the highly penetrant multi-system dominantly inherited conditions. Notable examples include rapamycin (sirolimus) in suppressing the mTOR pathway associated hamartomas in dominantly inherited cancer family syndromes and angiotensin converting enzyme receptor blockers (ACE-RB) in preventing aortic dilatation in Marfan syndrome and related familial arteriopathies. The translational genomic research is the essential prerequisite for developing sound evidence-based diagnostic, therapeutic and prognostic clinical protocols for the practice of personalised clinical medicine.

Population Genomics of Heart Diseases and Risk Factors: Going Wider and Deeper

This review summarizes the relevance of genome-wide association studies (GWAS) to the epidemiological study of cardiovascular disease (CVD). From six perspectives, this review describes the key elements for translational genomics research, in general and for CVD phenotypes in particular. The three perspectives in the dimension of width address the issues of size and complexity of phenotypes and genotypes. The three perspectives in the dimension of depth address the issues of functional relevance, gene environmental interaction, and clinical usage. The authors also comment on the relevance of these perspectives in successful design and conduct of genetic and genomic studies in Chinese population. [N A J Med Sci. 2011;4(4):249-253.]

Finding the tumor copycat: Approximating a human cancer

Finding the tumor copycat: Approximating a human cancer

Genome-wide Analysis of Genetic Loci Associated With Alzheimer Disease

Genome-wide association studies (GWAS) have recently identified CLU, PICALM, and CR1 as novel genes for late-onset Alzheimer disease (AD). To identify and strengthen additional loci associated with AD and confirm these in an independent sample and to examine the contribution of recently identified genes to AD risk prediction in a 3-stage analysis of new and previously published GWAS on more than 35,000 persons (8371 AD cases). In stage 1, we identified strong genetic associations (P < 10(-3)) in a sample of 3006 AD cases and 14,642 controls by combining new data from the population-based Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (1367 AD cases [973 incident]) with previously reported results from the Translational Genomics Research Institute and the Mayo AD GWAS. We identified 2708 single-nucleotide polymorphisms (SNPs) with P < 10(-3). In stage 2, we pooled results for these SNPs with the European AD Initiative (2032 cases and 5328 controls) to identify 38 SNPs (10 loci) with P < 10(-5). In stage 3, we combined data for these 10 loci with data from the Genetic and Environmental Risk in AD consortium (3333 cases and 6995 controls) to identify 4 SNPs with P < 1.7x10(-8). These 4 SNPs were replicated in an independent Spanish sample (1140 AD cases and 1209 controls). Genome-wide association analyses were completed in 2007-2008 and the meta-analyses and replication in 2009. Presence of Alzheimer disease. Two loci were identified to have genome-wide significance for the first time: rs744373 near BIN1 (odds ratio [OR],1.13; 95% confidence interval [CI],1.06-1.21 per copy of the minor allele; P = 1.59x10(-11)) and rs597668 near EXOC3L2/BLOC1S3/MARK4 (OR, 1.18; 95% CI, 1.07-1.29; P = 6.45x10(-9)). Associations of these 2 loci plus the previously identified loci CLU and PICALM with AD were confirmed in the Spanish sample (P < .05). However, although CLU and PICALM were confirmed to be associated with AD in this independent sample, they did not improve the ability of a model that included age, sex, and APOE to predict incident AD (improvement in area under the receiver operating characteristic curve from 0.847 to 0.849 in the Rotterdam Study and 0.702 to 0.705 in the Cardiovascular Health Study). Two genetic loci for AD were found for the first time to reach genome-wide statistical significance. These findings were replicated in an independent population. Two recently reported associations were also confirmed. These loci did not improve AD risk prediction. While not clinically useful, they may implicate biological pathways useful for future research.

Abstract 1160: Whole genome amplification and high-throughput sequencing of formalin-fixed paraffin-embedded colorectal cancer

Abstract Formalin-fixed paraffin-embedded (FFPE) tumors represent a valuable resource for translational cancer genomic research. However, genetic analysis of the FFPE material is challenging, as archived tissues are often small biopsies and the fixation process damages DNA. In researching a solution to this, we have evaluated the performance of different whole genome amplification methods for obtaining DNA samples from archived tumors and their use as a template in high-throughput sequencing. Two whole genome amplification methods were applied using 20 μm sections of FFPE colorectal cancer tissue and normal human genome DNA samples. Genomic DNA was amplified using Multiple Displacement Amplification (MDA) method and a modified version of Degenerate Oligonucleotide PCR (DOP) assay. Non-amplified human genomic DNA was used as a reference when genomic coverage, linearity and uniformity of the amplified products were assessed. Paired-end sequencing libraries were prepared from the DOP amplified templates while the MDA samples underwent single read library preparation. Sequencing was performed using an Illumina Genome Analyzer II. 2.5 million 54-mer reads mapping to the human genome were generated for each sample. Whole genome amplification was shown to produce artifacts when compared to non-amplified genomic DNA sequences. The modified DOP method preferentially amplified non-repetitive sequences in the human genome. Using the MDA-based method, genomic sequence coverage was generally more even between regions of repetitive and non-repetitive DNA. However, spread of the sequence read counts was greater in the MDA method and MDA amplification offered less dynamic range to identify copy number aberrations. Using whole genome amplification methods with the FFPE colorectal tumor sample we were able to generate 130 Mb of genomic sequence data and identify DNA copy number gains in chromosomes 13 and 20q. Whole genome amplification and high-throughput sequencing can be used to generate sequence data from minute amounts of FFPE material and identify DNA copy number aberrations in the archived tumors. Nonetheless, whole genome amplification produces artifacts by introducing bias towards specific regions of the genome, generating artificial and random DNA fragment assemblies (MDA) and introducing universal primer sequence in the ends of the amplified DNA fragments (DOP). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1160.

Joseph Goldstein and Michael Brown

Joseph Goldstein and Michael Brown

Effects of ondansetron on opioid withdrawal symptoms

Opioid dependence and withdrawal are major burdens for both the individual and society. Translational genomic research in a murine model has identified a critical role for the 5-HT3 receptor system in opioid withdrawal. This double-blind, placebo controlled, cross-over study aimed to test our hypothesis that ondansetron (Zofran®), a 5-HT3 receptor antagonist, would help relieve opioid withdrawal symptoms. Patients admitted to the Stanford Comprehensive Interdisciplinary Pain Program (SCIPP) for opioid detoxification were enrolled.

Research and applied medical genetics: filling the gap

Research and applied medical genetics: filling the gap

Translational Research in Genomics of Alzheimer's Disease: A Review of Current Practice and Future Perspectives

Alzheimer's disease (AD) is the most prevalent form of dementia and the number of cases is expected to increase exponentially worldwide. Three highly penetrant genes (AbetaPP, PSEN1, and PSEN2) explain only a small number of AD cases with a Mendelian transmission pattern. Many genes have been analyzed for association with non-Mendelian AD, but the only consistently replicated finding is APOE. At present, possibilities for prevention, early detection, and treatment of the disease are limited. Predictive and diagnostic genetic testing is available only in Mendelian forms of AD. Currently, APOE genotyping is not considered clinically useful for screening, presymptomatic testing, or clinical diagnosis of non-Mendelian AD. However, clinical management of the disease is expected to benefit from the rapid pace of discoveries in the genomics of AD. Following a recently developed framework for the continuum of translation research that is needed to move genetic discoveries to health applications, this paper reviews recent genetic discoveries as well as translational research on genomic applications in the prevention, early detection, and treatment of AD. The four phases of translation research include: 1) translation of basic genomics research into a potential health care application; 2) evaluation of the application for the development of evidence-based guidelines; 3) evaluation of the implementation and use of the application in health care practice; and 4) evaluation of the achieved population health impact. Most research on genome-based applications in AD is still in the first phase of the translational research framework, which means that further research is still needed before their implementation can be considered.

From metagenomics to the metagenome: Conceptual change and the rhetoric of translational genomic research

As the international genomic research community moves from the tool-making efforts of the Human Genome Project into biomedical applications of those tools, new metaphors are being suggested as useful to understanding how our genes work - and for understanding who we are as biological organisms. In this essay we focus on the Human Microbiome Project as one such translational initiative. The HMP is a new 'metagenomic' research effort to sequence the genomes of human microbiological flora, in order to pursue the interesting hypothesis that our 'microbiome' plays a vital and interactive role with our human genome in normal human physiology. Rather than describing the human genome as the 'blueprint' for human nature, the promoters of the HMP stress the ways in which our primate lineage DNA is interdependent with the genomes of our microbiological flora. They argue that the human body should be understood as an ecosystem with multiple ecological niches and habitats in which a variety of cellular species collaborate and compete, and that human beings should be understood as 'superorganisms' that incorporate multiple symbiotic cell species into a single individual with very blurry boundaries. These metaphors carry interesting philosophical messages, but their inspiration is not entirely ideological. Instead, part of their cachet within genome science stems from the ways in which they are rooted in genomic research techniques, in what philosophers of science have called a 'tools-to-theory' heuristic. Their emergence within genome science illustrates the complexity of conceptual change in translational research, by showing how it reflects both aspirational and methodological influences.

The potential of optical proteomic technologies to individualize prognosis and guide rational treatment for cancer patients.

Genomics and proteomics will improve outcome prediction in cancer and have great potential to help in the discovery of unknown mechanisms of metastasis, ripe for therapeutic exploitation. Current methods of prognosis estimation rely on clinical data, anatomical staging and histopathological features. It is hoped that translational genomic and proteomic research will discriminate more accurately than is possible at present between patients with a good prognosis and those who carry a high risk of recurrence. Rational treatments, targeted to the specific molecular pathways of an individual’s high-risk tumor, are at the core of tailored therapy. The aim of targeted oncology is to select the right patient for the right drug at precisely the right point in their cancer journey. Optical proteomics uses advanced optical imaging technologies to quantify the activity states of and associations between signaling proteins by measuring energy transfer between fluorophores attached to specific proteins. Förster resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy (FLIM) assays are suitable for use in cell line models of cancer, fresh human tissues and formalin-fixed paraffin-embedded tissue (FFPE). In animal models, dynamic deep tissue FLIM/FRET imaging of cancer cells in vivo is now also feasible. Analysis of protein expression and post-translational modifications such as phosphorylation and ubiquitination can be performed in cell lines and are remarkably efficiently in cancer tissue samples using tissue microarrays (TMAs). FRET assays can be performed to quantify protein-protein interactions within FFPE tissue, far beyond the spatial resolution conventionally associated with light or confocal laser microscopy. Multivariate optical parameters can be correlated with disease relapse for individual patients. FRET-FLIM assays allow rapid screening of target modifiers using high content drug screens. Specific protein-protein interactions conferring a poor prognosis identified by high content tissue screening will be perturbed with targeted therapeutics. Future targeted drugs will be identified using high content/throughput drug screens that are based on multivariate proteomic assays. Response to therapy at a molecular level can be monitored using these assays while the patient receives treatment: utilizing re-biopsy tumor tissue samples in the neoadjuvant setting or by examining surrogate tissues. These technologies will prove to be both prognostic of risk for individuals when applied to tumor tissue at first diagnosis and predictive of response to specifically selected targeted anticancer drugs. Advanced optical assays have great potential to be translated into real-life benefit for cancer patients.