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Grimaldi KA, van Ommen B, Ordovas JM, Parnell LD, Mathers JC, Bendik I, Brennan L, Celis-Morales C, Cirillo E, Daniel H, de Kok B, El-Sohemy A, Fairweather-Tait SJ, Fallaize R, Fenech M, Ferguson LR, Gibney ER, Gibney M, Gjelstad IMF, Kaput J, Karlsen AS, Kolossa S, Lovegrove J, Macready AL, Marsaux CFM, Alfredo Martinez J, Milagro F, Navas-Carretero S, Roche HM, Saris WHM, Traczyk I, van Kranen H, Verschuren L, Virgili F, Weber P, Bouwman J. Proposed guidelines to evaluate scientific validity and evidence for genotype-based dietary advice. GENES & NUTRITION 2017; 12:35. [PMID: 29270237 PMCID: PMC5732517 DOI: 10.1186/s12263-017-0584-0] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 10/09/2017] [Indexed: 12/13/2022]
Abstract
Nutrigenetic research examines the effects of inter-individual differences in genotype on responses to nutrients and other food components, in the context of health and of nutrient requirements. A practical application of nutrigenetics is the use of personal genetic information to guide recommendations for dietary choices that are more efficacious at the individual or genetic subgroup level relative to generic dietary advice. Nutrigenetics is unregulated, with no defined standards, beyond some commercially adopted codes of practice. Only a few official nutrition-related professional bodies have embraced the subject, and, consequently, there is a lack of educational resources or guidance for implementation of the outcomes of nutrigenetic research. To avoid misuse and to protect the public, personalised nutrigenetic advice and information should be based on clear evidence of validity grounded in a careful and defensible interpretation of outcomes from nutrigenetic research studies. Evidence requirements are clearly stated and assessed within the context of state-of-the-art 'evidence-based nutrition'. We have developed and present here a draft framework that can be used to assess the strength of the evidence for scientific validity of nutrigenetic knowledge and whether 'actionable'. In addition, we propose that this framework be used as the basis for developing transparent and scientifically sound advice to the public based on nutrigenetic tests. We feel that although this area is still in its infancy, minimal guidelines are required. Though these guidelines are based on semi-quantitative data, they should stimulate debate on their utility. This framework will be revised biennially, as knowledge on the subject increases.
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Affiliation(s)
| | | | - Jose M. Ordovas
- JMUSDA-Human Nutrition Research Center on Aging at Tufts University, Boston, USA
- IMDEA Alimentacion, Madrid, Spain
| | - Laurence D. Parnell
- Agriculture Research Service, USDA, Human Nutrition Research Center on Aging, Boston, MA 02111 USA
| | - John C. Mathers
- Human Nutrition Research Centre, Institute of Cellular Medicine, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL UK
| | - Igor Bendik
- DSM Nutritional Products, Kaiseraugst, Switzerland
| | - Lorraine Brennan
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Carlos Celis-Morales
- Human Nutrition Research Centre, Institute of Cellular Medicine, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL UK
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, G12 8TA UK
| | | | - Hannelore Daniel
- Nutritional Physiology, Technische Universität München, 85350 Freising, Germany
| | | | - Ahmed El-Sohemy
- Department of Nutritional Sciences, University of Toronto, 150 College Street, 3rd Floor, Toronto, ON M5S 3E2 Canada
| | | | - Rosalind Fallaize
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, Berkshire RG6 6AP UK
| | - Michael Fenech
- CSIRO Health and Biosecurity, Gate 13, Kintore Avenue, Adelaide, SA 5000 Australia
| | - Lynnette R. Ferguson
- ACSRC and Discipline of Nutrition and Dietetics, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1184 New Zealand
| | - Eileen R. Gibney
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Mike Gibney
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Ingrid M. F. Gjelstad
- Department of Nutrition, Universitetet i Oslo, PO Box 1046, Blindern, N-0316 Oslo, Norway
| | - Jim Kaput
- Vydiant Inc, 2330 Gold Meadow Way, Gold River, 95670 CA USA
| | - Anette S. Karlsen
- Department of Nutrition, Universitetet i Oslo, PO Box 1046, Blindern, N-0316 Oslo, Norway
| | - Silvia Kolossa
- Nutritional Physiology, Technische Universität München, 85350 Freising, Germany
| | - Julie Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, Berkshire RG6 6AP UK
| | - Anna L. Macready
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, Berkshire RG6 6AP UK
| | - Cyril F. M. Marsaux
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre + (MUMC+), Maastricht, The Netherlands
| | - J. Alfredo Martinez
- IMDEA Alimentacion, Madrid, Spain
- Department of Nutrition, Food Science and Physiology, Centre for Nutrition Research, University of Navarra, Pamplona, Spain
- CIBERobn, Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Fermin Milagro
- Department of Nutrition, Food Science and Physiology, Centre for Nutrition Research, University of Navarra, Pamplona, Spain
- CIBERobn, Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Santiago Navas-Carretero
- Department of Nutrition, Food Science and Physiology, Centre for Nutrition Research, University of Navarra, Pamplona, Spain
- CIBERobn, Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Helen M. Roche
- Nutrigenomics Research Group, UCD Institute of Food and Health/UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - Wim H. M. Saris
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre + (MUMC+), Maastricht, The Netherlands
| | - Iwona Traczyk
- Department of Human Nutrition, Faculty on Health Sciences, Medical University of Warsaw, Warsaw, Poland
| | - Henk van Kranen
- Institute for Public Health Genomics (IPHG), Department of Genetics and Cell Biology, Faculty of Health, Medicine & Life Sciences, University of Maastricht, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands
| | | | - Fabio Virgili
- Council for Agricultural Research and Economics, Food and Nutrition Research Centre, (CREA - AN), via Ardeatina 546, 00178 Rome, Italy
| | - Peter Weber
- DSM Nutritional Products, Kaiseraugst, Switzerland
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Morris AH, Ioannidis JPA. Limitations of medical research and evidence at the patient-clinician encounter scale. Chest 2013; 143:1127-1135. [PMID: 23546485 DOI: 10.1378/chest.12-1908] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith's "invisible hand" with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective "invisible hand" operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the "invisible hand" does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence.
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Affiliation(s)
- Alan H Morris
- Pulmonary and Critical Care Divisions, Departments of Medicine, Intermountain Medical Center, Intermountain Healthcare and The University of Utah School of Medicine, Salt Lake City, UT.
| | - John P A Ioannidis
- Stanford Prevention Research Center, Department of Medicine, and Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA
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3
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Steinsbekk KS, Solberg B. Should genetic findings from genome research be reported back to the participants? TIDSSKRIFT FOR DEN NORSKE LEGEFORENING 2013; 132:2190-3. [PMID: 23243670 DOI: 10.4045/tidsskr.12.0078] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND Today, new and powerful sequencing technology is being used in biomedical research. In parallel, an intense ethical debate has arisen regarding the handling of the information which is generated through such comprehensive analyses. The conflict concerns whether any findings made during research, intended or incidental, should be reported back to the individual research participant. KNOWLEDGE BASIS: We reviewed international academic literature that has addressed the issue of feedback from genetic studies. The arguments in favour and against providing individual information from genome research to research participants were reviewed. Key arguments in this debate are presented and commented on. RESULTS A growing number of voices argue in favour of return of research-generated genetic information with reference to key values such as autonomy, respect, charity, mutuality and reciprocity. The counter-arguments are not as easily accessible, but concern the fundamental distinction between research and treatment, which indicates that researchers are not obliged to provide individual information to participants. Partly, the counter-arguments focus on the possible unfortunate consequences that such feedback may have for individuals, research and society as a whole. INTERPRETATION We are standing at a crossroads with regard to assessing whether returning research-generated genetic risk information at the individual level is a moral imperative. Here, individually based research ethics run up against concerns of social medicine and research-based obligations. The right balance has probably not yet been found.
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Affiliation(s)
- Kristin Solum Steinsbekk
- Institutt for samfunnsmedisin, Det medisinske fakultet, Norges teknisk-naturvitenskapelige universitet, Norway.
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4
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Systems genetics in "-omics" era: current and future development. Theory Biosci 2012; 132:1-16. [PMID: 23138757 DOI: 10.1007/s12064-012-0168-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2012] [Accepted: 10/25/2012] [Indexed: 02/06/2023]
Abstract
The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP-SNP genetic interactions, LD block-block interactions, miRNA-mRNA interactions, DNA-protein interactions, protein-protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate "-omics" datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.
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Khoury MJ, Gwinn ML, Glasgow RE, Kramer BS. A population approach to precision medicine. Am J Prev Med 2012; 42:639-45. [PMID: 22608383 PMCID: PMC3629731 DOI: 10.1016/j.amepre.2012.02.012] [Citation(s) in RCA: 77] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2011] [Revised: 12/21/2011] [Accepted: 02/23/2012] [Indexed: 01/20/2023]
Abstract
The term P4 medicine is used to denote an evolving field of medicine that uses systems biology approaches and information technologies to enhance wellness rather than just treat disease. Its four components include predictive, preventive, personalized, and participatory medicine. In the current paper, it is argued that in order to fulfill the promise of P4 medicine, a "fifth P" must be integrated-the population perspective-into each of the other four components. A population perspective integrates predictive medicine into the ecologic model of health; applies principles of population screening to preventive medicine; uses evidence-based practice to personalize medicine; and grounds participatory medicine on the three core functions of public health: assessment, policy development, and assurance. Population sciences-including epidemiology; behavioral, social, and communication sciences; and health economics, implementation science, and outcomes research-are needed to show the value of P4 medicine. Balanced strategies that implement both population- and individual-level interventions can best maximize health benefits, minimize harm, and avoid unnecessary healthcare costs.
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Affiliation(s)
- Muin J Khoury
- Office of Public Health Genomics, CDC, Atlanta, GA 30333, USA.
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6
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Sturm AC, Manickam K. Direct-to-Consumer Personal Genomic Testing: A Case Study and Practical Recommendations for “Genomic Counseling”. J Genet Couns 2012; 21:402-412. [DOI: 10.1007/s10897-012-9489-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2011] [Accepted: 01/20/2012] [Indexed: 11/29/2022]
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Rahm AK, Feigelson HS, Wagner N, Le AQ, Halterman E, Cornish N, Dearing JW. Perception of direct-to-consumer genetic testing and direct-to-consumer advertising of genetic tests among members of a large managed care organization. J Genet Couns 2012; 21:448-61. [PMID: 22278218 DOI: 10.1007/s10897-011-9477-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2011] [Accepted: 12/19/2011] [Indexed: 11/25/2022]
Abstract
This small qualitative study was designed to determine possible attitudes toward and understanding of direct-to-consumer (DTC) genetic testing among members of a large managed care organization, and whether differences might exist between population groups. Ten focus groups were conducted by population type (high risk, White, African American, Hispanic/Latino) to determine knowledge, attitudes and beliefs about DTC genetics. Focus group transcripts were coded for attitudes toward and framing of the issue. Study results found participants were negative towards DTC genetic testing but they also found some aspects useful. Participants framed the issue mainly in terms of disease prevention and uncertainty of reaction to results, with some variation between population types. The concept of an "Informed Consumer," or process to seek information when the issue becomes personally relevant, emerged. This concept suggests that individuals may seek additional assistance to make personally-appropriate choices when faced with a DTC advertisement or genetic test.
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Affiliation(s)
- Alanna Kulchak Rahm
- Institute for Health Research, Kaiser Permanente Colorado, Denver, CO 80237-8066, USA.
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8
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Ntzani EE, Liberopoulos G, Manolio TA, Ioannidis JPA. Consistency of genome-wide associations across major ancestral groups. Hum Genet 2011; 131:1057-71. [PMID: 22183176 DOI: 10.1007/s00439-011-1124-4] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2011] [Accepted: 11/29/2011] [Indexed: 12/31/2022]
Abstract
It is not well known whether genetic markers identified through genome-wide association studies (GWAS) confer similar or different risks across people of different ancestry. We screened a regularly updated catalog of all published GWAS curated at the NHGRI website for GWAS-identified associations that had reached genome-wide significance (p ≤ 5 × 10(-8)) in at least one major ancestry group (European, Asian, African) and for which replication data were available for comparison in at least two different major ancestry groups. These groups were compared for the correlation between and differences in risk allele frequencies and genetic effects' estimates. Data on 108 eligible GWAS-identified associations with a total of 900 datasets (European, n = 624; Asian, n = 217; African, n = 60) were analyzed. Risk-allele frequencies were modestly correlated between ancestry groups, with >10% absolute differences in 75-89% of the three pairwise comparisons of ancestry groups. Genetic effect (odds ratio) point estimates between ancestry groups correlated modestly (pairwise comparisons' correlation coefficients: 0.20-0.33) and point estimates of risks were opposite in direction or differed more than twofold in 57%, 79%, and 89% of the European versus Asian, European versus African, and Asian versus African comparisons, respectively. The modest correlations, differing risk estimates, and considerable between-association heterogeneity suggest that differential ancestral effects can be anticipated and genomic risk markers may need separate further evaluation in different ancestry groups.
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Affiliation(s)
- Evangelia E Ntzani
- Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, 45110 Ioannina, Greece
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9
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Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. Eur J Epidemiol 2011; 26:313-37. [PMID: 21424820 PMCID: PMC3088812 DOI: 10.1007/s10654-011-9551-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
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10
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Nakaoka H, Cui T, Tajima A, Oka A, Mitsunaga S, Kashiwase K, Homma Y, Sato S, Suzuki Y, Inoko H, Inoue I. A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis. PLoS One 2011; 6:e25389. [PMID: 21980439 PMCID: PMC3182219 DOI: 10.1371/journal.pone.0025389] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2011] [Accepted: 09/02/2011] [Indexed: 11/18/2022] Open
Abstract
Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: "leukocyte activation and differentiation", "pattern-recognition receptor signaling pathway", and "chemokines and their receptors".These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.
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Affiliation(s)
- Hirofumi Nakaoka
- Division of Human Genetics, Department of Integrated Genetics, National Institute of Genetics, Mishima, Shizuoka, Japan
| | - Tailin Cui
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
| | - Atsushi Tajima
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
- Department of Human Genetics and Public Health, Institute of Health Biosciences, The University of Tokusima Graduate School, Tokushima, Tokushima, Japan
| | - Akira Oka
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
| | - Shigeki Mitsunaga
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
| | - Koichi Kashiwase
- Department of Laboratory, Japanese Red Cross Tokyo Blood Center, Koto-ku, Tokyo, Japan
| | - Yasuhiko Homma
- Department of Clinical Health Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Shinji Sato
- Department of Internal Medicine, Division of Rheumatology, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Yasuo Suzuki
- Department of Internal Medicine, Division of Rheumatology, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Hidetoshi Inoko
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
| | - Ituro Inoue
- Division of Human Genetics, Department of Integrated Genetics, National Institute of Genetics, Mishima, Shizuoka, Japan
- Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
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11
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Janssens ACJW, Ioannidis JPA, Bedrosian S, Boffetta P, Dolan SM, Dowling N, Fortier I, Freedman AN, Grimshaw JM, Gulcher J, Gwinn M, Hlatky MA, Janes H, Kraft P, Melillo S, O'Donnell CJ, Pencina MJ, Ransohoff D, Schully SD, Seminara D, Winn DM, Wright CF, van Duijn CM, Little J, Khoury MJ. Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. Eur J Clin Invest 2011; 41:1010-35. [PMID: 21434890 DOI: 10.1111/j.1365-2362.2011.02493.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
• The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. • The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. • Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. • A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. • These recommendations aim to enhance the transparency, quality and completeness of study reporting and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
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Affiliation(s)
- A Cecile J W Janssens
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
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12
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Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. Eur J Hum Genet 2011; 19:18 p preceding 494. [PMID: 21407270 PMCID: PMC3083630 DOI: 10.1038/ejhg.2011.27] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
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13
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Gollust SE, Gordon ES, Zayac C, Griffin G, Christman MF, Pyeritz RE, Wawak L, Bernhardt BA. Motivations and perceptions of early adopters of personalized genomics: perspectives from research participants. Public Health Genomics 2011; 15:22-30. [PMID: 21654153 DOI: 10.1159/000327296] [Citation(s) in RCA: 137] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2010] [Accepted: 03/09/2011] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/AIMS To predict the potential public health impact of personal genomics, empirical research on public perceptions of these services is needed. In this study, 'early adopters' of personal genomics were surveyed to assess their motivations, perceptions and intentions. METHODS Participants were recruited from everyone who registered to attend an enrollment event for the Coriell Personalized Medicine Collaborative, a United States-based (Camden, N.J.) research study of the utility of personalized medicine, between March 31, 2009 and April 1, 2010 (n = 369). Participants completed an Internet-based survey about their motivations, awareness of personalized medicine, perceptions of study risks and benefits, and intentions to share results with health care providers. RESULTS Respondents were motivated to participate for their own curiosity and to find out their disease risk to improve their health. Fewer than 10% expressed deterministic perspectives about genetic risk, but 32% had misperceptions about the research study or personal genomic testing. Most respondents perceived the study to have health-related benefits. Nearly all (92%) intended to share their results with physicians, primarily to request specific medical recommendations. CONCLUSION Early adopters of personal genomics are prospectively enthusiastic about using genomic profiling information to improve their health, in close consultation with their physicians. This suggests that early users (i.e. through direct-to-consumer companies or research) may follow up with the health care system. Further research should address whether intentions to seek care match actual behaviors.
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Affiliation(s)
- S E Gollust
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA.
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14
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Users' motivations to purchase direct-to-consumer genome-wide testing: an exploratory study of personal stories. J Community Genet 2011; 2:135-46. [PMID: 22109820 DOI: 10.1007/s12687-011-0048-y] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2010] [Accepted: 05/10/2011] [Indexed: 01/13/2023] Open
Abstract
The relatively rapid growth of the direct-to-consumer (DTC) genetic testing market in the last few years has led to increasing attention from both the scientific community and policy makers. One voice often missing in these debates, however, is that of the actual user of these genetic testing services. In order to gain a better picture of the motivations and expectations that propel individuals to purchase DTC genome-wide testing, we conducted an exploratory study based on users' personal stories. Through qualitative content analysis of users' personal stories found on Internet blogs and DTC genetic testing companies' websites, we identified five major sets of motivations and expectations towards DTC genome-wide testing. These themes are related to (1) health, (2) curiosity and fascination, (3) genealogy, (4) contributing to research, and (5) recreation. Obtaining such information can help us to understand how users consider genome-wide testing and forms the basis for further research.
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Grimaldi KA, Look MP, Scioli GA, Clavero JC, Marinos S, Tagaris T. Personal genetics: regulatory framework in Europe from a service provider's perspective. Eur J Hum Genet 2011; 19:382-8. [PMID: 21119713 PMCID: PMC3060315 DOI: 10.1038/ejhg.2010.189] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2010] [Revised: 09/15/2010] [Accepted: 10/05/2010] [Indexed: 11/09/2022] Open
Abstract
The purpose of this article is to give an overview and discuss the relevant regulations in place, or under consideration, regarding healthcare-related personal genetics services in Europe - this is a rapidly evolving field and in most European Union (EU) countries the regulatory framework is not yet clear. The review will be framed from the perspective of potential service providers (companies, health services and practitioners, including medical, nutritional, complementary, etc), the growing number of which will need to be aware of potential regulatory hurdles existing now and that may arise in the future. The main conclusion from the survey is that strict regulations regarding practitioner-delivered personal genetic-testing services are unlikely to be enforced over the next 5 years in most EU countries, with the exception of Germany. There is broad-based, but by no means universal, support for a strong voluntary code of practice as an alternative to government regulations to protect consumers and to enable all stakeholders to recognise serious and reputable service providers. On the other hand, there are influential bodies calling for strict regulation. As genotyping costs rapidly fall, it is likely that it will become routine and a major challenge that does not seem to be addressed by current debate on regulations is the emergence of companies offering/selling personal genetic services based on a customer's pre-existing genetic results and therefore no actual laboratory testing involved.
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Affiliation(s)
- Keith A Grimaldi
- Biomedical Engineering Laboratory, Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
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16
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Janssens ACJW, Ioannidis JPA, Bedrosian S, Boffetta P, Dolan SM, Dowling N, Fortier I, Freedman AN, Grimshaw JM, Gulcher J, Gwinn M, Hlatky MA, Janes H, Kraft P, Melillo S, O'Donnell CJ, Pencina MJ, Ransohoff D, Schully SD, Seminara D, Winn DM, Wright CF, van Duijn CM, Little J, Khoury MJ. Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): explanation and elaboration. J Clin Epidemiol 2011; 64:e1-e22. [PMID: 21414753 DOI: 10.1016/j.jclinepi.2011.02.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
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Affiliation(s)
- A Cecile J W Janssens
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
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17
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Collins A, Politopoulos I. The genetics of breast cancer: risk factors for disease. APPLICATION OF CLINICAL GENETICS 2011; 4:11-9. [PMID: 23776363 PMCID: PMC3681174 DOI: 10.2147/tacg.s13139] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The genetic factors known to be involved in breast cancer risk comprise about 30 genes. These include the high-penetrance early-onset breast cancer genes, BRCA1 and BRCA2, a number of rare cancer syndrome genes, and rare genes with more moderate penetrance. A larger group of common variants has more recently been identified through genome-wide association studies. Quite a number of these common variants are mapped to genomic regions without being firmly associated with specific genes. It is thought that most of these variants have gene regulatory functions, but their precise roles in disease susceptibility are not well understood. Common variants account for only a small percentage of the risk of disease because they have low penetrance. Collectively, the breast cancer genes identified to date contribute only ~30% of the familial risk. Therefore, there is much interest in accounting for the missing heritability, and possible sources include loss of information through ignoring phenotype heterogeneity (disease subtypes have genetic differences), gene–gene and gene–environment interaction, and rarer forms of variation. Identification of these rarer variations in coding regions is now feasible and cost effective through exome sequencing, which has already identified high-penetrance variants for some rare diseases. Targeting more ‘extreme’ breast cancer phenotypes, particularly cases with early-onset disease, a strong family history (not accounted for by BRCA mutations), and with specific tumor subtypes, provides a route to progress using next-generation sequencing methods.
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Affiliation(s)
- Andrew Collins
- Genetic Epidemiology and Bioinformatics Research Group, Human Genetics Research Division, Southampton General Hospital, School of Medicine, University of Southampton, Southampton, UK
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18
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Novelli G, Predazzi IM, Mango R, Romeo F, Mehta JL. Role of genomics in cardiovascular medicine. World J Cardiol 2010; 2:428-36. [PMID: 21191544 PMCID: PMC3011138 DOI: 10.4330/wjc.v2.i12.428] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2010] [Revised: 10/25/2010] [Accepted: 11/01/2010] [Indexed: 02/06/2023] Open
Abstract
As all branches of science grow and new experimental techniques become readily accessible, our knowledge of medicine is likely to increase exponentially in the coming years. Recently developed technologies have revolutionized our analytical capacities, leading to vast knowledge of many genes or genomic regions involved in the pathogenesis of congenital heart diseases, which are often associated with other genetic syndromes, coronary artery disease and non-ischemic cardiomyopathies and channelopathies. The knowledge-base of the genesis of cardiovascular diseases is likely going to be further revolutionized in this new era of genomic medicine. Here, we review the advances that have been made over the last several years in this field and discuss different genetic mechanisms that have been shown to underlie a variety of cardiovascular diseases.
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Affiliation(s)
- Giuseppe Novelli
- Giuseppe Novelli, Irene M Predazzi, Department of Biopathology and Diagnostic Imaging, Section of Medical Genetics, School of Medicine, Tor Vergata University, Via Montpellier 1, 00133 Rome, Italy
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19
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Abstract
Genetic tests can help clinicians to diagnose rare monogenic liver diseases. For most common liver diseases, however, multiple gene variants that have small to moderate individual phenotypic effects contribute to the overall risk of disease. An individual's level of risk depends on interactions between environmental factors and a wide range of modifier genes, which are yet to be identified systematically. The latest genome-wide association studies in large cohorts of patients with gallstones, fatty liver disease, viral hepatitis, chronic cholestatic liver diseases or drug-induced liver injury have provided new insights into the pathophysiology of these illnesses and have suggested the contribution of previously unsuspected pathogenic pathways. Studies in mouse models have identified further susceptibility genes for several complex liver diseases. As a result, in the future polygenic risk scores might help to define subgroups of patients at risk of developing liver diseases who would benefit from preventative measures and/or personalized therapy. Now that whole-genome sequencing is possible, comprehensive strategies for integrating genomic data and counseling of patients need to be developed.
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Abstract
Wayne Hall and colleagues discuss the limitations of genomic risk prediction for population-level preventive health care.
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Affiliation(s)
- Wayne D Hall
- University of Queensland Centre for Clinical Research, The University of Queensland, Herston, Queensland, Australia.
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21
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Expectations, validity, and reality in omics. J Clin Epidemiol 2010; 63:945-9. [DOI: 10.1016/j.jclinepi.2010.04.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2010] [Revised: 03/22/2010] [Accepted: 04/08/2010] [Indexed: 01/24/2023]
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22
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Metzler I. Biomarkers and their consequences for the biomedical profession: a social science perspective. Per Med 2010; 7:407-420. [PMID: 29788645 DOI: 10.2217/pme.10.41] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Although biomarkers are not altogether new, they are gaining a new life in our postgenomic present. This article takes this as a good reason to explore biomarkers in depth and to speculate about the consequences that biomarkers might engender in clinical practices. First, the article ventures into an endeavor of ordering the dynamic field of biomarkers, suggesting a possible classification of biomarkers, and then argues that we are currently witnessing a 'biomarkerization' of health and disease - defined as an ongoing future-oriented process that seeks to solve biomedical as well as public health problems through investments into biomarker research at the present time. Subsequently, this article reflects on some possible consequences of this phenomenon. It argues that while the movement of candidate biomarkers into the clinic is arduous, biomarkers might develop a life of their own once they arrive in the clinic. This article outlines the direction of two such possible consequences. It suggests that biomarkers might be involved in a change of the actors that order and categorize diseases, as well as trigger transformations in our understanding of what counts as disease in the first place. Hence, this article seeks to shed light on the paradox that while biomarkers are designed to add more evidence into clinical practice, they might actually increase uncertainty and ambiguity.
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Affiliation(s)
- Ingrid Metzler
- Life-Science-Governance Research Platform, University of Vienna, Department of Political Science, Universitaetsstr. 7/2, A-1010 Vienna, Austria.
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Ioannidis JPA, Castaldi P, Evangelou E. A compendium of genome-wide associations for cancer: critical synopsis and reappraisal. J Natl Cancer Inst 2010; 102:846-58. [PMID: 20505153 DOI: 10.1093/jnci/djq173] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Since 2007, genome-wide association (GWA) studies have identified numerous well-supported, novel genetic risk loci for common cancers; however, there are concerns that this technology is reaching its limits. We provide an overview of GWA-identified genetic associations with solid tumors. We simulated the distribution of population risk alleles for colorectal, prostate, testicular, and thyroid cancers based on genetic variants identified in GWA studies. We also evaluated whether statistical power to detect typical genetic effects could be improved with studies performing GWA analyses of all available samples rather than multistage designs. Fifty-six eligible articles yielded 92 eligible associations between cancer phenotypes and genetic variants with a median per-allele odds ratio (OR) of 1.22 (interquartile range = 1.15-1.36). Half of the associations pertained to prostate, colorectal, or breast cancer. Individuals at the upper quartile of simulated risk had only 2.1- to 4.2-fold higher relative risk than those in the lower quartile. Comprehensive evaluation of currently available samples with GWA platforms would yield few additional variants with per-allele OR = 1.4, but many more variants with OR = 1.2 could be detected; statistical power to detect weak associations (OR = 1.07) would still be negligible. The GWA approach is effective in identifying common genetic variants with moderate effect; however, identifying loci with very small effects and rare variants will require major new efforts. At present, the utility of GWA-identified risk loci in risk stratification for cancer is limited.
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Affiliation(s)
- John P A Ioannidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece.
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Galvan A, Ioannidis JPA, Dragani TA. Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer. Trends Genet 2010; 26:132-41. [PMID: 20106545 DOI: 10.1016/j.tig.2009.12.008] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2009] [Revised: 12/22/2009] [Accepted: 12/22/2009] [Indexed: 02/06/2023]
Abstract
Genome-wide association studies (GWAS) using population-based designs have identified many genetic loci associated with risk of a range of complex diseases including cancer; however, each locus exerts a very small effect and most heritability remains unexplained. Family-based pedigree studies have also suggested tentative loci linked to increased cancer risk, often characterized by pedigree-specificity. However, comparison between the results of population- and family-based studies shows little concordance. Explanations for this unidentified genetic 'dark matter' of cancer include phenotype ascertainment issues, limited power, gene-gene and gene-environment interactions, population heterogeneity, parent-of-origin-specific effects, and rare and unexplored variants. Many of these reasons converge towards the concept of genetic heterogeneity that might implicate hundreds of genetic variants in regulating cancer risk. Dissecting the dark matter is a challenging task. Further insights can be gained from both population association and pedigree studies.
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Affiliation(s)
- Antonella Galvan
- Department of Predictive and for Prevention Medicine, Fondazione IRCCS, Istituto Nazionale Tumori, Via G. Venezian 1, 20133 Milan, Italy
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25
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Affiliation(s)
- D F Ransohoff
- Departments of Medicine and Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Ioannidis JPA, Tatsioni A, Karassa FB. A vision for the European journal of clinical investigation: note from the new editors. Eur J Clin Invest 2010; 40:1-3. [PMID: 20055893 DOI: 10.1111/j.1365-2362.2009.02229.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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