Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies

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Abstract

Background Vast sample sizes are often essential in the quest to disentangle the complex interplay of the genetic, lifestyle, environmental and social factors that determine the aetiology and progression of chronic diseases. The pooling of information between studies is therefore of central importance to contemporary bioscience. However, there are many technical, ethico-legal and scientific challenges to be overcome if an effective, valid, pooled analysis is to be achieved. Perhaps most critically, any data that are to be analysed in this way must be adequately ‘harmonized’. This implies that the collection and recording of information and data must be done in a manner that is sufficiently similar in the different studies to allow valid synthesis to take place.

Methods This conceptual article describes the origins, purpose and scientific foundations of the DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research; http://www.datashaper.org), which has been created by a multidisciplinary consortium of experts that was pulled together and coordinated by three international organizations: P ³G (Public Population Project in Genomics), PHOEBE (Promoting Harmonization of Epidemiological Biobanks in Europe) and CPT (Canadian Partnership for Tomorrow Project).

Results The DataSHaPER provides a flexible, structured approach to the harmonization and pooling of information between studies. Its two primary components, the ‘DataSchema’ and ‘Harmonization Platforms’, together support the preparation of effective data-collection protocols and provide a central reference to facilitate harmonization. The DataSHaPER supports both ‘prospective’ and ‘retrospective’ harmonization.

Conclusion It is hoped that this article will encourage readers to investigate the project further: the more the research groups and studies are actively involved, the more effective the DataSHaPER programme will ultimately be.

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Most cited references 61

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Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

Lachlan Coin, Joshua Randall, George Davey Smith (2009)

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

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A vision for the future of genomics research.

Francis Collins, Eric Green, Alan Guttmacher … (2003)

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The Canadian longitudinal study on aging (CLSA).

Archana Raina, Christina Wolfson, Holly Tuokko … (2009)

ABSTRACTCanadians are living longer, and older persons are making up a larger share of the population (14% in 2006, projected to rise to 20% by 2021). The Canadian Longitudinal Study on Aging (CLSA) is a national longitudinal study of adult development and aging that will recruit 50,000 Canadians aged 45 to 85 years of age and follow them for at least 20 years. All participants will provide a common set of information concerning many aspects of health and aging, and 30,000 will undergo an additional in-depth examination coupled with the donation of biological specimens (blood and urine). The CLSA will become a rich data source for the study of the complex interrelationship among the biological, physical, psychosocial, and societal factors that affect healthy aging.

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Author and article information

Journal

Journal ID (nlm-ta): Int J Epidemiol

Journal ID (publisher-id): ije

Journal ID (hwp): intjepid

Title: International Journal of Epidemiology

Publisher: Oxford University Press

ISSN (Print): 0300-5771

ISSN (Electronic): 1464-3685

Publication date (Print): October 2010

Publication date (Electronic): 2 September 2010

Publication date PMC-release: 2 September 2010

Volume: 39

Issue: 5

Pages: 1383-1393

Affiliations

¹Public Population Project in Genomics (P ³G), Montreal, QC, Canada, ²Research Center, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada, ³Department of Health Sciences and Department of Genetics, University of Leicester, Leicester, UK, ⁴Division of Population Health and Information, Alberta Cancer Board, Edmonton, AB, Canada, ⁵Ontario Institute for Cancer Research, MaRS Centre, Toronto, ON, Canada, ⁶Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada, ⁷Centre of Genomics and Policy, Faculty of Medicine, Department of Human Genetics, McGill University, Montreal, QC, Canada, ⁸LifeLines, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands, ⁹Generation Scotland, University of Edinburgh, Molecular Medicine Centre, Western, General Hospital, Edinburgh, UK, ¹⁰Division of Epidemiology, The Norwegian Institute of Public Health, Oslo, Norway, ¹¹Cartagene, Montreal, QC, Canada, ¹²Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, ¹³PhenX Project, Research Triangle Institute, Research Triangle Park, NC, USA, ¹⁴Department of Public Health, Norwegian University of Science and Technology, Trondheim, Norway, ¹⁵Cancer Control Research, British Columbia Cancer Agency, Vancouver, BC, Canada, ¹⁶Department of Health Care and Epidemiology, University of British Columbia, Vancouver, BC, Canada, ¹⁷Samuel Lunenfeld Research Institute of the Mount Sinai Hospital, Toronto, ON, Canada, ¹⁸Department of Medicine and Department of Paediatrics, Dalhousie University, Halifax, NS, Canada, ¹⁹Cancer Prevention Program, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA, ²⁰Department of Epidemiology, Statistics and Public Health, Centre for Health Sciences Research, Cardiff University, Cardiff, UK, ²¹Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²²Cancer Epidemiology Unit, University of Oxford, Oxford, UK, ²³UK Biobank, Stockport, UK, ²⁴Estonian Genome Project of University of Tartu, Tartu, Estonia, ²⁵Institute of Epidemiology, Helmholtz Zentrum München, Ludwig-Maximilians-Universität, Munich, Germany, ²⁶Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany, ²⁷Klinikum Grosshadern, Ludwig-Maximilians-Universität München, Munich, Germany, ²⁸Department of Pediatrics, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada, ²⁹Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada, ³⁰The Center for Genetic Medicine, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA, ³¹Banco Nacional de ADN, Universidad de Salamanca, Fundacion Genoma España, Consejería de Sanidad de la Junta de Castilla y León, Spain, ³²Department of Cardiology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands, ³³Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, ³⁴Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, WA, Australia, ³⁵National Institute for Welfare and Health, Helsinki, Finland, ³⁶Institute for Molecular Medicine Finland FIMM, University of Helsinki and National Public Health Institute, Helsinki, Finland, ³⁷Department of Endocrinology and Metabolism, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands, ³⁸Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK, ³⁹Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada and ⁴⁰Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

Author notes

*Corresponding author. Public Population Project in Genomics (P ³G), 3333 Queen Mary Road, Suite 590, Montreal H3V 1A2, Quebec, Canada. E-mail: ifortier@ 123456p3g.org

Article

Publisher ID: dyq139

DOI: 10.1093/ije/dyq139

PMC ID: 2972444

PubMed ID: 20813861

SO-VID: 80c599c1-c646-4dd2-b161-76de1ba40af3

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This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies

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Most cited references 61

Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

A vision for the future of genomics research.

The Canadian longitudinal study on aging (CLSA).

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