- Open Access
Current standards for the storage of human samples in biobanks
© BioMed Central Ltd 2010
- Published: 5 October 2010
Biobanks are diverse in their design and purpose; the idea of fully harmonizing historical and future biobanks is unaffordable and unfeasible. Biobanks should focus their efforts instead on developing and maintaining high-quality collections of samples capable of providing a wide range of biological information using processes that minimize introduced variability. A full data audit trail on sample processing, archiving, and quality control procedures should also be provided. This should enable the data derived from biobanks to contribute as part of wider collaborative efforts with other similar resources.
- Quality Control Procedure
- Quality Program
- Participant Sample
- Uniform Design
- Achievable Throughput
Biobanks are heterogeneous in their design and use, and they range in size from, say, 1,000 patients to 500,000 or more volunteers. They may contain data and samples from family studies, or from patients with a specific disease (plus ideally, matched controls), or they may be part of large-scale epidemiologic collections, or collections from clinical trials of new medical interventions. The samples collected will typically include whole blood and its fractions, extracted genomic DNA, whole cell RNA, urine, as well as, variously, saliva, nail clippings, hair and a variety of other tissues and material relevant to the design of specific studies. Inevitably, data and samples are collected under different conditions, to different standards and for different purposes. Some biobanks take a highly centralized approach to the collection, processing and archiving of samples (for example, UK Biobank ) where participant samples undergo minimal processing at the collection site, but are shipped to a central processing and storage facility. While ensuring robust quality control and data integrity and security, this approach inevitably introduces a delay between collection and cryopreservation that may result in the loss of labile species in the samples. Conversely, other large studies will aim to collect and process participant samples as quickly as possible (for example, the American Cancer Society Cancer Prevention Study-3 ). Here, samples are collected at fundraising events and in workplace settings and are processed within a few hours by local laboratories before low-temperature archiving. The challenges here are to maintain consistency of collection, shipping and processing. A hybrid approach is taken in other studies where a proportion of the participant samples are processed and stored locally, with a second set stored in a centralized archive. Here the challenges lie in process consistency, inventory control, and management of the use of the depletable aspects of the resource. This method is being considered for the Helmholtz consortium Biobank, which is under development in Germany.
Not surprisingly, given the challenges of data collection and sample storage within particular studies, there has been little standardization across biobanks. However, a number of international initiatives are aiming to provide guidance and protocols to address this issue going forward (for example, the DataSHaPER tools developed by the Public Population Project in Genomics (P3G) ). The aim is to facilitate data sharing between different resources, thereby increasing effective sample size and statistical power, especially for rare diseases . Rather than striving for uniformity across diverse studies, we believe it is more realistic to focus on developing and testing protocols that produce high-quality data and samples, with full information describing their collection and processing. In this way, studies will be optimized for the specific questions being investigated, while also potentially contributing to collaborative efforts that take advantage of samples from several biobanks.
Four key areas should be addressed in designing and implementing biobanks, regardless of their size and use.
Design and validate the sample collection protocol before main recruitment starts
An important early decision is whether samples collected from volunteers at multiple locations should be processed as quickly as possible at the collection site or shipped to a central processing facility. The first approach has the advantage that parameters that are rapidly lost within a sample may be captured, as well as avoiding possible degradation of the latent information during shipment; the second allows for a centralized approach to sample handling and processing, which may be cost-effective and result in better quality control. Either way, it is essential to minimize, as far as possible, the impact of the collection, processing, shipping and archiving protocol on the integrity of the samples. This requires properly designed pilot studies followed by robust procedures to ensure that the samples are collected, processed and handled strictly according to protocol [5–7].
Future proof the sample collection
Implement quality programs from the start of the study
The sample collection and processing protocol should be underpinned by a study-wide quality program with the aim of producing samples and data that are fit for research purposes. This should include quality assurance (preventing errors and variability from occurring) and quality control procedures (detecting errors and variability if they occur) that should be built into the study design from the outset. Many studies are implementing quality schemes, such as ISO9001:2008; these are suited to biobanks because they focus specifically on the quality of the samples and data. ISO accreditation also requires measurement of critical processes (for example, time from sample collection to ultra-low-temperature archiving) and continuous improvement efforts to optimize the performance of the organization. In UK Biobank, there has been the successful transfer of much from Japanese manufacturing quality approaches to optimize technology, processes and systems involved in sample processing . By paying careful attention to the critical points in the pathway, it has been possible to reduce the time from sample collection to ultra-low-temperature archiving from an average 25.6 h (standard deviation = 3.5) to 24.6 h (standard deviation = 2.6), close to the target of 24 h based on pilot studies .
Centralize and standardize as much as possible and limit the impact of variability
Rather than attempting to standardize biobanks to a uniform design, effort should be focused on designing and testing the sample collection protocol in a way that produces high-quality data and samples for research use. A full data audit trail should be generated on the sample collection process to allow collaborative use of samples and data across different biobanks. It is vital that quality programs are implemented to minimize the effect of introduced variability on the integrity of the samples and, where possible, consideration should be given to future proofing the collection. In this way sample biobanks should continue to provide valuable information well into the future and provide a long-term return on the initial investment in establishing the resource.
- UK Biobank. --- Either ISSN or Journal title must be supplied.. [http://www.ukbiobank.ac.uk]
- American Cancer Society: Cancer Prevention Study-3. --- Either ISSN or Journal title must be supplied.. [http://www.cancer.org/Research/ResearchProgramsFunding/Epidemiology-CancerPreventionStudies/CancerPreventionStudy-3/index]
- Fortier I, Burton PR, Robson PJ, Ferretti V, Little J, L'heureux F, Deschênes M, Knoppers BM, Doiron D, Keers JC, Linksted P, Harris JR, Lachance G, Boileau C, Pedersen NL, Hamilton CM, Hveem K, Borugian MJ, Gallagher RP, McLaughlin J, Parker L, Potter JD, Gallacher J, Kaaks R, Liu B, Sprosen T, Vilain A, Atkinson SA, Rengifo A, Morton R, et al: Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies. Int J Epidemiol. 2010, 10.1093/ije/dyq139.Google Scholar
- Burton PR, Hansell AL, Fortier I, Manolio TA, Khoury MJ, Little J, Elliott P: Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology. Int J Epidemiol. 2009, 38: 263-273. 10.1093/ije/dyn147.PubMedPubMed CentralView ArticleGoogle Scholar
- Elliott P, Peakman T: The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol. 2008, 37: 234-244. 10.1093/ije/dym276.PubMedView ArticleGoogle Scholar
- Peakman TC, Elliott P: The UK Biobank sample handling and storage validation studies. Int J Epidemiol. 2008, 37 (Suppl 1): i2-i6. 10.1093/ije/dyn019.PubMedView ArticleGoogle Scholar
- Downey P, Peakman T: Design and implementation of a high throughput biological sample processing facility using modern manufacturing principles. Int J Epidemiol. 2008, 37: i46-i50. 10.1093/ije/dyn031.PubMedView ArticleGoogle Scholar
- Ontario Health Study. --- Either ISSN or Journal title must be supplied.. [http://www.p3gobservatory.org/catalogue.htm;jsessionid=50373D569771511A84835184B76A6468?studyId=859]
- Barton RH, Nicholson JK, Elliott P, Holmes E: High throughput 1H NMR-based metabolic analysis of human serum and urine for large scale epidemiological studies: validation study. Int J Epidemiol. 2008, 37: i31-i40. 10.1093/ije/dym284.PubMedView ArticleGoogle Scholar