Sara Y. Nussbeck

A Framework for Biobank Sustainability

Each year funding agencies and academic institutions spend millions of dollars and euros on biobanking. All funding providers assume that after initial investments biobanks should be able to operate sustainably. However the topic of sustainability is challenging for the discipline of biobanking for several major reasons: the diversity in the biobanking landscape, the different purposes of biobanks, the fact that biobanks are dissimilar to other research infrastructures and the absence of universally understood or applicable value metrics for funders and other stakeholders. In this article our aim is to delineate a framework to allow more effective discussion and action around approaches for improving biobank sustainability. The term sustainability is often used to mean fiscally self-sustaining, but this restricted definition is not sufficient for biobanking. Instead we propose that biobank sustainability should be considered within a framework of three dimensions - financial, operational, and social. In each dimension, areas of focus or elements are identified that may allow different types of biobanks to distinguish and evaluate the relevance, likelihood, and impact of each element, as well as the risks to the biobank of failure to address them. Examples of practical solutions, tools and strategies to address biobank sustainability are also discussed.

The Global Genome Biodiversity Network (GGBN) Data Standard specification

Genomic samples of non-model organisms are becoming increasingly important in a broad range of studies from developmental biology, biodiversity analyses, to conservation. Genomic sample definition, description, quality, voucher information and metadata all need to be digitized and disseminated across scientific communities. This information needs to be concise and consistent in today’s ever-increasing bioinformatic era, for complementary data aggregators to easily map databases to one another. In order to facilitate exchange of information on genomic samples and their derived data, the Global Genome Biodiversity Network (GGBN) Data Standard is intended to provide a platform based on a documented agreement to promote the efficient sharing and usage of genomic sample material and associated specimen information in a consistent way. The new data standard presented here build upon existing standards commonly used within the community extending them with the capability to exchange data on tissue, environmental and DNA sample as well as sequences. The GGBN Data Standard will reveal and democratize the hidden contents of biodiversity biobanks, for the convenience of everyone in the wider biobanking community. Technical tools exist for data providers to easily map their databases to the standard. Database URL: http://terms.tdwg.org/wiki/GGBN_Data_Standard

How to Design Biospecimen Identifiers and Integrate Relevant Functionalities into Your Biospecimen Management System

Effective tracking of biospecimens within a biobank requires that each biospecimen has a unique identifier (ID). This ID can be found on the sample container as well as in the biospecimen management system. In the latter, the biospecimen ID is the key to annotation data such as location, quality, and sample processing. Guidelines such as the Best Practices from the International Society of Biological and Environmental Repositories only state that a unique identifier should be issued for each sample. However, to our knowledge, all guidelines lack a specific description of how to actually generate such an ID and how this can be supported by an IT system. Here, we provide a guide for biobankers on how to generate a biospecimen ID for your biobank. We also provide an example of how to apply this guide using a longitudinal multi-center research project (and its biobank). Starting with a description of the biobanks purpose and workflows through to collecting requirements from stakeholders and relevant documents (i.e., guidelines or data protection concepts), and existing IT-systems, we describe in detail how a concept to develop an ID system can be developed from this information. The concept contains two parts: one is the generation of the biospecimen ID according to the requirements of stakeholders, existing documentation such as guidelines or data protection concepts, and existing IT-infrastructures, and the second is the implementation of the biospecimen IDs and related functionalities covering the handling of individual biospecimens within an existing biospecimen management system. From describing the concept, the article moves on to how the new concept supports both existing or planned biobank workflows. Finally, the implementation and validation step is outlined to the reader and practical hints are provided for each step.

HDAC1 links early life stress to schizophrenia-like phenotypes

Significance Early life stress (ELS) is an important risk factor for schizophrenia. Our study shows that ELS in mice increases the levels of histone-deacetylase (HDAC) 1 in brain and blood. Although altered Hdac1 expression in response to ELS is widespread, increased Hdac1 levels in the prefrontal cortex are responsible for the development of schizophrenia-like phenotypes. In turn, administration of an HDAC inhibitor ameliorates ELS-induced schizophrenia-like phenotypes. We also show that Hdac1 levels are increased in the brains of patients with schizophrenia and in blood from patients who suffered from ELS, suggesting that the analysis of Hdac1 expression in blood could be used for patient stratification and individualized therapy. Schizophrenia is a devastating disease that arises on the background of genetic predisposition and environmental risk factors, such as early life stress (ELS). In this study, we show that ELS-induced schizophrenia-like phenotypes in mice correlate with a widespread increase of histone-deacetylase 1 (Hdac1) expression that is linked to altered DNA methylation. Hdac1 overexpression in neurons of the medial prefrontal cortex, but not in the dorsal or ventral hippocampus, mimics schizophrenia-like phenotypes induced by ELS. Systemic administration of an HDAC inhibitor rescues the detrimental effects of ELS when applied after the manifestation of disease phenotypes. In addition to the hippocampus and prefrontal cortex, mice subjected to ELS exhibit increased Hdac1 expression in blood. Moreover, Hdac1 levels are increased in blood samples from patients with schizophrenia who had encountered ELS, compared with patients without ELS experience. Our data suggest that HDAC1 inhibition should be considered as a therapeutic approach to treat schizophrenia.

Suitability of Customer Relationship Management Systems for the Management of Study Participants in Biomedical Research

BACKGROUND Longitudinal biomedical research projects study patients or participants over a course of time. No IT solution is known that can manage study participants, enhance quality of data, support re-contacting of participants, plan study visits, and keep track of informed consent procedures and recruitments that may be subject to change over time. In business settings management of personal is one of the major aspects of customer relationship management systems (CRMS). OBJECTIVES To evaluate whether CRMS are suitable IT solutions for study participant management in biomedical research. METHODS Three boards of experts in the field of biomedical research were consulted to get an insight into recent IT developments regarding study participant management systems (SPMS). Subsequently, a requirements analysis was performed with stakeholders of a major biomedical research project. The successive suitability evaluation was based on the comparison of the identified requirements with the features of six CRMS. RESULTS Independently of each other, the interviewed expert boards confirmed that there is no generic IT solution for the management of participants. Sixty-four requirements were identified and prioritized in a requirements analysis. The best CRMS was able to fulfill forty-two of these requirements. The non-fulfilled requirements demand an adaption of the CRMS, consuming time and resources, reducing the update compatibility, the systems suitability, and the security of the CRMS. CONCLUSIONS A specific solution for the SPMS is favored instead of a generic and commercially-oriented CRMS. Therefore, the development of a small and specific SPMS solution was commenced and is currently on the way to completion.

Is There a Protocol for Using the SPREC

The value of a biospecimen or biological resources depends on two factors: the intrinsic quality of the sample and the level of accurate data annotation. Recently, the relevance of pre-analytical variables during processing of biomaterials has been comprehended and scientists have become aware of the importance of this finding, launching a new field of research: ‘‘biospecimen science’’. 1 Now, it is assumed and often cited at conferences that due to the ignorance of pre-analytical variables in the earlier years of biobanking, a significant number of samples existing today are of inadequate quality and do not meet the needs of the modern molecular era. 2,3 Thus, research results based on biospecimens that have been suboptimally processed might be error-prone or of a sub-optimal quality. This lack of well-annotated process chain history is addressed by the Sample PRE-analytical Code (SPREC), 4‐6 as it allows the recording of pre-analytical variables across the process chain, from withdrawal of biomaterial to the storage of samples. The SPREC is gaining more importance throughout the biobanking community as it allows rapid and easy comparability of the quality of biological samples and improves interoperability of collaborating institutions by setting a standard. This may be especially relevant for emerging countries lacking one or more parts of research infrastructures (i.e., lack of reliable power grid, severe limitations in transport capacity, lack of trained personnel), where the SPREC would represent a valuable tool for researchers to become knowledgeable about sample quality and processing information. The aim of this column is to introduce, through guiding questions, the basic concept of the SPREC. The benefits of the code and how to use and design pre-analytical codes are explained using tools that have been designed for its implementation. How the code may be applied in different types of biobanks and biorepositories as well as the future development of the SPREC will be highlighted.

Why brain banking should be regarded as a special type of biobanking: ethical, practical, and data-management challenges

Biobanking of the brain and other central nervous system materials, ie, brain banking (BB), provides an important research tool for understanding the causes of neurodegenerative and psychiatric diseases. Particularly with aging societies, there is an increasing need for molecular neuropathological research in this field. While there is an extensive debate on biobanking in general, the specific challenges that the procurement, processing, and storage of postmortem human brain tissue, and especially whole brains, raise are hardly ever considered systematically. This paper analyzes the peculiarities that make BB a distinct type of biobanking by combining the perspectives of neuropathology, medical informatics, and medical ethics. While ethical, practical, and data-management issues are often dealt with separately and the focus of such research is on only specific aspects of BB, this paper aims at an integrated analysis of the whole process. Six crucial steps in the BB workflow are analyzed: a) donor recruitment, b) follow-up during the donors lifetime, c) postmortem brain donation, d) neuropathological diagnosis, e) research with brain tissue, and f) the provision of brain material to third parties. A compre- hensive understanding of the challenges that BB raises is vital for making this practice more effective but also to counteract the current decline in brain-donation rates.

“Life in Data”—Outcome of a Multi-Disciplinary, Interactive Biobanking Conference Session on Sample Data

Introduction: Clinical, biodiversity, and environmental biobanks share many data standards, but there is a lack of harmonization on how data are defined and used among biobank fields. This article reports the outcome of an interactive, multidisciplinary session at a meeting of the European, Middle Eastern, and African Society for Biopreservation and Biobanking (ESBB) designed to encourage a ‘learning-from-each-other’ approach to achieve consensus on data needs and data management across biobank communities. Materials, Methods, and Results: The Enviro-Bio and ESBBperanto Working Groups of the ESBB co-organized an interactive session at the 2013 conference (Verona, Italy), presenting data associated with biobanking processes, using examples from across different fields. One-hundred-sixty (160) diverse biobank participants were provided electronic voting devices with real-time screen display of responses to questions posed during the session. The importance of data standards and robust data management was recognized across the conference cohort, along with the need to raise awareness about these issues within and across different biobank sectors. Discussion and Conclusion: While interactive sessions require a commitment of time and resources, and must be carefully coordinated for consistency and continuity, they stimulate the audience to be pro-active and direct the course of the session. This effective method was used to gauge opinions about significant topics across different biobanking communities. The votes revealed the need to: (a) educate biobanks in the use of data management tools and standards, and (b) encourage a more cohesive approach for how data and samples are tracked, exchanged, and standardized across biobanking communities. Recommendations for future interactive sessions are presented based on lessons learned.