Managing sensitive phenotypic data and biomaterial in large-scale collaborative psychiatric genetic research projects: practical considerations

[Biobanking in Psychiatry]

Medical biobanking is concerned with establishing and maintaining large-scale repositories of biological specimens combined with comprehensive archives of clinical and biographical information on donors. This aims for controlled high and consistent quality of specimens for future biomedical research. One major objective is to assemble multiple blood components for various types of biochemical analysis and experimentation including different isolated cell types. With proper cryo-conservation, blood-derived cells can be conserved and revitalized after thawing and employed as in-vitro cell models carrying specific biological traits of donors. Optimizing pre-analytical methods can reduce pre-analytical variance thereby reducing imprecision of analytical data. This is particularly valuable for multivariate analyses of biological systems ("omics") and biomarker research. Introducing biobanking to psychiatry carries the challenge of making diagnostic allocation more compatible with biological entities than is achieved with current diagnostic categories of ICD-10 or DSM-V. Diagnostic or transdiagnostic subgroups can be stratified using biologically anchored clinical criteria. An important ethical issue of biobanking is the need for broad consent by the donors for specimen use in not yet defined future research projects. The organizational, logistic and financial costs of establishing and maintaining a biobank are considerable, but seem well warranted in view of the gainable advances in biomedical research quality, translations and clinical applications.

Liquid materials for biomedical research: a highly IT-integrated and automated biobanking solution

Various information technology (IT) infrastructures for biobanking, networks of biobanks and biomaterial management are described in the literature. As pre-analytical variables play a major role in the downstream interpretation of clinical as well as research results, their documentation is essential. A description for mainly automated documentation of the complete life-cycle of each biospecimen is lacking so far. Here, the example taken is from the University Medical Center Göttingen (UMG), where the workflow of liquid biomaterials is standardized between the central laboratory and the central biobank. The workflow of liquid biomaterials from sample withdrawal to long-term storage in a biobank was analyzed. Essential data such as time and temperature for processing and freezing can be automatically collected. The proposed solution involves only one major interface between the main IT systems of the laboratory and the biobank. It is key to talk to all the involved stakeholders to ensure a functional and accepted solution. Although IT components differ widely between clinics, the proposed way of documenting the complete life-cycle of each biospecimen can be transferred to other university medical centers. The complete documentation of the life-cycle of each biospecimen ensures a good interpretability of downstream routine as well as research results.

Pseudonymization for research data collection: is the juice worth the squeeze?

BACKGROUND

The collection of data and biospecimens which characterize patients and probands in-depth is a core element of modern biomedical research. Relevant data must be considered highly sensitive and it needs to be protected from unauthorized use and re-identification. In this context, laws, regulations, guidelines and best-practices often recommend or mandate pseudonymization, which means that directly identifying data of subjects (e.g. names and addresses) is stored separately from data which is primarily needed for scientific analyses.

DISCUSSION

When (authorized) re-identification of subjects is not an exceptional but a common procedure, e.g. due to longitudinal data collection, implementing pseudonymization can significantly increase the complexity of software solutions. For example, data stored in distributed databases, need to be dynamically combined with each other, which requires additional interfaces for communicating between the various subsystems. This increased complexity may lead to new attack vectors for intruders. Obviously, this is in contrast to the objective of improving data protection. What is lacking is a standardized process of evaluating and reporting risks, threats and countermeasures, which can be used to test whether integrating pseudonymization methods into data collection systems actually improves upon the degree of protection provided by system designs that simply follow common IT security best practices and implement fine-grained role-based access control models. To demonstrate that the methods used to describe systems employing pseudonymized data management are currently heterogeneous and ad-hoc, we examined the extent to which twelve recent studies address each of the six basic security properties defined by the International Organization for Standardization (ISO) standard 27,000. We show inconsistencies across the studies, with most of them failing to mention one or more security properties.

CONCLUSION

We discuss the degree of privacy protection provided by implementing pseudonymization into research data collection processes. We conclude that (1) more research is needed on the interplay of pseudonymity, information security and data protection, (2) problem-specific guidelines for evaluating and reporting risks, threats and countermeasures should be developed and that (3) future work on pseudonymized research data collection should include the results of such structured and integrated analyses.

A longitudinal approach to biological psychiatric research: The PsyCourse study

In current diagnostic systems, schizophrenia and bipolar disorder are still conceptualized as distinct categorical entities. Recently, both clinical and genomic evidence have challenged this Kraepelinian dichotomy. There are only few longitudinal studies addressing potential overlaps between these conditions. Here, we present design and first results of the PsyCourse study (N = 891 individuals at baseline), an ongoing transdiagnostic study of the affective-to-psychotic continuum that combines longitudinal deep phenotyping and dimensional assessment of psychopathology with an extensive collection of biomaterial. To provide an initial characterization of the PsyCourse study sample, we compare two broad diagnostic groups defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) classification system, that is, predominantly affective (n = 367 individuals) versus predominantly psychotic disorders (n = 524 individuals). Depressive, manic, and psychotic symptoms as well as global functioning over time were contrasted using linear mixed models. Furthermore, we explored the effects of polygenic risk scores for schizophrenia on diagnostic group membership and addressed their effects on nonparticipation in follow-up visits. While phenotypic results confirmed expected differences in current psychotic symptoms and global functioning, both manic and depressive symptoms did not vary between both groups after correction for multiple testing. Polygenic risk scores for schizophrenia significantly explained part of the variability of diagnostic group. The PsyCourse study presents a unique resource to research the complex relationships of psychopathology and biology in severe mental disorders not confined to traditional diagnostic boundaries and is open for collaborations.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia, part III: Molecular mechanisms

OBJECTIVES

Despite progress in identifying molecular pathophysiological processes in schizophrenia, valid biomarkers are lacking for both the disease and treatment response.

METHODS

This comprehensive review summarises recent efforts to identify molecular mechanisms on the level of protein and gene expression and epigenetics, including DNA methylation, histone modifications and micro RNA expression. Furthermore, it summarises recent findings of alterations in lipid mediators and highlights inflammatory processes. The potential that this research will identify biomarkers of schizophrenia is discussed.

RESULTS

Recent studies have not identified clear biomarkers for schizophrenia. Although several molecular pathways have emerged as potential candidates for future research, a complete understanding of these metabolic pathways is required to reveal better treatment modalities for this disabling condition.

CONCLUSIONS

Large longitudinal cohort studies are essential that pair a thorough phenotypic and clinical evaluation for example with gene expression and proteome analysis in blood at multiple time points. This approach might identify biomarkers that allow patients to be stratified according to treatment response and ideally also allow treatment response to be predicted. Improved knowledge of molecular pathways and epigenetic mechanisms, including their potential association with environmental influences, will facilitate the discovery of biomarkers that could ultimately be effective tools in clinical practice.

HDAC1 links early life stress to schizophrenia-like phenotypes

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.

[The German research network for mental disorders]

Mental disorders are among the greatest medical and social challenges facing us. They can occur at all stages of life and are among the most important commonly occurring diseases. In Germany 28 % of the population suffer from a mental disorder every year, while the lifetime risk of suffering from a mental disorder is almost 50 %. Mental disorders cause great suffering for those affected and their social network. Quantitatively speaking, they can be considered to be among those diseases creating the greatest burden for society due to reduced productivity, absence from work and premature retirement. The Federal Ministry of Education and Research is funding a new research network from 2015 to 2019 with up to 35 million euros to investigate mental disorders in order to devise and develop better therapeutic measures and strategies for this population by means of basic and translational clinical research. This is the result of a competitive call for research proposals entitled research network for mental diseases. It is a nationwide network of nine consortia with up to ten psychiatric and clinical psychology partner institutions from largely university-based research facilities for adults and/or children and adolescents. Furthermore, three cross-consortia platform projects will seek to identify shared causes of diseases and new diagnostic modalities for anxiety disorders, attention deficit hyperactivity disorders (ADHS), autism, bipolar disorders, depression, schizophrenia and psychotic disorders as well as substance-related and addictive disorders. The spectrum of therapeutic approaches to be examined ranges from innovative pharmacological and psychotherapeutic treatment to novel brain stimulation procedures. In light of the enormous burden such diseases represent for society as a whole, a sustainable improvement in the financial support for those researching mental disorders seems essential. This network aims to become a nucleus for long overdue and sustained support for a German center for mental disorders.

A generic solution for web-based management of pseudonymized data

BACKGROUND

Collaborative collection and sharing of data have become a core element of biomedical research. Typical applications are multi-site registries which collect sensitive person-related data prospectively, often together with biospecimens. To secure these sensitive data, national and international data protection laws and regulations demand the separation of identifying data from biomedical data and to introduce pseudonyms. Neither the formulation in laws and regulations nor existing pseudonymization concepts, however, are precise enough to directly provide an implementation guideline. We therefore describe core requirements as well as implementation options for registries and study databases with sensitive biomedical data.

METHODS

We first analyze existing concepts and compile a set of fundamental requirements for pseudonymized data management. Then we derive a system architecture that fulfills these requirements. Next, we provide a comprehensive overview and a comparison of different technical options for an implementation. Finally, we develop a generic software solution for managing pseudonymized data and show its feasibility by describing how we have used it to realize two research networks.

RESULTS

We have found that pseudonymization models are highly heterogeneous, already on a conceptual level. We have compiled a set of requirements from different pseudonymization schemes. We propose an architecture and present an overview of technical options. Based on a selection of technical elements, we suggest a generic solution. It supports the multi-site collection and management of biomedical data. Security measures are multi-tier pseudonymity and physical separation of data over independent backend servers. Integrated views are provided by a web-based user interface. Our approach has been successfully used to implement a national and an international rare disease network.

CONCLUSIONS

We were able to identify a set of core requirements out of several pseudonymization models. Considering various implementation options, we realized a generic solution which was implemented and deployed in research networks. Still, further conceptual work on pseudonymity is needed. Specifically, it remains unclear how exactly data is to be separated into distributed subsets. Moreover, a thorough risk and threat analysis is needed.

Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses

Background

We aimed to establish a bipolar disorder biobank to serve as a resource for clinical and biomarker studies of disease risk and treatment response. Here, we describe the aims, design, infrastructure, and research uses of the biobank, along with demographics and clinical features of the first participants enrolled.

Methods

Patients were recruited for the Mayo Clinic Bipolar Biobank beginning in July 2009. The Structured Clinical Interview for DSM-IV was used to confirm bipolar diagnosis. The Bipolar Biobank Clinical Questionnaire and Participant Questionnaire were designed to collect detailed demographic and clinical data, including clinical course of illness measures that would delineate differential phenotypes for subsequent analyses. Blood specimens were obtained from participants, and various aliquots were stored for future research.

Results

As of September 2014, 1363 participants have been enrolled in the bipolar biobank. Among these first participants, 69.0 % had a diagnosis of bipolar disorder type I. The group was 60.2 % women and predominantly white (90.6 %), with a mean (SD) age of 42.6 (14.9) years. Clinical phenotypes of the group included history of psychosis (42.3 %), suicide attempt (32.5 %), addiction to alcohol (39.1 %), addiction to nicotine (39.8 %), obesity (42.9 %), antidepressant-induced mania (31.7 %), tardive dyskinesia (3.2 %), and history of drug-related serious rash (5.7 %).

Conclusions

Quantifying phenotypic patterns of illness beyond bipolar subtype can provide more detailed clinical disease characteristics for biomarker research, including genomic-risk studies. Future research can harness clinically useful biomarkers using state-of-the-art research technology to help stage disease burden and better individualize treatment selection for patients with bipolar disorder.

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 biobank's 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.

Changing requirements and resulting needs for IT-infrastructure for longitudinal research in the neurosciences

The observation of growing "difficulties" in IT-infrastructures in neuroscience research during the last years led to a search for reasons and an analysis on how this phenomenon is reflected in the scientific literature. With a retrospective analysis of nine examples of multicenter research projects in the neurosciences and a literature review the observation was systematically analyzed. Results show that the rise in complexity mainly stems from two reasons: (1) more and more need for information on quality and context of research data (metadata) and (2) long-term requirements to handle the consent and identity/pseudonyms of study participants and biomaterials in relation to legal requirements. The combination of these two aspects together with very long study times and data evaluation periods are components of the subjectively perceived "difficulties". A direct consequence of this result is that big multicenter trials are becoming part of integrated research data environments and are not standing alone for themselves anymore. This drives up the resource needs regarding the IT-infrastructure in neuroscience research. In contrast to these findings, literature on this development is scarce and the problem probably underestimated.

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 system's 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.

Molecular genetics research in ADHD: ethical considerations concerning patients' benefit and resource allocation

Immense resource allocations have led to great data output in genetic research. Concerning ADHD resources spent on genetic research are less than those spent on clinical research. But there are successful efforts made to increase support for molecular genetics research in ADHD. Concerning genetics no evidence based conclusive results have significant impact on prevention, diagnosis or treatment yet. With regard to ethical aspects like the patients' benefit and limited resources the question arises if it is indicated to think about a new balance of resource allocation between molecular genetics and non-genetics research in ADHD. An ethical reflection was performed focusing on recent genetic studies and reviews based on a selective literature search. There are plausible reasons why genetic research results in ADHD are somehow disappointing for clinical practice so far. Researchers try to overcome these gaps systematically, without knowing what the potential future benefits for the patients might be. Non-genetic diagnostic/therapeutic research may lead to clinically relevant findings within a shorter period of time. On the other hand, non-genetic research in ADHD may be nurtured by genetic approaches. But, with the latter there exist significant risks of harm like stigmatization and concerns regarding data protection. Isolated speeding up resources of genetic research in ADHD seems questionable from an ethical point of view. There is a need to find a new balance of resource allocation between genetic and non-genetic research in ADHD, probably by integrating genetics more systematically into clinical research. A transdisciplinary debate is recommended.