|Year : 2020 | Volume
| Issue : 6 | Page : 194-199
Development of the myocite biobank: Cost-efficient model of public sector investigator-driven biobank for idiopathic inflammatory myositis
R Naveen, Anamika Kumari Anuja, Mohit Kumar Rai, Vikas Agarwal, Latika Gupta
Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
|Date of Web Publication||18-Jan-2021|
Dr. Latika Gupta
Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow - 226 014, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Background: Biobanking refers to the cryopreservation of the various biologic samples for future research. In the era of omics, biobanking has emerged as a vital process to aid research, more so for rare diseases.
Aims and Methods: We describe herein the development of a biobank for idiopathic inflammatory myopathies (IIMs), a rheumatic illness with low prevalence. This study addresses the sample collection, transport, storage, maintenance, retrieval, and disposal of samples with a focus on cost-effectiveness, limitations, ethics, and legal aspects involved.
Discussion: Financial constraints are juxtaposed next to a wealth of clinical data in the developing countries with a large population size and consequently high burden of rare diseases. Fine-tuning efforts toward the development of bio-archival facilities can maximize outcomes from research units in these countries. A time and cost-efficient model can be the first step toward such initiatives in the appropriate setting. Unique ethical, executive, and scientific challenges were encountered by the authors while establishing the MyoCite biobank in a resource-poor setting. The various efforts to foreclose these obstacles are discussed.
Conclusion: This brief summarizes the unmet need, unique challenges, and potential solutions based on the authors' experiences gathered while setting up the MyoCite biobank for research in IIM. It also outlines the means and directions for national and global collaborations in the times ahead.
Keywords: Biobank, dermatomyositis, ethics, India, muscle, myositis, polymyositis, urine
|How to cite this article:|
Naveen R, Anuja AK, Rai MK, Agarwal V, Gupta L. Development of the myocite biobank: Cost-efficient model of public sector investigator-driven biobank for idiopathic inflammatory myositis. Indian J Rheumatol 2020;15:194-9
|How to cite this URL:|
Naveen R, Anuja AK, Rai MK, Agarwal V, Gupta L. Development of the myocite biobank: Cost-efficient model of public sector investigator-driven biobank for idiopathic inflammatory myositis. Indian J Rheumatol [serial online] 2020 [cited 2021 Mar 4];15:194-9. Available from: https://www.indianjrheumatol.com/text.asp?2020/15/6/194/289183
| Introduction|| |
Biobanking refers to the systematic collection and storage of biologic samples from patients for research purposes. In the era of omics, biobanking has emerged as a vital process to aid research in rare diseases. The advent of precision medicine and hypothesis-free approaches has rendered it imperative to mine large data sets, replete with biologic samples for drawing meaningful conclusions. Precision medicine often involves multistep research studies to establish novel hypotheses.
The European League Against Rheumatism Scleroderma Trials and Research Group has pioneered a biobank for scleroderma patients (around 8200 as on 2011), paving the way for landmark developments in the field. Since research is a time and cost-consuming process, few efforts have been taken in this direction in the developing world. The prominent dearth of data arising out of rarity of the disease calls for similar efforts for the idiopathic inflammatory myopathies (IIMs).
Although biobanks have been established for various rheumatic diseases [RDs, [Table 1] previously, few exist in India. The large population size of most developing countries provides a potentially rich resource for patient data, more so for rare RDs. A structured approach to capture the wealth of clinical and laboratory data can aid in sustainable and quality research. We herewith describe one such effort, the first of its kind to develop a biobanking protocol for IIM at a single tertiary care center in northern India. Later, we discuss the unmet needs, specific challenges, and potential solutions for the future.
| Methodology|| |
The current biobank was developed for an investigator-initiated single-center study funded by an extramural agency. A clinical case record form (CRF) previously designed for obtaining patient-specific data replete with the various outcome measures in IIM from the coreset was used to gather patient details.[17a, b]
Establishing a biobank encompasses four crucial steps – sample collection, processing, storage, and retrieval. A multidisciplinary human chain was established with predesignated personnel for each of these, with a separate system for inventory tracking [Figure 1] and Supplementary [Table 1].,,,,, Samples obtained after due consent and completion of the predesigned CRF[17a, b] are sent for central processing with a targeted median transport time of 10–40 min and processing time under 2 h. Since the pilot study was designed to study metabolomics in IIM, both fasting and nonfasting samples are obtained. The hard copies of the CRF were stored with the principal investigator after archiving a scanned soft copy on a cloud-based platform.
Manual sample coding with linked identifiers is preferred to ensure easy traceability [Supplementary [Table 1]. The samples are divided into serum and anticoagulated blood (with a greater focus on the former) followed by parsing into numerous aliquots. Since most ELISA-based assays, as well as the myositis antibody assays, require minimal sample quantity, the sample after centrifuge is divided into 10 and 100 μL aliquots, while two aliquots of 300 mcl each are stored separately for metabolomics studies [Supplementary [Table 1]. The urine obtained (after due exclusions and precautions) is similarly stored in pop-up larger Eppendorf of 1.5 ml each.
Muscle biopsy is done by a minimally invasive sutureless conchotome procedure by the bedside and shipped for central processing for histopathology, metabolite, protein, and RNA studies [Supplementary Table 1]. The diseased muscle biospecimens are obtained from the mid-thigh, in the affected muscle, on the side opposite to the electromyogram needle placement. The control biopsies are collected from various sources Supplementary Table 1], including but not limited to the anterior abdominal muscles in patients undergoing laparotomy for nonsystemic diseases and young individuals undergoing limb surgeries for road traffic accidents (after excluding crush injuries by normal muscle enzymes and renal parameters). Elderly population or patients with chronic disease expected to result in sarcopenia such as diabetes mellitus, chronic liver disease, and chronic kidney disease are excluded [Supplementary [Table 2]. Control serum was taken from healthy controls and systemic lupus erythematosus patients.
Samples are banked at a centralized laboratory under the institute where research procedures are conducted routinely. The freezers (−40°C, −20°C, and −80°C) and liquid nitrogen cylinders are in place along with equipment and power backup. Samples for immediate processing go to the working freezer (−20°C) while −80°C freezer is used for long-term storage. The research laboratory also has a room temperature and cooling centrifuges, 37°C incubators, and pipettes for conducting the procedures.
The sample is received at the research laboratory by predesignated components of the human chain connected virtually over instant messaging/email and processed immediately. Since the laboratory is intimated when the sample is collected, the container labeling is complete by the time the samples are received in the laboratory. After due segregation, the various samples are stored at −80°C for ensuring long-term viability. Reserve storage arrangements are in place. Laboratory training for staff and students, equipment maintenance, and biosafety precautions are provided under the aegis of the tertiary care institute. Periodic audits are done, and standard quality control protocols are followed. Samples and wastes are disposed of as per standard biomedical waste management rules.
Apart from clinical data sets, it is essential to gather relevant information on controls. Since the healthy and disease control forms could possibly be filled by allied Specialities such as neurologists and surgeons, the variables required were kept to the bare minimum [Supplementary [Table 2] and [Table 3].
| Discussion|| |
The MyoCite biobank is the first bio-archival facility dedicated to myositis research in India. Being the first venture in a developing country, it was met with unique financial and cultural challenges. Various methods [Figure 2] such as a reduction in the sample quantity and diversity, fewer procedures, organizing a human chain for sample transport, using manual record maintenance and inventory tracking, and the use of established institute infrastructure were instrumental in developing this cost-efficient model.
|Figure 2: Bubble chart delineating methods for cost-efficiency in the MyoCite biobank|
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Felt need for biobanking and the benefits
A dearth of patient numbers in rare RDs leads to significant burden of participation (in studies) on patients following up at centers with a research facility. While drawing multiple samples is physically traumatic, consent on various occasions could adversely affect psychologic optimism and denigrate the patients' trust in the system. Moreover, in the era of omics and hypothesis-free research, numerous samples are required for multistep experiments. These are best drawn at a single time point for uniformity of disease activity across the series of experiments. Moreover, environmental factors can also significantly alter the results, more so for sensitive assays (such as metabolomics); thus, banking a larger volume would remove potential environmental confounders and yield meaningful conclusions.
Furthermore, attrition and survivorship bias can be mitigated by prospective banking. Over time, consistent collection can gather fair numbers for better understanding of regional phenotypes of the disease by participation in international collaborative efforts.
Unique challenges in India
The low health-care budget (1.7% of GDP in 2020) in India leaves researchers with precarious national as well as intramural funds for research. Moreover, a large population size leads to high burden on clinical service providers, limiting time available for research. Unlike most developed countries where the practitioner and research tracks are separate for rheumatologists in the public sector, this model is not operative in this part of the world, limiting the time devoted to writing grants and generating extramural funding. Consequently, most research work is carried out with limited resources, from both, within and outside the country [Table 2].
|Table 2: Challenges encountered in biobank creation in a developing nation|
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These hurdles were partly overcome by the use of available resources, including an established research laboratory and institutional equipment for the MyoCite biobank. The availability of workforce for transport and manual coding and using cheaper consumables reduced the expenses further. Students enrolled in PhD and DM programs added to the intellectual and skilled workforce. These are further depicted in a bubble diagram [Figure 2].
Unlike many developed countries where biobanking is universally acceptable right from the time of birth, patient motivation for contributing to research is an unmet need amid poor literacy, when understanding of such initiatives is rather limited. Patient education and engagement is a crucial step toward gathering their support while dealing with social, cultural, and psychologic barriers. This can be greater among women, a particular challenge for RDs such as IIM, which disproportionately affect the female gender. Garnering patient trust can begin with educating them about the primary research objectives, the felt need for such efforts, and ways in which it is likely to benefit society at large, and patients with this disease in particular. The benefit to the patient, if any, needs to be explained as well. Incentives such as a personal gain from results of autoantibody tests are likely to influence patient willingness to contribute, as seen from previous studies., However, this entails breaking through patient identifiers, thus feasible only in registries where the data are not entirely de-linked.
Most biobanks involve the collection of large volumes of blood (45–50 ml on an average). This can be a deterrent to contribute, more so for individuals with chronic disease. Thus, it might be prudent to take a smaller sample quantity at the first visit, and later provide them with the option of follow-up samples, at their discretion, as was done for the MyoCite biobank.
The various ethical issues encountered include the ownership of specimen, the type of consent taken, informed versus broad consent, re-consents if the sample is used for another project, and withdrawal of permissions if the patient wishes so at a later point in time. The latter could be difficult in biobanks with complete de-linkage of patient identifiers with the samples. Further, gray areas include the transfer of specimens across centers (in multicenter repositories, and collaborative research), destruction of samples, and commercialization with sharing of research benefits, which need to be addressed in national guidelines for biobanks. A broad consent was taken for the MyoCite bio-archival facility, with optional withdrawal from research on follow-up visits.
While it is prudent to disclose results of specific laboratory assays which carry grievous implications with the possibility of timely intervention with therapy (e.g., cancer in anti-TIF1 gamma-positive myositis, or rapidly progressive interstitial lung disease in anti-MDA-5-positive myositis), it is also important to be mindful of patient rights when dealing with less implicative results. For example, concerns of genetic reductionism have emerged among patients participating in large genetic biorepositories., In these situations, the risks need to be weighed against the expected benefits.
On the other hand, the presence of antisynthetase syndrome-related antibodies could signify evolution to other symptoms (which would include interstitial lung disease) in a proportion of cases over few years despite being minimally symptomatic at the time of testing. These pose a unique dilemma regarding the appropriateness of informing the patients, when sample is donated voluntarily for research. The mental burden of an anticipated illness could be immense, and the morbidity resulting from such anxiety needs to be weighed against the advantages of the probable lead time obtained by early detection.
Incentivizing the stakeholders
Patients, researchers, and the technical staff involved are the prime stakeholders in biobanking research. It is essential to identify patients as “contributors” and not mere participants in laboratory research. Limiting the sample quantity and attachment to an institute of repute also amounts to greater contributor trust, engagement, and participation, as seen from the previous studies. Informing the contributors about various patient support groups related to their disease can be motivating and empowering them to lead the way forward.
Choosing the right center (preferably tertiary care) will ensure larger sample population (and garner patient trust) while providing the laboratory infrastructure needed. This could also bring on board collaboration between a dedicated team of researchers with an interest and the expertise in the area.
Besides, the use of manual coding, record maintenance, and sample placement charting can be cost-efficient. Reducing the sample quantity, diversity, and procedures conducted can significantly reduce effort for the thin workforce. Further, reducing the frequency of biospecimen viability checks (within acceptable limits) merit consideration.,
Collaboration with existent national biobanks, for example, ICMR is another possibility that should be explored. Working with other smaller units to set up a network of smaller cost-efficient biobanks could build an ocean worth of data in a rare disease over time. Moreover, establishing similar biobanks at institutes across the country could be the stepping stone to better collaboration. Cross biobank sample transfer and research can accelerate the research on inflammatory myositis in a country of 1.38 billion population.
Finally, incentivizing local practitioners with education through CMEs, telemotivating patients through online patient support groups, and encouraging them with the antibody test results could aid referral and recruitment. The Myositis India Support Group was created with the intent to have a common platform for patients to engage, seek support, and gather fresh perspectives on their disease as well the future through interpatient interactions. Patient-initiated registries such as the Myositis Patient-Centered Tele-Research and patient-funded registries such as myositis.org and curejm.org are the pioneering efforts in IIM in the developed world. Awareness about biobanking for research is slowly gaining impetus among researchers and patients alike in India as well. The usage of data cards for convenient sample collection and storage and increased industry engagement could lead the way ahead in the times to come.
| Conclusion|| |
Thus, unique ethical, executive, and scientific challenges are expected in the establishment of a bio-archival facility in a resource-constrained setting. Proposed solutions may outline the means and directions for sustainable research in the times ahead.
The authors thank Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, and Asia Pacific League of Associations for Rheumatology (APLAR) for their support in establishing the MyoCite biobank.
Financial support and sponsorship
This study was financially supported by APLAR and intramural.
Conflicts of interest
LG is the founder of Myositis India patient support group and administrative team member of Myositis Global Network.
Supplementary Table 3: Glossary of case record form MyoCite: Control muscle biopsy version 9.0
Diabetes as per the American Diabetology Association definitions
A fasting plasma glucose level of 126 mg/dL (7.0 mmol/L) or higher, or
A 2-h plasma glucose level of 200 mg/dL (11.1 mmol/L) or higher during a 75-g oral glucose tolerance test, or
A random plasma glucose of 200 mg/dL (11.1 mmol/L) or higher in a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, or
A hemoglobin A1c level of 6.5% (48 mmol/mol) or higher.
Chronic liver disease refers to disease of the liver which last over a period of 6 months. It consists of a wide range of liver pathologies which include inflammation (chronic hepatitis), liver cirrhosis, and hepatocellular carcinoma.
Chronic kidney disease (CKD) as per KDIGO definitions.
CKD is defined as kidney damage or glomerular filtration rate <60 mL/min/1.73 m2 for 3 months or more, irrespective of the cause.
Section 1 (To be filled by the clinician collecting the sample)
- Date of collection. Date of the sample collection
- Medical record number (MRD). Refers to your hospital records/registration number. If CR/MRD number is less than 10 digits, make it 10 digits by adding zeroes in the beginning. If CR/MRD number is more than 10 digits, use your discretion to enter it below the spaces provided in the boxes. Patient's name – first two alphabets of first and last names are to be noted
- Age. Age of patient in years
- Gender. Male or female
- Weight and height in kg and cm, respectively
- Diagnosis. Road traffic accident, surgical abdomen, muscle dystrophy, or others (indication for which control muscle biopsy is taken is noted)
- Muscle weakness. Yes/no. If yes, MMT 8 is done, as described prior in CRF 3.0 glossary
- Muscle enzymes aspartate transaminase, alanine transaminase, lactate dehydrogenase, aldolase, and creatinine phosphokinase in IU/L
- Samples collected. Biospecimen collected for research to be noted; muscle biopsy from thigh, abdominal wall, or others; blood and urine.
Section 2 (For use by laboratory personnel only)
- Patient identifier code. This will be 10-character identifier – first 4 digits will be center code – say UPSG for Uttar Pradesh, Sanjay Gandhi Postgraduate Institute (this will be allotted by core team); next 2 characters will pertain to the investigator initials – say LG for Dr. Latika Gupta; last 4 digits will denote the patient number at your center. First patient will be identified as 0001 and so on. Hence, final patient identifier will be as follows: UPSGLG0001 (for above mentioned example)
- Samples stored. Muscle DNA, RNA, formalin, and lysate. Samples stored for DNA, serum, and microparticles are stored. Details of sample processing are as in Supplementary Table 1. The number of aliquots stored is noted for each type of sample
- Diagnosis and classification of diabetes mellitus. Diabetes Care 2004;27 Suppl 1:s5-10.
- Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: A position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 2005;67:2089-100.
- Gupta L, Appani SK, Janardana R, Muhammed H, Lawrence A, Amin S, et al. Meeting report: MyoIN – Pan-India collaborative network for myositis research. Indian J Rheumatol 2019;14:136-42.
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[Figure 1], [Figure 2]
[Table 1], [Table 2]
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