Kidney Biorepositories

Abstract

Biorepositories—centralized facilities for storing biologic specimens (such as blood, urine, and tissue) along with associated patient data—are critical resources that can drive progress in AKI research. To highlight their importance, the American Society of Nephrology's AKINow Basic Science Workgroup hosted a webinar titled “How to Build and Best Use Kidney Biorepositories,” featuring expert panelists Drs. A. Hung, S. Jain, and C. Parikh. This discussion, summarized here, focused on: (1) How biorepositories can support research, especially for early-stage investigators; (2) key logistical considerations for establishing a new biorepository; and (3) the benefits and trade-offs of creating a new biorepository versus existing ones. In addition, details related to existing biorepositories are provided to foster better utilization of these valuable resources. The goal is to inform nephrology investigators about how to leverage existing biorepositories to advance their research and to provide guidance for those interested in generating their own.

Improving the care of patients with AKI requires a more profound understanding of its underlying mechanisms, and biorepositories are critical to facilitate the research necessary to drive these clinical innovations.¹ A biorepository typically involves the centralized storage of biologic samples, such as kidney tissue, blood and urine, and associated patient data. Biorepositories may use an honest broker system through which a user has access to deidentified patient data, offering more granular information about the kidney injury and comorbidities, that can be linked to the biospecimen in a way that protects patient privacy and minimizes regulatory burdens. Many investigators stand to benefit from access to these samples, either by establishing their own local biorepository or, more commonly, by using existing resources. To leverage biorepositories in kidney injury, the American Society of Nephrology's AKINow Workgroup convened a panel of experts, Drs. A. Hung, S. Jain, and C. Parikh, for a discussion on April 18, 2024. This sponsored webinar titled, “How to Build and Best Use Kidney Biorepositories” covered the advantages and challenges of biorepositories and the considerations of building one versus using established resources.² Drs. A. Hung, S. Jain, and C. Parikh use their expertise with the Veterans Affairs (VA) Million Veteran Program,³ Kidney Translational Research Center (KTRC),⁴ Kidney Precision Medicine Project (KPMP),^5,6 Human Biomolecular Atlas Program (HuBMAP),^7,8 Translational Research Investigating Biomarker Endpoints in AKI (TRIBE-AKI),^9–12 and deceased donor study (DDS)^13–15 to provide advice to investigators interested in using existing or building their own biorepositories.^5,7

Advantages of Using Biorepositories in Kidney Research

Facilitating Biomarker Discovery and Outcome Research

The Translational Research Investigating Biomarker Endpoints (TRIBE) cohort, led by Dr. C. Parikh, has yielded key insights into the detection, prediction, and outcomes of AKI. Through collecting biospecimens from over 7000 patients undergoing cardiac surgery, the TRIBE cohort identified and validated over 20 biomarkers, including neutrophil gelatinase associated lipocalin (NGAL), IL-18, and kidney injury molecule 1,^9,16,17 which can detect AKI earlier than traditional methods, allowing for more timely interventions. The findings show that elevated levels of these biomarkers are associated with a higher risk of AKI and adverse outcomes, including prolonged hospitalization, progression to CKD, and increased mortality.⁹ The urine NGAL results that were first reported in TRIBE pediatric cohort have since been validated, and now urine NGAL is approved for use in pediatric AKI.^10,18–20 In addition, samples from TRIBE biorepository were used in approval of heart-type fatty acid binding protein in Canada and Japan in AKI after cardiac surgery.¹¹ The sample and data biorepository from the TRIBE cohort has enhanced our understanding of AKI pathophysiology, improved risk stratification, and laid the groundwork for future biomarker-targeted therapies and preventive strategies in kidney injury.²¹ Identifying and understanding existing biorepositories in the field of AKI is invaluable as they serve as essential resources for future research. The TRIBE cohort provides a robust foundation for groundbreaking early discovery studies as well as biomarker validation studies, with its extensive collection of urine, blood, and kidney tissue samples from over 7000 patients (Figure 1).

Figure 1.

The resources and opportunities available through the TRIBE biorepository. TRIBE, Translational Research Investigating Biomarker Endpoints.

In addition, the DDS led by Dr. C. Parikh is uniquely positioned as the only study to enroll both deceased organ donors and their matched kidney transplant recipients.^{14,15,22–24} This dual enrollment approach provides an unprecedented opportunity to investigate donor-recipient interactions and their impact on transplant outcomes. A key strength of the study is its collection of donor urine samples, offering novel insights into early biomarkers of kidney injury and function. In addition, the study maintains a rich recipient data repository, enabling comprehensive longitudinal analyses that can drive advancements in precision medicine and transplant care. The DDS biorepository has already enabled important discoveries that highlight its value for advancing precision transplantation. For example, higher levels of tubular repair biomarkers uromodulin and osteopontin measured in deceased donor urine were found to be independently associated with a lower risk of graft failure at 3 years post-transplant. These biomarkers are now being developed to inform organ allocation decisions, with the aim of reducing kidney discard rates and improving graft outcomes.²⁵

Several other cohorts are available as part of the TRIBE biorepository that could be found here: https://tribe.jhmi.edu/Site%20Pages/projects/projects_overview.html.

Supporting Personalized Medicine Approaches

Accelerating Drug Development and Testing

In the past 5 years, vast amount of highly granular single cell or regional molecular data have been generated from preclinical model systems of AKI and from human atlas development efforts that have revealed new pathways and potential markers/targets for different stages of AKI. Existing repository samples can accelerate validation efforts from potential leads from these datasets instead of waiting years to collect these resources.

Biorepositories: Subphenotyping AKI to Advance Research

AKI is a heterogeneous syndrome, and several biologic subphenotypes exist under the overarching clinical diagnosis of elevated serum creatinine.²⁶ These phenotypes may be related to host immune factors and/or insult-specific (ischemic, infectious, toxic) that caused AKI or biologic stages associated with the natural history of the disease. Sanjay Jain and colleagues through KPMP have identified several cell states/molecular subphenotypes in AKI using omics technologies or targeted biomarkers such as the inflammatory phenotype, ongoing subclinical injury phenotype, maladaptive (failed) tubular repair phenotype, heightened or suboptimal response of angiogenesis pathway, and a subgroup of patients with complement activation.^5,27–30 These phenotypes were identified by supervised or unsupervised clustering of transcriptome or soluble biomarkers and linking them to longitudinal outcomes. These subphenotypes present opportunities for therapeutic development by identifying targets from the dominant pathways or stratifying patients enriched with that characteristic to facilitate detection of a response to the targeted therapy. Recent work has identified angiopoietin-based vascular injury and repair phenotypes among patients with AKI, which reflect distinct biologic processes. For example, elevated angiopoietin-2 levels characterize a high vascular injury phenotype, which has been associated with adverse outcomes and represents a potentially targetable pathway. Several angiopoietin-2/Tie2–modulating agents are currently in clinical development, illustrating how biomarker-derived subphenotypes can help define therapeutic targets and guide precision interventions.^31,32

Resources to Empower Early-Stage and Established Investigators

Early-stage investigators (ESIs) often encounter challenges related to limited resources and time constraints.³³ Using existing biobanks can be a great opportunity for these investigators to answer their research questions in a relatively time-effective and cost-effective manner, particularly if applying a new technique or new line of inquiry to these existing samples. TRIBE repository has multiple types of samples (blood, urine, DNA, biopsies) and is linked to clinical longitudinal data with early, late kidney and nonkidney outcomes.¹² This setup provides desired flexibility for ancillary studies and supports all phases of biomarker studies. These studies include identification of new targets by genomics and proteomics, assay development and early translation for markers from preclinical studies, verification of new markers by case control studies and large cohort studies for confirmatory evidence of biomarkers that would lead to biomarker qualification or regulatory approval (Figure 1).^34–37 TRIBE biorepository has supported over 50 ancillary studies, most of them with junior investigators to support their scientific inquiry and career development. The ancillary studies have been enabled by appropriate consents at the time of sample acquisition, informatics associated with the biorepository that allow for efficient selection and retrieval of specific samples, and appropriate deidentification for material transfer agreements.

Similarly, the Washington University KTRC has a wide spectrum of tissue and fluid samples from consented patients for a broad scope of kidney research including multiomics.⁴ Users can leverage reference, AKI, and CKD tissue to test their hypotheses regarding specificity of biomarker of interest across varied clinic-pathologic settings of AKI. This is particularly useful for new or established investigators wishing to validate a new marker, use different tissue preservation methods to optimize an assay or conducting pilot studies for a grant proposal. Over 100 investigators across the globe, including industry, have benefitted from KTRC provided clinical data, tissue, and fluid samples for research in kidney diseases.^7,38–40 Leveraging existing biorepositories while building a smaller but more detailed biorepository with data relevant to a particular research question can also be a successful strategy for ESIs. This powerful approach of using big data provides essential initial validation, while the junior investigator invests time in data collection and more detailed phenotyping of their own biorepository.

Challenges of Building a Biorepository

Before building a biorepository, it is paramount to clearly define its intended users and the specific objectives it is meant to fulfill. Such clarity will help guide both the development process and the allocation of necessary resources.

Consent and Ethical Issues Warranting Consideration

Considering the potential audience and future usage of biospecimens is important when writing the Institutional Review Board and consent process.⁴¹ As new technologies emerge (e.g., spatial transcriptomics), biospecimens can be extremely valuable, but only if the consent is written with flexibility to allow for sample interrogation and sharing in an ethically responsible manner. This concept also applies to the human meta-data that can be extracted from the electronic health record. Broad, permissive consent language offers greater flexibility, while narrowly focused language may restrict biorepository use and limit accessibility beyond an individual's own research. Determining whether the audience is confined to academic investigators or extended to private entities such as industry partners will also affect the consent process which may require explicit language if nonacademic partners will use the biospecimens. It is also recommended that the consent includes language addressing how sequencing data generated from the samples will be shared with the community, as well as whether any genomic results will be returned to the patient.

Logistical Issues and Quality Control: Building a Biorespository

There are logistical challenges in storing both the biospecimens and human data in a manner that preserves their integrity and utility over the years and decades. To build a biorepository, basic infrastructure is needed to maintain high-integrity samples.⁴² An investigator needs storage space for −80°C freezers or liquid nitrogen cryotanks with a reliable backup electrical source, continuous monitoring alarm systems, and necessary ventilation to dispense the generated heat or liquid nitrogen vapors.

To maintain rigor and reproducibility, consistent practices for sample processing and preservation that maintain sample integrity for the desired molecular assays are critical.^1,43 Each biorepository should have standard operating protocols in place. One example of best practices is placing a robust quality assurance and control plan, akin to the one implemented in KPMP, please see https://www.kpmp.org/for-researchers#protocols for specific protocols.⁶ Kidney tissue can be a valuable resource for a biorepository, but this necessitates partnerships with pathologists, surgeons, and other clinicians.⁴⁴ Many molecular assays can potentially be applied to stored samples. Therefore, it is prudent to give careful thought to pre-analytical factors including warm and cold ischemia time, sample perfusate, type of fixative, time from harvest to preservation, time, and stamps on storage conditions. If tissue is transported, then tracking transportation conditions, shipping state, and tissue integrity before assay performance are important variables. Tissue morphology is important, and specimen physical orientation can affect their use for molecular studies (e.g., spatial technologies).⁴⁵ Quality control metrics should be implemented to ensure robust sample processing and assay performance. For repeated assay usage, one should store several blocks or vials of tissue or fluid samples in aliquots that can be repeatedly tested for assay drift or batch effects. Some type of disaster recovery plan is needed for a possible freezer failure. This contingency plan includes identifying personnel to retrieve the samples before they are lost, securing a backup freezer, and prioritizing in advance the samples that require lowest temperatures storage.⁴⁶

In addition to the infrastructure for physical biospecimens, it is equally important to establish an appropriate informatics system for tracking their usage.⁴⁷ Analogous to a financial bank, a biobank must keep track of deposits (i.e., samples going in) as well as withdrawals (i.e., samples coming out). A robust, precise tracking system should enable rapid location of samples by freezer, shelf, and box. Furthermore, linking the samples to specific studies or populations of interest will facilitate ease of access for follow-up analyses. In addition, tracking the sample age and usage can help control quality issues. One should be mindful of the type of software being used as commercially available options have not only a subscription cost but also limited flexibility. Newer technology allows for a decentralized biospecimen tracking system, which enhances data security, scalability, and real-time accessibility across sites, reducing reliance on central repositories.⁴⁷ This system works by using technology to create a secure distributed ledger that records all biospecimens transactions and metadata across multiple sites.

One example of a published biospecimen data management system that supports TRIBE-AKI is the samples inventory management system, a web-based platform for managing the life cycle of biologic samples, mainly urine, DNA and blood, collected as part of multiple clinical studies in the field of nephrology.⁴⁸ In TRIBE, personnel collect samples, store them in freezers, and deliver them to other laboratories as needed. Samples inventory management system tracks and monitors this multifaceted process. The system supports multiple simultaneous users and provides the functionality to manage the data categories which are described in Table 1. The informatics system that is chosen should be cost-effective and facilitate good governance through the generation of reports, location of samples, and connection between samples and studies.

Table 1.

Biospecimen management provided by samples inventory management system

Core Biospecimen Management and Tracking Activities

Specification of biospecimen collection protocols as part of a clinical study (e.g., the tissues to be sampled at each time point, and the number of aliquots for each sample)

Generation of barcoded labels are sent out to collaborating institutions and used to store collected biospecimens (which are then shipped back to our laboratory for analysis)

Recording of samples that are received by our laboratory with bar-code scanning

Tracking of storage location of samples in terms of freezer and sub-locations (e.g., rack, slot, box)

Tracking of samples that are shipped to external laboratories for analysis

Tracking of aliquot consumption, either as part of bulk-shipping for analysis, or dispatching of individual samples to research collaborators

Reporting on aliquots consumed and available (by patient, biospecimen type, and time point); reporting on the status of a freezer sublocation for biospecimen content

Please visit the following website for further information on the samples inventory management system: https://tribe.jhmi.edu/Site%20Pages/biorepository.html.

While this manuscript highlights several key biorepositories, it is not intended to be an exhaustive list; additional important resources—such as Nephropathy in Diabetes, Assessment, Serial Evaluation, and Subsequent Sequelae of AKI, and APOL1 Long-term Kidney Transplantation Outcomes Network—also contribute valuable biospecimen infrastructure for kidney research.^49–51

Maintaining a Successful Biorepository

Both the physical and informatics systems that support a biorepository must be maintained over time.⁵² Institutional buy-in is often necessary to obtain the storage space and initial investment in freezers and personnel costs. Over time, a successful biorepository may help fund itself (e.g., new freezers) through a cost recovery program whereby other users invest in such resource for sample utilization. However, it is imperative to recognize the additional costs for trained personnel including coordinators and technicians.⁵³ Furthermore, for a cost-recovery system not to be prohibitive to individual investigators, an institutional support or subsidy is crucial. The informatics system, particularly if not owned by the user, can be modified and upgraded, which can subsequently affect the workflow and ease of obtaining samples or information. This poses challenges, as the use of biosamples can fluctuate and individual investigators may move, jeopardizing the availability of this precious resource to the community. It is best for the local communities with a common interest or leadership to recognize the value of specimen-based research and encourage a more centrally managed resource; this also has the benefit of not burdening patients who are understandably overwhelmed due to participation in multiple studies.⁵⁴

Health Equity: Are All Populations Represented?

For kidney research to advance equitable care, biorepositories need to reflect the full population spectrum affected by kidney diseases.⁵⁵ This is essential because genetic, environmental, and socioeconomic factors influence disease risk, progression, and response to treatment. However, achieving equitable representation in biorepositories can be challenging. The socioeconomically disadvantaged populations are often underrepresented in research due to barriers such as limited access to health care, language differences, and historical mistrust stemming from past medical experiences. Engaging these communities requires culturally sensitive recruitment efforts, clear communication about the benefits and protections of participating in research, and building trust through transparency and community partnerships.

For example, HuBMAP is committed to including diverse donors with broad representation of factors such as age, sex, race, and ethnicity to create a comprehensive reference atlas. As a show of its dedication to diversity HuBMAP has a donor diversity portal that has visualizations of the diverse enrollment across HuBMAP donors. KPMP developed community advisory boards and cocreated recruitment materials with patients to ensure cultural and linguistic appropriateness. DDS has collaborated with organ procurement organizations to ensure multilingual and culturally sensitive communication strategies with donor families. The VA Million Veteran Program has partnered with Veteran Service Organizations and conducted targeted outreach to Black and Hispanic veterans through community events and VA facilities. These examples illustrate diverse and effective strategies to build trust, improve communication, and support the inclusion of under-represented communities in biorepository research.

Biorepository: Build Your Own or Leverage Existing?

There are several factors that may influence whether it is better to build a biorepository or use an existing database. The most important factors are the investigator's research question and the availability of biobanked specimens to answer the question or whether a new resource needs to be created to answer the question. Other considerations such as funding, institutional support, and personnel availability may also influence the decision.

Pros to Building a Biorepository

A major advantage to building a biorepository is the autonomy and flexibility that comes with having your own biosamples. The types of samples (blood, urine, DNA) and frequency of collection for a biorepository can be dictated by your future research questions in mind.⁵⁶ However, if using someone else's biorepository, the availability and the type of samples available may be more limited. Importantly, when using an existing biorepository, the user has no control over the quality of the biospecimen collection, storage, or the clinical information collected with the biospecimen. If internal quality control methods are not rigorous and documentation about the biospecimens incomplete, then reliance on established biorepositories could result in misinterpreting the data. Building a biorepository has the advantage of control over data quality as well as the amount of relevant clinical information and preanalytical conditions that are needed to answer an investigator's specific research question.

Pros to Using Existing Biorepositories

Using an existing biorepository can save the investigator both the time needed to collect the samples and financial investment in infrastructure and personnel to run and maintain a biobank. This is particularly advantageous if an existing biorepository has the samples available or patient and infrastructure accessible that are well-suited to answer an investigator's scientific question.⁵⁷ If an investigator needs to validate a target identified in preclinical mouse studies or only has short-term biorepository needs, then perhaps, leveraging existing resources is a better approach. For example, the Biobank Renal Transplantation, Leuven, housing bulk-cell and single-cell RNAseq data from serial kidney allograft biopsies, was promptly leveraged to validate the identified dynamic SOX9 activity, which determined regeneration with or without fibrosis, in humans.^58–60 From an ethical perspective, excessive number of biorepositories may be taxing on patients (additional consents) and health care systems without providing added benefit. Working with an existing infrastructure decreases the administrative burden on an individual laboratory and maximizes the utility of patients' donated tissue as samples and data can be used by other investigators even after the completion of an individual's project. Established biorepositories often have existing relationship with multiple providers, thus accelerating collection of samples. Existing biorepositories, particularly if including multiple centers, may also facilitate increased reproducibility of findings with standardized collection methods.

Procedures for accessing samples and data vary across biorepositories and are tailored to each study's governance structure. Investigators interested in using biospecimens or data should contact the principal investigator for the relevant study to initiate a request. Costs are determined on a case-by-case basis and depend on factors such as sample identification complexity, study design, sample volume, and whether additional processing or aliquoting is required before shipment. Given this variability, there is no standardized cost structure.

A key advantage of using existing biorepositories is the substantial time savings compared with initiating new prospective cohorts. For example, the TRIBE-AKI study required approximately 2.5 years to enroll 1200 participants, followed by an additional 3 years of follow-up to capture long-term outcomes—totaling 5–6 years from study launch to the availability of analyzable data.

Timelines for building cohorts can vary significantly depending on funding and resources. For example, during periods of O'Brien Center funding, the KTRC biorepository enrolled approximately 500 patients per year, each with multiple specimens collected. Once established, these repositories offer major efficiencies—saving investigators time required for regulatory approvals, patient recruitment, and molecular processing. For archived material, it is possible to obtain plasma, urine, and biopsy tissue from 50 existing patients in less than 2 months, underscoring the practical advantages of leveraging existing infrastructure for new studies.

The decision-making process for allocating samples from existing biorepositories is multifactorial and tailored to each study's governance and aims. Factors commonly considered include the scientific merit of the proposal, alignment with the parent study's objectives, whether the study aims to validate prior findings or generate new hypotheses, availability of funding, and support of ESIs. Controls are often more readily shared than scarce cases, and when sample availability is limited, proposals that demonstrate strong scientific value and alignment with the parent study are prioritized. While “first come, first served” may apply when inventory is sufficient, prioritization mechanisms ensure that high-impact studies are given preference in the setting of scarcity.

Ultimately, there is a balance between the effort involved in building a biorepository versus the autonomy and flexibility of designing a biorepository that can best answer a scientific question. Similarly, there is also tradeoff between biospecimen quantity (augmented by existing biorepositories) and quality (controlled when building a repository). One approach may be to lever large, established biorepositories (e.g., Million Veteran Program) and complement this with building a biorepository that has fewer people but more detailed phenotyping (e.g., proteomics, insulin glucose clamps).

Summary of Key Points and Future Directions

In summary, biorepositories are powerful resources to advance AKI-related research. They facilitate (1) biomarker discovery, (2) subphenotyping of AKI into mechanistically common groups that may help guide future clinical trials, and (3) validation of preclinical targets with human samples. Challenges posed by biorepositories include designing consent with careful consideration of future usage, ensuring proper quality control measures, implementing tracking systems for biospecimens and related data, securing funding for the maintenance and expansion of a biorepository, and achieving equitable representation in banked biospecimens. For most investigators, using existing biorepositories such as those listed in Table 2 will be preferred over creating a new biorepository. However, the flexibility afforded by building a biorepository may be attractive to some investigators.

Table 2.

Summary of preexisting biorepositories in kidney disease

Biorepository	Institution/Organization	Types of Samples Collected	No. of Participants	Patient Population	Primary Research Focus	Availability for External Researchers
HuBMAP7	WashU in St. Louis (via KTRC), funded by NIH common fund initiative involving multiple research institutions	Healthy human tissues from various organs, including uninvolved kidney tissue from tumor nephrectomy or deceased donors	Ongoing collection	Donors representing diverse demographics	Creating a comprehensive, high-resolution atlas of all human cells to understand tissue organization and function	Yes (molecular data and resources are publicly available through the HuBMAP data portal and tissue through KTRC); https://research.washu.edu/core-facilities/KTRC/
DDS biorepository	Multiple institutions, including Yale University and Johns Hopkins University	Deceased donor urine samples, recipient blood samples	>1000 deceased donors and their matched kidney recipients	Deceased kidney donors and their transplant recipients	Evaluating the impact of donor AKI and novel biomarkers on transplant outcomes, including graft function	Yes, data and samples are available on request https://www.hopkinsmedicine.org/research/labs/c/chirag-parikh-lab
KPMP5,6	Multicenter initiative funded by the NIH/NIDDK, including multiple recruitment, tissue interrogation and central hub and data management center	Kidney tissue biopsies, blood derivatives, urine, clinical data	Ongoing recruitment, over 600 participants	Patients with AKI and CKD including diabetic kidney disease, hypertensive nephropathy and healthy living donor kidney biopsies	Molecular and cellular characterization of kidney disease to develop precision medicine approaches	Yes (data and samples are available through KPMP's application process), info@kpmp.org; https://www.kpmp.org/
KTRC	WashU in St. Louis	Serum, urine, tissue, plasma, white blood cell pellets, DNA, frozen biopsies, FFPE tissue	Over 4000 patients (adults and children)	Patients with various kidney diseases and reference kidney tissue samples	Translational research in kidney diseases, including biomarker discovery and single-cell multiomics	Yes (through collaboration and appropriate regulatory approvals and a cost recovery process), https://research.washu.edu/core-facilities/KTRC/
TRIBE-AKI9–11	Multicenter study including Yale University, University of California San Francisco, University of Toronto and others	Blood, urine, clinical data	7588 participants	Cardiac surgery patients at risk for AKI	Identification and validation of biomarkers for early detection, prognosis, and risk stratification of AKI	Yes (data and samples are available through TRIBE's application process); https://tribe.jhmi.edu/Site%20Pages/about.html
VA Million Veteran program	US Department of VA	Blood samples for DNA extraction; health data from EHRs and self-reported surveys	Over one million veterans enrolled	Veterans from diverse backgrounds across the United States	Investigating how genes, lifestyle, military experiences, and exposures affect health and disease to improve veteran health care	Yes, VA-affiliated researchers can apply for access; https://www.research.va.gov/mvp/
Vanderbilt BioVU Alliance of Genetic Discovery	Vanderbilt University Medical Center	DNA and plasma available	DNA available in 348,000 samples and 250,000 whole genome sequencing	Population of the US Southeast region	To understand genetic and environmental factors determinants of health. A wealth of health data in the EHR	Yes, VUMC-affiliated researchers can apply for access; https://victr.vumc.org/biovu-description/

DDS, deceased donor study; EHR, electronic health record; FFPE, formalin fixed paraffin embedded; HuBMAP, Human Biomolecular Atlas Program; KPMP, Kidney Precision Medicine Project; KTRC, Kidney Translational Research Center; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIH, National Institutes of Health; TRIBE-AKI, Translational Research Investigating Biomarker Endpoints in AKI; TRIBE, Translational Research Investigating Biomarker Endpoints; VA, Veterans Affairs; VUMC, Vanderbilt University Medical Center; WashU, Washington University.

Biorepositories have already accelerated research, but the full potential of these resources has not been fully realized. Future efforts should focus on optimization and standardization of biospecimen collection and preservation such that a wide range of macromolecular studies could be performed. The more data investigators can extract from samples (e.g., cell free nucleic acids), the more effectively patients' samples can advance our understanding of AKI mechanisms. Standardizing processing methods across collections, although challenging, would accelerate collaborations between universities and facilitate the use of artificial intellegence methods, for example, on spatial technologies, and reduce technical variations. KPMP has guidelines that could help this standardization process.⁶ By nature, multiple users may use samples from the same established biorepository. Therefore, inclusion of the source and original deidentified ID of the biorepository used will be important to understand if data from a given participant is published multiple times, which is critical for meta-analyses, establishing reproducibility and obtain multimodal identity of a disease process. Finally, the ability to incorporate biorepositories to the electronic health record or national registries has the potential to magnify the information available to investigators.

Importantly, we would like to acknowledge the invaluable contributions of the patients who generously provided biospecimens for these biorepositories. Their participation plays a crucial role in advancing the understanding of kidney disease and fostering discoveries that may improve future patient care. The authors recognize the trust placed in this type of research and remain committed to conducting rigorous and meaningful scientific investigations to honor that commitment and engage patients actively in biomedical research.⁶¹

Disclosures

Disclosure forms, as provided by each author, are available with the online version of the article at http://links.lww.com/KN9/B406.

Author Contributions

Conceptualization: Amandeep Bajwa, Leslie S. Gewin, Sherry G. Mansour.

Data curation: Leslie S. Gewin.

Investigation: Leslie S. Gewin.

Methodology: Amandeep Bajwa, Leslie S. Gewin, Adriana Hung, Sanjay Jain, Sanjeev Kumar, Sherry G. Mansour, Mark Okusa, Chirag Parikh.

Resources: Adriana Hung, Sanjay Jain, Sanjeev Kumar, Sherry G. Mansour, Mark Okusa, Chirag Parikh.

Writing – original draft: Leslie S. Gewin, Sherry G. Mansour.

Writing – review & editing: Amandeep Bajwa, Leslie S. Gewin, Adriana Hung, Sanjay Jain, Sanjeev Kumar, Sherry G. Mansour, Mark Okusa, Chirag Parikh.

Funding

L.S. Gewin: NIH (R01DK108968). A. Hung: US Department of Veterans Affairs (BX03425 and CX001897). S. Jain: NIH (U54DK134301, P50DK133943, and 2U01DK114933). S. Kumar: NIH (R01DK118265) and OneLegacy Foundation. C. Parikh: NIH (U54DK137331, U01DK114866, U01DK129984, and R01DK093770). S.G. Mansour: NIH (K23DK127154) and AHA (23SCISA11431).