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BSCD Summer Undergraduate Research Fellowship in Pathophysiology, Biology, and Bioenergetics of Kidney Diseases - 2026

The University of Chicago Medicine & Biological Sciences
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This internship is part of the University’s Jeff Metcalf Internship Program. Click here to learn more about the program, its benefits, and the UChicago community of supporters. By applying to this internship, you agree to follow the Student Recruiting Guidelines.

Please make sure that if selected for an interview, you communicate to your prospective host organization/employer where you will be physically located during the internship, as your location may affect your (or your host organization/employer’s) ability to pursue this opportunity.   

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This role is not benefits-eligible.

Fellowship Award Amount: $5,500

 

  • Please complete the BSCD Fellowship Preference Form, which is required if you're applying for this fellowship:  
  • Please download the Educational Assignment form from the attachments section. Complete the form to the best of your ability. If applicable, you may also have your faculty mentor complete their designated portion. Finally, upload the completed form along with your other application materials.

 

Summer Undergraduate Research Fellowship in Pathophysiology, Biology, and Bioenergetics of Kidney Diseases 

Summer Research Program Description:

The Summer Undergraduate Research Fellowship in Pathophysiology, Biology, and Bioenergetics of Kidney Diseases takes advantage of the breadth and depth of the Departments of Medicine, Pathology and Radiology within the Sections of Nephrology, Genetics, Oncology and Physics. With a focus on common kidney disorders (Dr. Louis Baeseman, Dr. Rita McGill), access to care with end stage kidney disease (Dr. Louis Baeseman. Dr. Samantha Gunning, Dr. Rita McGill, and Dr. Bea Concepcion), access to renal replacement therapy (Dr. Louis Baeseman, Dr. Samantha Gunning, Dr. Rita McGill and Dr. Bea Concepcion), genetic risk factors for kidney disease in African American patients (Dr. Mohammed Rafey and Dr. Chapman), autosomal dominant polycystic kidney disease (ADPKD) (Drs Chapman, Chen, Faubert and Hanlon), nephrolithiasis (Drs Worcester and Prochaska), metabolomic/proteomic/transcriptomic analyses (Drs Chapman, Chen and Hanlon) , and kidney imaging involving radiomics, texture analysis and artificial intelligence (Drs Armato, Chapman and Kremer) summer fellows will learn about the kidney ‘s role in homeostasis and regulation/handling of key components of metabolism, mechanisms of urinary acidification, impact of the microbiome, bioenergetic regulation by the kidney in general and as it relates to sleep disorders, and imaging and textural analyses including magnetic resonance fingerprinting. In addition, fellowship students will be able to work directly with clinicians who are developing new models to improve access to renal replacement therapy (home dialysis and transitional kidney care).These programs will provide summer fellowship students with an introduction to the field of renal physiology, circadian biology, medical physics and cellular biology including proteomic and transcriptomic expression at the single cell level of renal tubular epithelial cells in the context of common kidney disorders as well as working with patients undergoing renal replacement therapy. This program is a small group experience (2-3 students/lab) with the opportunity for active and individual mentoring. The curriculum includes: 1) Attendance and participation in daily mid-day 50 minute lectures reviewing components of kidney function, physiology and molecular genetics, and metabolism with a focus on ADPKD, nephrolithiasis, metabolism and disorders of circadian biology with the opportunity to discuss these topics with experts in the field 2) Attending weekly academic conferences within the Section of Nephrology held at 4 pm on Thursdays and noon Fridays 3) Participation in the assigned mentor lab with daily lab work focusing on the student project and general meetings held at least twice a week 4) Participation in the summer principals of medical physics and radiomics (Drs. Armato and Kremer) 5) Shadowing expert clinicians in their weekly outpatient clinics on Tuesdays and Wednesdays (Drs Prochaska, McGill, Baeseman, Gunning and Chapman) to observe patients with underlying kidney problems that are the focus of the research studies in their respective labs 6) Observe and potentially participate in human subject research including overnight sleep studies on the Clinical Research Center which is a research-only inpatient and outpatient ward studying research participants suffering from chronic kidney disease.  There is an every other week seminar held during the fellowship, with presentations of ongoing work by the summer fellows with their faculty mentors. This seminar is led by the Chief of Nephrology, Dr. Arlene Chapman along with the faculty mentors. Students will briefly discuss the overall progress in their lab and highlight his/her own summer project. This will give the students the opportunity to present their progress to each other throughout the fellowship.  This will be a wonderful opportunity for this summer’s fellowship cohort. Overall, it is expected that the students in this program will be deeply immersed in their projects during the summer and as time permits throughout the rest of the academic year.

 

Requirements:

1. Required skills:

- Excellent written, verbal communications and analytical skills

- Ability to work as a team member

- Ability to manage time efficiently, multi-task and prioritize

- Self-directed and able to work independently with faculty support

- Proficient computer skills, including Microsoft Office Suite

 

2. Required Materials

- Resume or CV

- Cover Letter/Statement of Interest

- Please complete the BSCD Fellowship Preference Form, which is required if you're applying for this fellowship:  

https://bscd-fellowship-2026.netlify.app/

- Please download the Educational Assignment form from the attachments section. Complete the form to the best of your ability. If applicable, you may also have your faculty mentor complete their designated portion. Finally, upload the completed form along with your other application materials.

 

Please submit all materials as PDF files. 

NOTE: Students should identify the project(s) in which they are interested in their Cover Letter / Statement of Interest. Fellowship recipients will be paired with a faculty mentor based on availability.

 

Application Expiration Date:

Applications must be submitted by March 20, 2026.  

Interviews:

Interviews may be requested.

Potential Mentors:

  1. Arlene Chapman, MD, Professor of Medicine, Chief of Nephrology
  2. Peili Chen, PhD, Research Associate 
  3. Erin Hanlon, PhD, Research Associate
  4. Elaine Worcester, MD, Professor of Medicine
  5. Megan Prochaska, MD, Assistant Professor of Medicine
  6. Dr. Sam Armato, Professor of Radiology
  7. Dr. Linnea Kremer, Staff Scientist, Post Doctoral Fellow
  8. Dr. Louis Baeseman, Assistant Professor of Medicine
  9. Dr. Bea Concepcion, Professor of Medicine
  10. Dr. Samantha Gunning, Assistant Professor of Medicine
  11. Dr. Mohammed Rafey, Assistant Professor of Medicine
  12. Dr. Bea Concepcion, Professor of Medicine

 

Description of Projects:

Project # 1:

Title: Targeting Exosomes and PKD1/PKD2 signalling  in ADPKD

Mentors: Arlene Chapman, MD, Peili Chen, PhD, Dr. Brian Faubert, Departments of Medicine and Molecular Biology. Drs. Chapman, Faubert, and Chen will be available and committed to fully mentor students, including guidance about overall career development.

 

Project description

Autosomal dominant polycystic kidney disease (ADPKD), the most common hereditary kidney disease, is caused by mutations in the PKD1 or PKD2 gene which encode polycystin-1 and polycystin-2 transmembrane heterodimer proteins. Multiple signaling pathways are affected by mutated polycystin1 and polycystin2, including primary ciliary signaling and Ca2+/cAMP cascade that contribute to the abnormal proliferation of epithelial cells and cyst formation in ADPKD. Initiated in early childhood, progressive enlargement of kidney cysts damages kidney structure and function, eventually leading to kidney failure typically in the 5th to 6th decade of life. Despite promising results from recent studies and trials, therapies that cure or slow the progression of disease are limited. The slow progressive nature of ADPKD makes it difficult to diagnose and treat at early stage as kidney function or estimated glomerular filtration rate (eGFR) is normal for decades. Height corrected total kidney volume (htTKV), an accurate and reproducible FDA approved prognostic imaging biomarker can increase several-fold prior to loss of kidney function and represents kidney cyst burden and epithelial proliferation. 

 

Increasing understanding of the signaling and pathological derangements characteristic of ADPKD has revealed marked similarities to those of cancers at the cellular and molecular level. ADPKD shares most of cancer hallmarks including sustained proliferative signaling, evasion of growth suppressors, induction of angiogenesis, deregulation of cellular energetics, tumor promoting inflammation, genomic instability and mutation and abnormally reprogrammed metabolism. Metabolic reprogramming provides energy and substrates that is necessary to support tumor growth, survival, immune evasion, and metastasis. 

 

We have demonstrated comprehensive abnormalities in multiple metabolic pathways in our studies in urine and plasma in ADPKD patients with normal kidney function. Levels of histidine metabolites correlate measures of disease severity including cyst burden (htTKV) and kidney function (eGFR). In ADPKD cyst fluids, concentrations of all amino acids, except for glutamine and proline, are elevated compared to those in plasma and urine, with an accumulation of amino acids on the apical surface of cystic epithelia. Importantly urinary exosomes from primary cilia carry important polycystin 1/polycystin 2 cargo to renal tubular epithelial cells downstream that impact cellular metabolism and new cyst formation.

 

Through prior Summer Undergraduate Research Fellowship programs, iPSCs (pluripotent stem cells) have been derived from urinary epithelial cells from PKD1 and PKD2 patients. These cells are exposed to patient derived urinary exosomes to determine if there are different responses based on the pathogenic variant of the PKD genes. We also differentiate these iPSCs to human kidney organoids and human kidney tubuloids. These models will be used to address the differential impact of amino acid bioavailability, exposure to hypoxia and hypertonicity, exposures to urinary exosomes, and features to the microenvironment in the kidney. Single cell rnaseq of primary human cystic epithelia will be performed to assess differential regulation of cystic epithelial proliferation..

 

Specific Aims

To determine the effects of loss of the PKD1 or PKD2 genes on IPSC behavior, cystic epithelial response to urinary exosomes, transport and flux.

 

Approach and Methods

1. To investigate  amino acid homeostasis by evaluation of histidine transporters in small intestinal epithelia, hepatocyte and renal cystic (PKD1 or PKD2 mutations) compared to normal non-cystic epithelia. Expression and function of histidine transporters will be studied in tissues and specific cell types including resident macrophages, fibroblasts, cystic and non-cystic epithelial cells harvested from genetically modified mice using immunostaining and affinity assays.

2. To characterize histidine and its metabolic flux into different pathways in PKD1 and PKD2 knockdown cells established by siRNA using stable isotopic 13C-histidine.

3. To define difference in energy production from histidine in PKD1/PKD2 cells compared to normal non-cystic controls under controlled environmental conditions including cell starvation, hypoxia, histidine and glutamine deprivation.

4. To determine metabolic flux of isotopically labelled glucose, lactate and glutamine in human cystic epithelial cells.

4. To utilize human iPSCs derived from urinary epithelial cells to develop kidney organoids and tubuloids to test differences in amino acid bioavailability, hypoxia and hypertonicity as critical regulators of cyst proliferation and growth as well as determining single cell transcriptomic changes.

 

Project # 2: Dr. Sam Armato (Department of Medical Physics), Dr. Arlene Chapman (Section of Nephrology) and Dr. Linnea Kremer, (Department of Medicine)

Title: The implementation of AI models in tasks of predicting kidney function decline and automated kidney and cyst segmentation in autosomal dominant polycystic kidney disease using novel quantitative and conventional MRI techniques

Mentors: Linnea Kremer, Sam Armato, Arlene Chapman

 

Project Description

Currently, height-corrected total kidney volume (htTKV) is an FDA approved biomarker for monitoring autosomal dominant polycystic kidney disease (ADPKD) progression, using height-corrected total kidney volume, age and gender as a measure of disease severity. Although this method has been crucial monitoring ADPKD patients, htTKV alone does not capture quantifiable data such as non-cystic kidney tissue which is known to be damaged by the adjacent cysts. Radiomics is an emerging field of translating medical images into quantitative, mineable data using image features for underlying biological information. The implementation of novel artificial intelligence (AI) models, such as deep learning models for segmentation, and new imaging biomarkers, such as cyst and parenchymal characteristics, to enhance risk stratification in ADPKD has been studied in part. The implementation of AI models using novel magnetic resonance fingerprinting (MRF) for quantitative MRI with conventional qualitative MRI techniques for diagnosis, prognosis, and assessment of disease progression in ADPKD is the focus of this research work at the University of Chicago under Drs. Chapman, Armato, and Kremer. 

 

There are two major applications of AI models that are the focus of this work. The first involves leveraging deep learning architectures, specifically generative adversarial networks (GANs) and long short-term memory networks (LSTMs), to predict kidney function decline using longitudinal imaging. While most current ADPKD studies rely on a single imaging time point, this project will investigate how multi-timepoint imaging can be optimally utilized in autosomal dominant polycystic kidney disease (ADPKD) to improve patient outcomes and support personalized treatment planning. Although LSTM networks have been successfully applied in breast cancer to predict malignant tumor progression using temporal imaging data, comparable work in ADPKD remains limited. Our lab is currently exploring the use of hand-crafted radiomic features within LSTM models, and the goal of this summer research project is to expand this effort by comparing traditional radiomic feature extraction with deep learning–based radiomic extraction integrated into LSTM architectures. In parallel, GANs will be used to simulate realistic longitudinal imaging data. Applying GAN models to T1-weighted and T2-weighted MR images of ADPKD patients will enable the generation of predicted future MR images, supporting the forecasting of cyst formation and growth. This work aims to advance imaging biomarkers and deepen our understanding of tissue-level differences among ADPKD patients.

 

Our recent pilot study demonstrated strong discrimination between ADPKD patients and healthy volunteers using radiomic features derived from the non-cystic kidney parenchyma on MRF-based quantitative T1 and T2 maps. These findings suggest that early alterations in the non-cystic parenchyma can be detected using radiomic signatures, offering potential for earlier diagnosis and risk stratification. The second major research focus of our group is the development of AI models for automated kidney and cyst segmentation from MRF-based quantitative maps, as the pilot study utilized manual segmentations. In addition to these research opportunities, the Committee on Medical Physics will offer a summer course covering the physics of medical imaging.

 

Specific Aims

1.           Compare hand-crafted radiomic feature extraction to deep-learning–derived features in LSTM models for predicting kidney function decline in ADPKD.

2.           Develop an open-source GAN–LSTMN framework to simulate T1-weighted and T2-weighted MRI in ADPKD using the HALT-A PKD dataset.

3.          Identify the optimal segmentation model for automated kidney and cyst segmentation using novel MRF-derived T1 and T2 quantitative maps.

 

Approach and Methods

1.          Utilize open-source deep learning models (i.e., LSTMs) using open-source coding software, such as python, and MATLAB computing software.

2.          Build a GAN model using architecture from published literature using python for GAN-based MRI simulation. 

3.          Compare and quantify the performance of kidney and cyst segmentation methods on downstream classification tasks (i.e., healthy versus ADPKD) using MRF T1 and T2 maps.

 

Skills learned

Fundamental principles of MRI physics, coding, data/statistical analysis, MRI characteristics of ADPKD

Project # 3:

Title: Mechanisms of stone formation in Patients with Calcium Kidney Stone Disease

Mentors: Elaine Worcester, MD, Luke Reynolds, MD, Megan Prochaska, MD, Anna Zisman, MD. Departments of Medicine and Surgery. Drs. Worcester, Reynolds, Zisman and Prochaska will be available and committed to fully mentor the students, shadowing in outpatient clinic and guidance about overall career development.

 

Project Description

Diet sodium and acid intake strongly affect mineral metabolism and risk for kidney stone formation. Acid loads raise urine calcium losses, saturating urine with stone forming calcium salts, and foster bone mineral loss. The effects are most severe in those people with inherited hypercalciuria, a polygenic trait that makes calcium balance and urine calcium loss abnormally responsive to both salt and acid load. We have found that patients who make calcium phosphate stones, and women who make calcium oxalate stones, have abnormalities of acid-base status, compared to same-sex normal subjects. We have also discovered differences in acid-base handling that involve both gastrointestinal system and kidney in normal men and women. The group presently studies mechanisms for kidney stone formation. 

 

A full understanding of acid-base balance requires a complete accounting for all renal acid excretion, which is not obtainable from standard urine measurements. In order to better understand the abnormalities we have seen in various types of stone formers, as well as the differences in acid-base handling between normal men and women, we have added novel measurements of urine anion excretion that are the effectors of acid production from diet. We are studying these anions in response to altered diet sodium and alkali, in both types of calcium stone formers and normal subjects. 

  

Specific Aims

  1. Identify differences in metabolic syndrome parameters and visceral fat content between kidney stone patients and controls
  2. Identify how differences in metabolic syndrome parameters contribute to changes in urine composition 

 

Approach and Methods

  1. Use measured serum markers of insulin resistance, lipid levels and visceral fat content to compare differences in metabolic syndrome in stone formers and controls 
  2. Use urine markers of stone formation and acid and alkali balance to in stone formers and controls to understand how metabolic syndrome contributes to differences in stone formation risk

 

 

APOL1 Patient Registry – Summer Undergraduate Research Initiative

 

Purpose: To establish a query-ready APOL1 patient registry within the RedCap database managed by the University of Chicago. This registry will serve as a critical resource for clinical research, outcome studies, and personalized care pathways for patients with APOL1-associated kidney disease.

Project Scope & Student Involvement:
During the summer research term, undergraduate students will contribute to this foundational effort under the direct supervision of Dr. Arlene B. Chapman, MD, and Dr. Mohammed A. Rafey, MD, of the Nephrology Section, Department of Medicine. Their work will be integral to the registry's creation and will encompass:

  1. Retrospective Data Identification: Using EHR tools to identify patients who have undergone APOL1 genetic testing.
  2. Structured Data Abstraction: Extracting and organizing de-identified clinical data (e.g., eGFR, albuminuria, medications, comorbidities) into a standardized database template for storage in the RedCap database managed by the University of Chicago.
  3. Data Quality Assurance: Performing validation checks to ensure accuracy, consistency, and completeness.
  4. Training: Students will receive training on APOL1 genetics, data privacy (HIPAA), and clinical research ethics.

Expected Outcomes & Benefits:

  • For Research: Creates a high-quality data asset to support grant applications and studies on APOL1's role in kidney disease progression and risk modification.
  • For Patient Care: Lays the groundwork for precise, genetics-informed risk assessment and future precision medicine interventions.
  • For Students: Provides hands-on experience in clinical informatics, genetic medicine, and responsible research practices.

Scientific Rationale & Context:
To our knowledge, the University of Chicago Medicine is one of the few medical centers in the United States where patients routinely undergo APOL1 testing. This registry addresses a critical need for longitudinal data on APOL1-associated kidney disease. APOL1 high-risk variants (found predominantly in people of African ancestry) confer a significantly elevated but variable risk:

  • Disease Risks: Hypertension-attributed kidney failure (7–10x higher), FSGS (17–89x higher), HIV-associated nephropathy (29–89x higher), and general CKD (2–4x higher).
  • The Protective M1 Variant: Recent research identifies the p.N264K ("M1") variant as a key genetic modifier. In individuals with G2-containing high-risk genotypes, M1 provides substantial protection:
    • ~57% reduction in CKD risk and ~81% reduction in ESKD risk.
    • For FSGS, nearly 100% risk reduction in G2/G2 carriers and 86% reduction in G1/G2 carriers.
  • Progression Data: A 2023 study found individuals with high-risk APOL1 variants experience faster kidney function decline (eGFR loss of 6.55 vs. 3.63 ml/min/1.73 m²/year), an ~8-year earlier onset of kidney failure (age 45 vs. 54), and a 1.58-fold higher risk of kidney failure.

Registry's Unique Opportunity:
Current studies are largely cross-sectional. This registry will enable the longitudinal tracking needed to:

  • Establish genotype-specific disease progression curves (G1/G1, G1/G2, G2/G2, G2-M1).
  • Identify factors that differentiate rapid from slow progressors.
  • Clarify the clinical phenotype of single-allele (heterozygous) carriers.
  • Inform clinical reclassification—individuals with G2-M1 genotypes may be counseled as "non-high-risk," impacting care and transplant decisions.

Compliance & Supervision: The project will operate under an approved IRB protocol. Students will complete all required training (CITI, HIPAA) and receive close mentorship from faculty and research staff.

Ultimate Goal: To launch a living registry that enhances our institution's nephrogenetics research capabilities while offering a meaningful, educational research opportunity for undergraduates.

 

References: