About

Dr. Whitney Besse is an Assistant Professor of Medicine in the Department of Internal Medicine, Section of Nephrology at Yale School of Medicine. Her research interests focus on genetic kidney diseases, particularly polycystic kidney disease, utilizing genetic approaches to identify novel disease genes for dominantly inherited polycystic kidney and liver diseases. She employs in vitro and animal models to investigate disease gene mechanisms, contributing to the understanding of how the central PKD protein, Polycystin-1, matures through the endoplasmic reticulum. Her work has identified and investigated multiple genes, advancing knowledge of disease pathways and mechanisms. Dr. Besse's active research program involves recruiting patients with genetically unresolved polycystic kidney and liver diseases or other inherited kidney diseases for gene and pathway discovery, with the goal of translating genetic findings into molecular biology investigations that can lead to better understanding of disease mechanisms and potential treatment targets.

Research topics

• Biology
• Medicine
• Genetics
• Pathology
• Bioinformatics
• Computational biology
• Internal medicine
• Endocrinology
• Intensive care medicine

Selected publications

• Scoping Review of Global Kidney Genetics Clinic Models and Outcomes

  Kidney International Reports · 2026-05-01

  articleOpen access
  PublisherDOI

• P615: Solving the unsolved: HiFi long-read sequencing reveals hidden structural variants in ADPKD

  Genetics in Medicine Open · 2026-01-01

  articleOpen access

  cholesterol measurements recorded in the EHR.Of 20 individuals evaluated for ASCVD, ten (50%) demonstrated evidence of disease, including coronary artery calcification, aortic valve sclerosis, carotid artery plaque or thickening, or infarct. Conclusion:This study expands the limited literature by demonstrating that multiple different heterozygous LP/P LDLRAP1 variants, in the absence of pathogenic variants in other hypercholesterolemia genes, co-occur with elevated LDL-C, hypercholesterolemic pharmacotherapy, signs of ASCVD, and a positive family history of elevated LDL-C and/or ASCVD.These results are supportive of a role for LDLRAP1 haploinsufficiency in hyperbetalipoproteinemia and imply that heterozygous individuals should be prompted to have their cholesterol measured and managed accordingly.Furthermore, consideration should be given to include LDLRAP1 in Tier 1 genetic screening for hypercholesterolemia.

  PublisherOA PDFDOI

• KDOQI US Commentary on the KDIGO 2025 Clinical Practice Guideline for the Evaluation, Management, and Treatment of Autosomal Dominant Polycystic Kidney Disease (ADPKD)

  American Journal of Kidney Diseases · 2026-03-19 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• Co-occurrence of Heterozygous Variants in PKD1 and ALG9 in a Patient With Early-Onset ESKD: A Case Report

  Kidney International Case Reports · 2026-03-01

  articleOpen access
  PublisherDOI

• Optimizing next-generation sequencing for genetic diagnosis in autosomal dominant polycystic kidney disease

  Genetics in Medicine · 2026-02-04

  articleSenior author
  PublisherDOI

• PERADIGM: Phenotype Embedding Similarity-based Rare Disease Gene Mapping

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-04-07 · 1 citations

  preprintOpen access

  Identifying genes associated with rare diseases remains challenging due to the scarcity of patients and the limited statistical power of traditional association methods. Here, we introduce PERADIGM (Phenotype Embedding Similarity-based Rare Disease Gene Mapping), a novel framework that leverages natural language processing techniques to integrate comprehensive phenotype information from electronic health records for rare disease gene discovery. PERADIGM employs an embedding model to capture relationships between ICD-10 codes, providing a nuanced representation of individual phenotypes. By utilizing patient similarity scores, it enhances the identification of candidate genes associated with disease-specific phenotypes, surpassing conventional methods that rely on binary disease status. We applied PERADIGM to the UK Biobank dataset for three rare diseases: autosomal dominant polycystic kidney disease (ADPKD), Marfan syndrome, and neurofibromatosis type 1 (NF1). PERADIGM identified additional candidate genes associated with ADPKD-related and Marfan syndrome-related phenotypes, some of which are supported by existing literature, and demonstrated enhanced signal detection for NF1-specific phenotypes beyond traditional methods. Our findings demonstrate the potential of PERADIGM to identify genes associated with rare diseases and related phenotypes by incorporating phenotype embeddings and patient similarity, providing a powerful tool for precision medicine and a deeper understanding of rare disease genetics and clinical manifestations.

  PublisherOA PDFDOI

• Optimizing Next-Generation Sequencing for Genetic Diagnosis in ADPKD

  Journal of the American Society of Nephrology · 2025-10-01

  articleSenior author
  PublisherDOI

• PERADIGM: Phenotype embedding similarity-based rare disease gene mapping

  PLoS Genetics · 2025-12-18

  articleOpen access

  Identifying genes associated with rare diseases remains challenging due to the scarcity of patients and the limited statistical power of traditional association methods. Here, we introduce PERADIGM ( Phenotype Embedding similarity-based RAre DIsease Gene Mapping), a novel framework that leverages natural language processing techniques to integrate comprehensive phenotype information from electronic health records for rare disease gene discovery. PERADIGM employs an embedding model to capture relationships between ICD-10 codes, providing a nuanced representation of individual phenotypes. By utilizing patient similarity scores, it enhances the identification of candidate genes associated with disease-specific phenotypes, surpassing conventional methods that rely on binary disease status. We applied PERADIGM to the UK Biobank dataset for three rare diseases: autosomal dominant polycystic kidney disease (ADPKD), Marfan syndrome, and neurofibromatosis type 1 (NF1). PERADIGM identified additional candidate genes associated with ADPKD-related and Marfan syndrome-related phenotypes, some of which are supported by existing literature, and demonstrated enhanced signal detection for NF1-specific phenotypes beyond traditional methods. Our findings demonstrate the potential of PERADIGM to identify genes associated with rare diseases and related phenotypes by incorporating phenotype embeddings and patient similarity, providing a powerful tool for precision medicine and a deeper understanding of rare disease genetics and clinical manifestations.

  PublisherDOI

• Emerging Therapies in Autosomal Dominant Polycystic Kidney Disease

  Kidney360 · 2025-12-12 · 1 citations

  articleOpen access

  Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder and a leading monogenic cause of kidney failure. Reduction or loss of polycystin-1 (PC1) and polycystin-2 (PC2) function disrupts ciliary calcium signaling, elevates cyclic AMP (cAMP), reprograms cellular metabolism, and activates proliferative cascades that drive cyst expansion. Tolvaptan, a vasopressin V2 receptor antagonist, established cAMP modulation as a disease-modifying strategy but is limited by aquaretic effects and hepatotoxicity risk. This review highlights emerging therapeutic strategies in clinical trial development that extend beyond vasopressin antagonism. Gene-directed therapies aim to restore polycystin dosage, including anti-miR-17 oligonucleotides (e.g., farabursen) and pharmacochaperones that rescue misfolded PC1 and restore trafficking in select PKD1 missense variants (e.g., VX-407). Paracrine signaling can be modulated with anti-pregnancy-associated plasma protein A (PAPP-A) antibodies that reduce insulin-like growth factor-1 (IGF-1) bioavailability in cystic microenvironments. Metabolic reprogramming is targeted by agents such as metformin, bempedoic acid, GLP-1 receptor agonists, and structured dietary interventions. Sodium-glucose cotransporter 2 (SGLT2) inhibitors hold theoretical promise but await definitive results from ongoing trials. A novel cAMP-lowering strategy via phosphodiesterase-4 (PDE4) activation is advancing toward clinical testing. Looking ahead, gene therapy and genome editing offer the potential to raise polycystin levels above the threshold for cystogenesis, although challenges in vector capacity, kidney-specific delivery, and durability remain. Artificial intelligence (AI)-guided discovery, coupled with human organoid platforms, is accelerating therapeutic repurposing and rational combination design. Collectively, these advances signal a transition toward a layered, mechanism-guided framework in which vasopressin blockade is integrated with metabolic, other signaling, and genotype-specific therapies. As biomarkers and risk stratification tools mature, ADPKD management is poised to become increasingly precise, tolerable, and effective.

  PublisherDOI

• Genetic Analysis of Severe Polycystic Liver Disease in Japan

  Kidney360 · 2024-05-01

  letterOpen accessCorresponding

  Key Points Among patients with severe polycystic liver disease (PLD) (height-adjusted total liver volume of <1800 ml/m), PKD2 variants were found in 34%. Three patients with PKD1 or PKD2 variants are reported with severe PLD but normal-sized kidneys (hTKV of < 250 ml/m). Background Polycystic liver disease (PLD) is present in most patients with autosomal dominant polycystic kidney disease (ADPKD). PLD can alternatively be found with few, if any, kidney cysts as a diagnosis of isolated PLD (autosomal dominant PLD [ADPLD]). Several genes are identified as causative for this spectrum of phenotypes; however, the relative incidence of genetic etiologies among patients with severe PLD is unknown. Methods Patients with ADPKD or ADPLD having severe PLD defined as height-adjusted total liver volume (hTLV) >1800 ml/m were recruited. Subsequent clinical care was followed. Genetic analysis was performed using whole exome sequencing. Results We enrolled and sequenced 49 patients (38 women, 11 men). Pathogenic or suspected pathogenic variants in polycystic disease genes were found in 44 of 49 patients (90%). The disease gene was PKD1 in 20 of 44 patients (45%), PKD2 in 15 of 44 patients (34%), PRKCSH in 5 of 44 patients (11%), GANAB in 2 of 44 patients (5%), SEC63 in 1 of 44 patients (2%), and ALG8 in 1 of 44 patients (2%). The median hTLV was no different between genetically defined ADPKD and ADPLD groups (4431 [range, 1817–9148] versus 3437 [range, 1860–8211]) ml, P = 0.77), whereas height-adjusted kidney volume was larger as expected in ADPKD than in ADPLD (607 [range, 190–2842] versus 179 [range, 138–234] ml/m, P < 0.01). Of the clinically defined ADPKD patients, 20 of 38 patients (53%) were PKD1 , 15 of 38 (39%) were PKD2 , and 3 (8%) remained genetically unsolved. Among patients with a pathogenic PKD1 or PKD2 variant, we found three patients with a liver-dominant ADPKD (severe PLD with height-adjusted total kidney volume <250 ml/m). Conclusions ADPLD-related genes represent 20% of patients with severe PLD in our cohort. Of those enrolled with ADPKD, we observed a higher frequency of PKD2 carriers than in any previously reported ADPKD cohorts. Although there was no significant difference in the hTLV between patients with PKD1 and PKD2 in this cohort, our data suggest that enrollment on the basis of severe PLD may enrich for patients with PKD2 .

  PublisherDOI

Recent grants

• Molecular genetic bases of polycystic and tubulointerstitial kidney diseases

  NIH · $939k · 2019–2024

Frequent coauthors

• Christophe Benoist

  Harvard University

  36 shared

• Diane Mathis

  Harvard University

  36 shared

• Matt Roy

  Lakehead University

  26 shared

• Paul Desany

  Brigham and Women's Hospital

  17 shared

• Adriana Ortiz-Lopez

  Harvard University

  17 shared

• Mark Lathrop

  16 shared

• Anne Puech

  16 shared

• Koichiro Ohmura

  Kobe City Medical Center General Hospital

  16 shared

Labs

• Whitney Besse LabPI

Education

• B.S., Biomedical Engineering

  Brown University

  2003

• Other, Genetics

  Joslin Diabetes Center