Aug 2026· Journal of Developmental Biology· Vol 14, pp. 36· 0 citations· 561 references
Medicine
TL;DR
Underused Drosophila melanogaster offers high genomic and pathway conservation, a wealth of genetic tools, and rapid generation times, making it a reliable and sustainable model for mechanistic, genome-wide, and precision medicine studies.
Abstract
Both genetics and the environment affect the phenotypes of polycystic kidney diseases (PKD), such as autosomal dominant (AD) PKD, autosomal recessive (AR) PKD and nephronophthisis (NPH). Variable phenotypes, pleiotropy, divergent severity and progression, even in family members who inherited the same disease-causing mutation(s), signal the involvement of networked genes and modifiers. Several PKD-linked genes function in development and renal tubule morphogenesis. Cystic renal tissues feature metabolic remodeling, functional reprogramming and dysregulation of several shared factors and pathways. ADPKD, ARPKD and NPH partially phenocopy each other. Understanding the developmental arc of cystic kidney disease and its complex phenotypes would improve diagnostics and help develop effective personalized treatments. However, this is challenging to study in vertebrate systems due to genetic redundancy, functional overlap, and a dearth of genetic tools. Underused in this context, Drosophila melanogaster offers high genomic and pathway conservation, a wealth of genetic tools, and rapid generation times, making it a reliable and sustainable model for mechanistic, genome-wide, and precision medicine studies. Here, we surveyed ADPKD, ARPKD, and NPH, compared renal and extrarenal phenotypes, and examined the network of shared and unique contributors, their healthy and diseased functions and conservation from the perspective of mechanistic whole-animal modeling.
A certain proportion of patients with Mendelian diseases are overlooked, although substantial technical advances in molecular genetics have been achieved. Massively parallel sequencing (MPS) increasingly identifies genetic variants of unknown significance, which may remain clinically unhelpful. Furthermore, difficult niches in the genome exist, which cannot be solved by standard MPS. In the reported family autosomal dominant kidney disease leading to renal failure in middle adulthood runs through the maternal and paternal family. Comprehensive genetic analyses and customized functional evaluation solved the genetic etiologies: autosomal dominant polycystic kidney disease (ADPKD-PKD1, maternal) and autosomal dominant tubulointerstitial kidney disease (ADTKD-UMOD, paternal), with the index patient suffering from both diseases. The pathogenic variant in PKD1 (c.2180T>C, p.(Leu727Pro)) was not identified by exome sequencing (ES) but was unveiled by traditional long-range amplification protocols and whole genome sequencing. The ease of use of MPS increasingly tempts non-specialized genetic laboratories to perform broad analyses of numerous diseases, which in specific cases may worsen the quality of investigations, i.e. for the relatively frequent ADPKD.
Arif B. Ekici, K. Knaup, C. Schaeffer et al.· American Journal of Kidney D...· 0 citations
Polycystic kidney disease (PKD) arises from mutations in cilia-associated genes, such as PKD1 and PKD2, expressed in renal epithelial cells, leading to progressive kidney dysfunction and end-stage kidney disease (ESKD). PKD patients exhibit significant heterogeneity in disease progression, largely due to genetic and environmental modifiers. Like patients, mouse models of PKD also exhibit significant heterogeneity with regards to the gene mutated, age of disease onset, and rate of disease progression. To elucidate the cellular and molecular consequences of these variables, we constructed an integrated single-cell RNA sequencing atlas across mouse models of PKD, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models. Across models, single cell RNA sequencing (scRNAseq) data revealed increased Spp1 (osteopontin) expression and signaling from PKD-enriched clusters. Global deletion of Spp1 in Pkd1RC/RC mice resulted in a modest reduction in cyst severity and improved kidney function. From these studies, we created a freely available, searchable website (https://bmblx.bmi.osumc.edu/scPKD/) that can be used to identify cross- and intra-model changes in gene expression, guiding researchers to new therapeutic targets for treating PKD.
S. Miller, Hua Zhong, Weidong Wu et al.· JCI Insight· 0 citations
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most prevalent hereditary kidney disorder. While the disease is well-defined, its clinical course is highly variable, making the prediction of individual patient outcomes a significant challenge for clinicians and a source of psychological distress for those affected. Current prognostic tools fall into two primary categories: imaging-based models and genetic scoring systems. However, these unimodal approaches have inherent limitations. Imaging-based metrics often lose prognostic resolution in advanced disease stages as fibrosis begins to outweigh cyst expansion. Meanwhile, genetic scoring often fails to account for intrafamilial variability and may underestimate risk in a significant percentage of rapid progressors. Upcoming tools seek to fill these gaps by exploring new dimensions of the disease, including genome-wide polygenic scores (GPS) to account for background genetic influences and imaging approaches that use artificial intelligence that can capture cyst architecture and parenchymal changes beyond conventional volumetric measures. Future directions in ADPKD prognostication point toward multimodal frameworks that integrate AI-derived imaging features, genomic risk measures, clinical risk factors, and molecular biomarkers. Integrated prognostic tools could help translate complex disease information into more consistent, clinically actionable guidance for treatment decisions and shared decision-making.
Jeniffer Min, Claire Zhu, Liv Palma et al.· Kidney360· 0 citations
Autosomal dominant polycystic kidney disease (ADPKD) is one of the most common inherited kidney disorders and is characterized by the progressive formation and expansion of fluid filled cysts, ultimately leading to kidney failure. Although caused by reduced dosage of the polycystin proteins, the disease phenotype arises from a broad disruption of epithelial physiology rather than a single linear pathway. Loss of polycystin function destabilizes epithelial homeostasis and sensitizes cyst lining cells to proliferative and secretory cues. A central consequence is the emergence of a self reinforcing signaling environment in which cyclic AMP, Ca2+, and purinergic pathways amplify one another, promoting chloride driven fluid secretion and epithelial proliferation. In parallel, cyst epithelia exhibit disturbed cell turnover, including altered proliferation, apoptosis, autophagy, and ferroptotic stress, which reshape luminal architecture and sustain a pro secretory microenvironment. Metabolic reprogramming, characterized by enhanced glycolysis, mitochondrial dysfunction, and redox imbalance, provides energetic support for these processes and further strengthens proliferative and secretory signaling. Hypoxia inducible factor 1α (HIF 1α) integrates hypoxic, metabolic, and mechanical cues into transcriptional programs that reinforce cyst expansion. This review synthesizes these interconnected mechanisms and highlights potential therapeutic strategies, including restoration of polycystin expression, modulation of cAMP and purinergic signaling, inhibition of chloride secretion, metabolic targeting, and HIF 1α pathway intervention. Together, these insights support a model in which cyst growth arises from mutually reinforcing signaling, metabolic, and transcriptional programs. Effective disease modification will likely require multi nodal therapeutic approaches that address this integrated network.
R. Ursu, B. Buchholz, K. Skoczynski· American Journal of Physiolo...· 0 citations
Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is the most common endocrine disorder in women and is closely associated with complex diseases such as cardiovascular disease and type 2 diabetes. However, the mechanistic links between PMOS and its comorbidities remain poorly understood. Here, we present an integrative systems genetics platform that leverages genetic diversity in both mice and humans to dissect the drivers of PMOS and its associated complications. This framework uncovers conserved genetic and environmental factors underlying PMOS, identifies susceptible cell types and organs, and elucidates mechanisms linking PMOS to subsequent pathologies. For instance, we show that increased ovarian area contributes to both PMOS susceptibility and ovarian cancer progression, while specific ovary-heart signaling circuits modulate cardiac function with aging. We further identify ovarian SF3B1-mediated alternative splicing as a key mechanistic link between PMOS and metabolic traits. Pharmacologic inhibition of SF3B1 in mice reduced circulating testosterone, insulin and glucose levels, as well as fat mass expansion. Transcriptomics analysis of ovaries from mice and experiments using human cell lines localized these effects to exon skipping events in granulosa cells. Together, this study offers a mechanistic framework for modeling the diversity of PMOS pathologies and uncovers SF3B1-mediated splicing as a link between ovary function and systemic metabolism.
Christy M. Nguyen, L. Velez, Youngseo Cheon et al.· Journal of Clinical Investig...· 0 citations
The genetic architecture of early-onset chronic kidney disease (CKD) is caused by more than 200 monogenic genes, where their common diagnostic classes include congenital anomalies of the kidney and urinary tract, steroid-resistant nephrotic syndrome, nephronophthisis-related ciliopathies, chronic glomerulonephritis, and urinary stone disease. While advancements in whole-exome and whole-genome sequencing have enabled identification of disease-causing variants, their rates of classification have remained unknown. Likewise, the molecular effects of these pathogenic variants remain unresolved, which is essential for improving personalized treatment approaches. In this study, we collected clinical and biophysical data from 117,373 genetic variants across 129 monogenic genes causing early-onset CKD. This data established the NephVar registry, which aims to be a molecular dictionary for nephrologists to classify variants and resolve their unique molecular effects. Through NephVar, we estimated 1-15% of alleles are reclassified and the time to reclassification per variant is 2-12 years in early-onset CKD. Furthermore, NephVar identified the molecular effects of all variant types, emphasizing missense variants. Our analyses indicate that intrinsically disordered regions of proteins are protective against disease-causing missense alleles across most diagnostic classes, but often occur through a buried loss-of-function (LoF) mechanism. Additionally, we show that the mode of inheritance for these monogenic genes influences clustering patterns of genetic variants, where autosomal dominant (AD) genes are more clustered than those of autosomal recessive (AR) genes. This data accurately predicted the non-LoF effects in INF2, PAX2, GATA3, ACTN4, and LMX1B causing inherited nephrotic syndromes. We demonstrate that variant effect prediction is effective for downgrading variants of unknown significance and classifying AR genes, but challenging for pathogenic alleles in AD genes. Lastly, we propose standards and guidelines for determining non-LoF effects, including gain-of-function and dominant negative, in inherited nephrotic syndrome. Overall, the NephVar renal registry has important implications for defining the molecular architecture and estimating the progress of molecular diagnostics for early-onset CKD.