Aug 2026· Journal of Developmental Biology· Vol 14· 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.
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
An integrated single-cell RNA sequencing atlas across mouse models of PKD is constructed, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models.
S. Miller, Hua Zhong, Weidong Wu et al.· JCI Insight· 0 citations
Future directions in ADPKD prognostication point toward multimodal frameworks that integrate AI-derived imaging features, genomic risk measures, clinical risk factors, and molecular biomarkers, which 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
A model in which cyst growth arises from mutually reinforcing signaling, metabolic, and transcriptional programs is synthesized, which support a model in which cyst growth arises from mutually reinforcing signaling, metabolic, and transcriptional programs.
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.