Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

The 14th International Podocyte Conference 2023: from podocyte biology to glomerular medicine

The 14th International Podocyte Conference took place in Philadelphia, Pennsylvania, USA from May 23 to 26, 2023. It commenced with an early-career researchers' meeting on May 23, providing young scientists with a platform to present and discuss their research findings. Throughout the main conference, 29 speakers across 9 sessions shared their insights on podocyte biology, glomerular medicine, novel technologic advancements, and translational approaches. Additionally, the event featured 3 keynote lectures addressing engineered chimeric antigen receptor T cell- and mRNA-based therapies and the use of biobanks for enhanced disease comprehension. Furthermore, 4 brief oral abstract sessions allowed scientists to present their findings to a broad audience. The program also included a panel discussion addressing the challenges of conducting human research within the American Black community. Remarkably, after a 5-year hiatus from in-person conferences, the 14th International Podocyte Conference successfully convened scientists from around the globe, fostering the presentation and discussion of crucial research findings, as summarized in this review. Furthermore, to ensure continuous and sustainable education, research, translation, and trial medicine related to podocyte and glomerular diseases for the benefit of patients, the International Society of Glomerular Disease was officially launched during the conference.

Keeping pace: the primary cilium as the conducting baton of the islet

Primary cilia are rod-like sensory organelles that protrude from the surface of most mammalian cells, including the cells of the islet, and mounting evidence supports important roles of these structures in the regulation of beta cell function and insulin secretion. The sensory abilities of the cilium arise from local receptor activation that is coupled to intrinsic signal transduction, and ciliary signals can propagate into the cell and influence cell function. Here, we review recent advances and studies that provide insights into intra-islet cues that trigger primary cilia signalling; how second messenger signals are generated and propagated within cilia; and how ciliary signalling affects beta cell function. We also discuss the potential involvement of primary cilia and ciliary signalling in the development and progression of type 2 diabetes, identify gaps in our current understanding of islet cell cilia function and provide suggestions on how to further our understanding of this intriguing structure.

Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence

With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unprecedented speed and scale every day. For the first time, these multi-modal biomedical data are able to make precision medicine close to a reality. However, due to data volume and the complexity, making good use of these multi-modal biomedical data requires major effort. Researchers and clinicians are actively developing artificial intelligence (AI) approaches for data-driven knowledge discovery and causal inference using a variety of biomedical data modalities. These AI-based approaches have demonstrated promising results in various biomedical and healthcare applications. In this review paper, we summarize the state-of-the-art AI models for integrating multi-omics data and electronic health records (EHRs) for precision medicine. We discuss the challenges and opportunities in integrating multi-omics data with EHRs and future directions. We hope this review can inspire future research and developing in integrating multi-omics data with EHRs for precision medicine.

A Role for Genetic Modifiers in Tubulointerstitial Kidney Diseases

With the increased availability of genomic sequencing technologies, the molecular bases for kidney diseases such as nephronophthisis and mitochondrially inherited and autosomal-dominant tubulointerstitial kidney diseases (ADTKD) has become increasingly apparent. These tubulointerstitial kidney diseases (TKD) are monogenic diseases of the tubulointerstitium and result in interstitial fibrosis and tubular atrophy (IF/TA). However, monogenic inheritance alone does not adequately explain the highly variable onset of kidney failure and extra-renal manifestations. Phenotypes vary considerably between individuals harbouring the same pathogenic variant in the same putative monogenic gene, even within families sharing common environmental factors. While the extreme end of the disease spectrum may have dramatic syndromic manifestations typically diagnosed in childhood, many patients present a more subtle phenotype with little to differentiate them from many other common forms of non-proteinuric chronic kidney disease (CKD). This review summarises the expanding repertoire of genes underpinning TKD and their known phenotypic manifestations. Furthermore, we collate the growing evidence for a role of modifier genes and discuss the extent to which these data bridge the historical gap between apparently rare monogenic TKD and polygenic non-proteinuric CKD (excluding polycystic kidney disease).

The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population

The Penn Medicine BioBank (PMBB) is an electronic health record (EHR)-linked biobank at the University of Pennsylvania (Penn Medicine). A large variety of health-related information, ranging from diagnosis codes to laboratory measurements, imaging data and lifestyle information, is integrated with genomic and biomarker data in the PMBB to facilitate discoveries and translational science. To date, 174,712 participants have been enrolled into the PMBB, including approximately 30% of participants of non-European ancestry, making it one of the most diverse medical biobanks. There is a median of seven years of longitudinal data in the EHR available on participants, who also consent to permission to recontact. Herein, we describe the operations and infrastructure of the PMBB, summarize the phenotypic architecture of the enrolled participants, and use body mass index (BMI) as a proof-of-concept quantitative phenotype for PheWAS, LabWAS, and GWAS. The major representation of African-American participants in the PMBB addresses the essential need to expand the diversity in genetic and translational research. There is a critical need for a "medical biobank consortium" to facilitate replication, increase power for rare phenotypes and variants, and promote harmonized collaboration to optimize the potential for biological discovery and precision medicine.

eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals

BACKGROUND

Genomic studies increasingly integrate expression quantitative trait loci (eQTL) information into their analysis pipelines, but few tools exist for the visualization of colocalization between eQTL and GWAS results. Those tools that do exist are limited in their analysis options, and do not integrate eQTL and GWAS information into a single figure panel, making the visualization of colocalization difficult.

RESULTS

To address this issue, we developed the intuitive and user-friendly R package eQTpLot. eQTpLot takes as input standard GWAS and cis-eQTL summary statistics, and optional pairwise LD information, to generate a series of plots visualizing colocalization, correlation, and enrichment between eQTL and GWAS signals for a given gene-trait pair. With eQTpLot, investigators can easily generate a series of customizable plots clearly illustrating, for a given gene-trait pair: 1) colocalization between GWAS and eQTL signals, 2) correlation between GWAS and eQTL p-values, 3) enrichment of eQTLs among trait-significant variants, 4) the LD landscape of the locus in question, and 5) the relationship between the direction of effect of eQTL signals and the direction of effect of colocalizing GWAS peaks. These clear and comprehensive plots provide a unique view of eQTL-GWAS colocalization, allowing for a more complete understanding of the interaction between gene expression and trait associations.

CONCLUSIONS

eQTpLot provides a unique, user-friendly, and intuitive means of visualizing eQTL and GWAS signal colocalization, incorporating novel features not found in other eQTL visualization software. We believe eQTpLot will prove a useful tool for investigators seeking a convenient and customizable visualization of eQTL and GWAS data colocalization.

AVAILABILITY AND IMPLEMENTATION

the eQTpLot R package and tutorial are available at https://github.com/RitchieLab/eQTpLot.