Episode 30: Heart in the Genes — A New Genetic Syndrome Linked to POPDC2

🫀 In this episode of Base by Base, we delve into a groundbreaking study by Nicastro et al. (2025), published in The American Journal of Human Genetics, which identifies bi-allelic variants in the POPDC2 gene as the cause of a novel autosomal recessive cardiac syndrome. This condition manifests with sinus node dysfunction, atrioventricular (AV) block, and in some cases, hypertrophic cardiomyopathy (HCM).

🔍 Study highlights:
The research demonstrates that pathogenic variants in POPDC2 disrupt its ability to bind cyclic AMP (cAMP), compromising its interaction with the TREK-1 potassium channel and affecting cardiac electrical activity.
Through in vitro electrophysiology, mutant POPDC2 variants failed to enhance TREK-1 current density, unlike the wild-type protein.
Structural modeling showed that disease-causing mutations cluster around key functional domains critical for cAMP binding and dimerization.
Muscle biopsy from an affected individual revealed a marked reduction in both POPDC2 and POPDC1 proteins, suggesting destabilization of their membrane complex.
Single-cell and spatial transcriptomics confirmed that POPDC2 is highly expressed in specialized cardiac conduction tissues—especially in the AV node and bundle cells—where it often co-localizes with POPDC1.
Large-scale population data (>1 million individuals) showed that heterozygous carriers of these rare variants do not display the disease phenotype, indicating a recessive inheritance pattern without clinical penetrance in carriers.

🧠 Conclusion:
This study establishes POPDC2 as a new Mendelian gene responsible for a previously unrecognized cardiac syndrome. It emphasizes the importance of functional genomics and integrative modeling to unravel complex genotype–phenotype relationships in cardiogenetics. These findings expand our understanding of the molecular mechanisms underlying cardiac conduction disorders and have important implications for genetic counseling and early diagnosis in affected families.

📖 Reference:
Nicastro, M., Vermeer, A.M.C., Postema, P.G., et al. (2025). Bi-allelic variants in POPDC2 cause an autosomal recessive syndrome presenting with cardiac conduction defects and hypertrophic cardiomyopathy. The American Journal of Human Genetics, 112, 1–18. https://doi.org/10.1016/j.ajhg.2025.04.016

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

🎙️ Episode 29: Rethinking Agency for Genetic Testing Intention among Latinos — Determining Predictors of Intention for Carrier Screening and Cancer Predisposition Testing

🧬 In this episode of Base por Base, we explore a pre-proof by Chavez-Yenter and Kaphingst (2025) in Genetics in Medicine that leverages the Integrated Behavioral Model to uncover how attitudes, social norms, and perceived agency drive Latino adults’ intentions to pursue both carrier screening and cancer predisposition testing .

🔍 Study Highlights:
The authors first applied confirmatory factor analysis to refine latent constructs for attitude, norms, and agency, removing indicators with loadings below .500, and then employed structural equation modeling to predict behavioral intention for carrier screening (CS) and cancer predisposition testing (CPT) . Across both outcomes, perceived agency emerged as the strongest positive driver—β = .381 (p < .01) for CS and β = .559 (p < .01) for CPT—while stronger normative beliefs from family and friends boosted CS intention and attitudes showed a modest negative association with CS intention . Sensitivity analyses excluding participants with prior genetic testing upheld these agency and norm effects for carrier screening but attenuated IBM effects for cancer testing .

🧠 Conclusion:
These findings suggest that interventions designed to empower Latino patients—by enhancing their perceived ability to access testing and engaging family and social networks—may be more effective at increasing genetic testing uptake than strategies focused solely on information provision and attitude change .

📖 Reference:
Chavez-Yenter D, Kaphingst KA. Rethinking Agency for Genetic Testing Intention among Latinos: Determining Predictors of Intention for Carrier Screening and Cancer Predisposition Testing. Genetics in Medicine. 2025. https://doi.org/10.1016/j.gim.2025.101455

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – https://creativecommons.org/licenses/by/4.0/

🎙️ Episode 28: Cell-Type-Resolved TWAS — scPrediXcan Integrates Deep Learning and Single-Cell Data for Transcriptome-Wide Association Studies
🧬 In this episode of Base por Base, we explore the groundbreaking framework scPrediXcan introduced by Zhou et al. (2025) in Cell Genomics. This approach combines a deep learning–based model, ctPred, with single-cell RNA-seq data to predict cell-type-specific gene expression, and then linearizes those predictions into a SNP-based model, ℓ-ctPred, for use in S-PrediXcan. By leveraging only GWAS summary statistics and in silico expression references, scPrediXcan enables transcriptome-wide association studies at unprecedented cellular resolution .

🔍 Highlights of the study:
ctPred leverages a pretrained sequence-to-epigenomics model (Enformer) to predict cell-type-specific gene expression with high accuracy across diverse scRNA-seq datasets.
The ℓ-ctPred linear model robustly approximates ctPred outputs, allowing efficient TWAS using GWAS summary statistics without individual-level data.
In type 2 diabetes, scPrediXcan identifies 222 candidate genes across 108 independent LD blocks, compared with just 12 and 111 genes recovered by pseudobulk and bulk TWAS approaches.
Applied to systemic lupus erythematosus, scPrediXcan nominates 129 genes across 24 LD blocks, uncovering cell-type-specific drivers such as PYCARD and ITGAM that bulk analyses miss.
By integrating deep learning–based prediction with cell-type resolution, the framework reveals nuanced disease mechanisms and markedly improves gene prioritization for complex traits.

🧠 Conclusion:
scPrediXcan represents a major advance in genetic epidemiology by enabling large-scale, cell-type-specific TWAS using only summary statistics and single-cell-informed prediction models. It dramatically expands the set of candidate causal genes, refines our understanding of cellular mechanisms in disease, and lays the groundwork for more targeted experimental follow-up and therapeutic discovery.

📖 Reference:
Zhou, Y., Adeluwa, T., Zhu, L., et al. (2025). scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework. Cell Genomics, 5, 100875. https://doi.org/10.1016/j.xgen.2025.100875

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – http://creativecommons.org/licenses/by/4.0/

🎙️ Episode 27: Nucleocytosolic Vehicles — A CRISPR RNP Delivery Breakthrough

🧬 In this episode of Base by Base, we delve into a novel virus-like particle (VLP) platform, ENVLPE, developed by Geilenkeuser et al. (2025) in Cell. This innovation harnesses nucleocytosolic shuttling and RNA aptamer recruitment to efficiently package and deliver fully assembled CRISPR ribonucleoproteins (RNPs), overcoming spatial and loading limitations of previous VLP approaches.

🔍 Main Highlights:
The ENVLPE system integrates a PP7 coat protein into the HIV-1 Gag polyprotein and appends PP7-tagged guide RNAs to selectively load base editors, prime editors, nucleases, and trans-activators as RNPs rather than mRNA or protein fusions.
Active nuclear export and localization signals shuttle editor RNPs into the cytosol, synchronizing RNP assembly with VLP budding and greatly enhancing packaging efficiency.
Co-expression of the RNA endonuclease Csy4, which remains bound to a 3′ hairpin on pegRNAs, protects guide RNAs from degradation and substantially boosts prime editing performance under low-dose conditions.
A streamlined “miniENVLPE” variant retaining only essential Gag elements and coiled-coil oligomerization domains matches full-length editing efficiency, demonstrating the platform’s modularity and scalability.
In vivo subretinal delivery of ENVLPE in mouse models achieves robust editor uptake by retinal cells and functional gene correction in inherited eye disease—with minimal off-target activity.

🧠 Conclusion:
ENVLPE represents a versatile, high-efficiency vehicle for RNP delivery of CRISPR effectors in both ex vivo and in vivo settings. By combining RNA-mediated recruitment, active transport, and modular VLP engineering, this platform opens new avenues for precise therapeutic genome editing.

📖 Reference:
Geilenkeuser, J., Armbrust, N., Steinmaßl, E., et al. (2025). Engineered nucleocytosolic vehicles for loading of programmable editors. Cell, 188, 2637–2655. https://doi.org/10.1016/j.cell.2025.03.015

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – https://creativecommons.org/licenses/by/4.0/

🎙️ Episode 26: Reannotation in Focus — Uncovering Functional Non-Coding Mutations in Melanoma

🧬 In this episode of Base por Base, we delve into a breakthrough study by Pepe et al. (2025) in The American Journal of Human Genetics that challenges conventional cancer mutation annotation. The authors present an automated pipeline combining RNA-seq–based transcript quantification and Ensembl VEP reannotation to map somatic variants to the transcripts actually expressed in melanoma tumors. By integrating TCGA and COSMIC datasets, deep-learning predictions, and functional assays, this framework exposes a hidden layer of non-coding promoter mutations driving melanoma pathogenesis.

🔍 Study Highlights:
The reannotation approach revealed that many mutation clusters previously labeled as synonymous or missense events in cancer databases instead reside in promoter regions of expressed genes and adjacent loci, with 22% of 52 hotspots in melanoma belonging to this non-coding category. Functional validation using CRISPR-Cas9–edited melanocyte models and luciferase reporter assays demonstrated that IRF3/BCL2L12 promoter variants downregulate IRF3, BCL2L12, and downstream TP53 signaling, and disrupt ETS and SP/E2F transcription factor binding motifs as predicted by the DeepMEL2 model and PhysBinder/FABIAN-variant analyses. Systematic reannotation of KNSTRN and SLC27A5 clusters further confirmed non-coding promoter activity alterations, underscoring the prevalence and significance of regulatory mutations overlooked by reference-transcript annotation.

🧠 Conclusion:
By anchoring mutation annotation to expressed transcripts, the BayesMRnet reannotation pipeline (Salmon + VEP) ushers in a more precise era of cancer genomics, uncovering functional non-coding drivers in melanoma and offering a scalable tool to refine driver mutation discovery and guide future therapeutic strategies.

📖 Reference:
Pepe, D., Janssens, X., Timcheva, K., Marrón-Liñares, G. M., Verbelen, B., Konstantakos, V., … De Keersmaecker, K. (2025). Reannotation of cancer mutations based on expressed RNA transcripts reveals functional non-coding mutations in melanoma. The American Journal of Human Genetics, 112, 1–21. https://doi.org/10.1016/j.ajhg.2025.04.005

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – http://creativecommons.org/licenses/by/4.0/

🎙️ Episode 25: Uncovering Mitochondrial DNA Diseases — The Solve-RD Experience with Genotype and Phenotype Integration

🧬 In this episode of Base por Base, we delve into a groundbreaking study by Ratnaike et al. (2025) published in The American Journal of Human Genetics, which presents a semi-automated workflow combining mtDNA variant filtering and MitoPhen-based HPO phenotype similarity scoring applied to exome and genome data from the Solve-RD cohort of undiagnosed rare disease cases .

🔍 Study highlights:
Our workflow applied MToolBox for mtDNA reconstruction and MITOMAP annotations with stringent quality filters (≥50% mtDNA assembly and ≥5× coverage) to prioritize 136 rare variants across 9,923 individuals from 9,483 families without prior suspicion of mitochondrial disease .
Phenotype similarity scoring using the curated MitoPhen database achieved 100% sensitivity at a 0.3 threshold and distinguished confirmed mtDNA disease cases from nuclear genetic diagnoses with an AUC of 0.82 .
A total of 21 confirmed and 16 likely causative mtDNA diagnoses were made, boosting the overall diagnostic yield by 0.4% and uncovering 37 new diagnoses .
The pipeline efficiently handled off-target exome sequencing data, retaining 90% of datasets for analysis and enabling detection of pathogenic variants at heteroplasmy levels as low as 1% .
Structured, phenotype-driven curation underscored the importance of comprehensive HPO annotation and highlighted the value of iterative genotype-phenotype evaluation in improving rare disease diagnostics .

🧠 Conclusion:
This study demonstrates a scalable approach to integrate mtDNA analysis into routine exome and genome reanalysis by leveraging automated bioinformatic filtering and phenotype similarity scoring, offering a powerful tool to improve diagnostic rates for mitochondrial disorders in heterogeneous cohorts .

📖 Reference:
Ratnaike, T., Paramonov, I., Olimpio, C., et al. (2025). Mitochondrial DNA disease discovery through evaluation of genotype and phenotype data: The Solve-RD experience. The American Journal of Human Genetics, 112(1), 1–12. https://doi.org/10.1016/j.ajhg.2025.04.003

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – http://creativecommons.org/licenses/by/4.0/

🎙️ Episode 24: The Role of the X Chromosome in Complex Trait Genetics — Unraveling Dosage-Compensation Mechanisms
🧬 In this installment of Base por Base, we delve into groundbreaking work by Fu et al. (2025) in The American Journal of Human Genetics, which systematically interrogates how the X chromosome shapes human quantitative traits. Leveraging data from over 350,000 UK Biobank participants with replication in more than 400,000 FinnGen individuals, the study quantifies the X chromosome’s contribution to trait heritability, examines sex-specific genetic variance, and elucidates the interplay between X-inactivation and upregulation processes in balancing dosage between sexes and with the autosomes .

🔍 Key Highlights: In a comprehensive analysis of 48 traits, the authors report that the X chromosome accounts for roughly 3% of the heritability explained by autosomes, demonstrating a proportional yet distinct contribution to complex trait variation; they confirm near-complete X chromosome inactivation in females and hemizygosity in males, leading to approximately double the genetic variance on X in men versus women; compelling evidence emerges for partial escape from inactivation impacting traits such as height; moreover, the study reveals that single active copies of X-linked loci exert allele effects about 1.6-fold greater than those on autosomes, supporting a model of partial transcriptional upregulation on X relative to autosomes .

🧠 Conclusion: By integrating large-scale biobank data with advanced heritability and effect-size modeling, this work inaugurates a new era in understanding X-linked genetic architecture. It highlights how near-complete inactivation, nuanced escape, and dosage compensation via allele-level upregulation collectively maintain balanced contributions of the X chromosome to human phenotypic diversity, offering vital insights for future locus discovery and sex-specific analyses in genomics .

📖 Reference:
Fu, Y., Kenttämies, A., Ruotsalainen, S., Pirinen, M., & Tukiainen, T. (2025). Role of X chromosome and dosage-compensation mechanisms in complex trait genetics. The American Journal of Human Genetics, 112, 1–14. https://doi.org/10.1016/j.ajhg.2025.04.004

📜 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – https://creativecommons.org/licenses/by/4.0/

🎙️ Episode 23: Evaluating the Return of Additional Findings from the 100,000 Genomes Project — Participant Experiences of Secondary Genomic Findings

🧬 In this episode of Base por Base, we explore a mixed-methods study by Stafford-Smith et al. (2025) published in Genetics in Medicine, which examines how participants in England’s 100,000 Genomes Project experienced the disclosure of additional (secondary) genomic findings. By combining a cross-sectional survey of 147 adults who received either cancer- or familial hypercholesterolemia-related findings with in-depth interviews of 35 positive-finding recipients and 29 individuals with no additional findings, this research sheds light on the psychological, behavioural, and communication aspects of returning actionable genetic results through NHS pathways.

🔍 Study highlights:
Participants rated the utility of their results exceptionally high (mean 8.9/10 now; 9.0/10 for future use) and most (82%) reported that knowing their finding would influence health management. Those who learned of a cancer-related variant often felt initial shock and anxiety, whereas individuals with familial hypercholesterolemia findings described relief and readiness to act. Recipients of no additional findings welcomed the reassurance but sometimes struggled to distinguish these results from their primary diagnostic findings. Overall decisional regret was low (median score 5/100), though a minority experienced mild or high regret initially. Thematic analysis revealed that clear, tailored communication and timely clinical support were critical for helping participants adjust, share results with family, and implement risk-reducing strategies.

🧠 Conclusion:
Stafford-Smith et al. demonstrate strong participant support for routinely offering actionable secondary findings alongside genome sequencing, while emphasizing the need for condition-specific pathways, improved consent-to-result timelines, and enhanced informational resources for no-finding recipients. Their work lays the groundwork for more patient-centred genomic medicine practices and underscores the importance of psychosocial support in “genome-first” care models.

📖 Reference:
Stafford-Smith B., Daniel M., Peter M., et al. (2025). Evaluating the return of additional findings from the 100,000 Genomes Project: A mixed methods study exploring participant experiences of receiving secondary findings from genomic sequencing. Genetics in Medicine. https://doi.org/10.1016/j.gim.2025.101446

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – https://creativecommons.org/licenses/by/4.0/