Biomedical subjects

Lars M Steinmetz

Publications and source records attributed to Lars M Steinmetz.

3 recordsLinked to original sources

PubMed2026

Dysregulated Ribonucleoprotein Granules Impair Mitochondrial Function in RBM20-Related Dilated Cardiomyopathy.

BACKGROUND: Pathogenic variants in RBM20 cause severe dilated cardiomyopathy. Loss-of-function variants disrupt splicing; neomorphic gain-of-function (GoF) variants also mislocalize RBM20 to cytoplasmic ribonucleoprotein granules and are associated with more aggressive disease. The mechanism by which RBM20 mislocalization drives cardiac dysfunction remains unknown. METHODS: We investigated the effects of Rbm20 GoF and loss-of-function (LoF) variants using proteomic profiling, protein solubility assays, mitochondrial respiration and calcium flux analyses, and ultrastructural imaging in mouse models. Human induced pluripotent stem cell-derived cardioids were used to validate variant-specific phenotypes. RESULTS: Rbm20 GoF, but not LoF, variants caused posttranscriptional downregulation of soluble mitochondrial proteins, including the calcium efflux regulator TMEM65 (transmembrane protein 65), and reduced solubility of mitochondrial membrane proteins. Electron microscopy revealed enlarged mitochondria with cristae disorganization. Functional assays confirmed impaired oxidative phosphorylation, reduced mitochondrial membrane potential, and abnormal calcium handling in Rbm20 GoF models. Human cardioids reproduced these findings, demonstrating that cytoplasmic mislocalization, rather than splicing deficiency, drives mitochondrial dysfunction. CONCLUSIONS: Cytoplasmic mislocalization of RBM20 disrupts mitochondrial function by reducing mitochondrial protein abundance, leading to oxidative phosphorylation failure and abnormal mitochondrial calcium handling. This mechanism distinguishes RBM20 GoF from LoF variants and may explain the more severe heart failure phenotype observed in patients with RBM20 GoF variants. These insights advance the mechanistic understanding of RBM20-related cardiomyopathy and identify mitochondrial mRNA/protein regulation as a key node in cardiac energetics.

cardiomyopathy, dilated↗

PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗

PubMed2025

Functional phenotyping of genomic variants using joint multiomic single-cell DNA-RNA sequencing.

Genetic variants (both coding and noncoding) can impact gene function and expression, driving disease mechanisms such as cancer progression. The systematic study of endogenous genetic variants is hindered by inefficient precision editing tools, combined with technical limitations in confidently linking genotypes to gene expression at single-cell resolution. We developed single-cell DNA-RNA sequencing (SDR-seq) to simultaneously profile up to 480 genomic DNA loci and genes in thousands of single cells, enabling accurate determination of coding and noncoding variant zygosity alongside associated gene expression changes. Using SDR-seq, we associate coding and noncoding variants with distinct gene expression in human induced pluripotent stem cells. Furthermore, we demonstrate that in primary B cell lymphoma samples, cells with a higher mutational burden exhibit elevated B cell receptor signaling and tumorigenic gene expression. SDR-seq provides a powerful platform to dissect regulatory mechanisms encoded by genetic variants, advancing our understanding of gene expression regulation and its implications for disease.

Humans↗