Erik Ben van Den Akker

Introduction: The RNA sensor RIG-I performs a critical role in surveying the cytoplasm for the presence of viral nucleic acids and initiating the downstream anti-viral type I interferon pathway. Through recognition of specific features, such as the presence of a 5’ tri/diphosphate motif or highly structured base-paired regions, RIG-I effectively differentiates between RNA of viral- and self-origin. In Singleton-Merten syndrome (SMS), gain-of-function variants in RIG-I lead to a breakdown in this surveillance system and results in aberrant sensing of self-RNAs and deleterious upregulation of type I interferons. The identity of the self-RNAs binding to gain-of-function RIG-I mutants has remained elusive and their elucidation would provide a greater understanding of the aetiology of SMS. Methods: Here we used an infrared individual-nucleotide resolution UV-crosslinking and immunoprecipitation (irCLIP) approach to determine the RNA profile bound to a previously characterised ATPase-deficient SMS variant, RIG-IC268F. Results: irCLIP identified a broad array of self-RNAs, primarily those transcribed by RNA polymerase III, that were bound to RIG-I. Subsequent native RNA immunoprecipitation confirmed a prominent and specific interaction between RIG-IC268F and Y-RNAs, a family of four structurally similar non-coding RNAs. Conclusion: Manipulation of Y-RNAs alone by targeting either Y-RNA transcripts or Y-RNA stabilising proteins was insufficient to negate RIG-I induced interferon responses, hinting at a broader profile of RNA polymerase III-derived RNAs being influential in driving the sterile activation of gain-of-function RIG-I variants.

Background The increase in human lifespan without a proportional increase in healthspan imposes a substantial burden on individuals and society. Exceptionally long-lived individuals and members of long-lived families exhibit compression of multi-morbidity. Genetics, and in particular rare protein-altering variants, appear to play an important role in their longevity. Methods In this study, we employed a targeted pathway approach to provide functional evidence of the significance of rare variants in the insulin/insulin-like growth factor 1 signalling - mechanistic target of rapamycin (IIS/mTOR) signalling pathway identified in long-lived individuals. To this end, we used CRISPR/Cas9 to introduce these rare genetic variants into mouse embryonic stem cells (mESCs). We subsequently assessed several functional readouts that have previously been associated with lifespan regulation in model organisms and/or IIS/mTOR and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signalling pathway activity. Results Functional characterisation revealed that the variants exhibit both shared and distinct effects on the signalling pathways. Principal component analysis of omics-based datasets showed that the variants clustered into two groups, a distribution that corresponds with the grouping observed for a subset of functional readouts. All variant mESC lines exhibited a downregulation in IIS/mTOR and MAPK/ERK signalling pathway activity as well as an increase in Foxo3 expression and FOXO3 binding activity. We identified alterations in lipid and mitochondrial metabolism, including a reduction in mitochondrial DNA levels, which were mostly shared among all variants. All variant mESC lines exhibited a signature implying increased pluripotency. The effects on stress resistance and growth rate diverged between the two variant groups, with partially opposing effects. Group 1 demonstrated a reduced growth rate and increased resistance to a subset of stressors, while Group 2 demonstrated an increased growth rate and reduced resistance to a subset of stressors. Conclusions Here, we provide evidence that rare genetic variants in the IIS/mTOR and MAPK/ERK signalling pathways identified in long-lived human individuals result in shared functional effects associated with longevity in model organisms. These insights can serve as a foundation to better understand the role of rare variants in the insulin signalling network in the regulation of human longevity.

Background/Objectives: Acute myeloid leukemia (AML) comprises genetic subclasses with distinct gene expression profiles. While AML gene expression studies have mainly focused on protein-coding genes, our understanding of expression patterns of long intergenic noncoding RNAs (lincRNAs) remains incomplete. This is due to limited sample sizes, as well as incomplete annotation of lncRNAs with context-dependent expression. Methods: To address this gap, we developed the bioinformatic pipeline LIRA (long intergenic noncoding RNA annotator) to identify novel lincRNAs using stringent criteria, including spliced and intergenic transcripts, and algorithms to exclude coding potential. Results: By applying LIRA to RNA-sequencing data from 878 pediatric and adult AML cases and 20 healthy controls, we identified 1560 novel lincRNAs, expanding the GENCODE v38 lincRNA catalog by 27%. Integration of in-house-generated CAGE- and ChIP-sequencing data from KMT2A::MLLT3 samples revealed that 80% of the novel lincRNAs are 5′ capped, and at least 67% harbor activating epigenetic marks at their transcription start sites. Unsupervised analysis of the 1000 most variable known and newly identified lincRNAs uncovered subclass-specific expression patterns, mirroring those observed for protein-coding genes. Weighted Gene Co-expression Network Analysis identified 17 lincRNA expression modules associated with AML subclasses. Notably, expression of these modules decreased upon degradation of the leukemogenic onco-fusion proteins KMT2A::MLLT3 and PML::RARA, indicating that lincRNA expression is responsive to oncogenic signaling. Conclusions: This comprehensive analysis shows that lincRNAs exhibit similar subclass-specific expression patterns as protein-coding genes and establishes a valuable resource for future studies on genetically defined AML subclasses, with potential implications for biomarker discovery and therapeutic targeting.

Primarily recognized as the site for T cell development, the thymus supports a complex interplay between thymic stromal cells and developing thymocytes, which is essential for T cell maturation and the establishment of central tolerance. Emerging evidence indicates that thymic B cells contribute to tolerance induction by functioning as antigen-presenting cells. However, their developmental pathways and functional roles remain poorly understood. Using tissue mass cytometry, we localized B cells in the thymus and their orientation towards other cells in the medulla. We characterized the heterogeneity of thymic B cells using single-cell RNA sequencing of cells isolated from human thymi, identifying naive, germinal center-like, plasma cell, and multiple memory B cell populations. We identified a distinct pre-B cell subset with local thymic B cell development potential, that can develop due to the inhibition of Notch signaling by Deltex1, a Notch antagonist. Using BCR repertoire analysis, we explored clonal diversity, somatic hypermutation patterns and class switch recombination of thymic B cells. Spectral flow cytometry further validated the surface phenotype of thymic B cell populations and confirmed the presence of distinct CD21-CD27- memory compartments with heterogeneous surface immunoglobulin isotype usage. In doing so we provide novel insights into the unique biology of human thymic B cells, their development, and their differentiation in the human thymus. We conclude that the human thymus supports local B cell development and differentiation into medullary memory-like populations that undergo class switching with limited somatic hypermutation, suggesting secondary lymphoid-like B cell programs adapted to central tolerance induction.

Rheumatic diseases are chronic, immune-mediated conditions characterized by significant heterogeneity in presentation and disease course. However, current clinical approaches often rely on snapshot-based assessments that fail to capture the complex longitudinal evolution of these conditions. To address these limitations and support the implementation of precision medicine, we present the design for the Rheumatic Digital Twin, a novel, modular conceptual framework intended to integrate heterogeneous multimodal data, ranging from electronic health records and clinical notes to imaging and omics, into a dynamic, computational representation of the patient journey. Our theoretical architecture addresses challenges related to data silos and variable availability of data modalities through a multistage approach that envisions the use of domain-specific foundation models to independently process distinct data modalities. To effectively model the temporal progression inherent in chronic diseases, the proposed design utilizes Transformer architectures, leveraging self-attention mechanisms to treat patient events, such as lab results or medication changes, as sequential data tokens. We describe how these unimodal representations would subsequently be fused via joint embedding techniques to construct a shared, multimodal representational space. Envisioned to function analogously to a recommender system, the Rheumatic Digital Twin framework is modeled to map patients into a latent space where proximity reflects clinical and biological similarity. By identifying “nearest neighbors,” historical patients with comparable trajectories, the system aims to enable in silico cohorting, theoretically allowing clinicians to forecast key clinical events, predict treatment responses, and identify likely disease courses based on the outcomes of similar peers.

Objectives: Rheumatoid arthritis (RA) exhibits clinical and biological heterogeneity, with synovial tissue stratified into histological pathotypes: lympho-myeloid, diffuse-myeloid, and pauci-immune fibroid. Although GWAS have uncovered RA risk loci, how genetic risk relates to synovial immunopathology remains unclear. To better understand how genetic predisposition may shape divergent early disease mechanisms, we characterised the expression patterns of GWAS-identified RA susceptibility genes and related rheumatic diseases across the synovial pathotypes. Methods: RNA-sequencing data from synovium of 87 treatment-naïve, early RA patients from the Pathobiology of Early Arthritis Cohort. Differential gene expression between pathotypes and pathway enrichment analyses were performed using susceptibility genes for RA, osteoarthritis (OA), ankylosing spondylitis, psoriatic arthritis and systemic lupus erythematosus. Results: RA susceptibility gene expression in synovial tissue separated patients by pathotype and correlated with markers of disease activity. RA susceptibility genes were significantly enriched among genes upregulated in lympho-myeloid synovium and linked to lymphocyte activation and differentiation pathways. In contrast, OA susceptibility genes were upregulated in diffuse-myeloid and fibroid synovium. Both patterns were most pronounced in ACPA-positive and directionally consistent in ACPA-negative patients. Conclusion: RA genetic susceptibility is not evenly distributed across synovial pathotypes but is strongly biased toward the lympho-myeloid pathotype, indicating that current GWAS signals preferentially capture immune-driven disease mechanisms. Enrichment of OA susceptibility genes in diffuse-myeloid and fibroid pathotypes, even among ACPA-positive patients, suggests shared biological features between auto-immune and non-inflammatory degenerative joint diseases in certain RA subtypes. Synovial pathotype stratification is therefore essential for interpreting genetic risk and understanding disease heterogeneity. Key messages: What is already known on this topic: - Rheumatoid arthritis (RA) is clinically and biologically heterogeneous, and its affected synovial tissue can be stratified into distinct immunohistological pathotypes. - GWAS have identified numerous genetic risk loci for RA and related rheumatic and inflammatory diseases. - It remains poorly understood how RA genetic risk relates to synovial tissue heterogeneity. What this study adds: - GWAS-identified RA susceptibility genes show strong, pathotype-specific expression in synovial tissue, with marked enrichment in the lympho-myeloid pathotype. - OA susceptibility genes are primarily upregulated in diffuse-myeloid and pauci-immune fibroid RA synovium, indicating shared fibroblast- and remodelling-related pathways. - These gene expression patterns are most pronounced in ACPA-positive RA but remain directionally consistent in ACPA-negative RA. How this study might affect research, practice or policy: - Synovial pathotype stratification should be incorporated into genetic studies of RA. - Pathotype-aware genetic studies may improve patient stratification and guide development of more targeted therapeutic strategies.

Chronological age overlooks the heterogeneity in aging. In response, a wide range of molecular aging biomarkers has been developed to better capture an individual”s aging rate. Yet, a comprehensive comparison of modeling choices in the development of these biomarkers is lacking. In this study, we trained aging biomarkers on the Rockwood frailty index (FI) and all-cause mortality using UK Biobank Olink proteomics and metabolomics ( ¹ H-NMR) data ( n =40,696). We systematically established the impact of model choice, target outcome, and molecular data source on several age-related outcomes. From this, we developed ProteinFrailty (ProtFI), an elastic net model using a minimal set of proteins to predict FI. ProtFI outperformed established aging biomarkers in relation to diverse outcomes, including incident cardiovascular disease, handgrip strength, and self-rated health, both in internal validation and two Dutch external cohorts ( n =995, n =500). Our findings show that an efficient frailty-trained proteomic biomarker robustly predicts age-related decline.

NPM1-mutated AML is one of the largest entities in international classification systems of myeloid neoplasms, which are based on integrating morphologic and clinical data with genomic data. Previous research, however, indicates that bulk transcriptomics-based subtyping may improve prognostication and therapy guidance. Here, we characterized the heterogeneity in NPM1-mutated AML by performing single-cell RNA-sequencing and spectral flow cytometry on 16 AML belonging to three distinct subtypes previously identified by bulk transcriptomics. Using single-cell expression profiling we generated a comprehensive atlas of NPM1-mutated AML, collectively reconstituting complete myelopoiesis. The three NPM1-mutated transcriptional subtypes showed consistent differences in the proportions of myeloid cell clusters with distinct patterns in lineage commitment and maturational arrest. In all samples, leukemic cells were detected across different myeloid cell clusters, indicating that NPM1-mutated AML are heavily skewed but not fully arrested in myelopoiesis. Same-sample multi-color spectral flow cytometry recapitulated these skewing patterns, indicating that the three NPM1-mutated subtypes can be consistently identified across platforms. Moreover, our analyses highlighted differences in the abundance of rare hematopoietic stem cells suggesting that skewing occurs early in myelopoiesis. To conclude, by harnessing single-cell RNA-sequencing and spectral flow cytometry, we provide a detailed description of three distinct and reproducible patterns in lineage skewing in NPM1-mutated AML that may have potential relevance for prognosis and treatment of patients with NPM1-mutated AML.