AI reveals insights into link between CD33 and cognitive impairment in Alzheimer's Disease.

Modeling biological mechanisms is a key for disease understanding and drug-target identification. However, formulating quantitative models in the field of Alzheimer's Disease is challenged by a lack of detailed knowledge of relevant biochemical processes. Additionally, fitting differential equation systems usually requires time resolved data and the possibility to perform intervention experiments, which is difficult in neurological disorders. This work addresses these challenges by employing the recently published Variational Autoencoder Modular Bayesian Networks (VAMBN) method, which we here trained on combined clinical and patient level gene expression data while incorporating a disease focused knowledge graph. Our approach, called iVAMBN, resulted in a quantitative model that allowed us to simulate a down-expression of the putative drug target CD33, including potential impact on cognitive impairment and brain pathophysiology. Experimental validation demonstrated a high overlap of molecular mechanism predicted to be altered by CD33 perturbation with cell line data. Altogether, our modeling approach may help to select promising drug targets.

scATAcat: cell-type annotation for scATAC-seq data.

Cells whose accessibility landscape has been profiled with scATAC-seq cannot readily be annotated to a particular cell type. In fact, annotating cell-types in scATAC-seq data is a challenging task since, unlike in scRNA-seq data, we lack knowledge of 'marker regions' which could be used for cell-type annotation. Current annotation methods typically translate accessibility to expression space and rely on gene expression patterns. We propose a novel approach, scATAcat, that leverages characterized bulk ATAC-seq data as prototypes to annotate scATAC-seq data. To mitigate the inherent sparsity of single-cell data, we aggregate cells that belong to the same cluster and create pseudobulk. To demonstrate the feasibility of our approach we collected a number of datasets with respective annotations to quantify the results and evaluate performance for scATAcat. scATAcat is available as a python package at https://github.com/aybugealtay/scATAcat.

Fluid shear stress-modulated chromatin accessibility reveals the mechano-dependency of endothelial SMAD1/5-mediated gene transcription.

Bone morphogenetic protein (BMP) signaling and fluid shear stress (FSS) mediate complementary functions in vascular homeostasis and disease development. It remains to be shown whether altered chromatin accessibility downstream of BMP and FSS offers a crosstalk level to explain changes in SMAD-dependent transcription. Here, we employed ATAC-seq to analyze arterial endothelial cells stimulated with BMP9 and/or FSS. We found that BMP9-sensitive regions harbor non-palindromic GC-rich SMAD-binding elements (GGCTCC) and 69.7% of these regions become BMP-insensitive in the presence of FSS. While GATA and KLF transcription factor (TF) motifs are unique to BMP9- and FSS-sensitive regions, respectively, SOX motifs are common to both. Finally, we show that both SOX(13/18) and GATA(2/3/6) family members are directly upregulated by SMAD1/5. These findings highlight the mechano-dependency of SMAD-signaling by a sequential mechanism of first elevated pioneer TF expression, allowing subsequent chromatin opening to eventually providing accessibility to novel SMAD binding sites.

Enhancer hijacking at the ARHGAP36 locus is associated with connective tissue to bone transformation.

Heterotopic ossification is a disorder caused by abnormal mineralization of soft tissues in which signaling pathways such as BMP, TGFß and WNT are known key players in driving ectopic bone formation. Identifying novel genes and pathways related to the mineralization process are important steps for future gene therapy in bone disorders. In this study, we detect an inter-chromosomal insertional duplication in a female proband disrupting a topologically associating domain and causing an ultra-rare progressive form of heterotopic ossification. This structural variant lead to enhancer hijacking and misexpression of ARHGAP36 in fibroblasts, validated here by orthogonal in vitro studies. In addition, ARHGAP36 overexpression inhibits TGFß, and activates hedgehog signaling and genes/proteins related to extracellular matrix production. Our work on the genetic cause of this heterotopic ossification case has revealed that ARHGAP36 plays a role in bone formation and metabolism, outlining first details of this gene contributing to bone-formation and -disease.