Organization of gene programs revealed by unsupervised analysis of diverse gene-trait associations

Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity

Methods for cell clustering and gene expression from single-cell RNA sequencing (scRNA-seq) data are essential for biological interpretation of cell processes. Here, we present TRIAGE-Cluster which uses genome-wide epigenetic data from diverse bio-samples to identify genes demarcating cell diversity in scRNA-seq data. By integrating patterns of repressive chromatin deposited across diverse cell types with weighted density estimation, TRIAGE-Cluster determines cell type clusters in a 2D UMAP space. We then present TRIAGE-ParseR, a machine learning method which evaluates gene expression rank lists to define gene groups governing the identity and function of cell types. We demonstrate the utility of this two-step approach using atlases of in vivo and in vitro cell diversification and organogenesis. We also provide a web accessible dashboard for analysis and download of data and software. Collectively, genome-wide epigenetic repression provides a versatile strategy to define cell diversity and study gene regulation of scRNA-seq data.

New Drug Targets and Preclinical Modelling Recommendations for Treating Acute Myocardial Infarction

Acute myocardial infarction (AMI) is the leading cause of morbidity and mortality worldwide and the primary underlying risk factor for heart failure. Despite decades of research and clinical trials, there are no drugs currently available to prevent organ damage from acute ischaemic injuries of the heart. In order to address the increasing global burden of heart failure, drug, gene, and cell-based regeneration technologies are advancing into clinical testing. In this review we highlight the burden of disease associated with AMI and the therapeutic landscape based on market analyses. New studies revealing the role of acid-sensitive cardiac ion channels and other proton-gated ion channels in cardiac ischaemia are providing renewed interest in pre- and post-conditioning agents with novel mechanisms of action that may also have implications for gene- and cell-based therapeutics. Furthermore, we present guidelines that couple new cell technologies and data resources with traditional animal modelling pipelines to help de-risk drug candidates aimed at treating AMI. We propose that improved preclinical pipelines and increased investment in drug target identification for AMI is critical to stem the increasing global health burden of heart failure.

Methodological quality assessment of genetic studies on brain arteriovenous malformation related hemorrhage: A cross-sectional study

Objectives: Rupture of a brain arteriovenous malformation (bAVM) can cause intracranial hemorrhage and severe clinical outcomes. At present, the mechanisms of bAVM-related hemorrhage are poorly understood. This study aimed to summarize the potential genetic risk factors for bAVM-related hemorrhage and appraise the methodological quality of existing genetic studies on bAVM-related hemorrhage using a cross-sectional design. Methods: A systematic literature search was conducted on genetic studies associated with bAVM-related hemorrhage published in PubMed, Embase, Web of Science, China National Knowledge Internet, and Wangfang databases, up to November 2022. Subsequently, a cross-sectional study was performed to describe the potential candidate genetic variants of bAVM associated with risk of hemorrhage and to evaluate the methodological quality of the identified studies using the Newcastle-Ottawa quality assessment scale and Q-genie tool. Results: Of the 1811 records identified in the initial search, nine studies met the filtering criteria and were included. Twelve single nucleotide polymorphisms (SNPs), including IL6 rs1800795, IL17A rs2275913, MMP9 rs9509, VEGFA rs1547651, and EPHB4 rs314353, rs314308, and rs314313, were associated with bAVM-related hemorrhage. However, only 12.5% of the evaluated SNPs showed statistical power> 0.80 (α = 0.05). Methodological quality assessment revealed significant flaws in the designs of the included studies, such as less reliable representativeness of recruited individuals, short follow-up periods in cohort studies, and less comparability between groups of hemorrhagic and non-hemorrhagic patients. Conclusion: IL1B, IL6, IL17A, APOE, MMP9, VEGFA and EPHB4 were potentially associated with bAVM-related hemorrhage. The methodological designs of the analyzed studies required improvement in order to obtain more reliable results. Regional alliances and rare disease banks need to be established to recruit large numbers of bAVM patients (especially familial and extreme-trait cases) in a multicenter, prospective cohort study with an adequate follow-up period. Furthermore, it is important to use advanced sequencing techniques and efficient measures to filter candidate genetic variants.