Biology subjects

Reisner, Y.

Publications and source records attributed to Reisner, Y..

3 recordsLinked to original sources

bioRxiv2025

Comprehensive Survey of Gut Microbiome Associations with Health Conditions in the Human Phenotype Project

The human gut microbiome is increasingly implicated with diverse health conditions, highlighting the importance of developing comprehensive resources to systematically map these associations. In this study, we leveraged the Human Phenotype Project (HPP) 10K cohort, a large, deeply phenotyped population study cohort with extensive metagenomic profiling, to explore associations between the gut microbiome and 37 health indications. These include conditions with established or emerging links to the microbiome, such as obesity, diabetes, hyperlipidemia, metabolic syndrome, inflammation, liver disease, cardiovascular and kidney conditions, immune and allergic diseases, gastrointestinal symptoms, mental health, and sleep-related traits. Using a curated set of approximately 200 refined phenotypic features and analyzing 1,184 microbial species, we performed robust statistical association analyses. We observed significant enrichment of associations in 14 health indications, with most associations reflecting increased microbial abundance in favorable health states, thereby suggesting potential microbial targets for intervention. This work introduces a publicly available, high-resolution resource to facilitate future research and support the development of microbiome-informed health strategies.

genomics↗

bioRxiv2024

Genetic underpinnings of predicted changes in cardiovascular function using self supervised learning

BackgroundThe genetic underpinnings of cardiovascular disease remain elusive. Contrastive learning algorithms have recently shown cutting-edge performance in extracting representations from electrocardiogram (ECG) signals that characterize cross-temporal cardiovascular state. However, there is currently no connection between these representations and genetics. MethodsWe designed a new metric, denoted as Delta ECG, which measures temporal shifts in patients cardiovascular state, and inherently adjusts for inter-patient differences at baseline. We extracted this measure for 4,782 patients in the Human Phenotype Project using a novel self-supervised learning model, and quantified the associated genetic signals with Genome-Wide-Association Studies (GWAS). We predicted the expression of thousands of genes extracted from Peripheral Blood Mononuclear Cells (PBMCs). Downstream, we ran enrichment and overrepresentation analysis of genes we identified as significantly predicted from ECG. FindingsIn a Genome-Wide Association Study (GWAS) of Delta ECG, we identified five associations that achieved genome-wide significance. From baseline embeddings, our models significantly predict the expression of 57 genes in men and 9 in women. Enrichment analysis showed that these genes were predominantly associated with the electron transport chain and the same immune pathways as identified in our GWAS. ConclusionsWe validate a novel method integrating self-supervised learning in the medical domain and simple linear models in genetics. Our results indicate that the processes underlying temporal changes in cardiovascular health share a genetic basis with CVD, its major risk factors, and its known correlates. Moreover, our functional analysis confirms the importance of leukocytes, specifically eosinophils and mast cells with respect to cardiac structure and function.

systems biology↗

bioRxiv2022

Identification of a multipotent lung progenitor for lung regeneration

We recently showed that intravenous infusion of mouse or human, fetal or adult lung cells following conditioning of recipient mice leads to lung chimerism within alveolar and bronchiolar lineages, in distinct patches containing both epithelial and endothelial cells. We show here, using R26R-Confetti mice as donors, that these multi-lineage patches are derived from a single lung progenitor. FACS of adult mouse lung cells revealed that the putative patch-forming progenitors co-express the endothelial marker CD31 (PECAM-1) and the epithelial marker CD326 (EPCAM). Transplantation of lung cells from transgenic Cre/lox mice expressing nuclear GFP under the VEcad promoter (VEcad-Cre-nTnG), led to GFP+ patches comprising both GFP+ endothelial and epithelial cells in vivo, and in ex-vivo culture of CD326+CD31+ progenitors. Single cell RNA sequencing of CD326+CD31+ lung cells revealed a subpopulation expressing canonical epithelial and endothelial genes. Such double positive GFP+NKX2.1+SOX17+ cells were also detected by immunohistological staining in lungs of VEcad-Cre-nTnG (expressing nuclear GFP) mice in proximity to blood vessels. These findings provide new insights on lung progenitors and lung development and suggest a potential novel approach for lung regeneration. SummaryWe show in the present study, that multi-lineage regenerative patches in our transplantation model are derived from a single lung progenitor, co-expressing the endothelial marker CD31 and the epithelial marker CD326. These findings provide new insights on lung progenitors and lung development.

cell biology↗