# Exploring the molecular intersection for hypertension, hyperlipidemia and their comorbid conditions through multi-omics approaches

## TL;DR

This study explores how hypertension and hyperlipidemia interact at the molecular level using multi-omics data to identify key biomarkers and pathways for better diagnosis and treatment.

## Contribution

The study identifies novel biomarkers and intersecting metabolic pathways in hypertension and hyperlipidemia using integrated metabolomic and metagenomic analyses.

## Key findings

- Altered sphingolipids and phosphatidylcholines are linked to vascular and lipid metabolism changes.
- Microbial taxa like Escherichia coli and Bacteroides vulgatus correlate with lipid and carbohydrate metabolism deviations.
- Sphingomyelin d18:1/16:0 and d18:1/24:1(15Z) are potential diagnostic biomarkers across conditions.

## Abstract

Hypertension and hyperlipidemia are interconnected conditions that heighten cardiovascular risk, yet their intricate multi-scale molecular signatures remain inadequately mapped. This study aimed to conduct an integrated multi-omics investigation to unravel the key pathways and biomarkers underlying hypertension, hyperlipidemia, and both conditions.

Metabolomic analysis was performed on serum samples and metagenomic analysis on fecal samples collected from individuals with hypertension (n = 16), hyperlipidemia (n = 19), or both conditions concurrently (n = 20). In addition, 20 healthy individuals were recruited as controls.

Metabolomics uncovered altered levels of sphingolipids, phosphatidylcholines, glycylprolines, and nucleic acid metabolites, which may be associated with changes in vascular tone, lipid and protein homeostasis, and thyroid signaling. Metagenomics showed depletion in the abundance of the Fibrobacteres phylum. Altered abundances of Escherichia coli and Bacteroides vulgatus were also observed, which were correlated with deviations in lipid and carbohydrate metabolism. Sphingomyelin d18:1/16:0 and sphingomyelin d18:1/24:1(15Z) were the key metabolites that were identified as potential diagnostic biomarkers across conditions. Microbial taxa such as Enterococcus cecorum, Lachnospiraceae bacterium, Prevotella histicola, and Flavobacterium discriminated these diseases. Pathway analysis revealed glycoxylate, amino acid, purine, and sphingolipid metabolism alterations intersecting hypertension and hyperlipidemia.

This multi-omics landscape of comorbid disease pathways and biomarkers lays the foundation for precision diagnosis and treatment of prevalent cardiovascular conditions.