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Unveiling key pathways and potential biomarkers for high-altitude hypertension: a pilot multi-omics study
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  • Published: 24 February 2026

Unveiling key pathways and potential biomarkers for high-altitude hypertension: a pilot multi-omics study

  • Ju Huang1,2 na1,
  • Zhuoga Danzeng1,2,4 na1,
  • Luobu Gesang1,2,
  • Bai Ci1,2,
  • Yangzong Suona2,3,
  • Rui Zhang2,3,
  • Zhuoma Ciren2,
  • Chunyan Yuan2,
  • Yangjin Baima2,
  • Yuansheng Wang2,
  • Zhuoma Pubu2,
  • Panduo Zhuoma2,
  • Zhuoga Lamu2 &
  • …
  • Wangjie Suolang5 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biochemistry
  • Biomarkers
  • Cardiology

Abstract

High altitude has a considerable impact on the pathophysiology of the human cardiovascular system and disease occurrence. We aim to use an integrated approach of metabolomics and proteomics to reveal key pathways and biomarkers of hypertension at high altitude. Thirty Tibetan patients with hypertension and 30 healthy individuals residing on the Tibetan Plateau at a very high altitude (> 4500 m) were included in the study. Metabolomic analysis was conducted using Vanquish ultra-high performance liquid chromatography, while proteomic analysis utilized the timsTOF Pro2 mass spectrometer. Correlation analysis revealed key signaling pathways and biomarkers associated with hypertension in Tibetan patients. The results showed 87 differentially expressed metabolites and 61 differentially expressed proteins in individuals with hypertension at high altitude. The results of metabolomic differential metabolite pathway analysis indicated that Caffeine metabolism had the most significant impact. Specific metabolites like PI(16:0/16:0), Caffeine, and Plastoquinone 3 were found to be significantly up-regulated in hypertensive patients. The combination of five metabolites achieved an area under the curve (AUC) of 0.871 for hypertension prediction. Proteomic analysis revealed that the identified differential proteins primarily functioned in signaling receptor binding. It was confirmed that Creatine kinase B (CKB) and Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta (YWHAZ) could serve as a protein biomarker combination for hypertension in plateau regions, showing an AUC of 0.764 (0.585–0.944). Upon conducting an integrated analysis of metabolomics and proteomics, the combined AUC improved to 0.982 (0.949–1.000). A comprehensive analysis utilizing metabolomics and proteomics revealed that alterations in signal transduction-related pathways and lipid metabolism pathways were implicated in hypertension among plateau populations. Additionally, YWHAZ was observed as a potential biomarker for this condition.

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Data availability

All data associated with this study are present in the paper. The raw metabolomics data generated in this study are stored in the OMIX database at the National Center for Biological Information (accession number: OMIX005362). Raw proteomics data are stored in the iPROX database (accession number: IPX0007730001). We uphold the principles of open science and encourage collaborative exploration for legitimate research purposes. To ensure ethical compliance and protect privacy, data access requires prior approval through an application process. Researchers interested in utilizing the data should contact the corresponding author (kelsangnorbu@hotmail.com) with a clear statement of research objectives and a detailed data usage plan. We will evaluate each request and grant access to approved researchers. We appreciate your interest in this study and hope these data will advance further scientific discoveries.

Abbreviations

CV:

cardiovascular

GWAS:

Genome-Wide Association Studies

MYH9:

myosin heavy chain IIA

HC:

healthy controls

DIA:

data-independent acquisition

DDA:

data-dependent acquisition

LC-MS/MS:

liquid-liquid mass spectrometry

PRM:

Parallel reaction monitoring

OPLS-DA:

Orthogonal Partial Least Squares -Discriminant Analysis

ROC:

Receiver operating characteristic

RF:

random forest

PLS-DA:

partial least squares discriminant analysis

IGHV3-15:

immunoglobulin heavy variable 3-15

SCGB1A1:

Uteroglobin

IGLL1:

immunoglobulin lambda-like polypeptide 1

GXYLT2:

glucoside xylosyltransferase 2

SOD1:

superoxide dismutase [Cu-Zn]

LMNA:

prelamin-A/C

CTSG:

cathepsin G

CKB:

creatine kinase B-type

ACTG1:

actin, gamma 1

APOB:

apolipoprotein B

MPO:

myeloperoxidase

ACTN1:

alpha-actinin-1

C8A:

component C8 alpha chain

CRISP3:

cysteine-rich secretory protein 3

CTSG:

cathepsin G

YWHAZ:

tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta

APOF:

apolipoprotein F

AZGP1:

alpha-2-glycoprotein 1, zinc-binding

IGLV5-39:

immunoglobulin lambda variable 5-39

H2AC8:

histone H2A type 1-C/E/F/G/I

LMNA:

lamin A/C

PLTP:

phospholipid transfer protein

SERPINA11:

serpin family A member 11

CKB:

creatine kinase B 1, zinc-binding

ECM1:

extracellular matrix protein 1

VNN1:

vanin 1

LTA4H:

leukotriene A4 hydrolase

GXYLT2:

glucoside xylosyltransferase 2

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Acknowledgements

The study was supported by the Tibet Autonomous Region People’s Hospital. We are very grateful to the research team for their valuable contribution to this study. Also, thanks to “BIOTREE” for assisting in the experimental detection and analysis.

Funding

This research was supported by Science and Technology Projects of Xizang Autonomous Region, China (NO.XZ202401JD0013, NO.XZ202201ZY0018G, NO.XZ202501YD0014).

Author information

Author notes

  1. These authors contributed equally to this work and share first authorship: Ju Huang and Zhuoga Danzeng.

Authors and Affiliations

  1. High Altitude Medical Research Institute, People’s hospital of Xizang Autonomous Region, Lhasa, 850000, China

    Ju Huang, Zhuoga Danzeng, Luobu Gesang & Bai Ci

  2. People’s Hospital of Xizang Autonomous Region, 18 Linguo North Road, Lhasa, 850000, China

    Ju Huang, Zhuoga Danzeng, Luobu Gesang, Bai Ci, Yangzong Suona, Rui Zhang, Zhuoma Ciren, Chunyan Yuan, Yangjin Baima, Yuansheng Wang, Zhuoma Pubu, Panduo Zhuoma & Zhuoga Lamu

  3. Key Laboratory of Translational Medicine for Human Adaptation to the High-altitude of Xizang Autonomous Region, Lhasa, 850000, China

    Yangzong Suona & Rui Zhang

  4. Xizang Autonomous Region Clinical Research Center for High Altitude Diseases, Lhasa, 850000, China

    Zhuoga Danzeng

  5. Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850000, China

    Wangjie Suolang

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Contributions

Luobu Gesang contributed to the study’s conceptualization, funding acquisition, project administration, supervision, and specifically, the critical review of this article. Ju Huang and Zhuoga Danzeng conducted data curation, formal analysis, investigation, methodology, and the original draft writing. Bai Ci and Yangzong Suona assisted with research data, original draft writing, and gave a lot of valuable opinions. Bai Ci, Zhuoma Ciren, Chunyan Yuan, and Panduo Zhuoma contributed to the investigation and resources of study materials provision. Rui Zhang, Yangjin Baima, Yuansheng Wang, Zhuoma Pubu, Zhuoga Lamu, and Wangjie Suolang contributed to the Investigation of data collection.

Corresponding author

Correspondence to Luobu Gesang.

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Huang, J., Danzeng, Z., Gesang, L. et al. Unveiling key pathways and potential biomarkers for high-altitude hypertension: a pilot multi-omics study. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38806-y

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  • Received: 01 July 2025

  • Accepted: 31 January 2026

  • Published: 24 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38806-y

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Keywords

  • High altitude
  • Hypoxia
  • Hypertension
  • Metabolomics
  • Proteomics
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