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Cognitive Impairment Mechanisms in High-Altitude Exposure: Proteomic and Metabolomic Insights
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  • Qin Zhao
    Qin Zhao
    Department of Biobank, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
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    Orcidhttps://orcid.org/0000-0002-3519-9190
  • Jinli Meng
    Jinli Meng
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
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  • Li Feng
    Li Feng
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
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  • Suyuan Wang
    Suyuan Wang
    Department of Endocrinology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Suyuan Wang
  • Kejin Xiang
    Kejin Xiang
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Kejin Xiang
  • Yonghong Huang
    Yonghong Huang
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Yonghong Huang
  • Hengyan Li
    Hengyan Li
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Hengyan Li
  • Xiaomei Li
    Xiaomei Li
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Xiaomei Li
  • Xin Hu
    Xin Hu
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Xin Hu
  • Lu Che
    Lu Che
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
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  • Yongxing Fu
    Yongxing Fu
    Department of Cardiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Yongxing Fu
  • Liming Zhao
    Liming Zhao
    Department of Cardiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    More by Liming Zhao
  • Yunhong Wu*
    Yunhong Wu
    Department of Endocrinology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    *Email: [email protected]
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  • Wanlin He*
    Wanlin He
    Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    *Email: [email protected]
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Journal of Proteome Research

Cite this: J. Proteome Res. 2024, 23, 12, 5586–5599
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https://doi.org/10.1021/acs.jproteome.4c00841
Published November 20, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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High-altitude exposure can adversely affect neurocognitive functions; however, the underlying mechanisms remain elusive. Why and how does high-altitude exposure impair neurocognitive functions, particularly sleep? This study seeks to identify the molecular markers and mechanisms involved, with the goal of forming prevention and mitigation strategies for altitude sickness. Using serum proteomics and metabolomics, we analyzed blood samples from 23 Han Chinese plain dwellers before and after six months of high-altitude work in Tibet. The correlation analysis revealed biomarkers associated with cognitive alterations. Six months of high-altitude exposure significantly compromised cognitive function, notably, sleep quality. The key biomarkers implicated include SEPTIN5, PCBP1, STIM1, UBE2L3/I/N, amino acids (l/d-aspartic acid and l-glutamic acid), arachidonic acid, and S1P. Immune and neural signaling were suppressed, with sex-specific differences observed. This study innovatively identified GABA, arachidonic acid, l-glutamic acid, 2-arachidonoyl glycerol, and d-aspartic acid as biomarkers and elucidated the underlying mechanisms contributing to high-altitude-induced neurocognitive decline with a particular focus on sleep disruption. These findings pave the way for developing preventive measures and enhancing adaptation strategies. This study underscores the physiological significance of high-altitude adaptation, raising new questions about sex-specific responses and long-term consequences. It sets the stage for future research exploring individual variability and intervention efficacy.

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1. Introduction

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Hypoxia, the primary physiological challenge in high-altitude environments, profoundly disrupts aerobic metabolism and subsequently impacts both physiological and cognitive functions. As modern society has advanced, an increasing number of individuals are transiently or chronically exposed to high-altitude environments for reasons such as tourism and work. Long-term exposure to high altitudes is associated with various bodily dysfunctions, including cognitive dysfunction; (1) spatial memory impairment; (2) and deficits in attention, executive function, and memory. (3) On the other hand, acute exposure to high altitudes causes significant executive and memory deficits among healthy children, although these deficits recover three months after the return to low altitudes. (4) Exposure to high altitude results in cognitive deficits, brain edema, and oxidative stress manifestations in the hippocampi of rats. (5) Furthermore, acute hypoxia exposure at high altitudes can lead to neurological deficits through formaldehyde accumulation. (6) During initial exposure to high altitude, cognitive function declines, potentially followed by an improvement during the acclimatization phase; however, cognitive function ultimately decreases upon prolonged. (7) Insufficient sleep and cognitive decline frequently coincide with alterations in emotional states, with individuals potentially experiencing anxiety, depression, or irritability. (8) However, the understanding of the cognitive and physiological mechanisms among individuals exposed to high altitudes for six months is limited. For example, studies have shown that males and females may exhibit different physiological and cognitive responses to hypoxic conditions. (9) These differences could be due to variations in sex hormone levels, which influence oxidative stress and neuronal cell death. (10) Our previous research revealed that hypoxia negatively affects the hippocampus of Han Chinese individuals exposed to high altitudes. (11) Understanding the impacts of high-altitude exposure on the Han Chinese population and the underlying mechanisms facilitate the adoption of necessary preventative measures by individuals engaged in work or travel.
In recent years, metabolomics and proteomics, which are essential branches of systems biology, have provided novel insights and methodologies for understanding the impact of high-altitude exposure on human physiological functions. Metabolomics, which involves the study of changes in small molecule metabolites within organisms, can reflect metabolic responses following high-altitude exposure. For example, Liu et al. (12) reported an increase in circulating l-glutamine levels and decreases in l-glutamate and l-leucine levels after high-altitude exposure. Hu et al. (13) reported significant alterations in the plasma levels of short-chain fatty acids (SCFAs), bile acids (BAs), amino acids, neurotransmitters, and free fatty acids in rats subjected to hypobaric hypoxia. Conversely, proteomics focuses on protein expression, modification, and interactions, which are critical for understanding the regulation of life activities. Functional enrichment analysis of proteins that were significantly altered in human intestinal organs during hypoxia and reoxygenation revealed processes associated with mitochondrial metabolism, other metabolic pathways, and immune responses. (14) In hypoxic rats, significant changes in the plasma levels of 177 proteins and 33 metabolites were observed. (15) Proteomic and metabolomic integration revealed the pivotal role of arachidonic acid metabolism in the hypoxic response of the spleen in mice. (16) Previous studies have shown significant alterations in plasma metabolites and proteins under hypoxic conditions, elucidating the intricate biological responses involved. By combination of these omics approaches, a comprehensive understanding of the effects of high-altitude exposure on the metabolic network and protein expression profile of the human body, as well as an understanding of their interactions, can be obtained.
The present study aimed to elucidate the impact of hypoxic environments at high altitudes on cognitive functions and their underlying biological mechanisms. Responses to cognitive-related questionnaires and metabolite and protein alterations in the same group of individuals were measured and compared before and after exposure to high altitudes. This research not only improves our understanding of the physiological mechanisms of human adaptation to high-altitude environments but also provides a scientific basis for preventing and mitigating altitude-related diseases, thereby improving the quality of life for residents in those regions.

2. Methods

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2.1. Recruitment of Volunteers

A total of 23 individuals who had relocated from Chengdu to the Tibetan region (Amduo County [4828 m] and Nyima County [4645 m], Nagqu city) and resided at altitudes above 4600 m for at least six months from December 2020 to June 2022 were recruited (Table 1). The after-plateau exposure (APE) group comprised individuals from plain regions who were exposed to high-altitude conditions for six months. In contrast, the before plateau exposure (BPE) group consisted of the same population prior to exposure to high-altitude environments. Each volunteer provided informed consent. The participants completed the following questionnaires and tests before ascending to the plateau and upon returning to the plains: the Pittsburgh Sleep Quality Index (PSQI_RES), Self-Rating Depression Scale (SDS_Standard_Score), Zung Self-Rating Anxiety Scale (SAS_Standard_Score), Patient Health Questionnaire (PHQ_9_Score), Generalized Anxiety Disorder 7-item Scale (GAD_7_Score), Forward Digit Span Test (Anteroposterior_Score), Reverse Digit Span Test (Reverse_digit_Score), Montreal Cognitive Assessment (MoCA) total score (MoCAtotal_Score), Mini-Mental State Examination (MMSE) (MMSE_Score), Immediate and Delayed Logical Memory I scores (Memory_Immediately_Score and Memory_Delay_Score), and Immediate and Delayed Visual Memory I scores (VM_Immediately_Score and VM_Delay_Score). Blood samples (5 mL) were collected within 1 week before departing from Tibet and after returning to Chengdu. After centrifugation at 5000 rpm for 10 min, the serum was obtained and stored at −80 °C in the Biobank of the Chengdu Office of the People’s Government of the Tibet Autonomous Region. This study received approval from the Ethics Committee of the Hospital of the Chengdu Office of the People’s Government of the Tibet Autonomous Region (batch number: 2023-13). The study adhered to the principles outlined in the Declaration of Helsinki.
Table 1. Comparison of Demographic and Preexposure Clinical Characteristics of Subjects Exposed to High Altitudes
 totalfemalemale 
characteristicsmean ± SD or n (%)N = 18N = 5p.overall
nation: Han23 (100%)18 (100%)5 (100%)/
age39.1 (5.09)38.6 (3.78)40.8 (8.79)0.613
height160 (5.97)158 (3.50)169 (5.26)0.007
weight55.5 (8.23)51.9 (3.30)68.4 (7.70)0.007
BMI21.5 (1.95)20.8 (1.45)23.9 (1.59)0.008

2.2. Serum Proteomics Analysis

For protein processing and purification, 100 μL of serum was added to 900 μL of protein lysis buffer without sodium dodecyl sulfate (SDS) for denaturation and extraction. After purification, the protein samples were resuspended in 25 μL of 50 mM NH4HCO3, vortexed for 1 min, centrifuged for 1 min, and then quantified.
For protein enrichment, the dried proteins were resuspended in 20 μL of 50 mM ammonium bicarbonate and quantified. Protein purity was assessed by using SDS–polyacrylamide gel electrophoresis.
An equal amount of peptides from each sample was pooled into a mixture, and 20 μg of the mixture was diluted with 2 mL of mobile phase A (5% ACN, pH 9.8) for injection. Liquid chromatography-based separation was conducted using a Shimadzu LC-20AB HPLC system with a Gemini high pH C18 column.
The eluate was collected every minute, resulting in 10 fractions, which were frozen and dried. The dried peptide sample was resolubilized in mobile phase A (2% ACN and 0.1% FA) and centrifuged, and the supernatant was injected for separation using a Thermo UltiMate 3000 UHPLC system.
The separated peptide fragments were ionized and analyzed using a timsTOF Pro tandem mass spectrometer in data-independent acquisition (DIA) mode. The MSstats differential analysis was performed using R programming for the statistical evaluation of significant differences in protein levels between samples, with differentially expressed proteins (DEPs) identified according to the criteria of a fold change >1.5 and a P value <0.05.

2.3. Serum Metabolomics Analysis

Serum samples (100 μL, including quality control [QC] samples) were mixed with 700 μL of extraction solvent (methanol/acetonitrile/water, 4:2:1 v/v/v) containing an internal standard. After shaking for 1 min, the samples were incubated at −20 °C for 2 h. Following centrifugation at 25,000g for 15 min at 4 °C, 600 μL of the supernatant was transferred to a new tube, dried, and then dissolved in 180 μL of methanol/water (1:1 v/v) via vortex shaking for 10 min. After a second centrifugation step, the supernatant was transferred to a fresh tube. QC samples were created by combining 20 μL from each processed sample. Metabolites were separated using a Waters UPLC I-Class Plus system interfaced with a Q Exactive mass spectrometer employing a BEH C18 column (1.7 μm, 2.1 mm × 100 mm). The mobile phase composition differed for positive and negative ion modes, with formic acid in water and methanol for positive mode and ammonium formate in water and methanol for negative mode. A gradient elution method was used, varying from 2 to 98% of mobile phase B over time. The flow rate was 0.35 mL/min, the column temperature was 45 °C, and the injection volume was 5 μL. Mass spectrometric data were acquired on a Q Exactive mass spectrometer (Thermo Fisher Scientific) for both primary and secondary spectra. Parameters such as the scan range, resolution, and ionization conditions were optimized for the best performance. After acquisition, the data were analyzed using Compound Discoverer 3.3 software along with the BMDB, mzCloud, and ChemSpider databases, generating a comprehensive matrix of peak areas and metabolite identifications. The pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database to determine the primary biochemical pathways and signaling cascades related to the identified metabolites. Differentially expressed metabolites (DEMs) were identified according to the criteria of variable importance in projection (VIP) ≥ 1, fold change ≥ 1.2 or ≤ 0.83, and p < 0.05, as derived from the orthogonal partial least-squares discriminant analysis (OPLS-DA) model.

2.4. Bioinformatics Analysis

All bioinformatics analyses were conducted with R software. The “mixOmics” package in R was used to conduct partial least-squares discriminant analysis (PLS-DA). Distance-based redundancy analysis (dbRDA) was implemented with the rdacca.hp (17) package. Constrained ordination by inertia analysis (COIA) was performed using the ade4 (18) package. Procrustes analysis was performed with the vegan package. The KEGG pathway enrichment analysis was conducted by using the tidyverse package. For a comprehensive analysis of enriched pathways of both metabolites and proteins, we employed the RampDB platform (https://rampdb.nih.gov/about). Gene set enrichment analysis (GSEA) was performed with the GSEA software package. Key proteins and metabolites were identified by constructing via 10-fold 10-fold cross-validation with the random forest algorithm implemented through the R package “randomForest”. Furthermore, the metabolite network analysis was conducted using MetaboAnalyst (https://www.metaboanalyst.ca/faces/home.xhtml). The differential analysis between groups was performed using the reshape2 (19) and ggplot2 packages, with the t test method employed for statistical calculations. The scatter matrix correlation analysis was accomplished by using the PerformanceAnalytics package. The pathview (20) package was used to integrate protein expression profiles and metabolite data and visualize the KEGG pathway maps. The “ggpairs” function within R package GGally was employed to construct a matrix of comparative visualizations for paired variables. Graphical output was generated by using R software.

3. Results

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3.1. Assessment of the Effects of High-Altitude Exposure on Cognitive and Physiological Functions

We administered a range of questionnaires to assess cognitive performance both before and after exposure and to investigate the cognitive consequences of high-altitude exposure. The t test revealed significant changes in PSQI_RES scores specifically, indicating altered sleep patterns following exposure (Figure 1a). Furthermore, a correlation analysis between the scores of the questionnaires revealed strong associations between the PSQI_RES scores and the SDS_Standard_Score and PPHQ_9_Score (Figure 1b). These findings suggest that sleep quality is significantly affected by high-altitude exposure, potentially leading to altered cognitive and emotional states. Recent research conducted among Tibetan college students highlighted the associations between poor sleep quality and increased levels of anxiety and depression. (21) We performed a dbRDA correlation analysis between cognition-related questionnaires and proteomic and metabolomic data sets to obtain deeper insights into the relationships between cognition and the proteome and metabolome (Figure 1c,d). The findings indicated that MMSE_Score, PSQI_RES, and Reverse_Digit_Score presented the highest explanatory power for the proteome, whereas PSQI_RES, Memory_Delay_Score, and PHQ_9_Score presented the greatest explanatory capacity for the metabolome. We employed COIA and Procrustes analysis for the correlation analysis of proteomic and metabolomic data sets to gain deeper insights into the physiological effects of high-altitude exposure and the intricate relationships between proteins and metabolites in biological systems. The results indicated significant associations and concordance between the proteome and metabolome (Figure S1).

Figure 1

Figure 1. a. Intergroup differences in cognitive-related questionnaires or test scores before and after plateau exposure. ns., p > 0.05; ***, p < 0.001. (b) Correlation analysis between questionnaires or tests. X, p > 0.05. (c) Distance-based Redundancy Analysis (dbRDA) of proteomics (dots) and questionnaire test variables (arrows). (d) Distance-based Redundancy Analysis (dbRDA) of metabolomics (dots) and questionnaire test variables (arrows).

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3.2. Impacts of High-Altitude Exposure on Proteomic and Metabolomic Profiles

PLS-DA revealed a distinct separation between the APE and BPE groups (Figure 2a,d). Fifteen proteins were upregulated, whereas 137 proteins were downregulated (Figure 2b). We conducted a KEGG enrichment analysis and calculated the differential abundance score (DAS) to obtain additional insights into the functions of these proteins. Our findings revealed that the following pathways were significantly downregulated by high-altitude exposure: neurodegenerative disease; immune system; infectious disease; bacterial-related pathways, such as ubiquitin-mediated proteolysis; Parkinson’s disease; the Hippo signaling pathway-fly; Salmonella infection; legionellosis; pathways of neurodegeneration-multiple diseases; SNARE interactions in vesicular transport; platelet activation; and shigellosis (Figure 2c). GSEA revealed a pronounced enrichment of proteins implicated in G protein-coupled receptor (GPCR) downstream signaling in the APE group, whereas proteins associated with the immune system and Rho GTPase-mediated signaling were significantly enriched in the BPE group (Figure S2). These findings suggest that prolonged exposure to high altitudes may influence physiological functions through the modulation of signal transduction pathways and immune responses.

Figure 2

Figure 2. Basic information on proteomic and metabolomics bioinformatics analysis. a. Partial least-squares discriminant analysis (PLSDA) score plot based on serum proteomic data. b. Volcano plot of differentially expressed proteins between APE and BPE. c. Top 20 KEGG enrichment of the 152 differentially expressed proteins. d. Partial least-squares discriminant analysis (PLSDA) score plot based on serum metabolome data. e. Volcano plot of differentially expressed metabolites comparing APE vs BPE. f. Top 20 KEGG enrichment of the 201 differentially expressed metabolites.

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Remarkably, after six months of exposure to high altitude, 45 metabolites were upregulated, whereas 156 metabolites were downregulated (Figure 2e). A KEGG enrichment analysis was performed to obtain deeper insights, revealing significant enrichment in the following metabolic pathways: pentose and glucuronate conversions; GABAergic synaptic transmission; phospholipase D signaling; long-term potentiation; FcγR-mediated phagocytosis; arachidonic acid metabolism; glutathione metabolism; cysteine and methionine metabolism; d-amino acid metabolism; alanine, aspartate, and glutamate metabolism; taurine and hypotaurine metabolism; and retrograde endocannabinoid signaling. These pathways belong to various KEGG subclasses, including the immune system, nervous system functions, amino acid metabolism, carbohydrate metabolism, lipid metabolism, and signal transduction (Figure 2f). Intriguingly, these pathways were downregulated in individuals exposed to high altitudes.

3.3. Mechanisms Underlying the Effect of Hypoxia on Cognitive Function

We extracted proteins and metabolites specifically related to cognitive function from the functional enrichment results (Table S3). We constructed a Sankey diagram to visualize the cognition-related pathways and the associated DEPs and DEMs between the APE and BPE groups (Figure 3a). The results revealed that the calcium signaling pathway, the cellular response to hypoxia, and the ferroptosis pathways were jointly regulated by both proteins and metabolites.

Figure 3

Figure 3. a. Sankey diagram of cognitive-related pathways, differentially expressed proteins (DEPs), and metabolites (DEMs) enriched in KEGG and rampdb Web sites, respectively. b.Paired difference t-test of DEPs between APE and BPE groups. c. Paired difference t-test of DEMs between APE and BPE groups. d. Spearman correlation analysis of proteins and metabolites involved in cognitive-related pathways.

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We assessed the changes in proteins and metabolites before and after exposure to high altitude by conducting paired t tests (two-sided) on individual samples (Figure 3b,c). We performed Spearman correlation analysis to further investigate the relationships among these cognition-related molecules. Except for SNCA, Gamma-Aminobutyric Acid (GABA), 2-arachidonoyl glycerol, and oxoglutaric acid, which presented limited correlations with other metabolites and proteins, most of the other metabolites and proteins exhibited significant correlations (Figure 3d).
SEPTIN5, PCBP1, STIM1, UBE2L3, UBE2I, UBE2N, l-glutamic acid, l-aspartic acid, arachidonic acid, d-aspartic acid, and d-erythro-sphingosine 1-phosphate (S1P) were identified by random forest analysis as potential indicators of cognitive alterations in response to chronic hypoxia, with significant downregulation occurring after high-altitude exposure (Figure 3b,c,d; Figure S3). These molecules play pivotal roles in brain metabolism and function, and their dysregulation contributes to the molecular mechanisms underlying neurocognitive pathologies. We analyzed the differences in these biomarkers between males and females to better understand their universality. The results revealed no significant differences between the sexes, suggesting that the adaptations of these biomarkers to hypoxia are not sex-specific (Figure S4). The marked decrease in these biomarkers in individuals from lowland populations exposed to high altitudes may be related to the body’s response to the hypoxic environment, suggesting their potential as biomarkers for the cognitive changes associated with high-altitude exposure.

3.4. Sex-Specific Effects of High-Altitude Exposure on Females

A sex-stratified t test revealed significant increases in PSQI_RES scores for both women and men following high-altitude exposure (Figure S5a), indicating a pronounced impact on sleep quality. Notably, women presented significantly higher Memory_Delay_Score values after high-altitude exposure than did men (Figure S5b). In contrast, there was a significant decrease in women’s Memory_Immediate_Score before and after high-altitude exposure was observed (Figure S5c), suggesting sex-specific differences in the impact of high-altitude exposure on logical memory.
In the present study, female volunteers constituted more than 70% of the participants, prompting a sex-specific reanalysis to focus primarily on the impact of the plateau environment on women. An intersection of the enriched KEGG pathways among the different comparison groups (Figure 4a) revealed that, regardless of sex, proteins that regulate ubiquitin-mediated proteolysis, Parkinson’s disease, neurodegeneration pathways (multiple diseases), SNARE interactions in vesicular transport, platelet activation, and shigellosis pathways are all affected by the high-altitude environment. Metabolome-regulated FcγR-mediated phagocytosis, long-term depression, the phospholipase D signaling pathway, d-amino acid metabolism, and arachidonic acid metabolism are affected by a high altitude. These pathways prominently impact the neurocognitive functions of the organism. However, glutathione metabolism is concurrently modulated by both metabolomic and proteomic factors, as depicted in Figure 4a (Figure S7a). Notably, metabolic variations in glutathione metabolism persist before and after high-altitude exposure but can also be used to distinguish between females before and after exposure (Figures S6b and S7c). Additionally, proteomic disparities in glutathione metabolism emerged between males and females after high-altitude exposure, with downregulation observed in males (Figures S6c and S7b). Compared with neurons in male patients, neurons in female patients exhibit greater resistance to oxidative stress. (22) These findings underscore the pivotal role of glutathione metabolism in high-altitude adaptation, which is potentially associated with oxidative stress responses.

Figure 4

Figure 4. a. Collection of significantly enriched KEGG pathways across comparison groups. APE-f: Female group after plateau exposure; BPE-f: Female group before plateau exposure; APE-m: Male group after plateau exposure; DEP: DEP-enriched KEGG pathways; DEM: DEM-enriched KEGG pathways. b. The network diagram for Spearman correlation analysis of DEM and DEP between APE-f and BPE-f group. Circles represent DEM and squares represent DEP. Red lines represent positive correlations and green lines represent negative correlations. The purple fonts in the figure represent metabolites or proteins involved in the regulation of neurocognitive functions under long-term hypoxia. Only the relationship pairs with p < 0.05 and |r| ≥ 0.7 are shown in the figure.

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We subsequently conducted a correlation network analysis encompassing all DEPs and DEMs between the females in the APE (APE-f) group and the females in the BPE (BPE-f) group to elucidate the underlying molecular regulatory mechanisms before and after high-altitude exposure. Notably, a significant positive correlation was observed among the majority of DEPs and DEMs, which may be attributed to the concerted downregulation of numerous proteins and metabolites following prolonged high-altitude exposure (Figure 4b). This coordinated regulation likely reflects the efforts of the body to maintain homeostasis by modulating multiple metabolic pathways and protein expression in response to environmental pressures at high altitudes. Among the metabolites identified as being associated with neurocognitive alterations, eicosapentaenoic acid, l-glutamic acid, and S1P displayed numerous statistically significant interactions with various proteins. However, the proteins associated with neurocognitive alterations, including UBE2L3, VASP, and SEPTIN5 had the great number of associations with the differentially abundant metabolites. After females were exposed to the plateau, they adapted to environmental stress through complex molecular regulatory networks, which involved coordinated changes in multiple metabolic pathways and protein expression.
In the proteomic analysis comparing the APE and BPE groups, the Alzheimer’s disease, estrogen signaling, tight junction, and hepatitis C pathways were not significantly enriched (p < 0.05). However, when the APE-f group was compared with the BPE-f group, these protein-modulated pathways were significantly enriched (Figure S6). These findings suggest a distinct role for these protein-regulated pathways in the adaptation of females to high-altitude environments. In the context of metabolomic enrichment, the efferocytosis pathway was not significantly enriched in the comparison between the APE and BPE groups (p < 0.05). However, it was significantly enriched in the comparison between APE-f and BPE-f groups. Importantly, there was no overlap in the enriched pathways of the APE vs BPE and APE-f vs BPE-f comparisons. These findings suggest the existence of a unique molecular mechanism underlying metabolism in women adapting to high-altitude environments (Figure 4 and Figure S6b). After high-altitude exposure, a significant decrease in the Memory_Immediate_Score was observed among women (Figure S5c), and these enriched pathways were suppressed (Figure S6b), indicating their potential regulation by the hypoxic environment of the plateau and subsequent impact on cognitive function among women.
Owing to significant differences in the Memory_Delay_Score between men and women following exposure to the plateau, we also focused on proteomic and metabolomic changes in both sexes. The results revealed distinct adaptations to hypoxia in men and women after high-altitude exposure (APE-f vs APE in males [APE-m]) (Figure S6c). Pathways such as HIF-1 signaling, glutathione metabolism, and glycerophospholipid metabolism, which were enriched in the proteome, have been reported to play crucial roles in the effects of high-altitude exposure and are associated with cognitive function. On the other hand, the cAMP signaling pathway and tyrosine metabolism, which were enriched in the metabolome, exhibited significant metabolite differences between men and women after high-altitude exposure (Figure S6d). Notably, women presented significantly higher Memory_Delay_Score values after high-altitude exposure than men did (Figure S5b). Both proteomics and metabolomics revealed significantly enriched pathways that were downregulated, suggesting that the suppression of these pathways may play a positive role in women’s adaptation to the plateau environment.

3.5. Mechanisms Underlying the Effect of Hypoxia on Sleep Quality

Exposure to high altitudes poses significant challenges to individuals accustomed to lower elevations, particularly in terms of sleep. (23) When the APE and BPE groups were compared and stratified by sex, significant differences in sleep quality were observed among the overall population, males, and females following exposure to high altitudes. A correlation analysis was performed between core proteins and metabolites and PSQI_RES to gain deeper insights into the relationships between sleep and hypoxia-related biomarkers. A significant correlation was not observed between the core protein levels and the PSQI_RES score. Significant associations were identified between GABA, arachidonic acid, l-glutamic acid, 2-arachidonoyl glycerol, and d-aspartic acid expressions and PSQI_RES (Figure 5). In contrast to proteins, metabolites, which are direct products of biochemical reactions within organisms, may provide a more immediate reflection of physiological alterations and energetic metabolic states during sleep. The Rampdb pathway enrichment analysis revealed that BMAL1:CLOCK and NPAS2 activate circadian gene expression and that circadian clock pathways are closely associated with sleep. The serum metabolite arachidonic acid is implicated in these pathways and was significantly differentially expressed between the APE and BPE groups. The accumulation of arachidonic acid during chronic hypoxia-induced damage and its increased expression at high altitudes hint at a pivotal role in modulating the hypoxia response and its consequences for sleep quality among exposed individuals. These findings suggest that the poor sleep quality observed in Han Chinese individuals during prolonged high-altitude exposure may be correlated with arachidonic acid expressions. Our analysis of sex differences in these biomarkers revealed that GABA expression differed significantly between males and females after high-altitude exposure, whereas other sleep-related metabolites did not differ significantly between the sexes (Figure S8). Therefore, we speculate that GABA may play a role in the physiological activities related to the differences in cognition between males and females during high-altitude exposure.

Figure 5

Figure 5. Pearson correlation analysis between PSQI_res and the key metabolites. *, p < 0.05; ***, p < 0.001

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4. Discussion

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4.1. High-Altitude Exposure and Decreased Sleep Quality

Exposure to high altitude results in the suppression of most metabolic and proteomic pathways, with more severe effects observed in women. Hypoxia and high altitude can impact various organs, leading to impairments in crucial physiological functions. (24) Acute hypoxia exposure at high altitude can induce numerous adverse neurological outcomes, including paralysis, blindness, sleep disorders, mental disorders, cognitive impairments, (6) hippocampal neurodegeneration, and memory deficits. (25) Significant sleep disturbances among Han Chinese individuals exposed to high altitude occurred in both males and females and were jointly regulated by proteomic and metabolic pathways. Although inconsistent changes in logical memory were observed between the sexes, overall women appeared to be more affected, possibly because of the greater proportion of female participants in our study. Future research with a larger sample size is warranted to confirm these findings. Our previous research revealed that hypoxia caused by high-altitude exposure negatively impacts the hippocampus in Han Chinese individuals, although these effects may not be sufficient to cause a statistically significant reduction in hippocampal volume. (26) Additionally, our other cognitive questionnaires did not reveal significant cognitive impairments resulting from high-altitude exposure. This finding might indicate the presence of more refined regulatory mechanisms. On the one hand, high-altitude adaptation mechanisms may help individuals maintain cognitive function under hypoxic conditions. (27) On the other hand, factors such as the duration of exposure might also play a role. (28) Six months of high-altitude exposure can affect cognitive function in Han Chinese individuals but is unlikely to result in significant cognitive changes. However, long-term exposure may yield different results.
A cross-sectional study among Tibetan college students residing at high altitudes revealed that individuals with moderate to poor sleep quality were more susceptible to anxiety disorders. (29) Furthermore, we investigated the role of various molecules, including GABA, arachidonic acid, l-glutamic acid, 2-arachidonoyl glycerol, and d-aspartic acid, in adaptation to high-altitude environments and their potential effects on sleep mechanisms. Notably, GABA is known to regulate vascular tone, blood pressure, anxiety, mood, and sleep. Our findings indicate that high-altitude exposure increases GABA levels, aiding the brain in adapting to low oxygen through adaptive physiological responses. (30) The observed differences in GABA levels between males and females may reflect sex-specific physiological responses to hypoxic conditions. Additionally, arachidonic acid has been reported to be associated with poor sleep quality and an insufficient or excessive sleep duration. (31) l-glutamic acid has been reported to be associated with sleep regulation. (32) Sleep deprivation activates the endocannabinoid system, leading to an increase in 2-arachidonoyl glycerol levels in the body. (33) Furthermore, reduced levels of aspartic acid have been observed in the hippocampus of rats experiencing sleep fragmentation. (34) Notably, alterations in d-aspartic acid metabolism have been implicated in neuropsychiatric disorders. (11) Our study confirms that high-altitude exposure can impact cognitive function, emphasizing the importance of understanding the mechanisms of cognitive alterations to prevent mental stress and mitigate the damage caused by high-altitude exposure.

4.2. Physiological Alterations Associated with High-Altitude Exposure

Exposure to high altitude profoundly impacts both proteomic and metabolomic profiles, resulting in significant correlations and concordances across the two omics layers. Hypoxia, a condition prevalent at high altitudes and observed in various pathological scenarios such as trauma, stroke, inflammation, autoimmunity, and neurodegenerative diseases, can lead to severe brain damage, resulting in cognitive, learning, or memory deficits. (35) Recently, Li et al. (36) conducted a combined proteomic and metabolomic analysis to investigate the mechanisms underlying brain dysfunction induced by hypoxia stress in yellow catfish. Furthermore, Chen et al. (37) reported increased susceptibility to to bodily fatigue under hypoxic conditions at high altitudes, which affects both the peripheral muscles and the central nervous system (CNS). Acute exposure to high altitude triggers the upregulation of inflammatory signaling pathways, leading to increased expression of inflammation-related genes involved in immune sensitization. (38) Enrichment analyses of affected pathways revealed that high-altitude exposure significantly disrupted the functioning of the nervous and immune systems in individuals accustomed to lower altitudes.
Research has demonstrated changes in energy metabolism following high-altitude exposure, with the downregulation of glycolysis and upregulation of alternative metabolic pathways. (39) Consistent with these findings, our study revealed a decrease in pyruvic acid and lactic acid levels after high-altitude exposure, highlighting persistent effects on energy metabolism.
The present study investigates the influence of high-altitude exposure on critical biomolecules and metabolic networks within the human body. Central to our investigation are l-glutamic acid, l-aspartate, and GABA─critical excitatory and inhibitory neurotransmitters that regulate neuronal function in the CNS. Notably, we observed marked decrease in the levels of these neurotransmitters following high-altitude exposure. The neurotransmitter l-glutamic acid is significantly depleted following subacute traumatic brain injury, as reported in a previous study. (40) Furthermore, a reduction in l-aspartic acid levels has been correlated with the severity of Alzheimer’s disease. (41) GABA, another neurotransmitter, exerts neuroprotective effects by mitigating the adverse impacts of neural injury, thereby safeguarding neuronal cells from further damage. (42) An increase in GABA levels may represent a compensatory response. In addition to neurotransmitter alterations, notable changes, predominantly downregulation, have been observed in metabolites and proteins associated with neurocognitive function after high-altitude exposure. d-Aspartic acid is currently recognized as a modulator of neuronal transmission and hormone secretion. (43)
We acknowledge that the relatively small sample size of male participants may limit the robustness of our sex-specific findings. However, despite this limitation, our results suggest that the potential protein and metabolic biomarkers related to cognitive changes caused by high-altitude exposure are not sex-specific, with the exception of GABA. Decreased levels of l-glutamic acid, l-aspartic acid, and d-aspartic acid may impair neurotransmitter synthesis, consequently reducing the efficiency of signal transduction between neurons. Additionally, reduced levels of S1P have been implicated in the dysregulation of neural signaling, (44) potentially compromising neuronal protective mechanisms and synaptic function. Moreover, the abnormal levels of arachidonic acid, which are associated with the pathology of Alzheimer’s disease (AD), (45,46) observed in our high-altitude-exposed cohort may have led to diminished neuroprotective mechanisms and increased neuronal sensitivity to hypoxic injury. Intriguingly, a decrease in SEPTIN5 protein levels has been correlated with an increased degree of neurofibrillary pathology. (47) This downregulation of SEPTIN5 may indirectly contribute to neurocognitive health by modulating autophagy and amyloid-β (Aβ) levels. (48) PCBP1, which regulates erythrocytic iron storage and heme biosynthesis, (49) is downregulated under hypoxic conditions, potentially disrupting normal mRNA processing and translation and thereby affecting the synthesis of various neurotransmitters and neuromodulatory proteins. Moreover, the concerted action of UBE2N, UBE2L3, and UBE2D2/3 in facilitating Parkinson’s disease-mediated mitophagy (50) can lead to the accumulation of deleterious proteins or the depletion of essential proteins. These molecules play pivotal roles in cytoskeletal stability, mRNA processing, calcium homeostasis, protein degradation, neurotransmitter synthesis and transmission, and lipid signaling. The altered expression patterns of these proteins reflect adaptive adjustments and potential damage to the brain under hypoxic conditions.
Exposure to high altitudes in females elicits notable variations in protein and metabolite profiles, which collaboratively modulate the body’s physiological responses to the altered environment. Proteins play a unique role in the adaptation of females to high-altitude environments by regulating critical pathways such as those involved in Alzheimer’s disease and estrogen signaling. Hypoxia impairs mitochondrial metabolism in microglia from patients with Alzheimer’s disease through HIF1. (51) Crosstalk between estrogen signaling and hypoxia-dependent signaling pathways has been identified, with interactions between estrogen signaling and HIF-1α and between estrogen signaling and HIF-2α. (52) Although the HIF1 protein expression did not differ significantly between the groups in this study, its role in hypoxic environments cannot be overlooked. As a key regulator of hypoxic responses, HIF1 may indirectly influence the adaptation of females to high altitudes by modulating other proteins and pathways. Cellular responses to hypoxia, such as energy deficiency and increased metabolic demands, may involve the regulation of the tight junction pathway, affecting intercellular communication and material exchange. Future studies should further explore these relationships to identify novel therapeutic strategies. Additionally, these findings underscore the importance of studying female health in high-altitude environments, particularly with respect to cognitive function and metabolic adaptation.

4.3. Glutathione Metabolism: A Critical Regulatory Role in High-Altitude Exposure

Glutathione metabolism, a pivotal intracellular pathway, plays a crucial role in various biological processes such as antioxidant defense, detoxification, and energy generation. In challenging plateau environments characterized by hypoxia and cold exposure, organisms utilize multiple mechanisms to adapt to these extreme conditions. Previous research has indicated that glutathione metabolism might play a significant role in the adaptation of Tibetan sheep to hypoxic and cold environments. (53) In our study, the glutathione metabolism pathway was found to be concurrently regulated by both metabolites and proteins, and this pathway was suppressed following exposure to the plateau. Notably, sex-specific differences were observed in response to plateau exposure, which might reflect distinct physiological and pathological changes during human adaptation to hypoxic conditions. These changes encompass oxidative stress responses, metabolic adjustments, protein function regulation, and alterations in disease susceptibility. Sex-specific differences introduce a layer of complexity in the role of glutathione metabolism in plateau adaptation. Previous studies have reported that estrogen protects against high-altitude polycythemia, (54) whereas male plateau residents have higher ferritin levels promoting erythrocyte proliferation. (55) By further exploring these mechanisms, we aim to develop novel strategies to enhance human adaptation to plateau environments, thereby improving the health outcomes of residents and travelers. Additionally, these studies provide valuable insights into the sex-specific strategies employed by the human body in response to extreme environments.

5. Limitations of the Study

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While the present study provides valuable insights into the molecular markers and mechanisms underlying neurocognitive and sleep impairments associated with high-altitude exposure, several limitations should be acknowledged. First, the study population consisted exclusively of Han Chinese plain dwellers, limiting the generalizability of the findings to other ethnicities or populations accustomed to lower altitudes. Additional research with more diverse samples is needed to confirm the universality of the identified biomarkers and pathways. Second, the duration of high-altitude exposure was six months, which, while substantial, may not fully capture the long-term effects of continuous altitude exposure. Further research with more diverse samples is needed to confirm the universality of the identified biomarkers and pathways. Additionally, the study relied solely on serum proteomics and metabolomics, neglecting potential changes in other tissues or body fluids that may also contribute to the observed effects. Finally, the study focused on the associations between biomarkers and cognitive alterations but did not establish causality. Experimental manipulation or interventional studies are needed to definitively determine the roles of the identified biomarkers in mediating the neurocognitive and sleep impairments observed at high altitudes.

6. Conclusions

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Following exposure to high altitude, neurocognitive sleep is most profoundly impacted, irrespective of sex. This exposure significantly altered both the metabolomic and proteomic profiles of the participants, indicating potential interactions and correlations between these two systems. SEPTIN5, PCBP1, STIM1, UBE2L3, UBE2I, UBE2N, l-glutamic acid, l-aspartic acid, arachidonic acid, d-aspartic acid, and S1P have emerged as potential biomarkers of cognitive changes associated with high-altitude exposure. Notably, GABA, arachidonic acid, l-glutamic acid, 2-arachidonoyl glycerol, and d-aspartic acid may jointly regulate sleep in this context. Additionally, high-altitude exposure impacts the suppression of the immune system and neural-related pathways. Glutathione metabolism, which is concurrently modulated by metabolites and proteins, provides insights into diverse physiological and pathological adaptations to hypoxic conditions at high altitudes.

Data Availability

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The data of this study have been deposited into the OMIX of China National Center for Bioinformation (CNCB) (56) with accession number PRJCA024705 (OMIX006479 and OMIX006492) and is publicly available as of the date of publication. The R code used in this study can be found on Github (https://github.com/langlibaitiaoshuafeidao/High-Altitude-Effects-on-Plains-Brains-Proteomic-Metabolomic-Clues).

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jproteome.4c00841.

  • COIA and Procrustes analysis between proteomics and metabolomics (Figure S1); GSEA enrichment analysis of DEP (Figure S2); top 30 protein and metabolic predictors of high-altitude exposure based on random forest variable importance (Figure S3); Log2FC values of cognitive-related proteins and metabolites, illustrating the changes between male and female groups before and after plateau exposure (Figure S4); bar charts of t test analysis and differentially expressed proteins and metabolites grouped by gender (Figure S5); top 20 KEGG enrichments of DEPs and DEMs in various comparison groups related to high-altitude exposure (Figure S6); KEGG pathway diagram and expression values of proteins and metabolites involved in glutathione metabolism (Figure S7); Log2FC values of metabolites in APE-f/APE-m and BPE-f/BPE-m comparing male and female groups before and after plateau exposure (Figure S8) (PDF)

  • annotation for the differentially expressed proteins (Table S1); annotation for the differentially expressed metabolites (Table S2); and results of pathway enrichment analysis of differentially expressed metabolites and differentially expressed proteins conducted on the rampdb web site (Table S3) (XLSX)

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Author Information

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  • Corresponding Authors
    • Yunhong Wu - Department of Endocrinology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China;  Email: [email protected]
    • Wanlin He - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China;  Email: [email protected]
  • Authors
    • Qin Zhao - Department of Biobank, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China;  Orcidhttps://orcid.org/0000-0002-3519-9190
    • Jinli Meng - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Li Feng - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Suyuan Wang - Department of Endocrinology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Kejin Xiang - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Yonghong Huang - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Hengyan Li - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Xiaomei Li - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Xin Hu - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Lu Che - Department of Radiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Yongxing Fu - Department of Cardiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
    • Liming Zhao - Department of Cardiology, Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital.C.T.), 20 Ximianqiao Rd, Chengdu, Sichuan Province 610041, China
  • Author Contributions

    Qin Zhao and Jinli Meng contributed equally to this work. Conceptualization: Qin Zhao, Jinli Meng, Yunhong Wu, and Wanlin He; Data curation: Qin Zhao, Suyuan Wang, and Wanlin He; Formal analysis: Jinli Meng and Yunhong Wu; Funding acquisition: Wanlin He; Investigation: Li Feng, Suyuan Wang, Kejin Xiang, Yonghong Huang, Hengyan Li, Xiaomei Li, Xin Hu, Lu Che, Yongxing Fu, and Liming Zhao; Methodology: Jinli Meng, Yunhong Wu, and Wanlin He; Project administration: Wanlin He; Resources: Jinli Meng, Li Feng, Suyuan Wang, Kejin Xiang, Yonghong Huang, Hengyan Li, Xiaomei Li, Xin Hu, Lu Che, Yongxing Fu, Liming Zhao, and Yunhong Wu; Software: Li Feng, Suyuan Wang, and Wanlin He; Supervision: Li Feng, Suyuan Wang, and Yunhong Wu; Validation: Qin Zhao and Wanlin He; Visualization: Qin Zhao; Writing─original draft: Qin Zhao; Writing─review and editing: Qin Zhao, Jinli Meng, and Wanlin He.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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This work was financially sponsored by the Science and Technology Department of Tibet, the central government guides local projects (XZ202301YD0041C and XZ202202YD0011C); Science and Technology Department of Tibet, Nature Science Foundation (XZ202401ZR0081 and XZ202301ZR0049G); Hospital-level Project of the Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (2022-YJ-10); and Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G01).

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  • Abstract

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    Figure 1

    Figure 1. a. Intergroup differences in cognitive-related questionnaires or test scores before and after plateau exposure. ns., p > 0.05; ***, p < 0.001. (b) Correlation analysis between questionnaires or tests. X, p > 0.05. (c) Distance-based Redundancy Analysis (dbRDA) of proteomics (dots) and questionnaire test variables (arrows). (d) Distance-based Redundancy Analysis (dbRDA) of metabolomics (dots) and questionnaire test variables (arrows).

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    Figure 2

    Figure 2. Basic information on proteomic and metabolomics bioinformatics analysis. a. Partial least-squares discriminant analysis (PLSDA) score plot based on serum proteomic data. b. Volcano plot of differentially expressed proteins between APE and BPE. c. Top 20 KEGG enrichment of the 152 differentially expressed proteins. d. Partial least-squares discriminant analysis (PLSDA) score plot based on serum metabolome data. e. Volcano plot of differentially expressed metabolites comparing APE vs BPE. f. Top 20 KEGG enrichment of the 201 differentially expressed metabolites.

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    Figure 3

    Figure 3. a. Sankey diagram of cognitive-related pathways, differentially expressed proteins (DEPs), and metabolites (DEMs) enriched in KEGG and rampdb Web sites, respectively. b.Paired difference t-test of DEPs between APE and BPE groups. c. Paired difference t-test of DEMs between APE and BPE groups. d. Spearman correlation analysis of proteins and metabolites involved in cognitive-related pathways.

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    Figure 4

    Figure 4. a. Collection of significantly enriched KEGG pathways across comparison groups. APE-f: Female group after plateau exposure; BPE-f: Female group before plateau exposure; APE-m: Male group after plateau exposure; DEP: DEP-enriched KEGG pathways; DEM: DEM-enriched KEGG pathways. b. The network diagram for Spearman correlation analysis of DEM and DEP between APE-f and BPE-f group. Circles represent DEM and squares represent DEP. Red lines represent positive correlations and green lines represent negative correlations. The purple fonts in the figure represent metabolites or proteins involved in the regulation of neurocognitive functions under long-term hypoxia. Only the relationship pairs with p < 0.05 and |r| ≥ 0.7 are shown in the figure.

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    Figure 5

    Figure 5. Pearson correlation analysis between PSQI_res and the key metabolites. *, p < 0.05; ***, p < 0.001

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      Ferreira, C. B.; Marttinen, M.; Coelho, J. E.; Paldanius, K. M. A.; Takalo, M.; Mäkinen, P.; Leppänen, L.; Miranda-Lourenço, C.; Fonseca-Gomes, J.; Tanqueiro, S. R.; Vaz, S. H.; Belo, R. F.; Sebastião, A. M.; Leinonen, V.; Soininen, H.; Pike, I.; Haapasalo, A.; Lopes, L. V.; de Mendonça, A.; Diógenes, M. J.; Hiltunen, M. S327 phosphorylation of the presynaptic protein SEPTIN5 increases in the early stages of neurofibrillary pathology and alters the functionality of SEPTIN5. Neurobiol. Dis. 2022, 163, 105603  DOI: 10.1016/j.nbd.2021.105603
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      March-Diaz, R.; Lara-Ureña, N.; Romero-Molina, C.; Heras-Garvin, A.; Ortega-de San Luis, C.; Alvarez-Vergara, M. I.; Sanchez-Garcia, M. A.; Sanchez-Mejias, E.; Davila, J. C.; Rosales-Nieves, A. E.; Forja, C.; Navarro, V.; Gomez-Arboledas, A.; Sanchez-Mico, M. V.; Viehweger, A.; Gerpe, A.; Hodson, E. J.; Vizuete, M.; Bishop, T.; Serrano-Pozo, A.; Lopez-Barneo, J.; Berra, E.; Gutierrez, A.; Vitorica, J.; Pascual, A. Hypoxia compromises the mitochondrial metabolism of Alzheimer’s disease microglia via HIF1. Nat. Aging 2021, 1, 385– 399,  DOI: 10.1038/s43587-021-00054-2
      51
      Hypoxia compromises the mitochondrial metabolism of Alzheimer's disease microglia via HIF1
      March-Diaz Rosana; Lara-Urena Nieves; Romero-Molina Carmen; Heras-Garvin Antonio; Ortega-de San Luis Clara; Alvarez-Vergara Maria I; Sanchez-Garcia Manuel A; Rosales-Nieves Alicia E; Forja Cristina; Navarro Victoria; Sanchez-Mico Maria V; Viehweger Adrian; Vizuete Marisa; Lopez-Barneo Jose; Vitorica Javier; Pascual Alberto; Romero-Molina Carmen; Sanchez-Mejias Elisabeth; Davila Jose C; Navarro Victoria; Gomez-Arboledas Angela; Sanchez-Mico Maria V; Vizuete Marisa; Lopez-Barneo Jose; Gutierrez Antonia; Vitorica Javier; Romero-Molina Carmen; Navarro Victoria; Sanchez-Mico Maria V; Vizuete Marisa; Vitorica Javier; Heras-Garvin Antonio; Ortega-de San Luis Clara; Sanchez-Garcia Manuel A; Sanchez-Mejias Elisabeth; Davila Jose C; Gomez-Arboledas Angela; Gutierrez Antonia; Sanchez-Mejias Elisabeth; Davila Jose C; Gomez-Arboledas Angela; Gutierrez Antonia; Viehweger Adrian; Gerpe Almudena; Berra Edurne; Hodson Emma J; Bishop Tammie; Serrano-Pozo Alberto
      Nature aging (2021), 1 (4), 385-399 ISSN:.
      Genetic Alzheimer's disease (AD) risk factors associate with reduced defensive amyloid β plaque-associated microglia (AβAM), but the contribution of modifiable AD risk factors to microglial dysfunction is unknown. In AD mouse models, we observe concomitant activation of the hypoxia-inducible factor 1 (HIF1) pathway and transcription of mitochondrial-related genes in AβAM, and elongation of mitochondria, a cellular response to maintain aerobic respiration under low nutrient and oxygen conditions. Overactivation of HIF1 induces microglial quiescence in cellulo, with lower mitochondrial respiration and proliferation. In vivo, overstabilization of HIF1, either genetically or by exposure to systemic hypoxia, reduces AβAM clustering and proliferation and increases Aβ neuropathology. In the human AD hippocampus, upregulation of HIF1α and HIF1 target genes correlates with reduced Aβ plaque microglial coverage and an increase of Aβ plaque-associated neuropathology. Thus, hypoxia (a modifiable AD risk factor) hijacks microglial mitochondrial metabolism and converges with genetic susceptibility to cause AD microglial dysfunction.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB2s7ms1aluw%253D%253D&md5=049b9700c60840887e21fd46e6f6cc56
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      Protective role of estrogen against excessive erythrocytosis in Monge's disease
      Azad, Priti; Villafuerte, Francisco C.; Bermudez, Daniela; Patel, Gargi; Haddad, Gabriel G.
      Experimental & Molecular Medicine (2021), 53 (1), 125-135CODEN: EMMEF3; ISSN:2092-6413. (Nature Research)
      Monge's disease (chronic mountain sickness (CMS)) is a maladaptive condition caused by chronic (years) exposure to high-altitude hypoxia. One of the defining features of CMS is excessive erythrocytosis with extremely high hematocrit levels. In the Andean population, CMS prevalence is vastly different between males and females, being rare in females. Furthermore, there is a sharp increase in CMS incidence in females after menopause. In this study, we assessed the role of sex hormones (testosterone, progesterone, and estrogen) in CMS and non-CMS cells using a well-characterized in vitro erythroid platform. While we found that there was a mild (nonsignificant) increase in RBC prodn. with testosterone, we obsd. that estrogen, in physiol. concns., reduced sharply CD235a+ cells (glycophorin A; a marker of RBC), from 56% in the untreated CMS cells to 10% in the treated CMS cells, in a stage-specific and dose-responsive manner. At the mol. level, we detd. that estrogen has a direct effect on GATA1, remarkably decreasing the mRNA (mRNA) and protein levels of GATA1 (p < 0.01) and its target genes (Alas2, BclxL, and Epor, p < 0.001). These changes result in a significant increase in apoptosis of erythroid cells. We also demonstrate that estrogen regulates erythropoiesis in CMS patients through estrogen beta signaling and that its inhibition can diminish the effects of estrogen by significantly increasing HIF1, VEGF, and GATA1 mRNA levels. Taken altogether, our results indicate that estrogen has a major impact on the regulation of erythropoiesis, particularly under chronic hypoxic conditions, and has the potential to treat blood diseases, such as high altitude severe erythrocytosis.
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  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jproteome.4c00841.

    • COIA and Procrustes analysis between proteomics and metabolomics (Figure S1); GSEA enrichment analysis of DEP (Figure S2); top 30 protein and metabolic predictors of high-altitude exposure based on random forest variable importance (Figure S3); Log2FC values of cognitive-related proteins and metabolites, illustrating the changes between male and female groups before and after plateau exposure (Figure S4); bar charts of t test analysis and differentially expressed proteins and metabolites grouped by gender (Figure S5); top 20 KEGG enrichments of DEPs and DEMs in various comparison groups related to high-altitude exposure (Figure S6); KEGG pathway diagram and expression values of proteins and metabolites involved in glutathione metabolism (Figure S7); Log2FC values of metabolites in APE-f/APE-m and BPE-f/BPE-m comparing male and female groups before and after plateau exposure (Figure S8) (PDF)

    • annotation for the differentially expressed proteins (Table S1); annotation for the differentially expressed metabolites (Table S2); and results of pathway enrichment analysis of differentially expressed metabolites and differentially expressed proteins conducted on the rampdb web site (Table S3) (XLSX)


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