Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

EPMA J. 2026 Aug 21;17(3):665-700. doi: 10.1007/s13167-026-00465-4. eCollection 2026 Sep.

ABSTRACT

Chronic atrophic gastritis (CAG) is a critical precancerous stage in the development of gastric cancer (GC). Circadian rhythm disruption perturbs the core clock gene network, including circadian locomotor output cycles kaput (CLOCK), brain and muscle ARNT-like 1 (BMAL1), period circadian protein homolog (PER), and cryptochrome (CRY). These alterations contribute to a multi-layered pathological cascade involving DNA damage accumulation, epigenetic remodeling, altered epithelial cell plasticity, cellular senescence, microbiota dysbiosis, tumor microenvironment remodeling, metabolic reprogramming, aberrant angiogenesis, and dysregulated cell death, thereby accelerating CAG to GC progression. However, existing studies have predominantly treated the circadian rhythm as a passive risk factor for disease onset and have yet to elevate it to an actionable interventional target within the full-course management of gastric precancerous lesions. Building on a systematic synthesis of the mechanistic evidence outlined above, this review proposes a predictive, preventive and personalised medicine (PPPM/3PM) three-tier management framework grounded in circadian-based individualised protection. At the predictive level, digital biomarkers (sleep-wake rhythms, light exposure, physical activity, and dietary behavior), multi-omics profiles, and circadian-related molecular signatures are integrated to achieve dynamic risk stratification of CAG populations. At the targeted prevention level, pharmacological agents and natural compounds with circadian-regulating potential are deployed to develop proactive protective strategies tailored to distinct pathological stages and circadian phenotypes. At the personalised treatment level, lifestyle interventions, chronotherapy, nano-carrier-based circadian-synchronised delivery, and dynamic biomarker monitoring are combined to formulate precision intervention regimens informed by individual circadian phenotypes. This framework repositions the circadian rhythm from a latent risk factor to a protectable and therapeutically targetable axis, offering new insights into time-optimised intervention strategies for the inflammation to cancer transition in CAG.

PMID:42682657 | PMC:PMC13530114 | DOI:10.1007/s13167-026-00465-4