Evidence map›Paper›PMID 42405211›Full record

ReviewImmune network2026

Respiratory Microbiome Remodeling in Aging: Implications for Immunosenescence and Therapeutic Intervention.

Seong-Mook Jung, Wonkeon Sunwoo, Young Min Son

Abstract readReview
In one paragraph

Review in Immune network, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Seong-Mook JungDepartment of Systems Biotechnology, Chung-Ang University, Anseong 17456, Korea.ORCID https://orcid.org/0009-0000-0250-6775
Wonkeon SunwooDepartment of Systems Biotechnology, Chung-Ang University, Anseong 17456, Korea.
Young Min SonDepartment of Systems Biotechnology, Chung-Ang University, Anseong 17456, Korea.ORCID https://orcid.org/0000-0003-2978-8703

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging involves progressive declines in lung structure and immune function, increasing the incidence and severity of respiratory diseases and reducing vaccine responsiveness. Meanwhile, the respiratory tract harbors a dynamic microbial ecosystem that contributes to immune homeostasis and colonization resistance. Growing evidence indicates that aging disrupts this host-microbe balance within the respiratory tract; however, the mechanisms and therapeutic implications remain incompletely integrated. This review summarizes age-related remodeling of the respiratory microbiome. Beyond compositional shifts, aging alters microbial functions, including metabolic output and resilience to perturbation, exhibiting downstream effects on epithelial barriers, mucus clearance, and immune priming. Furthermore, as the microbiome-immune axis is modifiable, microbiome-targeted therapies represent key opportunities to restore respiratory homeostasis during aging. These interventions, combined with senescence- and cytokine-directed immunomodulation and vaccine optimization using adjuvants and mucosal immune-informed designs, may reduce infection burden and chronic lung disease progression in older populations. Together, this review highlights that a deeper understanding of age-related respiratory microbiome remodeling and its interplay with immunosenescence will be essential for the rational design of microbiome-informed therapies.

Indexed as

AgingHost microbial interactionsImmunosenescenceMicrobiome-targeted therapiesMicrobiotaMucosal immunityRespiratory system

Identifiers

PMID42405211
PMCPMC13333243

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.