---
title: "Tissue-resident immune cells and genetic risk in autoimmune and lung diseases"
id: "nature-immunology-1-tissue-resident-immune-cells-drive-genetic-risk-in-autoimmune-and-lung-diseases"
canonical_url: "https://medichelpline.com/clinical-feed/nature-immunology-1-tissue-resident-immune-cells-drive-genetic-risk-in-autoimmune-and-lung-diseases"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Nature Immunology"
source_url: "https://www.nature.com/articles/s41590-026-02596-2"
published_at: "2026-08-03T12:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Tissue-resident immune cells and genetic risk in autoimmune and lung diseases
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/nature-immunology-1-tissue-resident-immune-cells-drive-genetic-risk-in-autoimmune-and-lung-diseases
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Nature Immunology
- **Source URL:** [Original Journal Publication](https://www.nature.com/articles/s41590-026-02596-2)
- **Published At:** 2026-08-03T12:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The study generated a large single-cell transcriptomic dataset of **1,150,336** immune cells from **120** surgically resected human lung tissue samples (mean 9,255 cells per individual) to enable high-resolution expression quantitative trait locus (**eQTL**) mapping in tissue immune cells. - Five major immune populations were FACS-enriched from each lung sample to ensure representation and permit unbiased clustering, revealing **29 transcriptionally distinct immune cell subsets** among CD45+ tissue-resident immune cells. - The authors performed single-cell eQTL analysis across the 29 lung immune cell subsets to link common genetic variants to gene expression in tissue-resident immune cells, addressing the gap left by blood-focused eQTL studies and bulk tissue analyses. - Colocalization analyses compared lung immune cell eQTLs with genome-wide association study (**GWAS**) signals for lung diseases, infectious diseases and autoimmune diseases, identifying disease-associated variants and their target genes that act in a single or restricted group of cell types. - Several genes, including **ZFP57**, showed significant colocalization between lung immune cell eQTLs and GWAS signals across multiple systemic and organ-restricted autoimmune diseases, indicating shared genetic mechanisms mediated via tissue immune cells. - The lung was selected as a model tissue because of sample accessibility from surgical resections, its central role in respiratory infection and target status in many immune-mediated diseases, and because tissue-resident immune cells share core regulatory and transcriptional features across organs. - The dataset and findings are presented as a resource for studying how disease-associated variants influence gene expression in **tissue-resident immune cell** types, with a public access point referenced ().
## Clinical Analysis & Structured Key Points
Loading [MathJax]/jax/output/HTML-CSS/config.js ## Your privacy, your choice We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media, as well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection. See our [privacy policy](https://www.nature.com/info/privacy) for more information on the use of your personal data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies [Skip to main content](https://www.nature.com/articles/s41590-026-02596-2#content) Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement [ ![Nature Immunology](https://media.springernature.com/full/nature-cms/uploads/product/ni/header-ce329d5b570f961b651db20c364a103a.svg) ](https://www.nature.com/ni) * [ View all journals ](https://www.nature.com/siteindex) * [ Saved research ](https://www.nature.com/saved-research) * [ Search ](javascript:;) ## Search Search articles by subject, keyword or author Show results from All journals This journal Search [ Advanced search ](https://www.nature.com/search/advanced) ### Quick links * [Explore articles by subject](https://www.nature.com/subjects) * [Find a job](https://www.nature.com/naturecareers) * [Guide to authors](https://www.nature.com/authors/index.html) * [Editorial policies](https://www.nature.com/authors/editorial_policies/) * [Log in](https://idp.nature.com/auth/personal/springernature?redirect_uri=https://www.nature.com/articles/s41590-026-02596-2) * [ Content Explore content ](javascript:;) ## Explore content * [ Research articles ](https://www.nature.com/ni/research-articles) * [ Reviews & Analysis ](https://www.nature.com/ni/reviews-and-analysis) * [ News & Comment ](https://www.nature.com/ni/news-and-comment) * [ Videos ](https://www.nature.com/ni/video) * [ Current issue ](https://www.nature.com/ni/current-issue) * [ Collections ](https://www.nature.com/ni/collections) * [Follow us on X ](https://twitter.com/NatImmunol) * [Sign up for alerts ](https://journal-alerts.springernature.com/subscribe?journal_id=41590) * [ RSS feed ](https://www.nature.com/ni.rss) * [ About the journal ](javascript:;) ## About the journal * [ Aims & Scope ](https://www.nature.com/ni/aims) * [ Journal Information ](https://www.nature.com/ni/journal-information) * [ Journal Metrics ](https://www.nature.com/ni/journal-impact) * [ About the Editors ](https://www.nature.com/ni/editors) * [ Research Cross-Journal Editorial Team ](https://www.nature.com/ni/research-cross-journal-editorial-team) * [ Reviews Cross-Journal Editorial Team ](https://www.nature.com/ni/reviews-cross-journal-editorial-team) * [ Our publishing models ](https://www.nature.com/ni/our-publishing-models) * [ Editorial Values Statement ](https://www.nature.com/ni/editorial-values-statement) * [ Editorial Policies ](https://www.nature.com/ni/editorial-policies) * [ Content Types ](https://www.nature.com/ni/content) * [ Web Feeds ](https://www.nature.com/ni/web-feeds) * [ Posters ](https://www.nature.com/ni/posters) * [ Contact ](https://www.nature.com/ni/contact) * [ Publish with us ](javascript:;) ## Publish with us * [ Submission Guidelines ](https://www.nature.com/ni/submission-guidelines) * [ For Reviewers ](https://www.nature.com/ni/for-reviewers) * [ Language editing services ](https://authorservices.springernature.com/go/sn/?utm_source=For+Authors&utm_medium=Website_Nature&utm_campaign=Platform+Experimentation+2022&utm_id=PE2022) * [Open access funding](https://www.nature.com/ni/open-access-funding) * [Submit manuscript ](https://mts-ni.nature.com/cgi-bin/main.plex) * [ Sign up for alerts ](https://journal-alerts.springernature.com/subscribe?journal_id=41590) * [ RSS feed ](https://www.nature.com/ni.rss) 1. [nature](https://www.nature.com/) 2. [nature immunology](https://www.nature.com/ni) 3. [resources](https://www.nature.com/ni/articles?type=resource) 4. article Tissue-resident immune cells drive genetic risk in autoimmune and lung diseases [ Download PDF ](https://www.nature.com/articles/s41590-026-02596-2.pdf) [ Download PDF ](https://www.nature.com/articles/s41590-026-02596-2.pdf) * Resource * [Open access](https://www.springernature.com/gp/open-science/about/the-fundamentals-of-open-access-and-open-research) * Published: 03 August 2026 # Tissue-resident immune cells drive genetic risk in autoimmune and lung diseases * [Benjamin J. Schmiedel](https://www.nature.com/articles/s41590-026-02596-2#auth-Benjamin_J_-Schmiedel-Aff1) [ORCID: orcid.org/0000-0002-9103-9378](https://orcid.org/0000-0002-9103-9378)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Cristian Gonzalez-Colin](https://www.nature.com/articles/s41590-026-02596-2#auth-Cristian-Gonzalez_Colin-Aff1-Aff2)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[2](https://www.nature.com/articles/s41590-026-02596-2#Aff2), * [Vicente Fajardo-Rosas](https://www.nature.com/articles/s41590-026-02596-2#auth-Vicente-Fajardo_Rosas-Aff1-Aff2) [ORCID: orcid.org/0000-0002-1578-7438](https://orcid.org/0000-0002-1578-7438)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[2](https://www.nature.com/articles/s41590-026-02596-2#Aff2), * [Job Rocha](https://www.nature.com/articles/s41590-026-02596-2#auth-Job-Rocha-Aff1-Aff3) [ORCID: orcid.org/0000-0002-1292-2307](https://orcid.org/0000-0002-1292-2307)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[3](https://www.nature.com/articles/s41590-026-02596-2#Aff3), * [Hayley Simon](https://www.nature.com/articles/s41590-026-02596-2#auth-Hayley-Simon-Aff1)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Johannes Ottensmeier](https://www.nature.com/articles/s41590-026-02596-2#auth-Johannes-Ottensmeier-Aff1) [ORCID: orcid.org/0009-0003-7081-7964](https://orcid.org/0009-0003-7081-7964)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Ignacio E. Ramírez-Bernabé](https://www.nature.com/articles/s41590-026-02596-2#auth-Ignacio_E_-Ram_rez_Bernab_-Aff1)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [April Cano](https://www.nature.com/articles/s41590-026-02596-2#auth-April-Cano-Aff1) [ORCID: orcid.org/0009-0006-4324-0727](https://orcid.org/0009-0006-4324-0727)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Angel De la Cruz Castillo](https://www.nature.com/articles/s41590-026-02596-2#auth-Angel-De_la_Cruz_Castillo-Aff1-Aff4)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[4](https://www.nature.com/articles/s41590-026-02596-2#Aff4), * [Elizabeth Márquez-Gómez](https://www.nature.com/articles/s41590-026-02596-2#auth-Elizabeth-M_rquez_G_mez-Aff1-Aff4) [ORCID: orcid.org/0009-0009-5669-9432](https://orcid.org/0009-0009-5669-9432)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[4](https://www.nature.com/articles/s41590-026-02596-2#Aff4), * [Brendan Ha](https://www.nature.com/articles/s41590-026-02596-2#auth-Brendan-Ha-Aff1)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Jason A. Greenbaum](https://www.nature.com/articles/s41590-026-02596-2#auth-Jason_A_-Greenbaum-Aff1) [ORCID: orcid.org/0000-0002-1381-0390](https://orcid.org/0000-0002-1381-0390)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Lindsey Chudley](https://www.nature.com/articles/s41590-026-02596-2#auth-Lindsey-Chudley-Aff5) [ORCID: orcid.org/0000-0002-5202-7104](https://orcid.org/0000-0002-5202-7104)[5](https://www.nature.com/articles/s41590-026-02596-2#Aff5), * [Judith Cave](https://www.nature.com/articles/s41590-026-02596-2#auth-Judith-Cave-Aff6)[6](https://www.nature.com/articles/s41590-026-02596-2#Aff6), * [Aiman Alzetani](https://www.nature.com/articles/s41590-026-02596-2#auth-Aiman-Alzetani-Aff6-Aff7)[6](https://www.nature.com/articles/s41590-026-02596-2#Aff6),[7](https://www.nature.com/articles/s41590-026-02596-2#Aff7), * [Edwin Woo](https://www.nature.com/articles/s41590-026-02596-2#auth-Edwin-Woo-Aff6)[6](https://www.nature.com/articles/s41590-026-02596-2#Aff6), * [Michael Shackcloth](https://www.nature.com/articles/s41590-026-02596-2#auth-Michael-Shackcloth-Aff8) [ORCID: orcid.org/0000-0002-6494-9907](https://orcid.org/0000-0002-6494-9907)[8](https://www.nature.com/articles/s41590-026-02596-2#Aff8), * [Serena J. Chee](https://www.nature.com/articles/s41590-026-02596-2#auth-Serena_J_-Chee-Aff5-Aff8)[5](https://www.nature.com/articles/s41590-026-02596-2#Aff5),[8](https://www.nature.com/articles/s41590-026-02596-2#Aff8), * [Vivek Chandra](https://www.nature.com/articles/s41590-026-02596-2#auth-Vivek-Chandra-Aff1)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1), * [Mitchell Kronenberg](https://www.nature.com/articles/s41590-026-02596-2#auth-Mitchell-Kronenberg-Aff1-Aff9) [ORCID: orcid.org/0000-0001-6318-6445](https://orcid.org/0000-0001-6318-6445)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[9](https://www.nature.com/articles/s41590-026-02596-2#Aff9), * [Bjoern Peters](https://www.nature.com/articles/s41590-026-02596-2#auth-Bjoern-Peters-Aff1-Aff10) [ORCID: orcid.org/0000-0002-8457-6693](https://orcid.org/0000-0002-8457-6693)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[10](https://www.nature.com/articles/s41590-026-02596-2#Aff10), * [Christian H. Ottensmeier](https://www.nature.com/articles/s41590-026-02596-2#auth-Christian_H_-Ottensmeier-Aff1-Aff5-Aff11) [ORCID: orcid.org/0000-0003-3619-1657](https://orcid.org/0000-0003-3619-1657)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[5](https://www.nature.com/articles/s41590-026-02596-2#Aff5),[11](https://www.nature.com/articles/s41590-026-02596-2#Aff11), * [Anusha-Preethi Ganesan](https://www.nature.com/articles/s41590-026-02596-2#auth-Anusha_Preethi-Ganesan-Aff1-Aff12) [ORCID: orcid.org/0000-0003-3775-9996](https://orcid.org/0000-0003-3775-9996)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[12](https://www.nature.com/articles/s41590-026-02596-2#Aff12) & * … * [Pandurangan Vijayanand](https://www.nature.com/articles/s41590-026-02596-2#auth-Pandurangan-Vijayanand-Aff1-Aff10) [ORCID: orcid.org/0000-0001-7067-9723](https://orcid.org/0000-0001-7067-9723)[1](https://www.nature.com/articles/s41590-026-02596-2#Aff1),[10](https://www.nature.com/articles/s41590-026-02596-2#Aff10) Show authors [_Nature Immunology_](https://www.nature.com/ni) (2026) [Cite this article](https://www.nature.com/articles/s41590-026-02596-2#citeas) [ Save article ](https://www.nature.com/articles/s41590-026-02596-2/save-research?_csrf=crjxJK-oVcm535BSpTpqILs2toG-tQ3o) [ View saved research ](https://www.nature.com/saved-research) ## Abstract Common genetic variants are associated with risk of lung and autoimmune diseases. However, we have a limited understanding of the pathological effects of these disease variants, specifically in tissue-resident immune cells at the frontier of infection and disease in the lung. To address this, we performed single-cell expression quantitative trait locus (eQTL) analysis across 29 distinct immune cell subsets isolated from lung tissue. Colocalization analysis of lung immune cell eQTLs with genome-wide association study (GWAS) signals from lung diseases, and infectious and autoimmune diseases, implicate disease-associated variants and their target genes functioning in a single or restricted group of cell types. Several genes, including _ZFP57_ , showed significant colocalization between lung immune cell eQTLs and GWAS signals from multiple systemic and organ-restricted autoimmune diseases, highlighting shared genetic mechanisms underlying the risk of disease. Overall, our study shows that disease-associated variants from a wide range of autoimmune diseases impact gene expression in tissue-resident immune cell types ( ). ## Main Genetic factors play a key role in determining the risk of infectious and immune-mediated diseases, and can be leveraged to identify pathological mechanisms and new targets for diagnostics, prognostics and therapies[1](https://www.nature.com/articles/s41590-026-02596-2#ref-CR1 "Kwok, A. J., Mentzer, A. & Knight, J. C. Host genetics and infectious disease: new tools, insights and translational opportunities. Nat. Rev. Genet. 22, 137–153 \(2021\)."),[2](https://www.nature.com/articles/s41590-026-02596-2#ref-CR2 "Seldin, M. F. The genetics of human autoimmune disease: a perspective on progress in the field and future directions. J. Autoimmun. 64, 1–12 \(2015\)."). The genetic risk linked to diseases can be captured in an unbiased way by genome-wide association studies (GWAS), which have identified genetic variants accounting for a significant fraction of the heritable risk associated with a wide range of immune-mediated diseases or traits[3](https://www.nature.com/articles/s41590-026-02596-2#ref-CR3 "Yao, D. W., O’Connor, L. J., Price, A. L. & Gusev, A. Quantifying genetic effects on disease mediated by assayed gene expression levels. Nat. Genet. 52, 626–633 \(2020\)."). However, connecting these disease-risk variants to functional outcomes, and thereby identifying disease mechanisms and therapeutic targets, has been challenging. This is mainly due to the lack of studies in the disease-relevant cell types mediating the pathological effects of the variants. As the effects of genetic variants on gene expression can be highly cell type-specific[4](https://www.nature.com/articles/s41590-026-02596-2#ref-CR4 "Schmiedel, B. J. et al. Impact of genetic polymorphisms on human immune cell gene expression. Cell 175, 1701–1715 \(2018\)."), it is important to survey a broad set of disease-relevant cell types. Recent single-cell profiling studies of human tissues affected by infectious and immune-mediated diseases, along with functional studies in animal models, have implicated various tissue-resident immune cell types such as tissue-resident-memory T cells (TRM cells), B resident-memory cells (BRM cells), tissue-resident natural killer (NK) cells and macrophages as key drivers of barrier immunity and tissue pathology[5](https://www.nature.com/articles/s41590-026-02596-2#ref-CR5 "Li, J., Xiao, C., Li, C. & He, J. Tissue-resident immune cells: from defining characteristics to roles in diseases. Signal. Transduct. Target. Ther. 10, 12 \(2025\)."). However, due to the ease of sampling blood, most expression quantitative trait locus (eQTL) studies to determine how risk variants influence gene expression in specific cell types have focused on analyzing immune cell types in the blood, overlooking those that are primarily resident in the tissues. Meanwhile, studies that analyzed diverse, unseparated cell types in whole tissues lack the resolution needed to identify effects of disease-risk variants that are specific to tissue immune cell types[6](https://www.nature.com/articles/s41590-026-02596-2#ref-CR6 "GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 \(2020\)."). To address these issues, eQTL studies in purified populations of immune cells isolated from tissues of interest are needed. The human lung represents an ideal tissue source for studying effects of disease-risk variants in immune cells for several reasons: (1) a sufficient amount of unaffected tissue can be obtained from living individuals undergoing surgery for early stage cancer; (2) lung immunity plays a crucial role in respiratory infections; (3) the lung is the primary target tissue for many immune-mediated diseases such as asthma, chronic obstructive pulmonary disease (COPD) and sarcoidosis; (4) the lungs can be affected in some patients with multi-organ autoimmune diseases, including rheumatoid arthritis, lupus erythematosus and scleroderma; and (5) tissue-resident immune cells across different organs share a core _cis_ -regulatory landscape and transcriptional features[7](https://www.nature.com/articles/s41590-026-02596-2#ref-CR7 "Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 \(2017\)."), such that effects observed in one organ can be extrapolated to others. ## Results ### Single-cell atlas of lung immune cell types Although several single-cell lung atlases have been reported (Supplementary Table [1](https://www.nature.com/articles/s41590-026-02596-2#MOESM4)), limitations due to the number of cells and individuals studied preclude high-resolution eQTL analysis of various lung immune cell types. Therefore, we first generated a large-scale single-cell transcriptomic dataset of 1,150,336 immune cells isolated from surgically resected lung tissue samples of 120 living individuals (mean of 9,255 cells per individual; Fig. [1a–d](https://www.nature.com/articles/s41590-026-02596-2#Fig1)). We ensured representation of different immune cell types from each individual by sorting sufficient numbers of the five major immune cell populations in the lung tissue (Fig. [1b](https://www.nature.com/articles/s41590-026-02596-2#Fig1), Extended Data Figs. [1](https://www.nature.com/articles/s41590-026-02596-2#Fig6) and [2](https://www.nature.com/articles/s41590-026-02596-2#Fig7) and Supplementary Tables [2](https://www.nature.com/articles/s41590-026-02596-2#MOESM5) and [3](https://www.nature.com/articles/s41590-026-02596-2#MOESM6)). Unbiased clustering analyses of each cell type revealed 29 transcriptionally distinct immune cell subsets (Fig. [1b](https://www.nature.com/articles/s41590-026-02596-2#Fig1), Extended Data Fig. [3](https://www.nature.com/articles/s41590-026-02596-2#Fig8) and Supplementary Table [4](https://www.nature.com/articles/s41590-026-02596-2#MOESM7)), which showed substantial variations in the relative proportions across individuals (Fig. [1c](https://www.nature.com/articles/s41590-026-02596-2#Fig1)). **Fig. 1: Single-cell atlas of lung immune cell types.** ![Fig. 1: Single-cell atlas of lung immune cell types.](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41590-026-02596-2/MediaObjects/41590_2026_2596_Fig1_HTML.png) [Full size image](https://www.nature.com/articles/s41590-026-02596-2/figures/1) **a** , Study overview. **b** , Single-cell transcriptomes of the FACS-enriched, predefined immune cell populations displayed by Uniform Manifold Approximation and Projection (UMAP) and colored according to their specific cell subsets as determined by unbiased clustering analysis. The bar charts show the fractions of cells in the indicated cell subsets for each predefined immune cell population. IFNR, interferon receptor; ITGAE, integrin subunit α E (CD103); KIR, killer-cell immunoglobulin-like receptor; MAIT, mucosal-associated invariant T cell; TH cell, helper T cell; Treg cell, regulatory T cell; DC, dendritic cell; TCM, central memory T cell; TFH, follicular helper T cell; CTL, cytotoxic T cell. **c** , Individual-specific relative proportions of the indicated 29 distinct immune cell subsets among CD45+ tissue-resident immune cells in lung tissue. Each symbol represents an individual. **d** , Cell counts per individual across the 29 distinct immune cell s
## Related Clinical Research

- [CXCL10 rs8878 genotype associates with preserved T cells and 30‑day survival in sepsis](https://medichelpline.com/clinical-feed/frontiers-in-immunology-1-cxcl10-rs8878-identifies-a-genotype-associated-immune-phenotype-linked-to-t.md)
- [The Role Of ALOX15 In Inflammation-Related Diseases](https://medichelpline.com/clinical-feed/frontiers-in-immunology-7-the-role-of-alox15-in-inflammation-related-diseases.md)
- [Emergency diagnosis frequency and outcomes across 13 non-cancer conditions in England: analysis of](https://medichelpline.com/clinical-feed/plos-medicine-2-frequency-and-prognostic-outcomes-of-emergency-diagnosis-in-13-non-neoplastic.md)
- [Climate change worsens health for people with chronic illness](https://medichelpline.com/clinical-feed/stat-news-1-opinion-climate-change-is-making-people-with-chronic-illness-even-sicker.md)
- [Bupropion Hydrochloride for Improving Recovery in Acute Ischaemic Stroke: BASE Trial Protocol](https://medichelpline.com/clinical-feed/bmj-open-4-protocol-for-base-a-multicentre-double-blind-randomised-controlled-trial-of.md)

## Navigation
- [← Back to Infectious Disease Feed](https://medichelpline.com/clinical-feed/infectious-disease.md)
- [← All Clinical Specialties](https://medichelpline.com/clinical-feed.md)
## Medical & Regulatory Disclaimer

> [!CAUTION]
> MedicHelpline content is structured for research, educational, and professional discovery purposes. It does not constitute individual medical advice, clinical diagnosis, or treatment recommendations.
> Always verify dosing, contraindications, and regulatory alerts against official product labeling and primary regulatory sources before clinical decision-making.