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Continuous NRTI-based antiretroviral therapy induces progressive senescence-like reprogramming of alveolar macrophages [snMultiomics]

GSE307326 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2026/05/15 Platform GPL33758
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 32 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
32 samples: 32 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Continuous antiretroviral therapy induces progressive senescence-like reprogramming of alveolar macrophagesFrontiers in immunology · 2026
Summary (written by the submitters)
Background: Advances in antiretroviral therapy (ART) have substantially improved the lives of people with HIV (PWH) and reduced HIV acquisition through pre-exposure prophylaxis (PrEP). However, the long-term effect of ART on the physiological state of cells remains poorly understood. Despite the success of ART in preventing the progression of HIV infection to AIDS, the aging PWH are suffering from a disproportional burden of non-AIDS comorbidities, including lung diseases.
Read the full summary ↓
Methods: Given the central function of alveolar macrophages (AM) in pulmonary immunity, we evaluated the impact of nucleoside reverse transcriptase inhibitors (NRTI) based ART on AM of PWH and people on PrEP. We employed a retrospective cross-sectional design and evaluated the effects of continuous exposure to ART in the epigenetic and transcript of AM at bulk and single-nucleus multiomics levels. Results: We showed that continuous NRTI-based ART induces a progressive senescence-like pro-inflammatory state in AM, characterized by increased constitutive epigenetic and transcriptomic priming of genes involved in cell cycle arrest (e.g., CDKN1A/p21), components of the senescence-associated secretory phenotype (e.g., IL1A, IL6R, and CXCL8), as well as transcription factors subunits of the AP-1 family (e.g., FOSL1, JUN). At the AM single nucleus level we described a coordinated gene regulatory network linking key pro-inflammatory transcription factors to the transcriptomic alterations induced by ART. The senescence ART-linked epigenetic and transcriptomic changes were strongly dependent on the duration of ART and irrespective of HIV infection. A secondary time independent ART effect was observed for interferon signaling genes. This effect was more pronounced in people on PrEP and impaired AM response to ex vivo challenge with SARS-CoV-2. Conclusion: Combined, our data indicate that continuous NRTI-based ART promotes a dysregulated physiological state in AM, potentially contributing to age-related pulmonary comorbidities in PWH, such as COPD, pulmonary fibrosis, and asthma. PrEP is critically important for preventing HIV acquisition in the most vulnerable populations. By identifying therapeutical gaps in ART our study advocates for optimized or adjuvant therapies to prevent or mitigate potential long-term adverse effects of PrEP and to continuously improve the quality of life of PWH.
Published in
Continuous antiretroviral therapy induces progressive senescence-like reprogramming of alveolar macrophages
Fava VM, Dallmann-Sauer M, Orlova M et al. · Frontiers in immunology 2026 · PMID 42099614 · doi:10.3389/fimmu.2026.1805936
This dataset
Open GSE307326 in finder → Find more human ChIP / ATAC / CUT&Tag datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE307326_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1315233 and SRA study SRP617586. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42099614) ↗
Study design
32 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 32 sample titles: 32 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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