USC’s Macrophage Map Undercuts a Single Immune Aging Drug

A USC team found that mouse macrophages share a thin set of aging genes, then diverge by organ and by sex. The cross-tissue macrophage aging meta-analysis was published in BMC Biology on July 15, 2026, after the group reused public RNA datasets instead of running one new organ survey.

Lead author Ella Schwab, a PhD student in the Benayoun lab at the USC Alfred E. Mann School of Pharmacy, and senior author Bérénice Benayoun, an associate professor at the USC Leonard Davis School of Gerontology, set out to find whether immune aging follows one body-wide script. At the gene level it mostly does not, which is a problem for anyone hoping one macrophage drug will travel from lung to brain.

Public Datasets Did the Work a New Lab Could Not

Most macrophage aging papers still look at one tissue. Schwab’s group searched public bulk and single-cell RNA-seq collections for purified mouse macrophages with a clear age spread, then processed every file the same way. They first found 29 datasets from 10 tissue niches, all on C57BL/6 mice. After splitting mixed-sex studies so male and female samples were not averaged together, they held 33 datasets. Quality filters for sex labels, read depth, replicate counts, and signal left 24 high-quality datasets across 9 niches.

Benayoun said most work still “focus on a single tissue or organ, so little is known about how the local tissue environment can affect immune cell aging.” Schwab’s answer was to stop generating another lone-tissue experiment and to mine what was already sitting in the repositories. “There’s an incredible wealth of publicly available, underutilized sequencing data for studying immune aging,” she said. “By analyzing data from dozens of pre-existing studies, we could examine how macrophages age across tissues and between sexes, something no single study had the power to do alone.”

THE PATH TO THE PUBLISHED MAP

1. February 12, 2024: Hevolution names Benayoun among 49 HF-GRO awardees, under grant HF-GRO-23-1199072-28.
2. February 4, 2026: BMC Biology receives the manuscript.
3. February 6, 2026: A preprint of the same analysis is posted on bioRxiv.
4. June 24, 2026: The journal accepts the paper.
5. July 15, 2026: The study appears as BMC Biology volume 24, article 155, with co-authors Eyael Tewelde and Leon Chen.

The starting 29-set was lopsided, which later decided where sex effects could be measured with any confidence. Bone-marrow-derived macrophages and the two best-sampled resident niches carried most of the statistical weight.

NICHES IN THE STARTING 29 DATASETS

• Bone-marrow-derived: 6 datasets, cells often grown in culture rather than taken from a finished organ niche.
• Microglia: 5 brain datasets, one of two resident types with enough files for a sex split.
• Alveolar: 5 lung datasets, the other well-sampled resident niche.
• Skeletal muscle: 3 datasets.
• Adipose, peritoneal, spleen, bone callus: 2 datasets each.
• Skin and nerve-associated: 1 dataset each.

That mix is why a 2023 240-study macrophage aging review could tally hundreds of genes and proteins and still leave the body unmapped. In that review, 82 papers used peritoneal cells, 38 used bone-marrow-derived macrophages, 17 used alveolar macrophages, and 16 used microglia. A field that keeps sampling the same easy cells will keep missing the organs that actually fail in old age.

593 Genes Moved Together, Then the Map Split

When Schwab compared aging genes across niches, macrophages from the same organ looked most like each other, regardless of sex or the exact ages in each study. Overlap between different organs was modest. The paper’s own reading is that transcriptional remodeling with age is largely niche-specific at the gene level.

A smaller layer still repeats. Meta-analysis defined 593 genes that changed with age in more than three-quarters of the analyzed datasets, and the shared signal converged on faulty small GTPase signaling. Pathway tests found the same directional pattern in many macrophage types: older cells ramped up antigen presentation, antioxidant responses, and a brake on ferroptosis, a form of iron-linked cell death, while Wnt, GTPase, and extracellular-matrix programs ran lower.

SHARED PROGRAMS ACROSS MANY MACROPHAGE TYPES

Those shared switches are the part of the map drug hunters will want. They are also a thin slice of what actually changed. A sensitivity check still found age-linked genes in 21 of the 24 datasets, so the split is not an artifact of a few noisy studies. The body-wide clock, if it exists, is a short list sitting on top of organ-specific rewiring.

Lung and Brain Macrophages Follow Different Scripts

Jaccard similarity scores, which measure how much two gene lists overlap, were highest among alveolar-macrophage datasets and among microglia datasets. That partly reflects power: those niches had the most files. It also matches the biology. Alveolar macrophages live on the airway surface and turn over under constant particle load. Microglia tile the brain and last for years, shaped by neurons and the blood-brain barrier rather than by inhaled dust.

The paper’s niche-level networks pull those lives apart. Alveolar aging, on a transcriptional level, looks like a drop in proliferation programs. Microglial aging looks more like a coordinated rise in immune-effector genes, with cytoskeletal, synaptic, and metabolic genes falling. A treatment aimed at getting lung macrophages to divide again would be aiming at a different lever than a treatment aimed at quieting brain immune activation.

Benayoun put the design question in plain language when the paper came out.

We wanted to understand whether immune cells age in the same way throughout the body or whether each tissue has its own aging story.

Bérénice Benayoun, associate professor, USC Leonard Davis School of Gerontology

Each tissue does. Macrophages from one niche aged most like other macrophages from that niche, not like a generic “old macrophage” drawn from the rest of the mouse. For geroscience groups that still talk about macrophage aging as one process, that is the finding that should change the next experiment they fund.

Sex Rewrites Aging in the Same Cell Type

The lab did not treat sex as a nuisance variable. Benayoun’s group has spent years on peritoneal macrophage aging in females versus males, and in 2024 she gave a sex-dimorphic macrophage aging lecture after receiving AFAR’s Vincent Cristofalo Rising Star award. Schwab used the extra alveolar and microglia files to ask whether those sex gaps survive outside the peritoneum. They do.

ALVEOLAR MACROPHAGE GENES CHANGED WITH AGE

Female-specific upregulated genes outnumbered the male-specific set, and the shared upregulated set was smaller than either sex-specific list. Translation-related pathways even moved in opposite directions, rising in male alveolar macrophages and falling in females, which the authors read as a possible hit to the female translational machinery. In microglia, both sexes showed more immune activation and less cytoskeletal, synaptic, and metabolic gene activity, but females added ER-stress and protein-folding programs while males preferred to turn down leukocyte-mediated programs.

Other niches had only two datasets each, so the same sex split could not be drawn with equal force in spleen, bone callus, skeletal muscle, bone marrow, or adipose tissue. The honest limit is not “no sex effect elsewhere.” It is that the public archive is still too thin to prove it. Hevolution’s $115 million healthspan grants program, announced February 12, 2024, across 49 awards, is what paid for the attempt. Benayoun said at the time that the funded project was “close to my heart” because it asked why female and male innate immune aging differ, and that the money would help lay “the foundation for a lasting improvement of women’s health throughout aging.” The atlas delivered that sex split, then showed it is also an organ split.

Why a Single Immune-Aging Drug Would Miss

In August 2025, Matthew Park, Miriam Merad, and colleagues argued in Nature Aging that restoring resident tissue macrophages should be a major goal of healthy-aging therapy, either by fixing local self-renewal or by resetting myeloid production in bone marrow. That program only works if an old macrophage in one organ is close enough to an old macrophage in another for the same lever to matter. Schwab’s map says the gene programs are not close enough.

Benayoun stated the practical consequence on July 15, 2026, when she posted the paper: there are universal, niche-specific, and sex-specific effects, “which will be important to account for in interventions to mitigate inflammaging and immunosenescence.” Inflammaging here means the chronic, low-grade inflammation that tracks with age. Immunosenescence means the broader drop in immune function that leaves older people more open to infection, slower to heal, and more prone to diseases tied to aging.

Happy to share this new work by excellent Benayoun lab PhD Candidate #EllaSchwab, out today @BMCBiology: "Shared and niche-specific transcriptional signatures of macrophage aging revealed by a cross-tissue meta-analysis" @USCLeonardDavis 1/https://t.co/ZOfPZDY61Y pic.twitter.com/1mNL9zDrKs

— Bérénice A. Benayoun, PhD (@BBParis1984) July 15, 2026

A shared AP-1 or GTPase drug might still move a core module in many organs. It would not automatically fix female alveolar translation, male alveolar cytokine bias, or female microglial ER stress. Those are different failures wearing the same cell-type name. The irony of the atlas is that it was built to reveal targets, and the targets splinter as soon as the tissue or the sex changes.

The Shared Circuit Points at Small GTPases

If any slice of the map still supports a broad intervention, it is the short list that survived the strictest cutoff. The authors flagged 35 highly consistent macrophage aging genes. Several of them, including Arhgap18, Nucb1, Rabif, Wdr41, Sipa1, and Arap3, are tied to GTPase regulatory activity, which is how cells control small molecular switches that run migration, vesicle traffic, and membrane signaling. That is not a full recipe for a drug. It is a narrower hypothesis than “fix inflammation” or “clear senescent cells,” and it is the one the meta-analysis can actually defend across niches.

The conserved transcription-factor set points the same way. AP-1, C/EBPβ, PU.1, and Egr1 are not obscure names in myeloid biology. They are the regulators labs already know how to perturb in culture. What the atlas adds is evidence that their age-linked activity is not confined to one convenient macrophage population. A screen against that node at least has a rationale for being tested in more than one organ, and in both sexes, before anyone claims a systemic effect.

C57BL/6 Mice Are Not Patients

Every number in the paper comes from inbred mice. Young groups in the public files ran from 2 to 6 months and old groups from 10 to 24 months, so “aging” is not one interval. No human macrophage atlas of this breadth sits behind the conclusions. Resident macrophages in people also live for years in niches that mice only approximate, and patients are not a single genetic background.

WHAT WE KNOW

• The cell type: Macrophages clear debris, present antigen, and help repair tissue in almost every organ.
• The split: Gene-level aging is largely niche-specific; a smaller pathway and GTPase signature recurs across many datasets.
• The sex effect: Alveolar macrophages and microglia show large male-female differences in age-linked genes.

WHAT IS UNCONFIRMED

• Human transfer: Whether the 593-gene set, the 35-gene core, or the alveolar sex split survive in human tissues.
• Drug effect: Whether hitting AP-1 or small GTPases would restore function, or only move RNA levels.
• Thin niches: Whether spleen, muscle, adipose, and other low-count organs would show the same sex split with more files.

Schwab, Tewelde, Chen, and Benayoun offer the tables as a resource for labs that want to test those open points, not as a treatment plan. The map is public. The next useful paper is the one that asks whether a GTPase or AP-1 intervention that helps old alveolar macrophages does anything at all for old microglia, in both sexes, before anyone writes a protocol for people.

Frequently Asked Questions

Did the Study Use Human Macrophages?

No. The analysis used C57BL/6 mice only, the standard inbred strain in mouse aging research. Human transfer is untested here, even though age-related immune decline in people is the reason the map was built.

How Old Were the Mice in the Datasets?

Young groups ranged from 2 to 6 months and old groups from 10 to 24 months, because the team reused existing studies rather than setting one age pair. A 10-month “old” file and a 24-month “old” file are not the same biological moment, which is a built-in limit of the archive.

What Is the Difference Between Tissue-Resident and Bone-Marrow-Derived Macrophages Here?

Most adult tissue-resident macrophages, including microglia and alveolar macrophages, start from fetal yolk-sac progenitors and then maintain themselves by local self-renewal. Bone-marrow-derived macrophages, which supplied 6 of the original 29 datasets, are often differentiated in culture from marrow cells and do not carry the same lifelong niche history.

Can Other Labs Reuse the Analysis?

Yes. The paper is open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 license, and it was built from already public RNA-seq series. The authors also posted the work as a bioRxiv preprint in early February 2026, before the July 15, 2026 journal version.

Disclaimer: This article is news reporting on a published mouse study and is for information only. It is not medical advice, a diagnosis, or a recommendation to start, stop, or change any treatment for immune aging, inflammation, infection risk, or age-related disease. Readers who are considering health decisions tied to these findings should consult a physician or a qualified immunologist or geriatrician who can weigh human evidence. Gene counts, dataset totals, and study status reflect the BMC Biology paper and related sources as of the dates named above and may be revised if the authors or the journal issue corrections.