Single-cell RNA-seq reveals a persistent interferon signature in immune cells from Systemic lupus erythematosus patients with high versus low polygenic risk scores despite antimalarial treatment

Despite antimalarial treatment and low disease activity, single-cell RNA sequencing reveals that Systemic lupus erythematosus patients with high polygenic risk scores exhibit a persistent interferon signature across multiple immune cell types compared to those with low risk scores or healthy controls.

The Gist

The Big Picture: The "Genetic Volume Knob"

Imagine your immune system is a high-tech security system for your body. Its job is to spot intruders (like viruses) and sound the alarm. In Systemic Lupus Erythematosus (SLE), this security system is broken; it starts sounding the alarm even when there are no intruders, attacking the body's own tissues instead.

One of the main "alarms" in this system is a signal called Interferon (IFN). Think of Interferon as a loud, blaring siren that tells your immune cells to go into "war mode." In Lupus patients, this siren often won't stop blaring.

This study asked a simple question: Why does the siren keep blaring for some patients even when they are taking medication and feel fine?

The researchers suspected the answer lies in the patient's genetics. They used a tool called a Polygenic Risk Score (PRS), which is like a "genetic volume knob."

• Low PRS: The genetic volume knob is turned down low.
• High PRS: The genetic volume knob is turned up very high.

The Experiment: Checking the "Security Cameras"

The researchers looked at 16 female Lupus patients who were currently in remission (feeling good, low disease activity) and were taking only antimalarial drugs (a standard, mild treatment).

They split these patients into two groups:

1. The High-Risk Group: People with the "volume knob" turned up high.
2. The Low-Risk Group: People with the "volume knob" turned down low.

They also looked at 6 healthy people as a control group.

Using a powerful microscope technique called single-cell RNA sequencing, they took a snapshot of the genes inside individual immune cells (like T-cells, Monocytes, and Dendritic cells) to see what the cells were actually "thinking" and doing at a molecular level.

The Findings: The Siren That Won't Stop

Here is what they discovered, using our analogies:

1. The "High-Risk" Patients Have a Broken Siren
Even though these patients felt fine and were taking their medication, their immune cells were still screaming "ALARM!"

• The Result: The cells in the High-Risk group had a massive surge of Interferon signals. It was as if the security system was in "War Mode" 24/7, even though the house looked peaceful.
• The Specifics: Certain cells, like the "scouts" (plasmacytoid dendritic cells) and the "soldiers" (monocytes), were particularly loud. They were pumping out genes like ISG15 and IFI27, which are the molecular equivalent of shouting "Get ready to fight!"

2. The "Low-Risk" Patients Were Quiet
The patients with the "Low-Risk" genetic profile were much more like the healthy controls.

• The Result: Their immune cells were calm. The Interferon siren was off or barely humming. Their cells looked almost identical to the healthy people's cells.
• The Takeaway: This suggests that for these patients, the antimalarial medication was doing its job perfectly.

3. The Medicine Isn't Strong Enough for the "High-Risk" Group
This is the most important finding. The researchers found that standard antimalarial treatment is not strong enough to turn off the siren for people with high genetic risk.

• The Analogy: Imagine trying to stop a roaring fire with a tiny water pistol. For the "Low-Risk" patients, the water pistol (medication) was enough to put out the small spark. But for the "High-Risk" patients, the fire (genetic drive) is so intense that the water pistol just makes the smoke a little less visible, but the fire is still burning underneath.

4. The "Master Switches" (Transcription Factors)
The researchers looked for the "switches" inside the cells that turn these alarms on. They found two main switches: IRF7 and BATF3.

• In the High-Risk patients, these switches were stuck in the "ON" position, driving the cells to produce more Interferon. It's like someone has glued the light switch to the "ON" position, and the medication isn't strong enough to pry it off.

Why Does This Matter?

Currently, doctors treat Lupus based on how the patient feels (symptoms) and blood tests for inflammation. If a patient feels good, the doctor assumes the disease is under control.

This study suggests that "feeling good" might be a lie for some people.

• The Hidden Danger: Patients with high genetic risk might look healthy on the outside, but their immune systems are still raging on the inside. This "silent inflammation" could be why they eventually suffer more organ damage or have flares later on.
• The Future: In the future, doctors might check a patient's "Genetic Volume Knob" (PRS) at the start. If the knob is set to "High," they might need stronger medication or a different type of treatment immediately, rather than waiting for symptoms to appear.

Summary in One Sentence

Even when Lupus patients feel healthy and take their medicine, those with a high genetic risk still have their immune systems stuck in "alarm mode," suggesting that their treatment needs to be more aggressive to truly calm the storm.

Technical Summary

1. Problem Statement

Systemic Lupus Erythematosus (SLE) is a heterogeneous autoimmune disease driven by the dysregulation of the type I interferon (IFN) system. While Genome-Wide Association Studies (GWAS) have identified over 300 risk loci, the cumulative genetic burden (Polygenic Risk Score, or PRS) is known to correlate with more severe disease and organ damage. However, the molecular mechanisms by which this genetic risk translates into persistent immune dysregulation, particularly in patients who appear clinically quiescent (in remission) and are treated with standard antimalarial therapy, remain unclear. The study aims to determine if high genetic risk drives a persistent, subclinical IFN signature that is not suppressed by current standard-of-care treatments.

2. Methodology

The study employed a rigorous single-cell transcriptomic approach combined with genetic stratification:

• Cohort Selection:
  • Participants: 16 female SLE patients and 6 age/sex-matched healthy controls (HCs).
  • Stratification: Patients were selected from a larger cohort (N=353) based on extreme tails of a weighted PRS distribution (High-PRS vs. Low-PRS).
  • Clinical State: All patients were in Lupus Low Disease Activity State (LLDAS) with SLEDAI-2K scores ≤4.
  • Treatment: Patients were treated exclusively with antimalarials (Hydroxychloroquine or Chloroquine) with no corticosteroids or other DMARDs. Serum HCQ levels were confirmed to be therapeutic and comparable between groups.
• Genotyping:
  • A weighted PRS was calculated based on 57 non-HLA SLE-associated SNVs identified in European populations.
• Single-Cell RNA Sequencing (scRNA-seq):
  • Fresh Peripheral Blood Mononuclear Cells (PBMCs) were processed using the 10x Genomics Chromium Next GEM Single Cell 3' v3.1 platform.
  • Data Volume: ~1.68 billion reads generated; ~9,636 high-quality cells per donor retained after quality control (QC).
  • Analysis Pipeline: Data was processed using Cell Ranger (v7.1) and Seurat (v5.3.0). Clustering identified 10 major immune cell populations (including T cells, NK cells, monocytes, pDCs, B cells).
• Analytical Approaches:
  • Differential Gene Expression (DGE): Compared High-PRS vs. HCs, Low-PRS vs. HCs, and High-PRS vs. Low-PRS.
  • IFN Scoring: Calculated composite IFN scores based on Hallmark gene sets, as well as separate Type I and Type II IFN scores.
  • Pathway & TF Analysis: Reactome pathway enrichment and ChEA transcription factor (TF) enrichment analysis.
  • Protein-Protein Interaction (PPI): Network analysis of upregulated genes.

3. Key Contributions

• Decoupling Clinical Remission from Molecular Activity: The study demonstrates that clinical remission (LLDAS) under antimalarial monotherapy does not equate to molecular remission in patients with high genetic risk.
• Cell-Type Specific Resolution: It provides a high-resolution map of how genetic risk specifically alters transcriptional programs in distinct immune subsets (pDCs and monocytes), rather than just bulk tissue analysis.
• Identification of Persistent Drivers: It identifies specific transcription factors (IRF7, BATF3) and pathways that remain active despite therapeutic intervention in high-risk patients.

4. Key Results

A. Transcriptional Divergence by Genetic Risk

• High-PRS vs. HCs: Showed a massive transcriptional shift with 1,760 upregulated genes, dominated by Interferon-Stimulated Genes (ISGs) such as ISG15, USP18, IFI27, and RSAD2.
• Low-PRS vs. HCs: Showed a significantly muted response with only 694 upregulated genes.
• Overlap: Only 154 genes were shared across all comparisons, indicating a "core" SLE signature, but the High-PRS group exhibited a distinct, amplified signature not seen in Low-PRS patients.

B. Persistent IFN Signature in High-PRS Patients

• IFN Scores: High-PRS patients had significantly elevated IFN scores (p < 0.001) compared to HCs, whereas Low-PRS patients were statistically indistinguishable from HCs.
• Cellular Distribution: The elevated IFN signature in High-PRS patients was observed across multiple cell types, including T cells, NK cells, monocytes, and plasmacytoid dendritic cells (pDCs).
• Type I vs. Type II: Both Type I and Type II IFN scores were elevated in High-PRS patients. Notably, Type II IFN scores were also elevated in Low-PRS B cells, but the broad, multi-cellular activation was unique to the High-PRS group.

C. Mechanistic Insights (pDCs and Monocytes)

• pDCs: In High-PRS patients, pDCs showed significant enrichment of Type I IFN signaling pathways. Key upregulated genes included ISG15 and USP18.
• Monocytes: High-PRS monocytes showed enrichment in IFN-α/β and IFN-γ signaling, as well as TLR3 signaling.
• Transcription Factors:
  • IRF7: Identified as the top regulator in pDCs and monocytes for High-PRS patients. Its expression extended to NK and B cells in High-PRS, whereas it was restricted in HCs.
  • BATF3: Emerged as a key regulator in the High-PRS vs. Low-PRS comparison, suggesting a role in modulating the intensity of the immune response.
• Network Analysis: PPI networks revealed ISG15 as a central hub in pDCs and complex STAT/NF-κB clusters in monocytes, with significant overlap in targets for IRF7 and BATF3.

D. Treatment Implications

• Despite adequate serum levels of antimalarials (HCQ), the IFN pathway remained active in High-PRS patients.
• Pathway analysis suggested that while HCQ inhibits Type I IFN signaling, it may be insufficient to suppress the broader immune activation driven by high genetic load, particularly in Type II IFN pathways or via TLR3 feed-forward loops.

5. Significance and Conclusion

• Genetic Risk as a Driver of Subclinical Disease: The study establishes that a high polygenic risk score is associated with a persistent, genetically driven immune activation state that persists even when clinical symptoms are controlled.
• Limitations of Current "Treat-to-Target": Current clinical targets (like LLDAS) may be insufficient for patients with high genetic risk, as they may harbor significant molecular inflammation that predisposes them to future flares and organ damage.
• Precision Medicine Potential: The findings suggest that genetic risk stratification should be integrated into clinical practice. Patients with high PRS may require intensified maintenance therapy or targeted IFN blockade beyond standard antimalarials to achieve true molecular remission.
• Therapeutic Targets: The identification of IRF7 and BATF3 as key regulators in high-risk patients highlights potential targets for future therapeutic interventions aimed at breaking the cycle of innate immune activation in SLE.

In summary, this paper provides compelling evidence that genetic burden dictates the depth of immune suppression required, revealing that antimalarial monotherapy fails to fully silence the IFN axis in high-risk SLE patients, necessitating a shift toward precision medicine strategies.