Immune signs that predict strong protection against the flu
Influenza Modeling of Correlates of Protection for Optimal Immune Dynamics and Evolution.
['FUNDING_U01'] · EMORY UNIVERSITY · NIH-11251309
This project uses blood and immune data from people who had influenza to find early immune signals that predict who recovers well and to help design better vaccines.
Quick facts
| Phase | ['FUNDING_U01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | EMORY UNIVERSITY (nih funded) |
| Locations | 1 site (ATLANTA, UNITED STATES) |
| Trial ID | NIH-11251309 on ClinicalTrials.gov |
What this research studies
From your perspective, this research looks at detailed immune and molecular data already collected from people who got the flu, including a 280-person CHILE cohort with mild and severe cases. The team will examine blood-based omics (like gene activity, proteins, and antibody measurements) and immune cell responses collected during the first two weeks of infection. They will apply machine learning and deep-learning methods to find small sets of immune markers that appear early and are linked with better outcomes or vaccine responsiveness. The goal is to translate those signals into tests or vaccine targets that could help prevent severe flu in the future.
Who could benefit from this research
Good fit: Ideal candidates for the kinds of data used here are people with laboratory-confirmed influenza infection across a range of ages, vaccination histories, and health conditions similar to the CHILE cohort participants.
Not a fit: People without influenza infection or those whose care will not involve immune or molecular testing are unlikely to directly benefit from this project.
Why it matters
Potential benefit: If successful, this work could identify early immune markers that help predict protection and guide the development of more effective influenza vaccines.
How similar studies have performed: Multi-omic and immune-signature approaches have shown promise in COVID-19 and prior influenza work, but integrating longitudinal omics with sparse and deep-learning models to define early protective signatures is still relatively new.
Where this research is happening
ATLANTA, UNITED STATES
- EMORY UNIVERSITY — ATLANTA, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: MEDINA SILVA, RAFAEL A. — EMORY UNIVERSITY
- Study coordinator: MEDINA SILVA, RAFAEL A.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.