Tomorrow's Cure — Episode Summary

Episode Overview

Title: Predictive Medicine: Rethinking Rheumatoid Arthritis
Date: January 28, 2026
Host: Kathy Werzer
Guests:

• Dr. John Davis (Chair, Rheumatology Division, Mayo Clinic)
• Dr. Kevin Dean (University of Colorado Anschutz Medical Campus)

This episode explores the evolving future of rheumatoid arthritis (RA) care, focusing on early diagnosis, AI-driven prediction models, environmental and genetic risk factors, and how innovations in predictive medicine could enable interventions before irreversible joint and organ damage occurs. Both guests share insights from cutting-edge clinical research and discuss how technology, especially artificial intelligence, is shaping the next era of rheumatology.

Key Discussion Points & Insights

1. Understanding Rheumatoid Arthritis (RA)

• RA as a Systemic Autoimmune Disease
  • Not just joint inflammation; impacts whole body with symptoms like fatigue, mental fog, and organ involvement.
    • Dr. Dean: “Rheumatoid arthritis...is a systemic problem where the immune system has gone haywire throughout the body.” (02:42)
  • Chronic inflammation leads to irreversible joint and organ damage, loss of function, and increased risk of heart and lung disease.
    • Dr. Davis: “With chronic inflammation in the joints, it can lead to erosions forming where divots in the bone occur... when inflammation is allowed to persist over months and years, structural damage can occur, and that's irreversible.” (03:45)
• At-Risk Populations and Heterogeneity
  • Any age can develop RA; peak around age 50, more common in women (3:1 ratio).
  • Complexity suggests multiple pathways leading to disease.
    • Dr. Dean: “Basically any age can get it... probably tells us that the disease is...heterogeneous.” (05:15)
  • Genetic, environmental, and lifestyle factors all play a role.

2. Early Prediction & Biomarker Advances

• Autoantibodies and Early Detection
  • Blood tests for autoantibodies, especially anti-CCP and rheumatoid factor, can signal risk 3–5 years before symptoms. However, only about 30% with positive markers develop RA in that timeframe.
    • Dr. Dean: “Those are detectable on average three to five years before the arthritis sets in.” (05:15)
    • Dr. Dean: “Just those tests alone will only accurately predict that 30% of people with those abnormal blood tests will get rheumatoid arthritis within the next three or five years.” (09:35)
• Role of AI in Risk Stratification
  • Combining multiple data sources (genetics, blood markers, health behavior, wearables data, radiographic images) to improve predictive algorithms.
    • Dr. Davis: “...put together a lot of data that we can digitize about an individual... that may have important data that if we analyze using an AI algorithm, that could really learn a lot about the individual...” (07:13)
  • AI expected to offer more precise, individualized risk scores, enabling targeted clinical trials and preventive therapy.
    • Dr. Dean: “This is perfectly poised for AI to really help us take the next step to be able to predict who's actually going to get rheumatoid arthritis.” (09:35)

3. Prevention Trials & Clinical Research

• STOP-RA Trial
  • Sought to prevent RA by treating high-risk individuals with hydroxychloroquine; found no benefit.
    • Dr. Dean: “We gave them a drug...called hydroxychloroquine...Well, it turns out that drug didn't work at all.” (11:25)
    • “I was heartbroken, because we really thought it was a great idea.” (12:54)
  • Importance of negative results: rules out ineffective strategies and advances knowledge.
  • Other prevention studies show some drugs can delay onset but effects do not persist after stopping medication.

4. Lessons from Other Autoimmune Diseases

• Advances in Predictive and Preventive Care
  • Cites type 1 diabetes as a model, where pre-symptomatic interventions (e.g., teplizumab) have delayed disease onset.
    • Dr. Dean: “A couple years ago there was a great study...where a certain immune drug called teplizumab delayed progression...That drug is FDA approved...” (15:28)
  • Goal: apply similar techniques—screening, early intervention, and AI-driven risk scoring—to RA and lupus.

5. Environmental and Lifestyle Factors

• Role of the Exposome
  • Other environmental exposures (particularly at “mucosal surfaces” like gut and lungs) believed to trigger autoimmunity in genetically predisposed individuals.
    • Dr. Davis: “A lot of people have proposed this notion of the mucosal origins...where our immune system really comes into contact with the external environment.” (19:55)
  • Particulate Pollution & Inhalation
    • Recent studies link fine particulate matter (PM2.5), smoke (from fires), and nitrogen oxide exposure to increased RA risk.
      • Dr. Davis: “Exposure to certain particulate matter...is being associated with increased risk of rheumatoid arthritis...and also patients who develop the dreaded lung disease in the setting of having rheumatoid arthritis.” (23:52)
    • Smoking is a major historical risk factor, but ongoing fire smoke and occupational exposures represent new frontiers.

6. Microbiome & Personalized Therapy

• Gut and Nasal Microbiome in RA
  • Altered bacterial diversity (“dysbiosis”) linked to RA onset and other chronic illnesses.
    • Dr. Davis: “People who have chronic diseases, including rheumatoid arthritis...you can also see overabundance of some bacteria...that talks with our immune system...” (26:01)
  • Microbiome profiles may eventually predict not only who will develop disease but also which patients will respond to particular drugs (e.g., methotrexate), with early studies showing 80% accuracy.
    • “We can identify, just based on profiles of gut microbes and a couple of clinical factors, who is going to respond to methotrexate with relatively high accuracy.” (26:01)

7. Artificial Intelligence: Supercharging Prediction and Treatment

• Big Data & Complex Risk Integration
  • AI tools can integrate massive, diverse data streams to make individualized risk and treatment predictions beyond what traditional statistics can handle.
    • Dr. Dean: “I think AI is going to be able to help us tackle that vast amount of information and paint the right picture for the right person at the right time.” (28:43)
    • Dr. Davis: “...the next wave is about putting together multiple types of data...that are going to help us make better predictions about individuals...” (30:12)
  • Growing use of AI in daily clinical practice and documentation.
  • Key infrastructure challenge: develop large, high-quality, longitudinal datasets covering the “natural history” of pre-clinical and early RA.
    • Dr. Dean: “Now we think if that disease actually starts five to 10 years before...getting the data from that earlier time period to help inform us, that's going to be the next step.” (31:54)

8. Future Directions in Rheumatology

• Broader and More Accurate Testing
  • Expect routine use of larger antibody panels and biomarker arrays for diagnosis and risk stratification.
    • Dr. Davis: “We will be doing, you know, broader panels of antibody tests as we learn about newer markers...help with establishing a diagnosis or identifying people who are at risk.” (33:07)
• Data Interpretation & Communication
  • New challenge: distilling AI-generated data and risk predictions into understandable guidance for patients.
    • Dr. Dean: “If we can't do that, it becomes silly to have all this fancy data and whatnot if we can't communicate well.” (33:57)
• Innovative Treatments
  • AI-facilitated drug development may lead to targeted, more effective, and safer therapies, and possibly drugs designed in silico.
    • “Now AI can design a drug for you quite quickly and maybe even interpret how that's going to work and maybe avoid some of the bad side effects...” (33:57)

9. Access and Equity in Future Care

• Digital and Virtual Rheumatology
  • Anticipate more “digital” and “virtual” care, with tests and algorithms supplementing or replacing some in-person exams, especially for rural and underserved populations.
    • Dr. Davis: “Consumers are looking for easier ways to access care and needing to do it more digitally, more virtually...so I see care in the future becoming, you know, more digital, more virtual...” (35:19)
    • Dr. Dean: “That’s going to be an important way forward” for overcoming geographic barriers to specialist RA care. (36:51)

Notable Quotes & Memorable Moments

• On the lived experience of RA:
  • Kathy Werzer: “Folks who have it say it feels like they've been hit by a truck every day.” (02:22)
• On the heartbreak of negative trial results:
  • Dr. Dean: “I was heartbroken, because we really thought it was a great idea...It didn’t work. So that said, it’s still good that a drug we wanted to use and thought would work doesn’t work. And that is an important finding.” (12:54)
• On the potential of AI:
  • Dr. Dean: “AI is going to help us tackle that vast amount of information and paint the right picture for the right person at the right time.” (28:43)
  • Dr. Davis: “AI is here whether we like it or not.” (30:12)
• On the future of rheumatology:
  • Dr. Davis: “I think we will be doing a lot more prediction. I think we'll gain tests that will help us individualize treatments better.... using evidence and data to make better predictions about what drugs are best for a person.” (33:07)
  • Dr. Dean: “I have great hope that AI is going to help us...interpretation...into a digestible format where people can...make it meaningful themselves.” (33:57)
• On healthcare access innovation:
  • Dr. Davis: “People are going to need to access this more virtually and we're going to have to find ways to deliver care that's safe and effective and reliable...so exactly, that's how it's going to happen.” (36:22)

Timeline of Key Segments

| Timestamp (MM:SS) | Topic / Segment | |-----------------------|---------------------------------------------------------------------------------------------------------------| | 01:00 | Dr. Kevin Dean on early detection and the importance of longitudinal data | | 02:22 | Kathy introduces RA: impact on patients, Dr. Dean explains immune dysfunction | | 03:45 | Dr. Davis on damaging effects of chronic inflammation and systemic organ impact | | 05:15 | Dr. Dean discusses risk factors, heterogeneity, and gender/age distribution | | 07:13 | Dr. Davis on current/future AI-driven risk prediction and precise risk stratification | | 09:35 | Dr. Dean highlights autoantibody prediction limitations and need for integrated AI models | | 11:25 | STOP-RA trial summary and reflections (results, challenges, hope for future prevention research) | | 15:28 | Advances in other autoimmune diseases (lupus, type 1 diabetes, teplizumab) referencing multi-disease lessons | | 19:55 | The exposome, mucosal origins of RA, environmental exposures (gut, lungs, gums) | | 23:52 | Air pollution, PM2.5, and wildfire smoke as new risk factors in RA development | | 26:01 | Gut microbiome and future of predicting drug response and RA onset | | 28:43 | AI’s promises and limitations in precision medicine (prediction, diagnosis, data integration) | | 30:12 | Dr. Davis describes the pragmatic adoption of AI in clinical research and practice | | 31:54 | Importance of longitudinal, “natural history” studies to enable AI-powered insights | | 33:07 | Visions for rheumatology in 5–10 years: more data, better prediction, individualized treatment | | 35:19 | Future of virtual care, digital health, and improving rural healthcare access |

Concluding Thoughts

Throughout the episode, Drs. Davis and Dean provide an engaging, hopeful look at how predictive medicine, big data, microbiome science, and artificial intelligence are converging to reshape the fight against rheumatoid arthritis. By moving diagnosis and intervention earlier, integrating complex risk profiles, and using smart technology, the field aims for a future where devastating autoimmune diseases like RA can be prevented, customized, and managed with greater precision and less patient suffering.