Nature vs. Nurture & Their Roles in Autoimmunity

Note: This is a representative image and not the actual twins discussed here.

They looked exactly alike—tall, slightly scruffy gentlemen with denim overalls lightly stained with dirt and oil, with dusty trucker hats to match. The only difference was that one wore a red checkered shirt and the other wore a green one. Yet these similarities were deceptive. The one closest to me was the patient, the one who came into our clinic with swollen hands and wrists, as well as an impressively high rheumatoid factor and sedimentation rate. His twin apparently had no musculoskeletal issues at all. In fact, the patient—let’s call him Bob—said his hands had looked like his twin brother John’s only six months before.

The stories of patients like these absolutely fascinate me. Bob and John are identical twins, as if someone had hit copy and paste. And, as they mentioned, they had grown up in the same house in the same small Midwestern town, graduated from the same schools, worked in the same line of business, and even ate the same types of foods. And yet, Bob developed rheumatoid arthritis, but John had not experienced any symptoms to date. In fact, even a decade after Bob’s diagnosis, John continues to wait for his joints to start aching and swelling. We hope they never will.

Everyday mysteries like these are what originally drew me to rheumatology (and allergy/immunology). As a specialty, we tend to evenly divide the pathogenesis of our diseases into nature or nurture. But is this paradigm truly accurate? Let’s rheuminate!

Nature vs. Nurture?

Whether fairly or not, we assume that identical twins, sharing virtually all of their DNA, should also share identical destinies when it comes to their health. But clinical practice—and a growing body of research—reveals just how simplistic that assumption can be.¹ Bob and John are a case in point.

Despite their shared genome and nearly indistinguishable upbringings, their bodies told two very different immunologic stories.

This divergence highlights the rapidly evolving landscape of epigenetics—the study of how environmental exposures can switch genes on or off without altering the DNA sequence itself. If genetics provides predestined blueprints for an overarching structure, epigenetics fine-tunes this destiny to accommodate changes in fortune. One twin’s immune system, perhaps triggered by a respiratory infection, a shift in the microbiome or an occupational exposure, began expressing inflammatory genes in a way the other’s never did.

That’s not even accounting for the exposome. Even among twins, no two people occupy the exact same psychosocial niche.² Perhaps one had a slightly higher workload or a more stressful year, or lived in a house with more radon exposure—a frighteningly common phenomenon in the Midwest. Perhaps they differed in insurance coverage, proximity to care or the structure of their daily responsibilities. When social and economic stressors intersect with genetic predisposition, the balance can tip toward immune dysfunction and disease—particularly in rheumatology, in which multimorbidity is the norm, not the exception.

This is what makes our field both maddening and magnificent. The variables that shape our disease are countless, and the traditional dichotomy of nature vs. nurture does a disservice to the interconnectedness of it all. Sometimes, we simply have to marvel at how complex and intricate human variation is.

Situated Choice Among Immune Cells

Not too long ago, I fell down an internet rabbit hole and found a term in the sociology literature that appealed to me: situated choice. Sociologists use this term to describe how a decision or action is understood within the context of a specific environment, situation or location.³

As an immunologist, my first thought was about lymphocytes. After all, the way an immune cell makes decisions is never in a vacuum, but in the context of its surroundings. A T cell in a lymph node facing one set of cytokines will behave quite differently than that same T cell encountering an even slightly different milieu in the synovium or gut.

These decisions are contingent, local and adaptive. They’re not unlike the choices we make in our own lives, shaped by environment, history and proximity to others.

This application of situated choice to health has profound implications for how we can conceptualize disease pathogenesis. Why does one individual, like Bob, with a genetic predisposition develop an autoimmune disease while another doesn’t? Perhaps it comes down to where and when an immune cell encountered its antigen, what signals it received from surrounding cells, how cosmic rays displaced subatomic particles leading to a mutation, or what genetic and epigenetic states coincided at that time.

What’s more, these cellular choices, if we can give some liberties to immune cells for decision making, aren’t made solely once—they are part of a continuous chain that extends throughout all phases of the cell’s life. Multiplying this by thousands and millions of cells, it becomes clear that the immune system is in a perpetual state of negotiation, arbitrating between tolerance and attack, between regulation and activation. Our immune systems have evolved to become exquisitely sensitive to context, and because that context is always in flux, immune behavior—and therefore disease—becomes highly unpredictable.

For clinicians, this means we must resist the temptation to generalize too rigidly. Situated choice reminds us that every patient’s disease is an improvised performance, not a scripted play. It humbles us away from notions of predestination. Yet situated choice also inspires us to meet our patients where they are—in their environment, with their biology and in their particular chapter of life.

Tuning in to Statistical Noise in Clinical Trials

Zooming out of the basic science labs, we see the implications of situated choice in clinical research. Although clinical trials are the backbone of evidence-based medicine, they still feel a little dissonant in rheumatology. Our diseases are inherently heterogeneous, slow moving and filled with outliers. And yet our trials depend on averages—mean DAS28 scores, pooled ACR response rates and hazard ratios that assume or impose a homogeneity that simply isn’t there.

Because of this, we are inclined to dismiss outliers as statistical noise, but sometimes that noise carries a tune worth paying attention to. In every clinical trial, there’s someone who has a miraculous response—and someone who gets dramatically worse. We rarely investigate these cases with the same vigor that we celebrate P values and confidence intervals. But Bob and John’s case suggest that maybe we should.

Sometimes, those very outliers help us identify biomarkers, stratify subgroups and fine-tune our therapies. For example, early hints of JAK inhibitors’ utility in many autoimmune conditions came from noticing who responded—often unexpectedly well— to medications for other indications.⁴

Rather than viewing variability as a nuisance to be averaged out, we might see it as an invitation. What might we learn if we followed up every surprising responder—or non-responder—with the same rigor we devote to standardized endpoints? What if we treated clinical trials not as blunt instruments for population-wide answers, but as portals into the messy reality of immunologic individuality?

Variability as a Loyal Friend

To researchers and clinicians alike, variability can feel like the enemy. Even outside of twins, one patient flares despite biologic therapy; another feels great on hydroxychloroquine alone. One may report prohibitive side effects to methotrexate, while another asks if they can stop because they feel as if they are cured. As clinicians, we yearn for predictability, whether it is a sensitive and specific lab test that forecasts disease trajectory, guidelines that don’t just classify but wholesale diagnose a condition early and reliably, or a treatment algorithm that navigates the dazzling array of immunotherapies. But these are utopian thoughts.

Instead, maybe variability can be seen as less of an intractable foe and more of a frustrating but well-meaning and loyal friend. Variability forces us to personalize care—not because it’s trendy, but because it’s essential. Treat-to-target strategies in rheumatology work best when grounded in flexible thinking. We absolutely need protocols, but also permission to diverge from them when the patient’s circumstances demands creative solutions.

Variability calls for humility as much as it does for humanity. We often cannot know, at the start of treatment, how a given patient will respond. Our job is to collectively hold that uncertainty with grace— to explain it transparently to patients, to experiment (within safe boundaries, of course) and to always be ready to revise our assumptions at subsequent visits.

In short, reorienting our approach to variability means we are not normalizing immune status, because that is fundamentally not possible. Instead, we are constantly calibrating trust—in the patient’s body, in their lived experience and in our shared ability to navigate the unknown together.

Healthcare Policies to Manage Uncertainty

The fundamental variability of immune-mediated disease demands not just personalized clinical care, but policy structures that can accommodate complexity. Unfortunately, most healthcare systems are built for predictability—standard formularies, fixed prior authorization rules, cookie-cutter time limits for consultations. These constraints assume that patients follow a narrow path. We rheumatologists know better.

When policies ignore variability, they don’t just inconvenience clinicians, they unequivocally harm patients. Rigid fail-first/step therapy rules, limited access to diagnostic imaging, and constricted networks for referrals to specialists are all examples of systems that fail to account for the unpredictable journeys of patients like Bob and John. The result is frustration, delays and worse outcomes.

What we need instead are adaptive, human-centered policies—guidelines that allow for exceptions, that trust clinicians to make evidence-informed decisions in the face of uncertainty. Governmental oversight is needed so that insurance policies allow for flexibility. Prior authorization systems must be reformed so that they are centered on the trust and judgment of board-certified specialists rather than on peer reviewers who may not even know how to spell rheumatology.

Technology can help us in this pursuit. Designers of electronic health records are finally understanding the benefits of accommodating narrative nuance over templated check boxes. Machine-learning models, when thoughtfully designed, can stratify patients by risk and predict who might benefit from more intensive monitoring. Sharing data across institutions can help us recognize rare patterns and truly personalize care. But with these benefits also comes risk: Predictive models are only as good as the data and values that inform them. We must design healthcare systems that elevate precision and variability, not just efficiency.

The everyday mystery of Bob and John continues to tantalize me. Whenever I can, I share their story with trainees to show the limits of our knowledge. Yet the word mystery makes it out to be something that deserves to be solved, that there is a gnawing void that needs to be filled with information. After so much thought and reflection, I’ve realized this void is inevitable because every time we encroach upon the expanse of unknowability in the world, we become more acutely aware of our ignorance and insignificance. In so doing, a larger and more enigmatic void presents itself. That, fundamentally, is the beauty of the immune system and our world at large.

So I thank Bob and I thank John for entering my life. In coming to clinic with an everyday mystery, they have left me with an everyday opportunity to look at the universe and be infinitely grateful that I get to experience it as a rheumatologist.

Bharat Kumar, MD, MME, FACP, FAAAAI, RhMSUS, is the director of the rheumatology fellowship training program at the University of Iowa, Iowa City, and the physician editor of The Rheumatologist. Follow him on X (formerly Twitter) @BharatKumarMD.

References

1. Tusseau M, Khaldi-Plassart S, Cognard J, et al. Mendelian causes of autoimmunity: the lupus phenotype. J Clin Immunol. 2024 Apr 15;44(4):99.
2. Biton J, Saidenberg-Kermanac’h N, Decker P, et al. The exposome in rheumatoid arthritis. Joint Bone Spine. 2022 Nov;89(6):105455.
3. Antonaccio O, Botchkovar EV, Lorine A. Hughes LA. Ecological determinants of situated choice in situational action theory: Does neighborhood matter? J Res Crime Delinq. 2017;54(2):208–243.
4. Mortezavi M, Martin DA, Schulze-Koops H. After 25 years of drug development, do we know JAK? RMD Open. 2022 Jul;8(2):e002409.