By the time symptoms appear, more than half the neurons are already dead.
Nuevas tecnologías ultrasensibles detectan proteínas cerebrales en muestras de sangre mínimas, identificando neurodegeneración años antes de síntomas en Párkinson y Alzhéimer. En enfermedades reumatológicas, integrar múltiples biomarcadores permite seleccionar tratamientos personalizados; en cáncer, la biopsia líquida monitoriza tumores en tiempo real sin procedimientos invasivos.
- More than 200,000 people in Spain have Parkinson's disease; diagnosis is delayed an average of 1-3 years after first symptoms
- Researchers can now detect neurodegenerative changes from a blood sample smaller than a drop using ultrasensitive technology
- Rheumatoid arthritis affects approximately 25,000 people in Galicia; integrated biomarker tools help select personalized treatments
- Liquid biopsy detects tumor DNA in blood to monitor cancer progression and identify treatment resistance in real time
Los biomarcadores son señales medibles del organismo que permiten detectar, monitorizar y predecir enfermedades como Párkinson, Alzhéimer, artritis reumatoide y cáncer antes de que aparezcan síntomas clínicos, revolucionando el diagnóstico personalizado.
A single drop of blood. That is all that is needed now to detect the early whispers of Parkinson's disease, years before a person notices their hands have begun to shake. This is the promise of biomarkers—measurable signals from the body that reveal what is happening inside before symptoms arrive to announce it. A biomarker might be a protein floating in the bloodstream, a molecule in cerebrospinal fluid, a pattern on an imaging scan, or even a digital signature captured by sensors. What matters is that it can detect, track, or predict disease. We have known about some for decades: blood glucose levels in diabetes, for instance. But the biomarkers reshaping medicine now are still finding their way into everyday clinical practice, and they point toward a future where doctors treat not diseases in general, but the specific disease unfolding in a specific person's body.
In Galicia, researchers at the Center for Singular Research in Molecular Medicine and Chronic Diseases are hunting for the molecular fingerprints of Parkinson's. More than 200,000 people in Spain live with this neurodegenerative condition, yet diagnosis remains stubbornly clinical—based on what a neurologist observes rather than what a test confirms. The result is a cruel delay: on average, between one and three years pass from the first tremor or stiffness to the moment a doctor can say with certainty what is happening. By then, the damage is already substantial. When Parkinson's is finally diagnosed, more than half of the dopamine-producing neurons that the disease targets have already died. The process of neurodegeneration, researchers believe, begins ten to twenty years before any symptom appears. The nervous system compensates for the loss, masking the injury, until that compensation fails and the threshold is crossed. Then the patient walks into a neurologist's office. But by that point, the neurons are so depleted that the medications available can do only so much.
Ana Isabel Rodríguez and her team work with molecular biomarkers—proteins tied to the processes of neuronal death—using technology of extraordinary sensitivity. They can detect minute changes in brain signals from a blood sample so small it is barely more than a drop, even in people who have not yet felt a single symptom. This year they acquired the Argo HT System, a platform capable of measuring hundreds of proteins at concentrations so low they would have been invisible just years ago. The technology opens a door to identifying people in the prodromal phase, the stage before symptoms emerge. If those individuals could receive early interventions aimed at preserving dopamine neurons and reducing the inflammation that drives their loss, the onset of disease might be delayed significantly, or its course altered entirely.
The research extends beyond proteins in the blood itself. Rodríguez's group analyzes extracellular vesicles—tiny structures released by cells, including neurons, that carry proteins, lipids, and genetic material reflecting the state of their cell of origin. Some of these vesicles from the brain make their way into the peripheral bloodstream. By isolating them and analyzing their contents on ultrasensitive platforms, researchers can access information about what is happening in the brain without invasive procedures, filtering out the noise of other molecules in the blood. The implications reach beyond Parkinson's. The same platform can measure biomarkers for metabolic, cardiovascular, and cancer-related diseases.
In the study of Alzheimer's disease and other dementias, researchers are developing imaging biomarkers that measure not just the accumulation of amyloid-beta and tau proteins—the hallmarks of Alzheimer's pathology—but also neuronal connectivity itself, whether neurons have stopped communicating with one another. The challenge is formidable: the blood-brain barrier, a highly specialized semipermeable structure that protects the brain and spinal cord, blocks many molecules from entering. Glucose enters readily, but the information it provides is nonspecific. Larger molecules that offer more precise information penetrate poorly. Artificial intelligence is beginning to help by allowing researchers to combine different types of biomarkers—imaging data, blood markers, fluid analysis—into integrated platforms that no previous era of medicine could have assembled. The arrival of drugs that slow Alzheimer's progression in early stages has created urgency around these biomarkers. Until now, amyloid and tau markers lived mostly in research settings because there was no clear clinical need to tell a patient they had Alzheimer's if nothing could be done. Now, as treatments become available, identifying who will benefit from them becomes essential.
In rheumatologic diseases, the heterogeneity of conditions like rheumatoid arthritis and osteoarthritis means that two patients with identical diagnoses may have entirely different underlying biology, different rates of progression, different inflammatory burdens, and different responses to treatment. Rheumatoid arthritis affects roughly 25,000 people in Galicia alone. Clinicians already use biomarkers—rheumatoid factor, anti-CCP antibodies, C-reactive protein, erythrocyte sedimentation rate, genetic markers like HLA-DR1—to help diagnose and classify risk. But no single marker captures the full clinical picture. Researchers have built integrated tools that combine multiple biomarkers with clinical variables to answer specific questions: which treatment will work best for this patient? One such tool, OPTBIO, helps select the optimal therapeutic strategy when many options exist. For osteoarthritis, long viewed as merely mechanical wear and tear, understanding has shifted toward recognizing it as a low-grade inflammatory process affecting the entire joint. A tool called DiTOBA integrates clinical information, biomarkers, imaging data, and disease progression to identify patient subgroups that need different approaches. The principle is clear: the goal is not to accumulate tests, but to integrate information in ways that lead to better decisions.
In oncology, the liquid biopsy represents a fundamental shift. When a tumor forms, cancer cells release fragments of their DNA into the bloodstream. A liquid biopsy detects these fragments, offering a dynamic, global view of the disease without invasive procedures. The technology has advanced dramatically in recent years and now sits at a transition point—already in use in some clinical situations, being implemented in others. In advanced cancer with metastases, a liquid biopsy helps oncologists choose the best treatment at any given moment and monitor how the tumor evolves, revealing mechanisms of drug resistance before they become apparent on imaging. In localized cancers, it can detect minimal residual disease—whether tumor DNA remains in the blood after surgery. In colon cancer patients, the presence of circulating tumor DNA after surgery identifies those who will benefit from additional treatment and those who can safely avoid unnecessary therapy. The liquid biopsy allows real-time monitoring of tumor evolution, early detection of treatment resistance, and anticipation of relapse before conventional imaging shows it. The dream, still being pursued, is early detection of cancer itself—identifying tumors in asymptomatic people. A test commercialized in the United States can detect roughly twenty different cancers, but it does not yet meet European standards for sensitivity and specificity. Beyond clinical utility, the liquid biopsy improves quality of life by allowing doctors to adjust treatment intensity and avoid unnecessary toxicity, reducing emotional burden and disruption to daily living. The challenge now is to bring these techniques into public health systems in an orderly, evidence-based way, making personalized medicine accessible to everyone, not just those who can afford private testing.
Citações Notáveis
When Parkinson's is diagnosed clinically, more than 50% of dopamine-producing neurons have already been lost, limiting treatment effectiveness.— Ana Isabel Rodríguez, researcher at CiMUS
The goal is not to accumulate tests, but to integrate information to make better decisions.— Francisco Javier Blanco, chief of rheumatology at Complexo Hospitalario Universitario de A Coruña
Liquid biopsy allows us to spy on the tumor and prescribe better treatments to address cancer.— Rafael López, president of the Spanish Association for Cancer Research
A Conversa do Hearth Outra perspectiva sobre a história
Why does it take so long to diagnose Parkinson's—three years on average—when we can detect so much so quickly now?
Because the disease hides itself. Neurodegeneration starts a decade or two before you feel anything. Your brain compensates for the loss of neurons until suddenly it can't anymore. By the time symptoms appear and you see a doctor, more than half the relevant neurons are already dead. The biomarkers we're developing can see the damage happening in that silent phase, before compensation fails.
So these biomarkers are essentially early warning systems.
More than that. They're surveillance systems. They let us watch what's happening in real time—in the blood, in the cerebrospinal fluid, in tiny vesicles traveling from the brain. We can see not just that something is wrong, but what specifically is wrong, in which patient, at which stage.
You mentioned that in rheumatoid arthritis, two patients with the same diagnosis can be completely different biologically. How does that happen?
Disease names are human constructs. They're useful for communication, but they hide enormous variation. Two people might both have rheumatoid arthritis, but one's immune system is attacking in a different way, progressing faster, responding to different drugs. A single biomarker can't capture that complexity. You need to integrate multiple signals—proteins, imaging, clinical history—to see the actual person in front of you.
The liquid biopsy in cancer seems almost like spying on the tumor.
That's exactly what it is. Cancer cells are constantly shedding DNA into the bloodstream. We can catch those fragments, read them, understand what mutations the tumor has developed, what drugs it might resist. We can do this from a simple blood draw instead of biopsying tissue. And we can do it repeatedly, watching the tumor evolve in real time.
What's the biggest obstacle to making this real for patients?
Cost and implementation. The science works. We've proven it in research. But these technologies are expensive, and scaling them into public health systems requires infrastructure, training, standardization. The dream is that as these techniques spread, they become cheaper. But that's the real challenge—making personalized medicine accessible, not just to the wealthy.
Do you think we're close to catching cancer before symptoms appear?
In the United States, yes—there's already a test that can detect twenty different cancers. But it doesn't meet European standards yet for accuracy. We're getting there. The question is whether we can do it reliably enough that we're not chasing false alarms or missing real disease. That's still being worked out.