There is lack of agreement about how to precisely define who is a “patient” but it is generally accepted that persons who require medical care would be considered a patient. Over the past 15–20 years, our understanding of what it means to be a patient has undergone rapid change. In the recent past, patients could be treated only after symptoms of disease had already occurred. Today’s medical system, however, is increasingly focused on predicting and preventing disease1 in persons who are asymptomatic or have mild symptoms, hence expanding the patient pool. In many areas of medicine, from cardiology to oncology, early detection of disease has allowed patients to enjoy healthier and more productive lives.
These changes have also begun to transform neurology and psychiatry. Perhaps most importantly, recent advances in genetic testing, neuroimaging, and other healthcare technologies have allowed researchers to discover biological markers (or “biomarkers”) for specific brain diseases2. Some of these biomarkers can be detected years before these brain diseases present with symptoms that are typically diagnosed in the hospital or clinic. Today, for example, direct-to-consumer genetic testing allows healthy people to quickly and easily learn whether they carry genetic mutations or variations predisposing them to Alzheimer’s or Parkinson’s disease. The ability to detect these and other markers of brain disease has changed the way in which healthcare is understood by a number of stakeholders, including the general (and healthy) population, patients, clinicians, insurers, and drug developers. The earlier detection of persons at-risk for the development of these and other neurodegenerative diseases may also allow for the recruitment of these individuals for clinical trials which test the effectiveness of neuroprotective therapies. These discoveries also raise numerous questions regarding the definition of a “patient,” what qualifies as a “diagnosis,” and how patients’ knowledge of being at increased risk for a disease shapes their self-image and impacts their quality of life. In other words, how should we think about disease when it has yet to manifest with symptoms? Both patients and clinicians want to know.
In this four-part series, based on presentations given by Professors Christopher Correll (Hofstra Northwell School of Medicine, New York, USA), John Hardy (UCL Institute of Neurology London, UK) and Karen Rommelfanger (Center for Ethics, Emory College, Atlanta, USA) we explore how earlier detection of brain disorders could improve patient care. Part 1 in this series introduces the concept of prodromal and preclinical disease—a state in which patients have markers of a disease but few or no symptoms. Part 2 focuses on efforts to identify (and treat) the early stages of schizophrenia. Part 3 takes a similar approach to two neurological disorders: Alzheimer’s disease and Parkinson’s. Part 4 explores the ethical implications of preclinical diagnosis and proposes some preliminary solutions for patients in search of answers.
A new approach to brain disorders: Preclinical and prodromal disease
Today, most patients are diagnosed with brain disorders at a relatively late stage, often only after significant brain damage has already occurred. To adopt an analogy from Thomas Insel, the former Director of the National Institute of Mental Health, diagnosing someone at such a late stage is like recognizing and treating a patient’s coronary artery disease only after he or she is rushed to the hospital with a myocardial infarction3. We can do better. Like heart disease, which clinicians routinely diagnose early in the disease course using blood tests and imaging techniques, we now know that brain diseases are marked by pathological changes that begin years or even decades before the onset of clinical symptoms. The ability to identify these changes at earlier time points, especially before symptoms appear, would provide clinicians and patients with the opportunity to start disease-modifying treatments that could prevent or slow progression of the disease, so called primary prevention. As in other areas of medicine, early intervention would prevent unnecessary pain and suffering by pre-patients and their families while reducing health care costs.
Over the past two decades, especially in the case of neurological disorders such as Alzheimer’s and Parkinson’s disease, advances in both genetic and neuroimaging technologies have allowed us to discover a number of potential indicators of future disease onset. These markers have given us an understanding that brain diseases, like heart disease and many other medical problems, exist along a spectrum: disease begins in a pre-symptomatic or preclinical stage, advances to a prodromal period during which patients experience attenuated symptoms, and finally culminates in full disease onset as diagnosed by established criteria4. In neurology, for example, a healthy person who carries a strong genetic risk factor for a certain disease—such as the ApoE4 allele in Alzheimer’s disease or the LRRK2 mutation in Parkinson’s—could be said to be in the preclinical state of the disease. That same person who later exhibits slight motor signs or memory loss, perhaps considered “forgetfulness” by the patient or family members, has progressed to the prodromal state of disease: intervention here would be secondary prevention. Finally, the patient may experience full symptom onset and further disease progression which is the stage of treatment and tertiary prevention (see fig. 1).
The well-known “Jack” curve—named after an Alzheimer’s researcher who proposed that different biomarkers emerge at different stages of disease—illustrates how one could understand Alzheimer’s disease as a continuum. As seen in Figure 1, amyloid beta (Aβ), a protein that forms sticky plaques in the brain, begins to accumulate in the brains of patients with Alzheimer’s disease even while they are cognitively normal, setting the stage for eventual mild cognitive impairment (MCI) and dementia. These markers of disease are explored in more detail in Part 3 of this series.
Clinical course of Alzheimer’s disease based on biomarker changes.
Sources: Adapted from Sperling et al,5 see also Jack et al6
The difference between the preclinical and prodromal disease states lies not only in the progression of the disease but also in the phenomenological manifestation of the disease as demonstrated by the onset of specific symptoms. As testing methodologies become more advanced and clinically sophisticated, it is hoped that more and more markers of disease onset will be available to (future) patients, their family members, and clinical personnel in order to allow for earlier, and meaningful, intervention. Instead of simply treating the symptoms of diseases, the goal of these interventions would be ideally to target the underlying disease process.
How do we understand “disease” in psychiatry?
In psychiatry, biological markers comparable to the protein plaques in Alzheimer’s disease have proven to be more elusive. The absence of clinical biomarkers for mental disorders leaves psychiatric care at a disadvantage compared to other fields of medicine where, for example, genetic testing has allowed clinicians to detect disease before clinical onset. Without knowledge of such markers, psychiatric clinicians are largely left to treat the symptoms of psychiatric disease after they present themselves rather than considering or encouraging preventative measures.
In recent years, however, some exciting advancements in neuroimaging techniques such as positron-emission tomography (PET) and structural and functional magnetic resonance imaging (MRI and fMRI) have allowed researchers to search for and identify biomarkers of psychiatric illness5 (see our series of articles on brain imaging for psychiatrists Part 1, Part 2, and Part 3), even in childhood or adolescence6. Researchers are now able to understand the brain with more detail and precision than ever before, allowing them to examine, for example, the relationship between environmental factors and disease onset. Such knowledge provides researchers and clinicians with the potential to intervene at an earlier stage of psychiatric disease, perhaps even at the prodromal stage when symptoms may have yet to manifest in a manner noticeable to the individual or their loved ones. In the case of schizophrenia and other psychotic disorders, research has shown that early intervention leads to significantly faster recovery and reduces costs by nearly two-thirds compared with care delivered by traditional public health services7. The ability to intervene even earlier – before the first episode of psychosis – would likely reduce personal and societal costs and lower the incidence of psychiatric disease even further8.
Risk factors in psychiatry
Like most diseases in modern medicine, brain disorders are identified and diagnosed based on specific signs and symptoms and subsequently addressed by treating the symptoms of the presenting disease. As medical science has evolved over the years, especially with the aid of technological advances, researchers and clinicians have gained insight into environmental and genetic risk factors that may lead to disease even before symptoms present themselves. In psychiatry, although it is possible that a small number of genes may directly influence the pathogenesis of disease, it is more likely that the relevant genes influence a range of genetically-influenced intermediate characteristics (also called “endophenotypes”) that subsequently affect the risk of developing a disorder9. In the case of schizophrenia, for example, potentially useful endophenotypes include a decline in working memory and specific sensory abnormalities10. These and other endophenotypes are likely to reflect the actions of multiple genes and to relate to both genetic and environmental influences. As such, the risk of developing a psychiatric disorder is shaped by the way in which an individual’s genetic profile interacts with a particular set of risk factors11.
Neuroimaging presents a host of opportunities to better understand the brain in a number of facets, including in a developmental state, how it reacts under certain conditions such as stress, and what influence certain environmental factors have on the brain. For example, being born or living in a city, migration, and perceived social status have each been shown to be important risk factors for the future development of schizophrenia. Identifying risk factors for mental illness is particularly important as medicine strives to understand disease progression at prodromal and preclinical stages.
Is it possible to identify risk factors that have a causal relationship to the development of psychiatric disease or have an impact on brain function, particularly in a prodromal or preclinical phase of the disease? After all, the identification of such risk factors in their preclinical and prodromal states would likely aid in efforts to prevent the onset of these disorders. Although traditional risk factors such as stress, smoking, alcohol use, and diet influence the health and well-being of an individual and increase the risk of experiencing poor health, recent research suggests that other risk factors are correlated with the development and maintenance of select psychiatric disorders, including schizophrenia. As efforts increase to gain insight into schizophrenia and other psychiatric disorders at earlier stages of their progression, technologies such as genetic testing and neuroimaging have played an increasingly important role in identifying candidate biomarkers. Figure 2 illustrates how one could identify and understand biomarkers from the genetic and environmental level through to exhibited behaviour.
Advances in early detection
Breakthroughs in genetics
Genetic testing has produced a sea-change in our understanding of neurological disorders. In the past few years, millions of people have purchased genetic testing kits costing less than $200 USD that reveal information about their ancestral roots—and potentially whether they carry genetic markers for late-onset Alzheimer’s disease and Parkinson’s disease. The fact that genetic testing has reached mass-market availability is nothing short of astounding, especially considering that these methods were scientifically and financially inaccessible only a few years ago. For example, while the cost of performing whole genome sequencing (WGS) was over $3 billion USD only 15 years ago, it can now be accomplished in under two weeks for less than $1,000 USD12. And the cost of genetic testing continues to rapidly decrease while access is increasing.
Innovations in neuroimaging
The past decade has also seen stunning progress in neuroimaging techniques used to visualize the structure and function of the brain (see our three-part series on brain imaging for psychiatrists). For example, in Alzheimer’s disease, PET imaging has revealed subtle changes that occur in the brain during the prodromal or preclinical stages of disease, including the accumulation of tau protein and beta amyloid plaques13. Measurable changes in these biomarkers could one day be used to predict the onset of Alzheimer’s disease and allow clinicians to track disease progression. In Parkinson’s disease, imaging modalities such as PET, single photon emission computed tomography (SPECT), transcranial sonography (TCS), high-field/novel MRI sequences, and myocardial scintigraphy have demonstrated potential to identify preclinical/prodromal status14. Likewise, in psychiatry, neuroimaging techniques have offered a unique opportunity to examine the biological underpinnings of common disorders. In the following Feature in this series, we discuss how patients with warning signs of psychosis show specific changes in the brain that could be used to promote early detection and intervention.
It is likely that neuroimaging will continue to play a key role in illuminating the neurobiology of brain disorders. New technologies, such as those that can be used detect inflammatory changes in the brain, have offered a novel approach to identifying the roots of depression and schizophrenia5. Other researchers have leveraged artificial intelligence, especially machine learning techniques, to find patterns in MRI images that would go undetected even by the most experienced radiologists. After identifying these patterns, machine learning algorithms have successfully predicted whether individual patients would go on to develop schizophrenia15,16 or Alzheimer’s disease17,18 with a high level of accuracy—at least 80%. These new tools will allow researchers to better understand the pathophysiology of brain disorders while offering the hope that they could soon be treated before exerting their most devastating effects.
Psychiatry and neurology have entered a time of rapid and unprecedented change. Recent advances in genetics and neuroimaging have revealed that changes occur in the brains of patients with Alzheimer’s, Parkinson’s, and schizophrenia years before the onset of symptoms. In the following three Parts in this series, we explore how researchers and clinicians have taken steps to identify brain diseases at the earliest stages and treat patients before they develop potentially severe symptoms. Although the technical and ethical challenges of early diagnosis are significant, it is hoped that these discoveries will improve quality of life for patients at risk and ease the immense social and personal costs of untreated brain disease.