Developing Treatments for Alzheimer’s and Related Disorders with Precision Medicine: A Vision

Abstract

Precision medicine, also known as personalized medicine, is concerned with finding the right treatment for the right patient at the right time. It is a way of thinking focused on parsing heterogeneity ultimately down to the level of the individual. Its main mission is to identify characteristics of heterogeneous clinical conditions so as to target tailored therapies to individuals. Precision Medicine however is not an agnostic collection of all manner of clinical, genetic and other biologic data in select cohorts. This is an important point. Simply collecting as much information as possible on individuals without applying this way of thinking should not be considered Precision Medicine.

1. Introduction

Precision medicine, also known as personalized medicine, is concerned with finding the right treatment for the right patient at the right time. It is a way of thinking focused on parsing heterogeneity ultimately down to the level of the individual. Its main mission is to identify characteristics of heterogeneous clinical conditions so as to target tailored therapies to individuals. Precision medicine, however, is not an agnostic collection of all manner of clinical, genetic, and other biologic data in select cohorts. This is an important point. Simply collecting as much information as possible on individuals without applying this way of thinking should not be considered precision medicine.

The application of precision medicine to treatment development in the case of Alzheimer’s disease (AD) and related disorders (ADRD) is a natural next step for the field in light of challenges faced in treatment development focused on unitary explanations. Dementia is an expanding worldwide pandemic as in Fig. 1. In the absence of impactful disease-modifying therapies, the worldwide case count of dementia will increase from approximately 50 million in 2022 to well over 130 million cases in 2050, largely driven by population aging especially in Asia and the Americas.

Fig. 1.

People living with dementia around the world over time

2. Challenges in Treatment Development for Alzheimer’s Disease and Related Disorders

While dementia is best approached as a chronic brain disease, it is important to remember that ultimately it is a syndrome. There is growing understanding of the biology behind dementia—increasingly from more representative population-based studies—such that underlying pathogenic processes, brain structural and functional phenotypes, genetic associations, age affects, and clinical phenotypes at various disease stages are being understood. Further, informed by a life course perspective, a convincing body of evidence suggests a set of potentially modifiable dementia risk factors which likely interact with and influence these biological processes, disease phenotypes, and progression (e.g., education, hypertension, hearing impairment, smoking, obesity, depression, physical inactivity, diabetes, low social contact, alcohol consumption, traumatic brain injury, and air pollution) [1]. Consequently opportunities for targeted, designed therapies are growing. Table 1 displays the most common brain diseases that cause dementia. Recent understanding has emphasized that with increasing age, the complexity of neuropathology in people who die with dementia increases such that most cases of dementia are multifactorial. Further, population-based autopsy studies are demonstrating that neuropathologic lesions associated with dementia are common in individuals who die cognitively normal.

Table 1.

Causes of dementia

Alzheimer’s disease

Lewy body diseases (Parkinson ++)

Frontotemporal degenerations

Brain vascular disease

Large infarcts

Microinfarcts

Microbleeds

Vascular insufficiency

Late (limbic-predominant age-related TDP-43 encephalopathy)

Over 80 other proposed causes

Turning to AD, the brain pathology found in 50–70% of people who die with dementia, complexity should be considered the norm. Figure 2 is a cartoon that summarizes the microscopic appearance of the brain in AD. Without getting into detail, a number of key pathologic findings should be noted. These include the presence of A-beta 1–42 peptides misfolded into amyloid structures that accumulate into plaques, the presence of misfolded hyper-phosphorylated tau proteins inside neurons, synaptic degeneration, the presence of reactive astrocytes and microglia around plaques and degenerating synapses, as well as loss of neurons. Pathology is a static study of the brain, often at the end stage of a disease process, which cannot easily elucidate time sequences by which the findings appear. Nevertheless, autopsy and genetic studies have largely informed the widely discussed paradigm for the cause of AD the amyloid hypothesis, (Fig. 3). This hypothesis basically postulates that misprocessing of amyloid precursor protein leads to creation of toxic peptides that assemble into oligomers that over time deposit into plaques leading to synaptic degeneration and the emergence of tau phosphorylation inside neurons. Eventually sufficient loss of neurons leads to disconnectivity in key cognitive networks and the emergence of symptoms.

Fig. 2.

The brain in Alzheimer’s disease

Fig. 3.

The amyloid hypothesis

The amyloid hypothesis while exciting at the beginning has not borne the desired fruit of disease-modifying treatments. In 2020, after 40 years of research, we have in the USA four approved symptomatic therapies with very modest benefits, and none in the last 15 years. On June 7 2021 the United States Food and Drug Administration (FDA) granted accelerated approval to aducanumab for the treatment of mild AD on the grounds of its ability to remove amyloid from the brain despite the absence of clinical benefit. Despite this approval, there have been no clinically effective disease-modifying therapies even though multiple medications have been shown to remove or impact amyloid (in various forms) from the brain [2]. The treatment development field for AD is full of tombstones for therapies that failed to show benefit over placebo, and a few instances of therapies that may have worsened the clinical state relative to placebo. The most recent debate around aducanumab illustrates the complexity of this issue. As of this writing, the remaining benefit from “anti-amyloid” therapies rests with the possibility that they might be impactful for individuals who are asymptomatic, possibly even those who have not developed large numbers of amyloid plaques in their brains. A number of prevention trials are in the field that should bring an answer in the coming years. It should be noted though that these therapies have not proven effective in autosomal dominant “amyloid overproducing” gene carriers who develop dementia in mid to early late life.

So what is the problem? Treatment development for dementia is challenged in at least three ways. First, there has been excessive focus on the amyloid hypothesis which could be wrong or too restrictive. Perhaps anti-amyloid therapies will work for a subgroup of people or at a particular point in time of disease evolution. Second, while treatments have largely demonstrated efficacy in mice, especially transgenic mice, they have failed to benefit humans. Use of mouse models is understandable given the ethics, costs, and complexities involved with human studies. Fortunately, new opportunities exist to develop individualized, human models in the laboratory that could become platforms for the assessment of novel or repurposed FDA-approved therapeutics. Finally, much of what we know about ADRD comes from studies of highly select populations: those who enter studies at research centers in high-income countries. The few population-based studies have demonstrated that these individuals do not represent the general population. In fact, there is reason to think that individuals who have been studied represent the least heterogeneous group which has made it difficult for therapies to generalize when heterogeneity has increased. Further, we know from epidemiological data that prevalence and incidence rates of dementia vary substantially by race, ethnicity, and genetic ancestry—with persons from non-white backgrounds vastly underrepresented in research. Initiatives to increase heterogeneity have grown of late, aided by more attention in the media and the public messaging around ADRD and brain health. As a result, more and more individuals previously unable to come to research centers or skeptical/wary of research are volunteering to be in studies. A consequence of the emergent greater diversity is that control groups in clinical trials have had much slower clinical progression than in studies two decades ago.

3. Vision for a New Paradigm

At the Johns Hopkins Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, we propose to shift the paradigm to the one in Fig. 4. We believe that there is not a single pathway to symptoms. Many factors must be taken into account to parse heterogeneity and produce therapies that engage multiple targets simultaneously and that that are ultimately impactful at the population level. Factors such as genetics, education, environmental threats, lifestyle factors, reserve, trauma, physical health, and psychological stress are influential upstream from amyloid. Other processes such as inflammation, oxidative stress, insulin resistance, and brain perfusion play a role in progression down the cascade. And finally, we propose that it is important to broaden our approach beyond cognitive symptoms, recognizing that many individuals first present with neuropsychiatric (behavioral) symptoms such as irritability, anxiety, or depression well before any memory symptoms emerge [3]. Furthermore, there is evidence that some individuals first present with gait disorders that lead to falls and fractures [4].

Fig. 4.

The proposed new paradigm: AD is not one disease with different paths for different people

The Richman Center is therefore concerned with applying the concepts and culture of precision medicine to the challenge of developing treatments for ADRD. At the core of the center is a Brain Trust of scientists from several departments across Johns Hopkins in collaboration with scientists at the National Institute on Aging (the authors of this piece). The Brain Trust has developed a starting paradigm for its work (Fig. 5). At the core of this paradigm is the idea that three groups of symptoms should be considered resulting from progressive disintegration of synapses, then brain regions, then brain networks. Ultimately, the types of symptoms that emerge reflect the integrated function of the specific networks involved. The pathogenic cascade is affected by genetic variations that influence metabolism of amyloid precursor protein (APP), functions of APP, bioavailability of A-beta, toxicity of A-beta, disruption of tau functions, and excitotoxicity [5]. While these genetic variations are influential and impactful, they do not appear deterministic. And there is much to the genetic story that is unknown. Three additional influences affect progression down the cascade. One is cognitive reserve which reflects the ability of an individual brain to resist the ravages of degeneration. Reserve is intimately tied to a series of attenuators that involve diet, physical activity, as well as mental and social engagement through a lifetime. On the other side are variables that accelerate progression down the cascade including stress, chronic illness, comorbidities, impaired brain glucose metabolism, inflammation, as well as vascular processes that influence regional and global brain perfusion or result in macro- or micro-infarcts with corresponding brain tissue loss.

Fig. 5.

Precision medicine as applied to AD

To achieve its paradigm-changing goals, the Richman Center is bringing to bear a series of methodologies intended to overcome the challenges above. Large-scale, ethical access to individual patient medical records through electronic medical record platforms (EMRs) allows application of big data and machine learning analytics to very large numbers (hundreds of thousands) of real-world patients. Analyzing existing records over time offers the opportunity of defining subgroups with relevance to dementia while at the same time testing hypotheses regarding the influence of the variables in Fig. 5. This is an opportunity to understand whether there are distinct pathways to dementia. Is there an inflammatory pathway? A metabolic pathway? A sleep deprivation pathway? A reduced brain perfusion pathway? A post-anesthesia pathway? Medical records also contain digital brain images that can be automatically analyzed to relate clinical phenotypes to brain phenotypes using features such as regional brain volumes, or network connectivity. As suggested in Fig. 6, over the next few years, it will be possible to do first pass deep phenotyping of pathways to dementia. This will be relatively crude and hypothesis generating to lay the foundation for the addition of biologic variables derived efficiently from blood analysis. The Richman Center has developed a platform whereby a blood drawn can derive DNA, plasma, extracellular vesicles/(see below), and peripheral blood mononuclear cells (PBMCs) to develop induced pluripotent stem cell lines of individuals.

Fig. 6.

Schematic of the Richman Center approach: real-world cohorts meet big data

A few words about the individual approaches. EMR data offer many advantages including access to broadly representative patient populations, recognizing that most people in the ADRD age of risk are engaged in primary care. Access to EMRs offers large numbers but medical record data have challenges in variability of the information collected across providers. Medical records can provide information about illness course across several variables before and after a cognitive diagnosis. Examples include patterns of clinical presentation when a cognitive condition emerges and how critical events such as hospitalizations affect trajectory, effects of comorbidities and medication on course, patterns of service utilization, as well as correlates to brain images.

Extracellular vesicles (EVs) are nano-scale size particles that are coated by a lipid membrane and are continuously produced by all cells in the body; smaller EVs are termed ectosomes/microvesicles by subcellular origin. They play multiple roles that are still under investigation, in normal and pathologic cellular function, including in cell-to-cell communication and in cellular processes for the disposal of cellular toxins, unwanted intracellular molecules, or damaged organelles. These vesicles offer great promise because of a couple of characteristics. First, they pass through the blood-brain barrier to plasma where they can easily be collected and studied. Second, they have surface markers that appear to be unique to their cell type of origin. Third, their contents which include proteins, lipids, carbohydrates, and RNA and DNA species provide information about metabolic status inside the cells of origin. Simplistically therefore EVs sampled from an individual’s plasma that originate from cortical neurons or astrocytes can provide information about the intracellular processes of these brain cells. Thus, they could be useful markers in diagnosis, prognosis, treatment targeting, or evaluation of treatment effects. Recent evidences that the cargo of neuronal origin exosomes in plasma correlates strongly with CSF measures of AD relevant proteins are highly encouraging about biomarker discovery possibilities [6].

Finally, individual level iPSCs have great potential to serve as biomarker or drug testing platforms. Briefly, laboratories around the world are able to reprogram peripheral blood mononuclear cells (PBMCs) using viruses and episomal plasmids. The iPSCs can then be differentiated through the use of transcription factors to different types of brain cells such as neurons, glia, or microglia. In addition to 2D brain cell cultures, 3D brain cell cultures (“organoids”) are possible that closely replicate aspects of the brain environment. Studying the physiology of these brain cells can provide information about an individual’s disease risk, susceptibility to specific symptoms, or response to approved or novel medication. In the not-so-distant future, therefore, it might be possible for us all to have our brain cells growing in the lab so as to test whether individual drugs are likely to be helpful.

The Richman Center is engaged in a number of individual projects that involve, for example, MRI atrophy pattern phenotyping as a means of prognosticating dementia progression, symptomatic expression, or response to FDA-approved drugs. Other projects include investigation of specific pathways to dementia such as a vascular pathway using novel MRI measures of cerebrovascular reactivity. There is also an exploration of an inflammatory pathway based on measurement of a blood-derived endophenotype [7]. In addition, the Center is intent on early wins: by analyzing medical records, it will be possible to predict for primary care physicians which patients with dementia have a poor prognosis and would benefit from more intensive memory care coordination through a system developed at Hopkins, MIND, at HOME [8]. This care coordination model has been shown to delay transition to a nursing home, improve life quality, reduce weekly hours of care required of caregivers, and reduce healthcare costs.

4. Hope for the Future

While there have been several disappointments with treatment development for ADRD, there is hope that anti-amyloid therapies will be impactful if delivered early enough. More importantly, the treatment development paradigm is shifting to precision medicine with a series of efforts illustrated by work at Johns Hopkins. We anticipate that this will bring about near-term wins in healthcare delivery as well as long-term wins by defining therapeutically relevant biological sub-types of ADRD to which personalized approaches can be delivered.