Non-invasive diagnosis of Preclinical Alzheimer’s Disease

Alzheimer’s disease (AD) is one of the leading causes of death in the United States, and prevalence is on the rise. Effective therapeutics are extremely limited, and the overwhelming majority of clinical trials to date have failed¹.

Aducanumab is a very promising candidate and, while the future of this particular drug remains unclear, there is little doubt that science will advance and therapeutics will evolve. Eventually, an effective treatment agent will be discovered, and it will be critical that physicians are prepared to manage the deluge of patients that will present to clinic seeking treatment.

With such widespread prevalence of Alzheimer’s disease, the development of a new and effective therapeutic agent brings overwhelming promise for those affected by the disease. It will also introduce significant challenges for providers. One of the most prominent challenges to overcome will be identifying individuals that are most likely to benefit from treatment in a rapid, efficient, and safe manner. For drugs that target amyloid clearing, such as aducanumab, they may be most effective when administered in the preclinical phase.

Preclinical Alzheimer’s disease is the initial disease stage when there is evidence of biomarker positivity without the presence of an overt clinical syndrome². It is assumed that without intervention, the majority of individuals in the preclinical stage will develop the clinical syndrome and thus, advance to clinical Alzheimer’s disease. Intervening in this preclinical stage, when the disease is present but clear symptoms are not, is where interventions may hold the greatest promise. Without overt symptoms though, identifying these individuals can be incredibly difficult, especially with the currently available tools.
 

At present, there are a host of biomarkers available to determine the presence or absence of Alzheimer’s disease pathology. PET scans sensitive to amyloid, structural magnetic resonance imaging to identify neurodegeneration, cerebrospinal fluid to detect amyloid and tau, and genetic tests are all currently available, and the likelihood of eventually discovering a reliable serum test is high.
 

Until a simple blood test is validated, a major challenge with all of the currently available biomarkers is that they are costly, some are invasive, and most are not widely available outside of specialty clinics.

 

Thus, reliance on biomarkers alone to determine eligibility creates a significant barrier for patients and providers alike, which will hinder effective and widespread dissemination of treatments, and potentially slow delivery to those who need it the most.

Equally important is identifying those patients in the preclinical stages who are most likely to be accumulating amyloid, and thus, may benefit from intervention. Doing so will require non-invasive surrogate markers of amyloid that can be deployed across a multitude of settings with minimal resource demands, that are both time and cost efficient.
 

Cognitive testing may be a viable option to fill this void, especially if a specific tool can be validated with both high sensitivity and specificity to Alzheimer’s disease pathology.
 

The issue is that brief cognitive screenings such as the Mini Mental Status Exam³ or the Montreal Cognitive Assessment⁴, while sensitive to gross cognitive impairment, are so coarse that they lack specificity for detecting the subtle nuances of Alzheimer’s disease.
 

Comprehensive neuropsychological assessment, on the other hand, generates a fine-grained profile of cognitive functioning that is both sensitive and specific to Alzheimer’s disease; however, as with many of the available biomarkers, neuropsychological evaluation is expensive and inefficient for widespread population screening⁵ and is not widely available for the majority of patients who need it ⁶

What is needed is something that provides a more granular profile of cognitive functioning than a cognitive screening that is easily accessible and less resource demanding than traditional comprehensive neuropsychology.
 

Leveraging technology to its maximum and automating both administration and scoring of standardized neuropsychological measures readily fills this gap between cognitive screenings and comprehensive assessment and when integrated into routine clinical workflows, provides a low-friction digital solution that can be easily deployed at scale, with minimal resources. For example, measures of processing speed, and a rich characterization of executive functioning are notable weaknesses for most screening measures, which can be particularly important in differentiating very early manifestations of Alzheimer’s disease symptoms from other common causes of cognitive difficulty in older adults (e.g., cerebrovascular disease), but can be readily integrated into a digital platform. This is precisely the type of tool needed in order to address the challenges faced when a viable treatment for Alzheimer’s disease becomes available, in addition to its usefulness for assessing patients periodically to determine impact of treatment and disease progression.

Of critical importance with any digital assessment is validation, not only in terms of core psychometric properties of validity and reliability, but also in comparison to traditional analog neuropsychological measures. In doing so, such a tool would generate a cognitive profile of cognition far richer than the majority of simple screening tools currently available. The richness and the diversity of the cognitive domains measured is critically important, as it not only increases sensitivity to generalized cognitive impairment, but it also increases specificity to Alzheimer’s disease, which is where most other brief assessments fall short. An added advantage of digital assessments is the potential for novel outcomes, such as reaction time variability, that simply cannot be easily derived from analog measures. Such indices hold tremendous promise for being able to identify any subtle cognitive changes in the preclinical phase that have historically gone undetected.
 

Until a an accessible, non-invasive, and inexpensive biomarker is validated (e.g., a blood test) that can detect amyloid status reliably, the added sensitivity and specificity of a non-invasive, easily administered digital cognitive assessment will allow clinicians to rapidly triage patients and help  in diagnosing individual risk of any treatment decisions.  . With this added information, providers will be able to refer patients with elevated risk for confirmatory biomarker studies. This is also particularly important for clinical trials, where enrollment of amyloid negative participants can significantly undermine the success of the trial.

 

It is no longer a question of if there will be a treatment for Alzheimer’s disease, but when. And although there will be significant challenges once a drug is approved, finding the people who will benefit the most does not have to be one of them.

Justin B. Miller, PhD, ABPP/CN is the Director of Neuropsychology at the Cleveland Clinic Lou Ruvo Center for Brain Health in Las Vegas.  Dr. Miller is a paid consultant for Philips and has contributed to development of Philips IntelliSpace Cognition.  For more of Dr. Miller’s work on ISC, see ISC in the News section.

References

1. Cummings JL, Morstorf T, Zhong K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther. 2014;6(4):37. doi:10.1186/alzrt269
2. Dubois B, Hampel H, Feldman HH, et al. Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12(3):292-323. doi:10.1016/j.jalz.2016.02.002
3. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-198. doi:https://doi.org/10.1016/0022-3956(75)90026-6
4. Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: A Brief Screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699.
5. Miller JB, Barr WB. The Technology Crisis in Neuropsychology. Arch Clin Neuropsychol. 2017. doi:10.1093/arclin/acx050
6. The MarkeTech Group. Study of 75 Neurologists with Clinical Practices, Study Commissioned by Philips. Davis, CA; 2018.