There are a variety of neurodegenerative pathologies associated with the development of late-life dementia, with an equally complex and evolving array of diagnostic labels. While AD is by far the most prevalent [1
], cognitive brain failure associated with a variety of frontotemporal lobar degenerations (for example Pick’s disease, frontotemporal dementia with parkinsonism, frontotemporal dementia with motor neuron disease) and midbrain syndromes (such as Parkinson’s dementia, progressive supranuclear palsy, corticobasal degeneration) are also associated with progressive dementia. Each has a recognizable pathological fingerprint. The clinical phenotype, and thus the clinical diagnostic criteria for each, is primarily based on the areas of the brain most affected during the initial stage of the illnesses. However, mixed pathologies are common, challenging the clinician’s ability to identify the single or dominant pathology responsible for the patient’s cognitive brain failure.
Laboratory-based methods to detect the earliest changes associated with these neurodegenerative pathologies and definitively identify the responsible pathology have the potential to increase diagnostic certainty, particularly during the initial stage of cognitive brain failure, and perhaps to provide information about disease activity that can be used to measure treatment efficacy [2
AD is the major cause of late-life dementia in the United States, with an increasing personal, social and economically devastating burden associated with the steady growth of the number of individuals living into the eighth and ninth decade of life [3
]. As a result, progress in the early and reliable identification of AD and the discovery of disease-modifying treatments have become major public health goals. Accomplishing both will require a shift from the traditional approach of detecting and diagnosing specific types of late-life neurodegenerative dementia based on the clinical phenotype of cognitive failure to one that includes the detection of the responsible pathology as part of the diagnostic inclusion criteria. The laboratory tools to accomplish this include biochemical methods (detection of pathological proteins in cerebrospinal fluid), imaging methods (detection of regional atrophy patterns on MRI and the identification of deposits of aggregated protein using MRI T1ρ
), and the use of positron emission tomography (PET) and single photon emission computerized tomography (SPECT) compatible radioactive ligands retained by the neuropathologic lesions to visualize the distribution and intensity of the lesions. These tools are collectively called biomarkers, as they use biologically based methods to ‘mark’ the presence of pathology.
There are several reasons for the emerging need to incorporate biomarkers into the diagnostic criteria used by clinicians to identify the dominant pathology (or mix of pathologies) responsible for a patient’s cognitive failure. They include the increasing recognition that a variety of neurodegenerative and vascular pathologies can coexist, each capable of contributing to the symptomatic expression of cognitive brain failure. In addition, a single type of pathology can produce a variety of different types of cognitive and behavioral symptoms, making it difficult to reliably identify the pathology based solely on the clinical phenotype. And lastly, it is recognized that the pathological process begins decades before the first symptoms of brain failure, making early identification based on symptomatic cognitive failure difficult in a situation where the initiation of early treatment is imperative to achieve the maximum benefit from pathologically targeted disease-modifying drugs.
Developing the tools to accomplish this goal is the primary aim of the biomarkers of late-life dementia program at PENN. The focus is the identification of pathology associated with AD.
Because it is unlikely a single biomarker will provide the diagnostic certainty needed by clinicians and patients, we have initiated a multimodality approach that incorporates biochemical methods, anatomic imaging, molecular imaging, metabolic imaging and pathologic imaging.
A unique advantage of the PENN biomarker development program is the ability to determine the performance characteristics of candidate biomarkers using patients and cognitively normal elderly subjects comprehensively evaluated and followed longitudinally in the PENN Memory Center. All receive standardized assessments using a protocol established by the National Alzheimer’s Coordinating Center that is used for all individuals evaluated by the 32 Alzheimer’s Disease Centers, all of which are funded by the National Institute on Aging. In addition, this ‘Uniform Data Set’ assessment protocol has increasingly been adopted by national and international collaborative studies, including the Alzheimer’s Disease Neuroimaging Initiative funded by the National Institute on Aging, reflecting a recognition of the considerable advantage associated with different studies that share common assessment protocols.