Candidate Markers

Since the pathological process precedes the clinical manifestations of the disease, the earliest markers for the illness may not be found if the search for them begins with the first clinical symptoms. To aid diagnosis in the presymp-tomatic and preclinical stages, we need to find biological markers for the disease that are detectable well before even subtle clinical symptoms are apparent.

Many of the proposed markers for the AD process will be discussed throughout this book. Although, there are substantial differences in the existing approaches, in general, two major strategies have been employed. One strategy takes advantage of the characteristic anatomic distribution of the neu-ropathological changes of AD. The other strategy measures presumed byproducts of the underlying pathological process in, for example, cerebrospinal fluid (CSF), serum, urine, or skin.

Like any degenerative illness, AD does not afflict all neuroanatomical locations with equal severity. As is discussed in Chapter 3, there is a characteristic pattern of progression in the cortex that initially emphasizes limbic and posterior association regions and tends to spare primary sensorimotor areas (21,94,98,111-121). This distribution differs substantially from other degenerative processes such as frontotemporal dementia, which has a predilection for frontal and anterior temporal lobes (78,81,122-124). Many of the proposed diagnostic strategies take advantage of the relative anatomical selectivity of AD pathology, especially early in the course of the illness. The early involvement of limbic regions such as the entorhinal cortex and hippocampus is the basis for using morphometric MRI analysis of mesial temporal structures to distinguish patients with AD from normal controls, as discussed in Chapter 6. The early destruction of these regions essential to neuropsychological functions such as memory provides the anatomical basis for the pattern of neuropsychological deficits that mark the preclinical and early stages of the illness, as reviewed in Chapter 8. Functional imaging studies also take advantage of the predictable distribution of disrupted cortical metabolic or perfusion activity, which most often involves bilateral temporoparietal cortex, as reviewed in Chapter 7. Finally, the observations of exaggerated pupillary dilation to dilute tropicamide (a topical cholinergic antagonist) may be due to the early development of pathology in the Edinger-Westphal nucleus of the midbrain, a center for the regulation of pupillary response (see Chapter 10).

All strategies that take advantage of the distributional predilection of the AD pathological process suffer from the same potential limitations. The findings are not pathognomonic of AD. Other diseases that may affect similar areas of the brain could generate similar patterns and thus "false positive" results. Moreover, atypical cases of AD, with an unusual distribution of pathology, would likely yield false negative results. Although such problems might potentially diminish the utility of these diagnostic tools, we suspect that atypical presentations of AD and non-AD processes with overlapping anatomic distributional characteristics represent a relatively small percentage of cases. The impact of such cases on the diagnostic accuracy of these tests is an empirical question that will need to be addressed.

The second major strategy, measuring components or by-products of the pathological process of AD, relies on an understanding of the pathophysiol-ogy underlying AD. Chapter 4 presents one of the dominant theories about the pathogenesis of the illness. Additional information about the biology of the disease can be found in Chapter 5, addressing genetic factors, and Chapter 9 on peripheral markers. Despite major advances, many questions remain that have implications about "translating" our understanding of the biology of the illness into diagnostic strategies: Which products are directly linked to the pathologic process, and which represent nonspecific responses to ongoing cerebral injury? Which can be usefully measured without a brain biopsy? Which turn positive in the presymptomatic and preclinical phases? Some putative markers of AD, such as tau protein, are also found in other diseases. Thus, their specificity will depend in part on the distribution of the various dementing illnesses in a study population. Also, many assays currently require CSF. The need for a lumbar puncture is likely to limit their widespread application. Chapter 9 reviews a broad range of peripheral markers that have been proposed, including measurements of CSF tau, beta amyloid, neuronal thread protein, serum melanotransferin (P97), and mitochondrial DNA mutations. Recently, a consensus statement on criteria for evaluating potential biomarkers for the disease has been issued jointly by the Ronald and Nancy Reagan Research Institute of the Alzheimer's Association and the National Institute on Aging Working Group (see the Appendix, pp. 329-348, for the complete report).

Fig. 2. Theoretical sequence of biological markers for Alzheimer's disease.

Biological markers must be capable of detecting some aspect of the pathological cascade of AD that leads to end-stage disease. Different markers will tap different components of this pathological cascade at different points in the pathological process. Some markers may be manifested at relatively early periods in the presymptomatic stage, while others may only become positive in response to the presence of pathology at later periods. The best markers are those most directly related to the pathologic process or that are uniquely a consequence of the pathology. Moreover, they would predict as early as possible the presence of a pathological process that leads to end-stage disease. Figure 2 illustrates the concept of biologic markers that "turn positive" in sequence. Since few data are available to order the currently proposed markers, the scheme is presented without naming specific markers.

It seems unlikely that any single marker will predict the development of clinical symptoms with 100% certainty. We suspect that in the future more re searchers will take advantage of combining information from different techniques. For example, statistical techniques such as logistic regression and discrete-time survival analysis can be applied to data from longitudinal studies of at-risk elders, many, but not all, of whom subsequently become demented. These methods permit the development of models that reflect the relative predictive value of different biological markers. Once validated on a second sample, they can provide clinically useful estimates of the probability that individuals will develop dementia of the Alzheimer type. We can imagine setting a threshold probability level that would trigger the initiation of newly developed therapies. As we learn more about the relationship between specific indicators and the natural history of the disease, models assigning weights to different markers should have increasing clinical utility.

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