When does Alzheimer’s disease (AD) look like normal aging? In the oldest old, suggest scientists led by Dominic Holland, University of California, San Diego. Writing in the August 2 PLoS ONE, Holland and colleagues report that AD-associated decline slows with advancing age, while “normal” aging-associated decline picks up, so that it becomes harder to distinguish people developing AD late in life from their age-matched controls. This suggests that doctors and researchers should take age into account when diagnosing AD and conducting clinical trials, wrote the authors.

“These and other data indicate that clinical detection of AD and its distinction from normal aging is more difficult in the oldest old,” Kurt Jellinger, Institute of Clinical Neurobiology, Vienna, Austria, wrote to Alzforum in an e-mail. Jellinger was not involved in the study.

Few studies have taken a hard look at AD in the extreme elderly population, but some suggest that brains differ between people in their sixties and those in their nineties. For one thing, younger AD patients have more plaques and tangles than older ones at autopsy, and pathology can build up in normally aging healthy controls (see ARF related news story on Savva et al., 2009). Further, cross-sectional data suggest that reduced brain volume predicts AD better in 60- to 75-year-olds than in 80- to 90-year-old patients, and that cognitive decline, relative to age-matched controls, in younger AD patients surpasses that in older (see Stricker et al., 2011). Holland delved even further into the interaction of age with AD in a large sample, looking at brain shrinkage and cognitive decline over time, along with cerebrospinal fluid biomarkers (CSF).

The research group analyzed 723 people from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset who were 65 or older at baseline, including 222 healthy controls, 345 people with MCI, and 156 with early-stage sporadic AD. The Clinical Dementia Rating (CDR) was used to differentiate between groups. Participants came in every six or 12 months for clinical assessment and a magnetic resonance imaging (MRI) scan. About half also gave CSF samples at baseline. Those with AD were followed for up to two years, and healthy controls and those with MCI for up to three. This enabled the team to get baseline measures and, using available follow-up data, calculate annual rates of decline for each person. From this, the scientists derived a spectrum of measurements across ages 65 to 90.

What emerged was a convergence of almost every measure as people approached the oldest ages. For instance, atrophy rate in the whole brain, inferior parietal cortex, and retrosplenial cortex distinguished disease categories quite well in the youngest patients, but as people neared 85 and 90 years old, annual rates of change looked quite similar amongst all three groups. The same held true for two cognitive tests; the ADAS-Cog and the MMSE, but not for the CDR. Baseline values of certain CSF biomarkers also converged at older ages. While concentrations of Aβ42, total tau, and phosphorylated tau (p-tau) diverged among healthy 65-year-olds and those with MCI or AD, levels overlapped in the oldest participants. In particular, CSF p-tau, considered a general marker of neurodegeneration, was almost equal in all of the oldest old, irrespective of AD or MCI diagnosis. In addition, annual conversion rates from MCI to AD fell by half as people aged, dropping from about 16 percent in the youngest to about 8 percent in the oldest.

“It shows that AD proceeds more aggressively in younger patients than among older patients, which might explain why the AD burden [plaques and tangles] is similar among older healthy volunteers and older patients with AD," said Thaís Minett, University of Cambridge, UK.

These findings could be important in the clinic, where cognitive decline is currently the principal way to diagnose AD, said Holland. “In older people showing less deterioration [than younger AD patients], a doctor may be hesitant to diagnose AD,” he told Alzforum—though the patient may have the disease. Older patients may need to be more carefully evaluated to ensure that AD symptoms are not mistaken for simple aging, he said.

These results also have implications for clinical trials. Given the similar rates of decline between very old AD patients and age-matched normal controls, sample sizes would need to be very large to detect therapeutic benefit in this age group. Nevertheless, the oldest old should be included in clinical trials to be sure that they tolerate new medications and that the medicines work in that population, said Claudia Kawas, University of California, Irvine.

Kawas and the authors caution that these results may not apply to the general population. ADNI is a rigorous study and enrolls a selective cohort, she said. Younger, physically able 65-year-olds with aggressive disease are more likely to participate than rapidly declining 90-year-olds. “I’m a little concerned about the bias of the sample,” said Kawas. Further, while conversion to AD seems lower in the oldest people, it could be because MCI in old age is due to mixed pathologies, giving the illusion that these people are more stable, she said.

What explains the slower rates of decline in very old AD patients? One possibility is that they actually developed the disease early, but have always had a slow decline. Alternatively, a faster rate of progression in early disease could precede a slower one later in life. “Both are plausible interpretations of the data,” Holland said. In future studies, he hopes to model the full trajectories of all biomarkers for people at different onset ages to tease out the story further. With the current ADNI data he can start that analysis, though it remains to be seen if it has enough data points to flesh out the entire age spectrum, he said.—Gwyneth Dickey Zakaib

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  1. The paper by Dominic Holland et al. reporting that AD-associated decline slows with advancing age is interesting. Although no autopsy confirmation was available in this study, these data agree with neuropathologic studies in the oldest-old (Haroutunian et al., 2008).

    However, there are some limitations of this study, which only in part have been mentioned by the authors:

    1. The importance of confounding pathologies, in particular, cerebrovascular lesions including the importance of CAA (the authors only mentioned microvascular pathology), Lewy body pathology, argyrophilic grain disease, hippocampal atrophy, etc., which are frequent in aged human brains (see "mixed dementia," e.g., Kovacs et al., 2008; Jellinger and Attems, 2011). It should be emphasized that up to two-thirds of aged human brains contain non-AD type pathologies (Nelson et al., 2007, and others).

    2. A high percentage of demented persons aged 80+ do not meet the morphological criteria of AD and are classified "dementia of unknown etiology" (Crystal et al., 1988; Jellinger, 2001; Corrada et al., 2012), which cannot be detected without morphological verification.

    In general, density and pattern of neurofibrillary tangles (NFTs) show significant correlations with the severity of cognitive decline across old age including 90+ patients, at least in those without other pathologies superimposed (Nelson et al., 2007; Nelson et al., 2010; Nelson et al., 2012).

    It should further be considered that there are several morphological subtypes of AD, which differ in age, duration, and dementia severity (Murray et al., 2011; Jellinger, 2012).

    All together, these and other data indicate that clinical detection of AD and its distinction from normal (and "pathological") aging—the latter featured by generalized Aβ deposition with only little tau pathology limited to the limbic areas—are more difficult in the oldest old, as stated by the authors.

    References:

    . A population-based clinicopathological study in the oldest-old: the 90+ study. Curr Alzheimer Res. 2012 Jul 1;9(6):709-17. PubMed.

    . Clinico-pathologic studies in dementia: nondemented subjects with pathologically confirmed Alzheimer's disease. Neurology. 1988 Nov;38(11):1682-7. PubMed.

    . Role of the neuropathology of Alzheimer disease in dementia in the oldest-old. Arch Neurol. 2008 Sep;65(9):1211-7. PubMed.

    . Frequency of "dementia of unknown etiology" increases with age. Arch Neurol. 2001 Sep;58(9):1498-9. PubMed.

    . Neuropathological subtypes of Alzheimer's disease. Acta Neuropathol. 2012 Jan;123(1):153-4. PubMed.

    . Prevalence and pathology of dementia with Lewy bodies in the oldest old: a comparison with other dementing disorders. Dement Geriatr Cogn Disord. 2011;31(4):309-16. PubMed.

    . Mixed brain pathologies in dementia: the BrainNet Europe consortium experience. Dement Geriatr Cogn Disord. 2008;26(4):343-50. PubMed.

    . Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study. Lancet Neurol. 2011 Sep;10(9):785-96. PubMed.

    . Modeling the association between 43 different clinical and pathological variables and the severity of cognitive impairment in a large autopsy cohort of elderly persons. Brain Pathol. 2010 Jan;20(1):66-79. PubMed.

    . Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol. 2012 May;71(5):362-81. PubMed.

    . Clinicopathologic correlations in a large Alzheimer disease center autopsy cohort: neuritic plaques and neurofibrillary tangles "do count" when staging disease severity. J Neuropathol Exp Neurol. 2007 Dec;66(12):1136-46. PubMed.

    View all comments by Kurt A. Jellinger

References

News Citations

  1. Oldest Old—The New Face of Dementia?

Paper Citations

  1. . Age, neuropathology, and dementia. N Engl J Med. 2009 May 28;360(22):2302-9. PubMed.
  2. . Distinct profiles of brain and cognitive changes in the very old with Alzheimer disease. Neurology. 2011 Aug 23;77(8):713-21. PubMed.

Further Reading

Papers

  1. . Distinct profiles of brain and cognitive changes in the very old with Alzheimer disease. Neurology. 2011 Aug 23;77(8):713-21. PubMed.
  2. . Mild cognitive impairment, dementia, and their subtypes in oldest old women. Arch Neurol. 2011 May;68(5):631-6. PubMed.
  3. . Benefits and challenges of research with the oldest old for participants and nurses. Geriatr Nurs. 2005 Jan-Feb;26(1):21-8. PubMed.
  4. . No disease in the brain of a 115-year-old woman. Neurobiol Aging. 2008 Aug;29(8):1127-32. PubMed.
  5. . Clinicopathologic correlates in the oldest-old: Commentary on "No disease in the brain of a 115-year-old woman". Neurobiol Aging. 2008 Aug;29(8):1137-9. PubMed.

Primary Papers

  1. . Rates of decline in Alzheimer disease decrease with age. PLoS One. 2012;7(8):e42325. PubMed.