. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A. 2008 Mar 18;105(11):4441-6. Epub 2008 Mar 10 PubMed.


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  1. Which Came First?
    For over a decade, imaging studies of cerebral metabolism have determined the cingulate gyrus to be a region of interest in Alzheimer disease (e.g., Alexander et al., 1997; Imamura et al., 1997), and in some of these papers the focus was turned to the posterior cingulate gyrus (e.g., Reiman et al., 1996; Salmon et al., 2000). Thus, it is not surprising that the present manuscript should focus on energy metabolism in the posterior cingulate gyrus. However, these prior imaging studies have been unable to answer the question, Was the decreased metabolism of the posterior cingulate in AD attributable to neurons, to glia, or other cellular elements within the local region? To the great credit of the authors of the present paper, they have effectively addressed this major limitation of more global approaches by laser capturing single neurons of the posterior cingulate gyrus (as well as five other regions) and analyzing the expression of 80 nuclear genes related to energy metabolism. The essence of their findings is that 72 percent of metabolism-related genes showed reduced expression in the posterior cingulate gyrus. In middle temporal gyrus and hippocampus, 69 percent and 64 percent, respectively, of metabolism genes showed reduced expression. Surprisingly, in the entorhinal cortex, a major affected area in AD, only 23 percent did. This cannot be attributed to neuron loss since the data were derived from neurons remaining. Might it relate to normal aging versus AD? Other, traditionally less affected areas also showed a lower percentage of genes reduced.

    The choice of Affymetrix arrays (U133 Plus 2.0) dictated other aspects of the study, most notably the need to sum RNA collected from about 100 neurons (exact number not provided) from each brain region. Thus, although different cell types are not confounded, and although picked cells were characterized as lacking thioflavin S staining, summing expression of ~100 cells must confound cells in different states of AD pathology. For example, although negative thioflavin S staining demonstrates absence of frank neurofibrillary tangles, variation in other states of tau was admissible.

    Unfortunately, the sensitivity of current AFFY arrays is limited so that summation of material from large numbers of cells is required, even after two rounds of amplification, as was done here. From a statistical point of view, such summation discards information about one source of variance. cDNA arrays have, however, been demonstrated to have sufficient sensitivity that material from individual cells can provide reliable results (e.g., Chow et al., 1998). The ability to profile transcripts of single cells (of any specified type) in addition to allowing immunohistochemical (or otherwise) characterization also provides the option of borrowing from single unit electrophysiology the concept of population reconstruction of neuronal responses, which then could be correlated with psychophysical function (e.g., Mountcastle et al., 1967). Of course, the dimensionality of data in the case of single unit electrophysiology is much simpler than in the case of array data, where one may be dealing with hundreds or thousands of variables—a daunting statistical task that may require excessively large numbers of cells.

    Reviewers generally require validation of array data. Validation may be considered as addressing either technical variability or biological variability. Quantitative RT-PCR of the same samples as those used to obtain array data addresses technical variability, but not biological variability. If different samples are used, both technical and biological variability are addressed. By validating with Western blotting, Liang et al. have added another aspect to validation that deals with potential non-linearity of the relationship between message and protein expression. By apparently using the same samples for Western blotting as were used to obtain array data, the authors miss a chance to simultaneously address biological (sample-to-sample) variability.

    The authors appropriately point out the possibility that the reduced expression of transcripts related to metabolism may reflect reduced neuronal activity related to loss of synapses. So, the question remains whether reduced synaptic activity precedes reduced energy metabolism or whether reduced energy metabolism precedes reduced synaptic activity. Which is cause and which is effect? It is still a chicken-or-egg question.


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  2. This microarray-based study is quite provocative. This research group employed findings gleaned from earlier positron emission tomography (PET) and cerebral metabolic rate for glucose (CMRgl) studies in vulnerable regions of cerebral cortex and hippocampus to drive a microarray study evaluating nuclear-encoded genes for mitochondrial/metabolic function. Specifically, principal neurons were microaspirated via laser capture microdissection (LCM) from well-characterized normal aged subjects and persons diagnosed with Alzheimer disease (AD). The genes were then subjected to Affymetrix gene chip analysis. Essentially, the group isolated relatively pure populations of pyramidal neurons that did not contain neurofibrillary tangle (NFT) pathology from six brain regions. This included areas known to be affected early in AD based upon PET/CMRgl studies such as posterior cingulate cortex (PCC), as well as relatively spared regions such as visual cortex. To my knowledge, this is one of the few microarray studies that evaluated single populations of neocortical neurons from cingulate and visual cortex (among other temporal and hippocampal areas) within postmortem human brain. The datasets generated from these cases have the potential to be extremely exciting and informative on many levels. Based upon the author’s hypothesis that metabolic changes occur early in AD pathogenesis, they concentrated on assessing approximately 80 of the nuclear genes encoding subunits of the mitochondrial electron transport chain pathway. The experimental design enabled a solid microarray analysis that was validated at the protein level via immunoblot analysis.

    Interestingly, the data provide molecular and cellular evidence for early metabolic dysfunction in the PCC that truly corroborates findings based on regional imaging techniques in living patients. Significant decrements were found in the class of nuclear-encoded mitochondrial genes in vulnerable PCC, middle temporal gyrus, and hippocampus. Lesser changes were found in these same transcripts within entorhinal cortex, visual cortex, and superior frontal gyrus. These data were validated in the PCC via immunoblot analysis for five electron transport chain subunits, indicating that gene changes are quite robust.
    Importantly, the LCM-based paradigm enabled the investigators to demonstrate that the downregulation was fairly neuron-specific, not a contamination effect from glial or vascular cells.

    In summary, this study illustrates the power of combining LCM-based high resolution in postmortem human brain samples with microarray analysis for quantitative analysis of relevant classes of transcripts that may have profound implications for the integration of functional imaging studies in living subjects with neuropathological investigations to understand the initiation and progression of AD. It would be highly desirable in future studies to combine microarray assessment of nuclear-encoded electron transport chain genes with antemortem functional imaging and assessment of cognitive performance across the progression of dementia (e.g., aged normal, mild cognitive impairment, and AD subjects). Moreover, an evaluation of cortical interneuron populations within several of the cortical regions evaluated in this manuscript (including the PCC and occipital/temporal cortices) would shed light on the contribution of inhibitory neurons to AD pathogenesis at the molecular and cellular level.

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