Part 2: Synaptic Function in Aging and AD
To what extent is AD an acceleration of normal aging? This decades-old question receded in favor of the view that AD is a separate process from normal aging when studies showed that patterns of neuronal loss are different in aging and AD. Early AD entails selective loss of neuronal projections, such as the perforant path connecting the entorhinal cortex and the dentate gyrus of the hippocampus. Advanced AD features neuronal loss that far exceeds and differs in its regional pattern from that of normal aging. This anatomical data is undisputed and highlights the selective regional vulnerabilities in AD. But postmortem stereology is limited in that it assesses the brain after the initial pathogenesis has occurred, and therefore says less about cause than about features of disease progression. Hence, the question of aging versus AD continues to be debated. FAD mutations speak to both sides of the issue. They reduce the age at onset, diminishing the importance of age and validating overexpression approaches, but at the same time, even people whose FAD mutations flood their brains with Aβ from an early age appear healthy until their 40s. The current distinction between aging and AD is called into question by emerging comparisons of gene expression patterns between normally aging people and others with dementia.
One way to address the question is to study synaptic aging. Is Alzheimer disease a problem of synaptic maintenance? When synapses degenerate, is it a problem of "synaptosis" or "synecrosis"? In other words, does an active program inflict death by complement, aberrant reactivation of MCH class 1 proteins, or other outside signals, or does the synapse fall apart as synaptic organizing molecules disappear? GFP- and YFP-expressing transgenic mice allow repeated live imaging of peripheral synapses over time to monitor how synapses age normally and the building of a knowledge base for understanding how they age in AD models. Application of this method to neuromuscular junctions show that as these synapses age, they become fragmented and the postsynaptic side loses transmitter receptors and nerve contact. Aging nerve terminals sprout, leading to multiple innervations of a given postsynaptic site. Axonal dystrophy and balloon-like distensions of the axon are common. Over time, there is a net loss of innervation. The aging synaptic cleft widens in parallel with changes in the molecular composition of the basal lamina. The aging synapse loses expression of synaptic organizing molecules including agrin and certain types of laminin. Genetic deletion of one laminin form accelerates the morphological changes associated with aging synapses, suggesting that the molecular loss is one cause of the aging, rather than merely a correlate. Together, these results suggest that age-related synapse loss may be quite passive, a form of dedifferentiation where a developmental program rewinds itself as proteins that organize the synapse are progressively lost.
A related question concerns the unit that changes in aging and AD: do individual synapses weaken and disappear one at a time, as happens in activity-dependent synaptic plasticity, or does a given neuronal arbor lose all its synapses just before the axon retracts, much as a winter tree sheds its leaves? The two imply different proximal insults and mechanisms of synaptic loss. The answer to this question is still not clear, but studies of the YFP transgenic mice show that aging muscles tend to have fewer but larger motor units than in young mice, suggesting that some units lose their branches and die back, whereas others gain branches, overextending themselves before they, too, die. Synaptic activity is likely to be an important factor in this process, and could determine selective vulnerability of certain circuits and brain regions.
Technical problems of accessibility and size preclude application of this technique to CNS synapses, so it is unknown whether central circuits age similarly. It is already possible to examine the aging "neural unit," and rapidly improving methods may soon allow imaging of structural details at individual synapses. Further imaging and molecular studies of age-dependent changes in synaptic organizing molecules are needed to address this knowledge gap in AD research.
Live multiphoton microscopy enables prospective brain imaging of the fate of synapses in AD models, albeit at a lower level of resolution. For example, studies monitoring the temporal sequence of events in AD pathogenesis in APP and tau transgenic mouse models are challenging the conventional wisdom that AD represents a steady process of continuous decline. This work suggests instead that AD is punctuated by a series of fast, catastrophic changes. During the 20 years that AD lasts, association cortices lose most of their neurons, and spine and dendritic changes are too numerous to count. Even so, the underlying process may be one of spurts of sudden changes at the cellular and molecular level.
Clinical AD follows a prodromal phase of MCI, during which the brain already contains abundant plaques, tangles, and gliosis, and a majority of neurons have died in certain cortical areas. To identify which changes happen first, scientists monitor over time the same brain area in APP transgenic mice. This work shows that plaques do not grow gradually in size over months, as had been predicted; rather, they appear suddenly from one day to the next in their full size and then remain stable for months. This is consistent with the idea that they might precipitate out of solution. Likewise, within days of the appearance of a plaque, neurites abutting it become crooked and dystrophic. Some neurites stay that way for months; others break. Direct application of anti-Aβ antibody clears both plaques and neuritic dystrophy within a week. Dendrites in the vicinity of a plaque rapidly form new spines, but the spines are unstable, leading to net loss of dendritic spines near plaques within days of the appearance of a new plaque. Several studies have documented spine loss and dendritic changes near plaques (e.g., Tsai et al., 2004; Spires et al., 2005). These synaptic changes are a function of the APP transgene and independent of age.
Tangles in humans correlate with cognitive decline and neuronal loss, but neuronal loss exceeds the number of tangles (Gomez-Isla et al., 1996). Tangles can be imaged in Tg4510 mutant human tau transgenic mice, which develop tangle-like pathology and dramatic neuron loss in cortex and dentate gyrus (Spires, 2006). In these mice, individual tangle-bearing neurons remain stable for months even while neurons die in large numbers. Imaging reagents that fluoresce after a specific caspase has cleaved them indicate that tangle-bearing neurons are likely to activate caspases. They cleave tau, and still these neurons survive for months. Caspases remain present in the neuron after transgene expression is turned off. Markers of apoptosis are absent, yet monitoring of a given visual field captures occasional instances of a fluorescent neurite disintegrating over the course of 2 hours. This is seen only in Tg4510 mice, not in APP-transgenic or control mice. Together, these new data suggest that tangles and caspase activation precede additional biological changes that destroy the neuron by a still-mysterious mechanism.
The rapid appearance of fully grown plaques and the sudden collapse of tangle- and caspase-bearing neurites after months of apparent stability raise new questions about which biological changes dominate the long prodromal phase of human AD. Other mouse studies reporting that spine loss and synaptic changes precede plaques (e.g., Jacobsen et al., 2006), and work from multiple labs showing spine loss in response to oligomeric Aβ, keep alive the related debate about which Aβ species most damages spines. Imaging labels for diffusing, low-molecular-weight species of Aβ and tau are needed to resolve these issues in vivo.
Multiphoton microscopy of normally aging mouse brain has generated data to suggest that a large majority of dendritic spines remain stable and could serve to store long-term memories (Grutzendler et al., 2002; Zuo et al., 2005). More recent multiphoton imaging data implicate cortical microglia in dendritic spine plasticity. They show microglia to be highly plastic, reacting to an injury within hours by becoming activated and extending processes toward the injury (Davalos et al., 2005). The time course of this microglial activation parallels changes in spine dynamics following injury. The tools are in place for monitoring the dynamics of activated microglia around amyloid plaques.
Other areas of synaptic biology are expanding rapidly and should be explored for links to AD pathogenesis. They include the study of signaling between synapse and nucleus that enables those forms of long-lasting neuronal plasticity that require gene transcription. These pathways are being established in several laboratories (e.g., Martin and Zukin, 2006) and could be tested for their robustness in aging neurons and AD models. Another area that is already informing the study of AD is that of neuronal endocytosis. Ongoing work in the field is largely focusing on defects in vesicle transport, autophagy, and APP endocytosis and processing, yet additional proteins involved in the membrane traffic that controls synaptic vesicle recycling could expand this research area. Proteins of interest include the phosphoinositide phosphatase synaptojanin, an enzyme overexpressed in Down syndrome brain whose gene lies in the Down's region of chromosome 21. A cycling synaptic vesicle needs synaptojanin to shed its clathrin coat before it can be reloaded with transmitter. Proteins of growing interest also include the GTPase dynamin, a mechanoenzyme that, together with accessory proteins, pinches invaginated vesicles off the membrane (Roux et al., 2006). Researchers are beginning to understand that some isoforms of dynamin are sufficient for basal endocytosis, whereas the brain-specific version dynamin1 handles increased synaptic demand during intense stimulation/excitation. The field is beginning to generate hypotheses about dynamin's role in AD pathogenesis, but none have yet been independently confirmed and widely accepted. For example, dynamin has been implicated in genetic AD risk (Kuwano et al., 2006), in APP endocytosis (see ARF Eibsee conference report), and downstream of Aβ action on NMDA receptors (Kelly and Ferreira, 2006).
The question of Aβ effects on postsynaptic receptors of excitatory transmission has become an area of active investigation after a report proposed a negative feedback loop in which synaptic activity would increase APP processing, and Aβ in turn would restrain activity (Kamenetz et al., 2003). The same group has since expanded this initial data. New results suggest that Aβ likely destabilizes synapses by recruiting some of the postsynaptic signaling mechanisms that downregulate AMPA receptors during normal instances of long-term depression (LTD). This would, in effect, generate a situation of Aβ-induced chronic LTD that would weaken first the synapse and then the spine carrying it. How loss of AMPA receptors causes the spines to disappear is unclear, but researchers know that the intracellular tails of these receptors serve as organizing principals for other components of the postsynaptic density. Other labs have similarly implicated Aβ in glutamate receptor loss (see Chang et al., 2006; Cirrito et al., 2005; Snyder et al., 2005; Almeida et al., 2005). Together, the studies are generating interest in the role of LTD in aging and AD research. Big questions remain. Researchers have not definitively shown with which receptors Aβ may interact directly as opposed to which ones are affected secondarily, or which forms of Aβ have these effects in vivo. They also have not yet defined a physiological function of Aβ on glutamate receptors vis-a-vis an age- or disease-related one, or reached consensus on pre- versus postsynaptic generation of Aβ. α7 nicotinic acetylcholine receptors also are likely to play a role in Aβ-induced synaptic dysfunction, but a clear pathway has not been delineated in vivo.
Another question that is being actively studied concerns whether APP cleavage products other than Aβ can impair synaptic function. Some research indicates that the cytoplasmic C-terminus generated by BACE and γ-secretase cleavage undergoes further caspase cleavage and then becomes toxic to synaptic transmission. Called C31, this fragment could account for some of the behavioral abnormalities in APP transgenic mice. Evidence for the toxicity of C31 exists in vitro and in vivo. The latter suggests that a mutation abolishing the caspase cleavage site on APP's C-terminus, when crossed with APP-transgenic mice, rescues the deficits in hippocampal synaptic transmission and in the Morris water maze that several labs have established for the APP-transgenics alone. The synaptic rescue occurs in the presence of a full complement of amyloid plaques. These data point to an intracellular pathway by which aberrant APP processing could first lead to synaptic apoptosis and later to the death of the whole neuron (Galvan et al., 2006; also independent, unpublished work). The hypothesis proposes that high levels of Aβ are necessary but insufficient to cause the synaptic damage and neuron death seen in AD. Rather, Aβ induces formation of APP complexes that trigger the toxic caspase cleavage (Shaked et al., 2006). This work needs more study, particularly on the precise function of C31. This question, like many in AD mouse genetics, would benefit from the development of knock-in models, as well as cell-type-specific inducible knockouts of genes of interest in given brain regions, such as the CA1/CA3 synapse in the hippocampus.
Part 3: High-throughput Assays (Application of OMICS to AD)
Genomic/proteomic/metabolomics (OMICS) research in AD remains in its infancy. Most studies stall after discovering lists of hundreds of genes whose expression changes in the chosen comparison. Few groups have been able to validate their results, much less translate to clinical practice. The field needs to devise more focused studies that can advance in this way. General research priorities in the OMICS area include definition of useful algorithms for data mining, comparisons of the relative power of mRNA- versus protein-based approaches in capturing a given biological process, and attempts to characterize the role of post-translational modifications and of non-coding regions. Heterogeneity continues to pose challenges to OMICS, both between brain regions and within a given region. This can partly be addressed by laser capture microdissection.
One line of research that has moved past initial gene expression profiling is establishing a new hypothesis about the biology of brain aging as a way of approaching this old question at a new level of analysis. Classic aging studies have established that people slow down in verbal recall and other cognitive domains even with normal aging. A potential underlying mechanism for those changes is emerging from transcriptome comparisons of people across the human age range. In the prefrontal cortex and other brain areas, gene expression changes early in adult life, around age 40. It changes with a characteristic signature. Certain clusters of genes lose expression; these include synaptic plasticity and memory storage genes such as NMDA, AMPA, GABA, serotonin receptor subunits, calmodulin, calbindins, synaptic organizing molecules such as agrin, vesicle transport genes such as RAB GTPases, dynein, clathrin, kinesin, tau, and energy metabolism genes in mitochondria). Clusters of other genes are induced; this includes genes encoding stress response proteins, inflammatory mediators, antioxidant processes, metal binding, DNA repair, neuronal survival, and myelination. Analysis of this phenomenon has shown that the genes that lose expression have accrued disproportionate oxidative damage in their promoters and failed to repair it, generating the hypothesis that learning, memory, and neuronal survival genes are selectively vulnerable to DNA damage with age. Data are beginning to suggest that old people who maintain exceptional mental acuity have expression signatures similar to middle-aged people (Lu et al., 2004).
Since then, further analysis has indicated that on a given chromosome, DNA damage is not distributed randomly but is most intense in the promoter regions of certain genes, particularly so in promoters of aged samples. The promoters' vulnerability is linked to sequence motifs that bind iron. Iron binding to these promoters appears to increase with age and to lead to double-strand breaks. The working hypothesis coming out of this research holds that how the brain ages depends, in part, on its iron homeostasis, in that increasing iron binding tends to damage the promoters of a small set of genes that are critically important to synaptic plasticity and cognition. Why the affected genes fall into these groups remains unclear but may have to do with high expression in particularly active, that is, plastic, brain regions. (Expression of APP itself does not change with age, but that of some of its binding proteins do [e.g., X11, Fe65], possibly affecting its trafficking or endocytosis.)
A second example of a strategy to move beyond lists of differentially expressed genes lies in exploiting differences between brain areas toward understanding regional vulnerability in a given disease. In one study, high expression of a gene in mouse cerebellum, a region spared in frontotemporal dementia, hinted at a protective function. Follow-up work with fly genetics, in-vitro biochemistry, and human autopsy tissue pinpointed the new tau protease PSA. This aminopeptidase degrades tau protein and is expressed at much higher levels in human cerebellar granule neurons than cortical neurons (see ARF related conference story and Karsten et al., 2006) The bottleneck in this candidate-gene approach is apparent in that the original microarray experiment identified 30 genes of interest, and establishing the role for this one alone took years of a multidisciplinary and collaborative effort.
For faster identification of functionally important changes in gene expression, the field needs systems biology approaches, that is, techniques to trace higher-order features of the transcriptome. Such features include mechanisms of co-regulation of groups of genes, and expression networks that establish connectivity maps between genes. Microarray data can be analyzed to obtain a connectivity measure for a given gene that captures the sum of its connections and connection strengths. Comparison of gene connectivity between humans and chimpanzees shows that the connectivity of genes in human cortex diverges widely from that in chimpanzee cortex, whereas in other brain areas, gene connectivity in humans and primates are more similar. Measures of gene expression alone do not show this divergence, suggesting that the cortex in particular has undergone a massive expansion in gene connectivity from chimpanzee to human, and that expression data alone therefore cannot capture essential features of human cortical function.
Connectivity measures can point up relationships that expression data alone don't. For example, the new tau protease PSA shares many connections with the new FTD gene progranulin (Cruts et al., 2006; Baker et al., 2006), even though their expression is not correlated. Topologic overlap of connectivity data can identify previously known functional networks of genes. It can identify connectivity hubs that are specific to human cortex, as well as functionally relevant hubs that are linked to neurologic disease, such as ones centered on the PINK1 and UCHL1 genes (for further reading, see Khaitovich et al., 2004; Coppola and Geschwind, 2006).
A separate area of genomics focuses on identifying additional risk genes for AD. Here, the critical need lies in establishing larger sample collections than were previously used in order to power linkage and association studies or scans sufficiently high so that they can detect alleles that exert small effects or occur at low frequency. Underpowered studies have been holding back progress in AD and other diseases, notably psychiatric ones. In AD it is estimated that 3,000 patient samples will be necessary to detect variants that increase the relative risk by 1.25. Sample sizes in the hundreds have been typically used in the past; collaborative data sharing is necessary to move beyond this limitation. The Psychiatric Disease Initiative at the Broad Institute in Cambridge, Massachusetts, aims to use whole-genome scans to find risk genes for schizophrenia and bipolar disorder. In that initiative, collaborating groups have agreed to pool data to increase the number of available cases/controls to several thousand. To expand the sample base further, the initiative is tapping into the Swedish National Cohort Study of Schizophrenia, which aims to draw 7,500 schizophrenia patients and 7,500 matched controls from the country's national registers.
The study of complex disorders needs a better understanding of genetic variation. One novel resource in this regard is the International HapMap Project. Freely available as a public database, it to date has analyzed more than four million SNPs in samples from Africa, East Asia, and the U.S., offering a denser set of markers than previously available for association studies. Genotyping and analytic capabilities must also improve. New SNP microarrays contain all SNPs typed in HapMap samples. By themselves they still miss substantial fractions of all common human DNA variants, but improved genotype-calling algorithms can increase their coverage and accuracy such that they should detect common variants that increase risk for schizophrenia and bipolar disorder. Presently available arrays cannot capture the effect of rare variants. Applied to other diseases, the arrays already have identified new risk genes, for example, common variants of three complement factor genes that together explain half of the heritability of age-related macular degeneration, the leading cause of blindness in the aged (Maller et al., 2006). Until last year, almost none of thousands of prior papers on macular degeneration had mentioned complement, or vice versa. Moreover, new microarrays are more sensitive at detecting copy number variations, which can lead to mass effects at the RNA and protein levels. Mass effects in neurodegenerative diseases have been shown with rare gene duplications (Singleton et al., 2003; Rovelet-Lecrux et al., 2006), and promoter variants can exert similar, smaller effects that together may account for a significant fraction of the genetic variation in AD risk (Lahiri et al., 2005; Singleton et al., 2004).
Finally, environmental factors can tip the balance between whether a person develops or escapes a given disease for which they carry a moderate increase in genetic risk. Epidemiology can identify potential new environmental risk factors, and once a disease's risk genes are known, environmental factors can be studied more precisely.
On the proteomics front, a majority of applied studies in AD research attempt to identify panels of proteins that can detect and distinguish the disease better than the clinical diagnosis, and eventually will be able to identify preclinical AD or predict AD in mid-life. For one such study, see the Wyss-Coray presentation in the Alzforum report on the Translational Biomarkers Workshop. For validation, such research needs access to plasma from larger samples and younger cohorts of people. In the U.S., groups at University of California, San Diego; University of Washington, Seattle; Washington University, St. Louis; Columbia University, New York; and University of Pennsylvania School of Medicine, Philadelphia, are currently collecting samples longitudinally. The ADNI initiative funded by NIA is gearing up to bank fluids at participating centers, and will make samples available. A funding shortage and insufficient industry investment in diagnostic tests are additional bottlenecks in this area.
Both genomics and proteomics are areas of active technology development. Following below is an example of each, and both may become useful to the field at large. One is the RNAi Consortium. Formally established in 2004, this group aims to create an openly available lentiviral RNAi library that can be applied to large-scale, unbiased loss-of-function screens in mammalian cells, much as has been possible in yeast for some years. The consortium has created reagents to knock down most human and some mouse genes. It is currently focusing on validation techniques and on exploring how best to use the reagents for extracting biological information. In this area, the group emphasizes development of high-throughput imaging assays rather than lacZ or luciferase surrogate reporter assays; this will render this library attractive for neuroscience applications. Freeware to analyze thousands of cell images is already available for download.
To date, more than 140,000 reagents have been made, organized by gene groups, such as kinases, proteases, etc. They infect most cell types, including non-dividing cells and neurons, at low multiplicity of infection, and they yield stable expression of the respective shRNA. A robust, automated protocol for how to use the library has also been worked out. Technical hurdles at this stage include how to distinguish true hits from false-positive or off-target effects, obtaining larger numbers of effective hairpins (i.e., individual short RNAi sequences) per gene, knocking down a given gene strongly enough to see a biological effect, and generally validating the library with available funds. The question remains which features of complex diseases can be mimicked in cell-based assays and made amenable to genome-scale RNAi screens. Large-scale screens for a systems approach to pathways involved in a given function of interest are not yet feasible with this library.
Proteomics technologies that could be applied to fundamental questions of neural function and AD include, for example, phosphoproteomics. One uses mass spectrometry-based algorithms to track intracellular signaling circuits by analyzing phosphorylation. This technique allows the scientist to probe a cell's signaling pathways on a global level by quantifying key aspects of phosphorylation, such as the temporal sequence of successively phosphorylated sites, simultaneously for dozens of proteins (see Zhang et al., 2005; Chen and White, 2004). Applied to the research questions in AD, this technology could bring a network perspective to the study of tau phosphorylation. Other questions of interest that could be studied with greater power in this way include APP or ApoE signaling, or a neuron's response to NGF or to a glial signal and vice versa.
Further Topics of Discussion
A topic that was not on this year's workshop agenda generated significant discussion. It is ApoE, a perennially understudied area in AD research. The failure to find a second major risk gene for AD since the discovery of ApoE4 in 1993 only reinforces ApoE's status as the leading genetic risk factor. Yet initial research efforts on ApoE have waned; few groups today investigate it (for review, see ARF ISOA conference report). The role of ApoE in the periphery is better understood than in the brain. It appears to be a stress-response protein; its expression, like that of APP, soars after stroke or injury. The crystal structure of ApoE is available. ApoE shows isoform-specific effects in the brain, but their role in AD pathogenesis is unclear. ApoE4 shows a unique domain interaction, whereas ApoE2 and E3 don't. ApoE2 binds less tightly to the LDL receptor than ApoE3 and 4, which could affect cholesterol recycling and, in turn, synaptic function. Studies examining ApoE in the context of dendritic spines and LTP induction tend to find a favorable effect of ApoE2. Separately from its synaptic effects, ApoE4 enhances amyloid pathology dramatically and is associated with greater damage/poorer recovery in injury models.
ApoE4 carriers have higher levels of corticosteroids and show differences in PET scans even at young ages and without overt cognitive impairments.
ApoE2/2 homozygote carriers are rare and can have abnormally low cholesterol levels, but they rarely ever develop AD. This natural form of risk reduction presents an opportunity to understand its mechanism and exploit it for therapies. ApoE is one of the most abundantly produced and released proteins in astrocytes and should be explored for a potential signaling role. Studies modeling ApoE in animals must be aware of differences between lipid handling in mice and humans, which have made guinea pigs a favored model in the cholesterol field. In the brain, cholesterol and ApoE synthesis and turnover occur mostly locally, without much connection to the periphery. A research area is developing around the discovery that ApoE binds to receptors (i.e., LRP) that also bind APP and that use similar adaptor proteins (i.e., Fe65) to form heterodimeric complexes but, again, relevance for ApoE signaling and AD pathogenesis is not clear (see Eibsee report).
Participants debated the importance of understanding the biology of AD more fully versus focusing on a given hypothesis for therapy development. An area of common ground lies in the notion that the biology of statins and their effects on lipid lowering and reducing heart disease risk and mortality were not fully worked out before their long-term secondary prevention trials began. Despite the wide use and success of statins, the field of heart disease needs additional drugs. Likewise, anti-amyloid therapy development is timely even while gaps remain in the amyloid hypothesis. Basic research must lay the groundwork for alternative approaches in the event that secretase inhibition and immunotherapy fail. Even if they succeed, there will be ample need for alternative approaches as most researchers expect an effective AD therapy to have to act on multiple components of the disease. In this regard, emerging research on glia, immune system components, DNA repair, and synaptic maintenance open new horizons for AD.
Participants agreed that ways must be found to push the time frame of when people are treated, and experimental drugs tested, back into the preclinical phase from the mild-to-moderate phase of diagnosed AD that is the typical time of treatment today. Statins, for example, have their strongest effect as preventive agents, and researchers feel that a number of promising AD drugs may be failing trials because the patients were too advanced in their disease. Epidemiology is reaching consensus that metabolic factors exert their strongest effect on dementia risk during middle age. Secondary prevention trials are necessary but require validation of an antecedent marker and a surrogate marker that is based on the drug's action and that changes as a function of its dose (see Alzforum report on translational biomarkers). Cognitive tests are neither precise enough nor practicable for such trials.
Last but not least, participants agreed on a nagging technical problem that impedes AD research. It is the variability of Aβ preparations and detection assays used throughout the field, and a lack of precision in how authors describe Aβ preparations and measurements in publications. To reproduce and compare studied, Aβ preparations in any publication should be defined using consensus language with regard to their origin (synthetic, cell-secreted) and aggregation state and solubility. Likewise, the field should agree on a set of consensus assays for measuring different kinds of Aβ species in tissue sections vs. fluids vs. brain extracts, because using the incorrect assay can mask large fractions of Aβ present in the sample.
Part 4. Recommendations for Future Research
I. Immune mechanisms in aging and Alzheimer disease
- Determine whether endogenous immune mechanisms in the brain can be modulated to alter brain function or disease processes.
- Study differences between immune modulation in mice and humans, and their relevance to AD. How well do mice model the role of immune modulators in the AD process?
- Follow people from younger ages onward to study changes in immune function and cognition; correlate over time. Follow lymphocytes and macrophages separately—can their expression profiles predict who will decline?
- Aging increases human T cell reactivity to Aβ. Develop a blood-based readout of how the aging immune system is responding to an immunotherapy.
- Identify factors upstream of synapse loss in aging and AD: probe for role of complement factors, of components of immunological synapse, of synaptic organizing proteins.
- Understand why the innate immune system fails to clear amyloid.
- Elucidate the normal function of microglia, and their role in AD and other proteinopathies.
- MHC class 1 and Aβ peptide loading: do MHC class 1 present Aβ? If so, how does age-related proteasome dysfunction, intraneuronal Aβ accumulation, etc., affect MHC class 1 peptide loading? Does Aβ presentation affect synaptic function/plasticity, or stay functionally neutral as self-peptide? Does MHC class 1 variability affect Aβ display?
II. Synaptic function in aging and AD
- Study how synapses disappear in AD: active elimination or dedifferentiation? Loss of individual synapses or collective loss at level of neuron?
- Establish relationship of synaptic loss to other disease measures. Does loss of 20 percent of synapses imply a loss of 20 percent of axonal arbors, 20 percent shrinkage of arbors? At what stage of synapse loss does cognitive function start to fail?
- Develop PET and MRI imaging agents that target markers of neuronal activation and synaptic activity. Use those to track pathogenesis and effect of therapeutics.
- Why does cognitive activity protect against AD?
- Determine causes of DNA damage in neurons.
- Elucidate function of synaptic proteins. Of the 300 proteins known to date, only 5 percent have an identified function.
III. OMICS approaches, other technology development
- Foster conversation among researchers studying synaptic development, function, plasticity, and genomics/proteomics groups. Which synaptic proteins are best candidate genes?
- Use OMICS to understand molecular biology of regional vulnerability.
- Expend a greater effort on proteomic changes with aging.
- Establish networks for APP, tau, ApoE.
- Develop a way to assess synaptic function in live human brain.
- Branch out from amyloid imaging: develop ability to image microglial activation, response to treatment, in human patients.
- Bring together experts in hippocampal memory, e.g., Larry Squire, to devise better cognitive tests for early AD, particularly of spatial memory.
- Develop pharmacological stress test for AD diagnosis.
- Accelerate plasma collection, facilitate distribution to groups that need to validate proteomic biomarkers.
IV. Further priority areas: ApoE, others
- Clarify ApoE's role in brain lipoprotein metabolism. Encourage cross-talk among AD scientists and colleagues who study ApoE in periphery.
- What is ApoE's role in synaptic function? Build on PET data on differences in young ApoE4 carriers during cognitive tasks. Explore interaction of ApoE isoforms with synaptic plasticity molecules.
- What is ApoE's role in repair? Clarify glial vs. neuronal function.
- How are people with ApoE2 protected against AD?
- Focus on role of sirtuins in neuronal function, degeneration, protection.
- Develop best-practice assays for measuring Aβ.
- Develop consensus protocol for defining Aβ species in experimental protocols.
The role of the cerebral vasculature in AD remains a research priority (for details, see 2005 Enabling Technologies report).
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