For decades, researchers have wondered why Aβ deposits in the brain correlate poorly with local neural activity and cognition. Perhaps the correlation was not that weak, after all. A study in the June 4 Nature Communications suggests that it may all come down to where you look. Researchers led by Pedro Rosa-Neto at McGill University, Montreal, report that the presence of Aβ deposits in certain regions of the brain correlates tightly with hypometabolism in distal, connected regions. They conclude that hypometabolism, in turn, renders those distant neurons vulnerable to stress, from, lo and behold, local Aβ. The results suggest an Aβ double hit of sorts, where distal deposits prime neurons to succumb to local ones.
- Amyloid does not affect local neuron metabolism …
- … but it slows the metabolism of distant, connected neurons.
- This hypometabolism combines with nearby Aβ to hasten cognitive decline.
“I really liked how the authors used the regional data to ask whether amyloid had a local, global, or distant effect,” wrote Bernard Hanseeuw, Massachusetts General Hospital, Boston. “[They] show that Aβ burden globally affects brain metabolism, and that cognition depends on the synergy between Aβ and brain hypometabolism in specific brain regions, mainly the posterior midline.” (See comment below.)
David Jones, Mayo Clinic, Rochester, Minnesota, found the study interesting, but questioned the interpretation. “The authors largely rely on small-scale molecular brain physiology when interpreting their results and largely ignore large-scale brain physiology,” he wrote (see comment below).
First author Tharick Pascoal wondered why researchers had never consistently tied regional Aβ to local hypometabolism. On a global level, the amount of amyloid in the brain predicts the degree of overall hypometabolism, but locally this association breaks down (Lowe et al., 2014; Altmann et al., 2015). This disconnect would seem to fly in the face of the amyloid hypothesis, the authors reasoned, since it predicts that Aβ causes neurodegeneration.
What if regional hypometabolism results from Aβ at distal but connected sites? To test this, Pascoal compared florbetapir and FDG PET scans taken from 152 cognitively normal older adults and 170 people with mild cognitive impairment. All the MCI volunteers were amyloid-positive, as were 53 of the healthy controls. Looking voxel-wise across both sets of scans, Pascoal confirmed that in both MCI and normal controls, no correlation existed between local Aβ and local hypometabolism in many areas of the brain, including the posterior cingulate, precuneus, lateral temporal, and inferior parietal cortices. These are part of the default mode network (DMN), a series of interconnected brain regions that are both important for cognitive processing and a hotbed for amyloid deposition (Mar 2004 news; Sep 2005 news).
A different picture emerged when Pascoal looked for correlations further afield. In this analysis, amyloid in the posterior cingulate, precuneus, lateral temporal, and inferior parietal cortices did correlate with hypometabolism, but in distal regions within the DMN (see image above). Aβ in other regions either did not correlate with glucose metabolism or did so with regions outside the DMN.
Does this long-distance correlation have anything to do with cognition? Apparently not, but, in a surprising twist, local correlations do. When the authors tracked how Aβ/hypometabolism correlations in the DMN correlated with cognitive decline in the MCI group, it was synergism between local Aβ and local hypometabolism that predicted a decline in MMSE scores over 5.6 years.
“We see amyloid affecting the brain in two stages,” said Rosa-Neto (see image below). “In the first stage we see an effect on the network, that is, it causes hypometabolism in distant areas. The second strike is when amyloid starts to impose deleterious effects on localized tissue. This impacts cognition.”
Double Hit? The model predicts that Aβ from one neuron can make distant but connected neurons more vulnerable to stress. When local Aβ or other toxins compound that vulnerability, dementia follows. [Courtesy of Pascoal et al., Nature Communications.]
Marcus Raichle, Washington University, St. Louis, found the paper intriguing. “This type of network analysis is a very nice way of framing the pathology of AD, and opens up lines of thinking that broaden our horizons as to the pathophysiology,” he wrote (see comment below).
Is it Aβ that drives these correlations? Why not tau, which itself correlates with hypometabolism? To answer this, the authors repeated the analysis in transgenic rats that express human APP carrying the Swedish and Indiana mutations (Do Carmo and Cuello, 2013). These animals accumulate amyloid deposits but have no tau pathology. Here, too, Aβ correlated with hypometabolism in distal regions, and local synergism between Aβ and hypometabolism predicted poorer performance in a water maze. “We are not saying that tau may not be important. In fact, we think it will exacerbate the situation,” said Pascoal. “The point was to show this [cognitive effect] can be attributed to amyloid alone.”
Could these PET correlations help predict or track a person’s cognitive decline? “Possibly,” said Rosa-Neto. The authors did not conduct this analysis here, but published a machine-learning algorithm based on this data that predicted progression to AD over two years (Mathotaarachchi et al., 2017). More importantly, Rosa-Neto thinks that this two-hit hypothesis helps explain why clinical trials targeting amyloid have failed. “We see already in MCI that the network is vulnerable,” he said. “If you clean up Aβ later, that vulnerability is still there.” He agrees with the idea that Aβ must be targeted much earlier in disease to benefit cognition.—Tom Fagan
- Network Diagnostics: "Default-Mode" Brain Areas Identify Early AD
- Tracing Alzheimer Disease Back to Source
- Lowe VJ, Weigand SD, Senjem ML, Vemuri P, Jordan L, Kantarci K, Boeve B, Jack CR Jr, Knopman D, Petersen RC. Association of hypometabolism and amyloid levels in aging, normal subjects. Neurology. 2014 Jun 3;82(22):1959-67. Epub 2014 May 2 PubMed.
- Altmann A, Ng B, Landau SM, Jagust WJ, Greicius MD, Alzheimer’s Disease Neuroimaging Initiative. Regional brain hypometabolism is unrelated to regional amyloid plaque burden. Brain. 2015 Dec;138(Pt 12):3734-46. Epub 2015 Sep 29 PubMed.
- Do Carmo S, Cuello AC. Modeling Alzheimer's disease in transgenic rats. Mol Neurodegener. 2013 Oct 25;8:37. PubMed.
- Mathotaarachchi S, Pascoal TA, Shin M, Benedet AL, Kang MS, Beaudry T, Fonov VS, Gauthier S, Rosa-Neto P, Alzheimer's Disease Neuroimaging Initiative. Identifying incipient dementia individuals using machine learning and amyloid imaging. Neurobiol Aging. 2017 Nov;59:80-90. Epub 2017 Jul 11 PubMed.
No Available Further Reading
- Pascoal TA, Mathotaarachchi S, Kang MS, Mohaddes S, Shin M, Park AY, Parent MJ, Benedet AL, Chamoun M, Therriault J, Hwang H, Cuello AC, Misic B, Soucy JP, Aston JA, Gauthier S, Rosa-Neto P. Aβ-induced vulnerability propagates via the brain's default mode network. Nat Commun. 2019 Jun 4;10(1):2353. PubMed.