Molecular nexopathies: a new paradigm of neurodegenerative disease

Abstract

Neural networks provide candidate substrates for the spread of proteinopathies causing neurodegeneration, and emerging data suggest that macroscopic signatures of network disintegration differentiate diseases. However, how do protein abnormalities produce network signatures? The answer may lie with 'molecular nexopathies': specific, coherent conjunctions of pathogenic protein and intrinsic network characteristics that define network signatures of neurodegenerative pathologies. Key features of the paradigm that we propose here include differential intrinsic network vulnerability to propagating protein abnormalities, in part reflecting developmental structural and functional factors; differential vulnerability of neural connection types (e.g., clustered versus distributed connections) to particular pathogenic proteins; and differential impact of molecular effects (e.g., toxic-gain-of-function versus loss-of-function) on gradients of network damage. The paradigm has implications for understanding and predicting neurodegenerative disease biology.

Keywords: dementia; neural network; neurodegeneration; nexopathy.

Figure 1

A taxonomy of molecular nexopathy mechanisms. Here, we model putative ‘templates’ of neurodegenerative network damage at a given arbitrary time point following introduction of a pathogenic protein. In each panel, the stylised local neural circuit comprises nodes (N; e.g., neuronal somas) with links (e.g., axons or dendrites) that behave as either shorter-range clustered (unfilled lines) or longer-range distributed (filled lines) connections; the most highly connected node behaves as a local hub (H), whereas node I is the site of an instigating insult (wavy arrow) associated with a pathogenic protein. Grey symbols represent unaffected or minimally affected network elements; pathogenic effects are coded in red (filled circles representing deleted network elements and half-tone circles representing dysfunctional network elements) and pathogenic effects are assumed to be potentially bidirectional across network connections. The taxonomy shown assumes two basic, interacting dichotomies arising from the conjunction of pathogenic protein and intrinsic network characteristics: selective targeting of shorter-range clustered neural connections [e.g., I–N1–N2–H–N3–N4–N5 (A,B)] versus longer-range distributed neural connections [e.g., I-H-N5-N6, (C,D)]; and effects that are relatively uniform [no gradient, (A,C)] or strongly graded [gradient (B,D)] across the network. In each case, the hub H is intrinsically relatively more vulnerable due to its high connectedness with the rest of the network . Targeting of connection types could reflect subcellular compartmentalisation of pathogenic proteins and/or local synaptic properties or other morphological characteristics (e.g., targeting of dendritic versus axonal compartments). Gradients of effects could be established by intrinsic polarities in network protein expression and/or the net functional effect of a pathogenic molecular cascade (e.g., uniform toxic gain-of-function versus graded loss-of-function effects). The model that we propose requires propagation of disease effects across network elements, but does not specify the precise nature of those effects: for example, propagation could occur by direct protein transfer, protein ‘seeding’ or templating in contiguous elements, or deleterious pathophysiological signalling, all potentially operating at different stages of disease evolution. The model predicts coherence between culprit molecule, neural connection types predominantly targeted, and functional (e.g., cognitive) phenotype as the neurodegenerative process scales to the level of the whole brain (Figure 2, main text).

Figure 2

Scaling nexopathies to large-scale brain networks. The inset cartoon (left) shows a stylised axial view of the cerebral hemispheres in a normal brain. Circles represent neural network elements and colours code large-scale functional networks associated with generic clinical syndromes in previous connectivity work : the anterior temporal lobe semantic network (green); the frontoinsular ‘salience’ network implicated in behavioural variant frontotemporal dementia (yellow); the dominant hemisphere speech production network implicated in progressive nonfluent aphasia (magenta); the frontoparietal network associated with corticobasal syndrome (light blue); and the temporoparietal ‘default mode’ network implicated in Alzheimer's disease (dark blue). Putative shorter-range clustered (unfilled black lines) and longer-range distributed (filled black lines) connections between network elements are shown; connections between major functional networks are also represented (grey lines). The middle panels show proposed cross-sectional schemas of network breakdown (red, following Figure 1, main text), after an instigating insult (wavy arrow) associated with a pathogenic protein. Alongside each panel, axial and coronal MRI brain sections show corresponding observed atrophy profiles in patients with representative, canonical, pathologically confirmed, proteinopathies (CBD, corticobasal degeneration associated with 4-repeat tau pathology; GRN, mutation in progranulin gene; MAPT, mutation in microtubule-associated protein tau gene; TDPC, TDP-43 type C pathology , associated with the clinical syndrome of semantic dementia; the left hemisphere is on the left in all sections). These atrophy profiles illustrate macroanatomical scaling of the nexopathy templates proposed in Figure 1 (main text): (A) predominant involvement of clustered (shorter-range) connections with uniform extension, leading to relatively focal (temporal lobe) atrophy that is relatively symmetrically distributed between the cerebral hemispheres; (B) predominant involvement of clustered (shorter-range) connections with a strong gradient of network damage, leading to relatively focal (temporal lobe), strongly asymmetric atrophy; (C) predominant involvement of distributed (longer-range) connections with uniform extension, leading to distributed, relatively symmetrical atrophy; and (D) predominant involvement of distributed (longer-range) connections with a gradient of network damage, leading to distributed, strongly asymmetric atrophy. A particular proteinopathy here affects network connections with particular characteristics (e.g., clustered versus distributed synaptic linkages); functional networks will be targeted according to their specific network characteristics, but the effects of a particular nexopathy will in general tend to spread between functional networks, while continuing to target connections with similar properties across these networks. This would account for empirical variability in the closeness with which proteinopathies map onto particular functional networks (e.g., the mapping is relatively close for TDPC pathology with the semantic network, whereas most proteinopathies involve the salience network). The scheme makes specific predictions about the sequence of regional involvement with particular proteinopathies (e.g., sequential involvement of homologous contralateral temporal lobe regions with TDPC pathology) (see also Figure 3, main text).

Figure 3

Temporal evolution of disease and phenotypic heterogeneity. This schematic illustrates the application of the molecular nexopathy concept to the problem of phenotypic heterogeneity in neurodegenerative disease, using the example of corticobasal degeneration. The inset cartoon (left) shows major functional networks in a stylised normal dominant cerebral hemisphere, colour coded as in Figure 2 (main text). The panels illustrate evolving network involvement shortly after onset of the neurodegenerative insult (t0) and at two arbitrary later time points (t1 and t2). The initial location of the insult (wavy arrow) determines the clinical presentation (behavioural variant frontotemporal dementia, bvFTD; progressive nonfluent aphasia, PNFA; or ‘classical’ corticobasal syndrome, CBS). The core corticobasal functional network (light blue in inset) is involved with disease evolution in each case; however, variable additional involvement of other contiguous functional networks (the salience network, speech production network or default mode network) modulates the phenotype. Each of these phenotypes arises from a common template of network involvement determined by the type of neural connection predominantly involved (here, represented as longer-range distributed intrahemispheric projections); the common nexopathy signature of corticobasal degeneration is revealed in the temporal profile of disease evolution.