A cross-disorder connectome landscape of brain dysconnectivity

Abstract

Many human brain disorders are associated with characteristic alterations in the structural and functional connectivity of the brain. In this article, we explore how commonalities and differences in connectome alterations can reveal relationships across disorders. We survey recent literature on connectivity changes in neurological and psychiatric disorders in the context of key organizational principles of the human connectome and observe that several disturbances to network properties of the human brain have a common role in a wide range of brain disorders and point towards potentially shared network mechanisms underpinning disorders. We hypothesize that the distinct dimensions along which connectome networks are organized (for example, 'modularity' and 'integration') provide a general coordinate system that allows description and categorization of relationships between seemingly disparate disorders. We outline a cross-disorder 'connectome landscape of dysconnectivity' along these principal dimensions of network organization that may place shared connectome alterations between brain disorders in a common framework.

Fig. 1 |. Modular and hub organization of the human connectome-shaping disease processes.

a | The modular character of the connectome can shape the pattern of the disease-spreading process, with early effects of the disease remaining mostly concentrated in one specific network module. b | Damage to hub nodes (red nodes) and their connections (red connections) can lead to structural and functional changes across many places in the connectome. c | This part illustrates the ‘cascading network failure’ theory, which states that the initial, local changes to the connectome are cascaded across the network. Failure in one of the network nodes triggers compensatory effects in topologically adjacent nodes (for example, increased activity), aiming to take over the role of the failed nodes and to maintain optimal brain function. The increased burden on these nodes will in turn lead to an increased probability of their failure, triggering a cascade of failure of nodes across the entire network. The global connectivity character of hub nodes makes them more likely to be involved in such compensatory processes.

Fig. 2 |. Connectome landscape of dysconnectivity.

a | Two of the major principles of wiring the human connectome are the tendency to minimize the overall cost of wiring (x-axis), favouring the formation of local circuitry and local subsystems, and the drive to invest in resources that allow efficient global communication and integration (y-axis).Together, they describe a 2D space (referred to as ‘network morphospace’) of all possible network configurations. Within this space, the two principles compete and their trade-off (blue line) defines an efficient organization of the network, where both objectives are together optimized. The region beyond this front, relating to ‘greater optimization’ (grey area), cannot easily be realized given the constraints of geometry and physiology. In turn, networks in the region below the front could be considered as ‘suboptimal’ (green area, with shades of green indicating less and less optimal network configurations) in the sense that the trade-off between multiple objectives is inefficiently realized: with the subregion furthest away from the trade-off optimum (lower left corner space, lightest green) comprising networks that would be biologically unworkable and thus too maladaptive to support human behaviour. The area around the trade-off optimum and in between the regions of ‘impossible’ and ‘suboptimal’ networks describes the extent of normal variation of efficient cost integration in the general healthy human population (light-blue zone). Within the area of healthy human variation, certain individual variants in connectome organization may represent configurations of the connectome showing resilience or vulnerability to disease. In this framework, disease processes can be theorized to move an individual connectome away from the optimal balance (blue line) into the suboptimal regime (blue dotted line); the disease processes may exert effects along the architectural dimensions (arrows parallel to the x-axis and y-axis). Together, they form a characteristic ‘connectome landscape of dysconnectivity’ (shades of green). b | Distinct disease processes may involve different trajectories away from the area of healthy human variation and efficient network performance (blue) depending on how they affect the network (for example, disease X has a stronger effect on modular organization, whereas disease Y has a stronger effect on network integration). c | This may, in turn, lead to disorganized connectomes displaying specific types of connectional variation that occupy different subspaces (‘disease zones’) in the total landscape. Through this approach, relationships may be observed among otherwise seemingly discrete and disparate disorders. d | In some disorders, reorganization mechanisms (arrows) may work to refind a position for the shifted trade-off (dotted blue line) that is closer to the optimal trade-off in the human connectome (blue area) in order to maintain brain function.