Trends in Neurosciences - October 2013

8/13/2019 Trends in Neurosciences - October 2013

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Editor

Andrew M. Clark

Executive Editor, Neuroscience

Katja Brose

Journal Manager

Olaf Meesters

Journal Administrators

Ria Otten

Patrick Scheffmann

Advisory Editorial Board

Silvia Arber, Basel, Switzerland

Anders Bjrklund, Lund, Sweden

J. Paul Bolam, Oxford, UK

Sarah W. Bottjer, Los Angeles, CA, USABarry J. Dickson, Vienna, Austria

Chris Q. Doe, Eugene, OR, USA

Craig C. Garner, Stanford, CA, USA

Yukiko Goda, Wako, Japan

Kenneth D. Harris, London,UK

Nancy Ip, Kowloon, Hong Kong

Meyer Jackson, Madison, WI, USA

Maria Karayiorgou, New York, NY,USA

Robert C. Malenka, Stanford, CA, USA

Mark P. Mattson, Baltimore, MD, USA

Freda D. Miller, Toronto, Canada

Richard G.M. Morris, Edinburgh, UK

Maiken Nedergaard, Valhalla, NY, USA

Eric Nestler, New York, NY, USA

Hitoshi Sakano, Tokyo, Japan

Greg Stuart, Canberra, Australia

Wolf Singer, Frankfurt, Germany

Marc Tessier-Lavigne, New York, NY, USA

Chris A. Walsh, Boston, MA, USA

Editorial Enquiries

Trends in Neurosciences

Cell Press

600 Technology Square

Cambridge, MA 02139, USA

Tel: +1 617 3972823

Fax: +1 617 3972810

E-mail: [email protected]

Cover:The mammalian brain expends tremendous energy for its physiological function. On pages 587597 of this issue,

Mergenthaler, Lindauer, Dienel, and Meisel review the tight regulation of glucose metabolism as the foundation for normal

brain function, as well as the role of disturbed glucose metabolism in the pathophysiology of diverse brain disorders.

The sweets and the cupcake-like brain on the cover signify the reliance of the brain on sugar-derived energy, and the

background images, including the angel from Albrecht Drers Apocalypsis cum figuris, motifs from Jules Vernes adventure

novels, and Daniela Nickaus explorer, illustrate the infinite intellectual and imaginative capacity of the brain. Cover design

by Malte Nickau (www.graco-berlin.de).

October 2013 Volume 36, Number 10 pp. 555620

Jason D. Warren, Jonathan D. Rohrer,

Jonathan M. Schott, Nick C. Fox,

John Hardy, and Martin N. Rossor

Luis Puelles, Megan Harrison,

George Paxinos, and Charles Watson

Arvind Kumar, Ioannis Vlachos,

Ad Aertsen, and Clemens Boucsein

Philipp Mergenthaler, Ute Lindauer,

Gerald A. Dienel, and Andreas Meisel

Diane Lipscombe, Summer E. Allen, and

Cecilia P. Toro

Verena Wolfram and Richard A. Baines

561 Molecular nexopathies: a new paradigm of

neurodegenerative disease

570 A developmental ontology for the

mammalian brain based on the prosomeric

model

579 Challenges of understanding brain function

by selective modulation of neuronal

subpopulations

587 Sugar for the brain: the role of glucose in

physiological and pathological brain

function

598 Control of neuronal voltage-gated calcium

ion channels from RNA to protein

610 Blurring the boundaries: developmental and

activity-dependent determinants of neural

circuits

Opinions

Reviews

557 The Brain Prize 2013: the optogenetics

revolution

555 Looking back and looking forward

Andreas Reiner and Ehud Y. Isacoff

Andrew M. Clark

Science & Society

Editorial


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Looking back and looking forward

Andrew M. Clark

Trends in Neurosciences, Cell Press, 600 Technology Square, Cambridge, MA 02139, USA

Trends in Neurosciences (TiNS) was launched over 35

years ago with the aim of publishing insightful reviews,

opinions, and commentaries covering all disciplines of the

neurosciences. TiNS started strong; among the articles

appearing in the journal that first year include those

penned by a Nobel Laureate, previous and future chairs

of the Society for Neuroscience, and numerous other lead-

ing experts. Throughout its ensuing tenure, TINS has

continued to publish timely and authoritative pieces with

the goal of synthesizing, interpreting, and drawing novel

insights into an increasingly fractured and complex litera-

ture. Although the neuroscientists toolkit has greatly

expanded over recent years, the subjects covered remainsurprisingly consistent: neuropsychiatric diseases, cellular

and molecular studies of synapse development and plas-

ticity, and systems investigations of learning and memory,

to name but a few. The success of TINS in providing high-

quality coverage of such topics is reflected in its consistent

ranking among the best reviews journals in what has

grown from a handful of similar titles at its inception to

a plethora today.

Despite its long run, TiNS, until now, has had only four

editors, in chronological order: David Bousfield, Gavin

Swanson, Sian Lewis, and Rachel Jurd. Together, these

previous editors oversaw the launch and growth of the

journal,

shepherded

it

from

print

to

primarily

electronicdistribution in the internet age, developed new means for

engaging and building a community of readers, and

commissioned countless articles that, one hopes, not only

reviewed, but also helped set trends in the field. I am

humbled to follow in their footsteps and I aim to continue

in the tradition that they started; this latest issue reflects

both the breadth of coverage and the high standard of

quality that I aim to maintain at TINS.

The neurosciences are one of the preeminent fields in

biology today, as reflected in both the amount of resources

devoted to investigations of the nervous system and the

increasing number of major prizes being awarded for

breakthroughs in this field. In this issue, in a Science

and Society article, Reiner and Isacoff highlight the work

that led to the recent receipt of one of these significant

awards, the Brain Prize 2013, which was awarded to Ernst

Bomberg, Edward Boyden, Karl Deisseroth, Peter Hege-

mann, Gero Miesenbock, and Georg Nagel for their devel-

opment and refinement of optogenetics. Science and

Society pieces are intended to spotlight subjects of wide

interest, or topics at the intersection of the bench and the

wider world. Readers can look forward to continuing to see

more of both types in the future.

One of the key features of TiNS opinion articles is that

they present a personal viewpoint on a particular subject,

thus advancing a novel perspective or hypothesis. In this

issue, three such opinion articles present novel perspec-

tives on important issues in neurodegenerative diseases,

neural development, and neural coding, respectively. War-

ren, Rohrer, Scott, Fox, Hardy, and Rossor hypothesize

that specific neural networks are differentially susceptible

to particular pathogenic proteins and propagating protein

abnormalities, while Puelles, Harrison, Paxinos, and Wat-

son promulgate a hierarchical classification of brain struc-

tures based upon recent findings concerning differential

gene expression during development. Finally, Kumar,Vla-chos, Aersten and Boucsein note that the parallel, recur-

rent architecture of most real neural networks limits the

utility of selectively inactivating only particular elements

(e.g., a given cell class) one-by-one, suggesting careful

computational consideration of network structure will be

anecessaryprecondition of experiments seeking tounravel

network function. TiNS readers can expect to continue to

see creative, novel, and insightful opinion articles covering

other equally important topics in the future.

Brief, pointed reviews that go beyond simply reciting

the literature, to integrate and synthesize recent results

into alternative interpretations, and to suggest productive

areas

for

future

research

are

the

hallmark

of

TiNS. In

thisissue, one can find three such reviews from leading groups

in molecular, cellular, and systems neuroscience. Mer-

genthaler, Lindauer, Dienel, and Meisel review the role

of glucose in fueling brain function and the role of break-

downs in this process in neurological disorders, while

Lipscombe,Allen, and Toro cover the mechanisms control-

ling the expression of neuronal voltage-gated calcium

channels (CaV). Finally, Wolfram and Baines delve into

recent findings suggesting neurotransmitter phenotype

and expression of specific ion channels in neurons are

not always hard and soft wired, respectively.

In some form or another, all of my predecessors have

expressed in this space the statement that these are excit-

ing times to be a neuroscientist. That such a statement can

be repeated, in all earnestness, over such a long period of

time speaks to what a fascinating, dynamic, and exciting

endeavor the study of the nervous system is. Currently, the

field is faced with many challenges.According to the World

Health Organization (WHO), the socioeconomic burdens of

psychiatric and neurological diseases are only expected to

continue to increase [1]. Meanwhile, large scientific fund-

ing bodies in many countries continue to see their budgets

decline in real or inflation-adjusted terms. However, there

are also numerous possibilities and potentials for great

discoveries. The ongoing development of methods for

controlling the activity of identified neuronal subtypes

Editorial

Corresponding author: Clark, A.M. ([email protected]).

0166-2236/$ see front matter 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tins.2013.09.002 Trends in Neurosciences, October 2013, Vol. 36, No. 10 555
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on a fast timescale offers the potential to dissect circuit

function in exquisite detail, next-generation sequencing

offers the hope to better understand the genetic basis of

neurodegenerative and neuropsychiatric diseases, and

new computational tools for mining large and complex

data sets are constantly being refined. As always, the

journal welcomes feedback on our effort to cover this

exciting ground;

it would

be impossible

to

identify

andreport on all the newest trends without invaluable input

from our Advisory Editorial Board, authors, and readers.

In teaming with our colleagues at other Cell

Press journals, be they other Trends titles such as

Trends in Cognitive Sciences, Trends in Endocrinology

and Metabolism, or Trends in Pharmacological Sciences,

or premier research journals, such asNeuron and Cell, to

provide up-to-date and authoritative coverage of the

neurosciences, TiNS hopes to be able to serve the in-

creasingly diverse needs of this broad community. I will

be at the upcoming Society for Neuroscience conference

in San Diego, please stop by the Cell Press/Elsevier

booth to chat and pick up a free copy of TiNS, or stop

me

in a

poster

aisle or

at a

symposium,

to

let

me

knowyour thoughts on how the journal can best continue to

strive towards achieving this goal.

Reference1 World Health Organization (2011) Mental Health Atlas 2011, WHO

Editorial Trends in Neurosciences October 2013, Vol. 36, No. 10

556
http://refhub.elsevier.com/S0166-2236(13)00158-6/sbref0005http://refhub.elsevier.com/S0166-2236(13)00158-6/sbref0005http://refhub.elsevier.com/S0166-2236(13)00158-6/sbref0005http://refhub.elsevier.com/S0166-2236(13)00158-6/sbref0005


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The Brain Prize 2013: the optogenetics revolution

Andreas Reiner1 and Ehud Y. Isacoff1,2

1

Department

of

Molecular

and

Cell

Biology

and

Helen

Wills

Neuroscience

Institute,

University

of

California

Berkeley,

Berkeley,California 94720, USA2Physical Bioscience Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA

The 2013 Grete Lundbeck European Brain Research Prize

was awarded to Ernst Bamberg, Edward Boyden, Karl

Deisseroth, Peter Hegemann, Gero Miesenbo ck, and

Georg Nagel for their invention and refinement of opto-

genetics. Why optogenetics? And why this sextet? To

appreciate why, we turn first to some of the core ques-

tions of neuroscience and the technical difficulties that

long obstructed their resolution.

The beauty and the agony of brain circuits

How does the brain process sensory information, drive

behavior,mediate perception, thought, andmemory?Since

the late 1880s, when Santiago Ramon y Cajal used the

mysterious tendency of the Golgi stain to label only a

scattershot of neurons, and could thereby visualize the

shapes of individual cells and trace their connections,

neuroscientists have recognized that an essential part of

the explanation lies in the neuronal circuitry. Modern

morphological approaches allow the staining of entire cell

populations and visualization of the synaptic connections

therein. However, although these modern techniques, like

Cajals work originally, help in providing the physicalwiring diagram of the neural computer, they also illumi-

nate the difficulty of the neuroscience enterprise. They

demonstrate that every part of the nervous system con-

tains a multitude of neurons with distinct shapes, axonal

and dendritic arbors, and contact partners. The challenge

then is not only to find a way to determine who is actually

connected to whom, but how these individual synapses

transmit information, and how the many types of neurons

and connections give rise to functional networks that

perform diverse tasks.

Over the hundred years following Cajal the standard

approach to mapping this activity was to identify the

neurons

active

during

specific

sensory,

motor,

or

cognitiveevents, with the assumption that those neurons are direct-

ly involved in processing the relevant information. In these

studies, electrical signatures and cell location provided

some information about neuron type, but available

approaches could not discern the enormous variety of

cell types which was becoming evident from emerging

genetic analysis. In addition, the field lacked a method

for selectively stimulating or inhibiting activity in specific

cell types or transmission at specific synaptic connections.

The solution for discerning cell types and selectively

detecting their activity over an extended area came in the

form of genetically encoded fluorescent markers and opti-

cal reporters of action potential firing. This came from the

discovery of green fluorescent protein (GFP) as well as its

subsequent cloning and genetic engineering to generate

many color variants and to make optical reporters of cell

activity, work which was awarded the 2008 Nobel Prize inChemistry.

A major remaining challenge has been to develop the

means to manipulate activity in the nervous system with

the spatial, temporal, and cell-type resolution that is pro-

vided by the optical detection of activity using fluorescent

protein reporters. The 2013 Brain Prize was awarded this

year for the solution to this challenge (Figure 1).

Light as a force for exciting and inhibiting neuronal

activity

Having seen the power of light for visualization of neural

firing across a distributed network, one wonders if the

ability

to

focus

light

might

also

be

used

for

pinpoint

stim-ulation of neurons.Since 1970 effortsweremade todirectly

photostimulate neurons with light. The development of

light-sensitive protecting groups and their application to

photo-uncaging ofATP inspired the development of photo-

labile calcium chelators by Roger Tsien, Bob Zucker, and

Graham Ellis-Davis, and of caged neurotransmitters,

starting in the group of Peter Hess. These methods could

be used to stimulate specific cells that were genetically

identified by the selective expression of a fluorescent pro-

tein reporter, providing the desired cell type specificity.

However, they are best suited to stimulation of one cell at a

time, a limitationwhen one considers the great power both

for

circuit

mapping

and

behavioral

analysis

of

an approachthat would enable stimulation or inhibition of multiple

cells of a genetically select type. To achieve such a goal, a

genetically encoded system that can be reversibly con-

trolled by light seemed ideal.

Where can one turn to look for light-sensitive proteins?

The obvious place is in the vertebrate eye to the natural

worlds photoreceptor proteins, the opsins. But rhodopsin

and its cone cousins are G protein-coupled receptors that

signal to ion channels in the complex biochemical and

cellular context of the photoreceptor cell. There are several

factors which prohibit mammalian opsins from being at-

tractive candidates. However, the photoreceptor system in

the Drosophila eye is simpler. In 2002 Gero Miesenbock

Science & Society

Corresponding author: Isacoff, E.Y. ([email protected]).

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and Boris Zemelman [1] made a critical conceptual and

experimental step by expressing a trio of Drosophila pro-

teins (arrestin-2, rhodopsin, and its cognate Ga subunit:

dubbed chARGe) in cultured hippocampal neurons, en-

abling them to be excited by light. If one had to identify the

paper

that

launched

the

thousand

ships

of

optogenetics,this is it.

Beautiful as chARGe was, it had two shortcomings:

excitation by light was modest in strength and the ap-

proach could not be easily transferred to other systems

because of the difficulty of carrying out triple transfection.

The following year, Miesenbock combined photo-uncaging

of ATP or capsaicin with the heterologous cell-specific

expression of either the excitatory P2X or TrpV1 receptor

channels [2]. This approach also had limitations: It was

confined for use in animals that lack receptors forATP and

capsaicin, in other words, it could not be used in verte-

brates.At roughly the same time, Ed Callaways lab devel-

oped the reverse logic, expressing the Drosophila

allatostatin receptor in specific mammalian neurons and

activating it with allatostatin, which has no mammalian

receptor, to open G protein-gated inwardly rectifying K+

channels (GIRKs), and thereby inhibit action potential

firing. But allatostatin, like engineered GPCRs that are

activated only by synthetic ligands (e.g., the RASSLs de-

scribed by Bruce Conklin in 1998), had no light-activated

variant, and thus lacked the rapid switching and spatial

precision that is enabled by optical control.

Was there, then, a simpler opsin to which one could

turn, allowing for exploitation of Miesenbocks conceptual

breakthrough, but with fewer components, faster speed,

and sufficient strength? The answer is yes. Opsins from

bacteria and single-cell algae had been studied for decades.

But they were known to be different from their relatives in

the eye and were so foreign phylogenetically that one

wondered if they could ever be imported in a functional

form into the mammalian brain.

Starting

in

the

lab

of

Oesterhelt

in

the

mid-1980s,

ErnstBamberg and Peter Hegemann worked on two microbial

opsins from Halobacterium salinarium: bacteriorhodopsin

(bR) and halorhodopsin (hR). These opsins, although relat-

ed to the seven transmembrane helix G protein-coupled

receptor opsins of the eye, are self-contained light-driven

ion pumps. In response to light, bacteriorhodopsin pumps

H+ and halorhodopsin pumps Cl across the membrane,

thereby changing the ionic balance and membrane poten-

tial. Like rhodopsin, bR and hR use retinal as a chromo-

phore. In the late 1980s Hegemann branched out and

characterized the phototaxis in the single-cell algae Chla-

mydomonas reinhardtii, which appeared to depend on

another rhodopsin relative. The work culminated in two

seminal publications in 2002 and 2003 from ajoint effort of

the Bamberg and Hegemann labs, both with Georg Nagel

as a first author,which described the cloning, heterologous

expression, and functional characterization in Xenopus

oocytes of these opsins, which turned out to be cation-

selective ion channels that were named channelrhodopsin

1 and 2 (ChR1 and ChR2) [3,4]. Importantly, Nagel et al.

demonstrated that ChR2 could be expressed to achieve

light-induced depolarization in non-neuronal mammalian

cell lines.

Here one had, it seemed, theperfect and complementary

set of genetically encoded light-driven pumps and chan-

nels. But could they be used in neurons? The reputation

TRENDS in Neurosciences

Figure 1. The award ceremony for theBrain Prize 2013. From the left: Ernst Bamberg, Edward Boyden, Karl Deisseroth, Peter Hegemann, Gero Miesenbo ck, Georg Nagel,

Crown Prince Frederick, and former chairman of the board of the Grete Lundbeck Foundation Nils Axelsen. Reproduced with permission from the Grete Lundbeck

Foundation.

Science & SocietyTrends in Neurosciences October 2013, Vol. 36, No. 10

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ofmicrobial proteins was that they are notoriously difficult

to express, and they normally operate in extreme ionic

environments very different from those of the central

nervous system. Indeed, for various reasons bR and hR

from Halobacterium salinarium and ChR1 were never

successfully transferred to neurons. But in 2005 Karl

Deisseroth and Ed Boyden, in a collaboration with Nagel

and Bamberg,

and

Stephan

Herlitzes

lab

in

collaborationwith Hegemann and Lynn Landmesser, successfully

expressedChR2 inmammalianneurons anddemonstrated

robust firing of action potentials in response to blue light

[5,6]. In his study, Herlitze was also able to inhibit neuro-

nal firing usingvertebrate rhodopsin, coupling it to GIRKs

or P/Q-type Ca2+ channels, and performed the first in vivo

experiments in intact spinal cord and living chicken em-

bryo [6]. In the same year, Alexander Gottschalk, in col-

laborationwithNagel andBamberg, succeeded in optically

altering the behavior of the worm Caenorhabditis elegans[7], Hiromu Yawo demonstrated optical control of firing in

acute hippocampal slice following sterotatic injection of

ChR2-coding viruses in mouse [8], and Zhuo-Hua Pan

demonstrated functional ChR2 expression in the mouseretina [9]. In 2007 both Deisseroth, continuing the collab-

oration with Nagel and Bamberg, and Boyden used a

halorhodopsin from another archaeon, Natronomonas

pharaonis, which lives in soda lakes in Egypt, to pump

Cl ions into neurons in response to light of a different

wavelength from that used to activateChR2 and thereby to

hyperpolarize neurons and inhibit firing [10,11]. Later,

Boyden added pumps which extrude H+ to hyperpolarize

neurons.

In parallel to the development of opsins to control

neuronal firing, chemical optogenetics was developed,

thus enabling direct light-control of the signaling proteins

of

the

mammalian

synapse.

This

approach

was

inspired

byfoundational studies by Bernard Erlanger and coworkers

in the 1970s, who developed synthetic photoswitchable

tethered and diffusible ligands for muscle nicotinic recep-

tors. The first such control of neural activity, reported in

2004, was a light-blockedK+ channel, SPARK,which could

be used to inhibit neuronal firing [12]. Thiswas followed by

an excitatory light-activated ionotropic kainate-type glu-

tamate receptor, LiGluR [13], an inhibitory version of

LiGluR known as HyLighter, light-activated and light-

blocked neuronal nicotinic acetylcholine receptors [14],

and light-activated and light-blocked G protein-coupled

metabotropic glutamate receptors that inhibit spiking

and neurotransmitter release [15]. Although these light-

gated channels and neurotransmitter receptors can be

used in the manner of the opsins to excite and inhibit

neuronal firing, and to inject calcium into neurons or glia,

their unique promise is for gating synaptic transmission

and plasticity.

Expansion of tools, explosion of neuroscience

Since 2005, when ChR2 was first used to excite neurons

in response to light, efforts in the field, led by the sextet,

culminated in the isolation of new microbial opsins and

opsin engineering to generate excitatory and inhibitory

versions with larger currents and different ion selectivi-

ty, kinetics, and excitation spectra. As envisioned, light

as a minimally invasive stimulus allowed exquisite

spatiotemporal patterning of neuronal activity, whereas

the combination with elaborate genetic methods allowed

a specificity of targeting to cell type that was never

possible before. Soon, these methods were taken from

cellular studies in vitro to behavioral studies in awake

animals.

The spread

of

optogenetics

with

microbial

opsins

hasbeen nothing short of spectacular, a product of the com-

bined power of the method and its simplicity of use. Be-

cause retinal is bioavailable in the vertebrate nervous

system and because, unlike in visual rhodopsins, it binds

irreversibly to the microbial opsins, the user is only a

transfection, a viral infection, or genetic cross away from

an experiment. Consequently, the opsins have been

deployed across a wide range of organisms, from worm

to fly to fish to mouse to non-human primates. They have

been used to study brain waves, sleep, memory, hunger,

addiction, aggression, courtship, sensory modalities, and

motor behavior. They have also been used as models for

clinical treatment: for deep brain stimulation, on one hand,

and as a retinal prosthetic on the other.This revolution led to hundreds of papers a veritable

deluge that even swept away entertaining qualms of

Miesenbock about the optogenetic catechism. The sim-

plicity of the term and the power of the methodology have

conquered all. There is little question in the neuroscience

community that optogenetics deserves awards of the

magnitude of the 2013 Brain Prize. It is a great thing

that theprizehas recognized thepeople who launched the

field both those whose basic science on opsins paved the

way, as well as those who engineered them into the

nervous system.

AcknowledgmentsThis work was supported by the National Institutes of Health (NIH)

Nanomedicine Development Center for the Optical Control of Biological

Function (PN2EY018241).

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chARGed neurons. Neuron 33, 1522

2 Zemelman, B.V.et al. (2003) Photochemical gating of heterologous ion

channels: remote control over genetically designated populations of

neurons. Proc. Natl. Acad. Sci. U.S.A. 100, 13521357

3 Nagel, G. et al. (2002) Channelrhodopsin-1: a light-gated proton

channel in green algae. Science 296, 23952398

4 Nagel, G. et al. (2003) Channelrhodopsin-2, a directly light-gated

cation-selective membrane channel. Proc. Natl. Acad. Sci. U.S.A.

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5 Boyden, E.S. et al. (2005) Millisecond-timescale, geneticallytargeted optical control of neural activity. Nat. Neurosci. 8, 1263

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6 Li, X. et al. (2005) Fast noninvasive activation and inhibition

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7 Nagel, G. et al. (2005) Light activation of channelrhodopsin-2 in

excitable cells ofCaenorhabditis elegans triggers rapid behavioral

responses. Curr. Biol. 15, 22792284

8 Ishizuka, T. et al. (2006) Kinetic evaluation of photosensitivity in

genetically engineered neurons expressing green algae light-gated

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Molecular nexopathies: a newparadigm of neurodegenerative

diseaseJason D. Warren1, Jonathan D. Rohrer1, Jonathan M. Schott1, Nick C. Fox1,John Hardy2, and Martin N. Rossor1

1Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London,

London, UK2Reta Lilla Weston Laboratories and Department of Molecular Neuroscience, UCL Institute of Neurology, University College

London, London, UK

Neural networks provide candidate substrates for the

spread of proteinopathies causing neurodegeneration,

and emerging data suggest that macroscopic signaturesof network disintegration differentiate diseases. Howev-

er, how do protein abnormalities produce network

signatures? The answermay lie with molecular nexopa-

thies: specific, coherent conjunctions of pathogenic pro-

tein and intrinsic network characteristics that define

network signatures of neurodegenerative pathologies.

Key features of the paradigm that we propose here in-

clude differential intrinsic network vulnerability to

propagating protein abnormalities, in part reflecting de-

velopmental structural and functional factors; differential

vulnerability of neural connection types (e.g., clustered

versus distributed connections) to particular pathogenic

proteins;

anddifferential

impact

of

molecular

effects

(e.g.,toxic-gain-of-function versus loss-of-function) on gradi-

ents of network damage. The paradigm has implications

for understanding andpredicting neurodegenerative dis-

ease biology.

Introduction

Neural networks are a key theme in contemporary neuro-

science [13]. Operationally, a neural network can be de-

fined as a complex system comprising nodes and links

represented by neurons and their connections [4]. Neural

networksextend over scales ranging frommicroscopic (neu-

rons and synapses) to macroscopic (anatomical regions and

fibre tracts), and may be structural (defined by physical

connections; e.g., fibre tracts) or functional (defined by

physiological connections). Neuroimaging techniques, such

as functional MRI (fMRI) and diffusion tensor tractography

[4,5], coupledwithmethodologies suchasgraph theory[2,6],

have delineated intrinsic, distributed neural networks

supporting cognitive functions in the healthy brain [79].

Neural network models have been successfully applied to

common neurodegenerativesyndromes [35,715],building

on the key insight thatneurodegenerative diseases, such as

Alzheimers disease (AD) and frontotemporal lobar degen-

eration (FTLD), produce distinctive clinicalsyndromes withregularpatternsofevolutiondue to thespreadofpathogenic

protein abnormalities via large-scale brain networks.

To date, work in neurodegenerative disease has mainly

focussed on linking clinical phenotypes to network altera-

tions. However, it remains unclear how molecular (protein)

abnormalities translate to network damage and, thus,

clinical phenotypes; and whether pathological substrates

can be predicted reliably from macroscopic network signa-

tures. Recent advances in genetics and histopathology

have enabled the detailed mapping of neurodegenerative

clinico-anatomical phenotypes onto specific proteinopa-

thies, transcending broad categories such as tauopathy

or

ubiquitinopathy.

Histopathological

patterns

of

proteindeposition reflect underlying molecular (biochemical or

conformational) characteristics in a range of neurodegen-

erative diseases, most strikingly in the FTLD spectrum

[1624]. Although the concept requires further substanti-

ation and qualification, the diffusive intercellular or prion-

like spread of pathogenic misfolded proteins holds promise

as a general mechanism for the evolution of the neurode-

generative process in a wide range of diseases [8,9,2528].

Various candidate mechanisms that might link protein

pathophysiology with intercellular miscommunication

and local circuit disruption have been identified

[3,29,30]. However, the mechanisms that translate local

effects

of

proteinopathies

to

specific

patterns

of

large-scalenetwork disintegration remain largely unknown.

Here, we address this problem. We propose the term

molecular nexopathy (Latin nectere, tie) to refer to a coher-

ent conjunction of pathogenic protein and intrinsic neural

network characteristics expressed as a macroanatomical

signature of brain network disintegration. We argue that

improved understanding of the molecular mechanisms of

network disintegration will constitute a new paradigm of

neurodegenerative disease. The essential features of the

paradigm that we propose are presented in Box 1 and

Figures 13. Wenow consider potential mechanisms where-

by molecular dysfunction might be linked to neural circuit

disruption.We thenassess the extent towhich the molecular

Opinion

0166-2236/$ see front matter

2013 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.tins.2013.06.007

Corresponding author: Warren, J.D. ([email protected]).

Keywords: neurodegeneration; dementia; neural network; nexopathy.

Trends in Neurosciences, October 2013, Vol. 36, No. 10 561
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nexopathy paradigm can be reconciled with the central pro-

blemsofdiseaseevolutionandphenotypicheterogeneity,and

propose experimental tests of the paradigm in future work.

How do pathogenic molecules produce specific brain

network disintegration?

Networks

show

variable

intrinsic

vulnerability

toproteinopathies

The molecular nexopathy paradigm makes no assumptions

about the instigating event that triggers the neurodegen-

erative process, which might be stochastic but which

results in the creation of a potentially pathogenic molecule.

However, once initiated, the topography of neurodegenera-

tion preferentially targets network elements that are vul-

nerable to the instigating molecular species (Figure 1).

Emerging evidence, including inoculation experiments in

animals [3133] (Box 1), implies that a neurodegenerative

process may home to a brain region (or regions) based on

intrinsicvulnerability to the pathogenic protein. Neurode-

generation may propagate by prion-like seeding or tem-

plating of the protein abnormality (e.g., conformational

misfolding) across neural connections, in addition to phys-

ical transfer of instigating pathogenic proteins. The pres-

ence of a specific pathogenic abnormality that propagates

across a network would distinguish a neurodegenerative

molecular nexopathy from other diseases that disrupt

brain networks (for example, stroke and traumatic brain

injury): one important corollary is that compensatory or

homeostatic responses are ultimately inadequate in neuro-

degenerative nexopathies.

Regional neural vulnerability to a proteinopathy could

reflect anatomically restricted expression of the culprit

protein by cell populations or additionalepigenetic factors

that direct the expression of the protein to particular

brain areas [3436] or determine neuronal susceptibility

to toxic events [10]. Regional differentiation of protein

expression is a fundamental feature of normal brain

development [37], establishing intrinsic specificities of

connections within neural circuits [38,39] and thereby

in

turn directing the function

of the circuit.

Therefore,local profiles of protein expression could confer selective

vulnerability or resistance of particular networkelements

to particular neurodegenerative diseases, and would also

help drive the functional phenotypic signature of the

disease. For example, differential expression of neuropro-

tective factors has been linked to the relative vulnerabili-

ty of particular neuronal populations in the basal ganglia

in Parkinsons disease [40], and regional expression of

genes involved in inflammatory signalling may modulate

disease onset with progranulin (GRN) mutations [41]. By

contrast, epigenetic effects during brain development

alter the regulation and expression of amyloid precursor

protein andpotentially influence the later development of

AD [42]. Brain areas that are highly neuroplastic, more

specialised, or phylogeneticallymore recent (for example,

the language system) may be relatively more vulnerable

to proteinopathies [43], whereas primary motor and sen-

sory cortex both show relative resistance. The process of

neurodegeneration might selectively unravel the se-

quenceof normal ontogeny within the vulnerable network

(for example, by withdrawing essential trophic support,

repair mechanisms, or physiological signalling across

damaged synaptic connections) [29].

Regional specificity might also arise from cellular mor-

phological factors, particularly at synaptic connections:

even if a protein is widely expressed in the brain, its effects

Box 1. The molecular nexopathy paradigm: key substrates and constraints

Molecular, microstructural, and functional substrates

Pathogenic proteins, including misfolded aggregates and toxic

oligomers, could promote neural network disintegration by disrupt-

ing synaptic function or maintenance [57], axonal transport or repair

[79], or via downstream trophic [58,80] or cellcell signalling

abnormalities [3,10,29,62,8185] . Disease effects would exploit in-

trinsic network vulnerabilities: in particular, developmental patterns

of protein expression and structural and functional interactionsacross neural circuits [38,39] (Figure 1, main text). Shorter-range or

clustered dendritic and interneuronal connections appear particularly

vulnerable to some tauopathies [48,51], whereas longer-range, more

widely distributed (axonal) projections may be relatively more

vulnerable to other molecular insults (e.g., toxic oligomers derived

from amyloid precursor protein [58] or deficiency of trophic or

protective factors such as GRN [57]). The balance between molecular

net toxic gain-of-function and loss-of-function effects [57,62] might

help to determine the extent to which proteinopathies exert uniform

or graded effects across neural circuits (Figure 1, main text). Soft-

wired alterations in synaptic function, in part reflecting pervasive

network activity patterns,might give way to subsequent (irreversible)

hard-wired structural damage and cell loss.

Disease propagation

Transcellular and, in particular, synaptically mediated diffusion ofmisfolded proteins and permissive templating of protein misfolding

appear to be general principles of disease evolution across a range of

neurodegenerative proteinopathies [26,86], including prion [85], beta-

amyloid [3133], tau [8790], alpha-synuclein [91,92], TDP-43 [71,72],

and superoxide dismutase 1 [27]. Inoculation with beta-amyloid and

tau triggers uptake by cells and templated conformational alteration

of normally folded protein to a potentially pathogenic, misfolded

state [26,86]. Trans-synaptic spread of tau-containing tangle pathol-

ogy from entorhinal cortex neurons occurs in transgenic mice that

only express mutant MAPT in those neurons [89,90].

Macroanatomical signatures

Particular structural

and functional neuroimaging profiles

of net-work disintegration have speci f ic molecular associations

[7,16,17,2023,68,69,74,75,9395] (Figure 2, main text). In the FTLD

spectrum, structural neuroimaging evidence suggests a scheme for

partitioning pathologies according to whether the macroanatomical

brain atrophy profile is localised or distributed, andwhether atrophy

is relatively symmetric or strongly asymmetric between the cerebral

hemispheres [18,23] (Figure 2, main text). In the case of AD, early

(even presymptomatic) functional and structural alterations occur

within a specific distributed parieto temporofrontal network mediat-

ing default mode processing or stimulus-independent thought in

healthy individuals [4,11] and network disintegration tracks patho-

logical disease staging [11,14,96]. Variant AD phenotypes, such as

posterior cortical atrophy and logopenic progressive aphasia, may

reflect differential involvement of corticocortical projection zones

that together constitute a distributed AD-vulnerable network [15,97],

although the precise pathophysiological roles

of the

two

majorcandidate pathogenic proteins (beta-amyloid and phosphorylated

tau) and the factors that modulate the profi le of network damage

remain contentious [4,11,15]. Convergence of syndromes as disease

evolves may hold a solution to the problem of phenotypic hetero-

geneity (Figure 3, main text).

Opinion Trends in Neurosciences October 2013, Vol. 36, No. 10

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may propagate only in particular cell types [44] or across

specific patterns of connections [29]. Animal models have

demonstrated exquisite microanatomical and biochemical

specificity of intercellular connections in key vulnerable

structures (such as hippocampus) [45,46]. Age-related neu-

ronal resprouting may enhance local deposition of amyloid

precursor protein in entorhinal cortex early during the

course of AD [47]. Protein expression and morphological

specificity at receptors and synapses would interact with

subcellular molecular factors. For example, tau isoforms

show distinctive subcellular distributions [48,49]. De-

ranged microtubular transport of abnormal tau facilitates

accumulation of aggregated tau in somatic and dendritic

rather than axonal compartments [50,51], whereas diffus-

ible tau may further focus pathogenic effects of the protein

on local synaptic and glial connections [51]. The role of glial

elements is poorly understood, but may influence local

expression and development of network damage, reflected

macroscopically in the relative extent of grey matterversus

white matter damage [52].

Proteinopathies are fitted to neural circuits

Central to the molecular nexopathy paradigm is the fit

between the pathogenic molecule and local neural circuit

(and, ultimately, large-scale network) characteristics

(Figures 1 and 2). Although data on specific local interac-

tions of neural circuits with proteins remain limited, a

(A) Clustered no gradient

Distributed no gradient Distributed gradient

Clustered gradient

(C) (D)

(B)

I

N6

N5

N4

N3H

N2

N1

I

N6

N5

N4

N3H

N2

N1

I

N6

N5

N4

N3H

N2

N1

I

N6

N5

N4

N3H

N2

N1


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 (fi lled lines) connections; the most highly

connected node behaves as a local hub (H), whereas node I is the site of aninstigating insult (wavy arrow) associatedwitha pathogenic protein.Grey symbols

represent unaffected or minimally affected network elements; pathogenic effects

are coded in red (filled circles representing deleted networkelementsand half-tone

circles representing dysfunctional network elements) and pathogenic effects are

assumed to be potential ly 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., IN1N2HN3N4

N5 (A,B)] versus longer-range distributed neural connections [e.g., I-H-N5-N6,

(C,D)]; and effects thatare relatively uniform[nogradient, (A,C)] or stronglygraded

[gradient (B,D)] acrossthe network.In each case, thehubH is intrinsically relatively

more vulnerable due to its high connectedness with the rest of the network [60].

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 wepropose 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).

(A)MAPT

TDPC

CBD

GRN

(B)

(C)

(D)


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 withgeneric clinical syndromes in previousconnectivitywork

[7]: 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 Alzheimers 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 [19], associated with the clinical syndrome of

semanticdementia; theleft hemisphereis on theleft in allsections). 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) connectionswitha gradientof 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 spreadbetween functional networks, while continuing to target

connectionswith similar properties across these networks. Thiswould 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 involvementwith particular proteinopathies (e.g., sequential involvement

of homologous contralateral temporallobe regionswithTDPC pathology) (seealso

Figure 3, main text).


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proteinopathy might spread between brain regions by

causing connected regions to develop the same intracellu-

lar

protein

abnormality

or,

less

directly,

by

affecting

thefunction of those connected regions [3]. The coupling be-

tween functional and structural connectivity in neurode-

generative diseases remains poorly defined: however,

initial dysfunction could promote subsequent molecular

alterations and destruction of network elements, as shown

in lesion and tract-tracing studies in humans and nonhu-

man primates [5,6,53]. In more theoretical terms, the

effects of a proteinopathy on a network might be regarded

as a form of information flow, where information signifies

a change in network function (in particular, alterations in

synaptic properties) associated with the introduction of the

abnormal protein [3]. The characteristics of information

exchange across artificial neural networks have attracted

considerable interest in computational neurobiology [2,54]:

this theoretical framework might be adapted to the case of

proteinopathies. Pathogenic molecular effects often have

time constants that are much longer than those typically

associated with information flow in neural networks. How-

ever, dynamic downstream alterations in synaptic function

across circuits would occur over much shorter timescales.A

further, potentially related, factor is the role of pervasive

patterns of activity in circuit function and in predisposing

networks to the effects of neurodegenerative disease [55]:

examples include the differential and possibly use-

dependent susceptibility of particular motor pools to

amyotrophic lateral sclerosis (ALS) [27], or the altered

trafficking of amyloid and tau in the isodendritic core

associated with perturbations of the sleepwake cycle in

AD [56]. Putative behavioural and activity-related factors

are likely to interact with underlying genetic and epige-

netic predisposing factors, and the causal sequence in

general remains to be determined.

An important theoretical motivation for applying the

network information-processing

framework

to

the neurode-generativeproteinopathies is the rich taxonomy of network

activity patterns that follow from relatively simple starting

assumptions when modelling the evolution of artificial neu-

ral networks [54]. In particular, it has been shown in such

artificial networks that patterns of neural activity in local

network elements can, under certain conditions, scale up to

the entire network; that the characteristics of local micro-

circuits strongly influence the activity pattern produced by

the network as a whole; and, furthermore, that these pat-

terns may be highly polarised. All these are network prop-

erties predicted in the case of the neurodegenerative

proteinopathies, for which an activity pattern could be

interpreted as the cumulative effect of protein-associated

network damage integrated over time [55].Relevant network and protein characteristics have yet

to be worked out in detail for neurodegenerative proteino-

pathies. However, it has been shown that brain networks

have small-world properties expressed as a high degree of

clustering among network elements and short average

path lengths between clusters [2]. These small-world prop-

erties suggest a basic dichotomy between shorter-range

neural connections within clusters (local neural circuits,

with relatively long neural path length) and relatively

sparse longer-range neural connections (with relatively

short neural path length) between clusters, in line with

highly segregated and hierarchical brain network archi-

tectures

observed

empirically

[6]

and

with

limited

evidenceconcerning the cellular pathophysiology of certain protei-

nopathies [48,51,57,58] (Box 1). This putative dichotomy

between clustered and distributed network connections

suggests a morphological basis for partitioning neurode-

generative diseases according to whether they produce

relatively localised versus more distributed profiles of

macroscopic brain atrophy [18,20] (Figures 1 and 2). Clus-

tered and distributed connections could be modelled in

synthetic neural circuits and could be defined in brain

networks using anatomical methods that can measure

effective path lengths between network elements [6]; for

example, dynamic causal modelling. Alternative morpho-

logical dichotomies might also operate: for example, selec-

tive targeting of excitatory versus inhibitory projections

[44].

The degree of macroanatomical asymmetry of network

damage within and between cerebral hemispheres appears

to be a further partitioning characteristic of many neuro-

degenerative diseases (Figure 2), although to demonstrate

interhemispheric asymmetries, it may be necessary to

retain individual hemispheric asymmetry profiles when

pooling data in group neuroimaging studies [18,2022].

Network asymmetries could be determined, in part, by

configurational features of the host network that might

tend to polarise network activity. Such polarity has been

demonstrated in a computational model of Huntingtons

bvFTD

t0 t1 t2

PNFA

CBS


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, colourcoded 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 corticobasalfunctional network (light blue in inset)is involvedwith

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

arisesfrom a commontemplate of network involvement determinedby thetypeof

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.


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disease [44]. Asymmetries might be predicted based on

extrapolation from network architectures in the brains of

other species. For example, the nodes of large-scale net-

works in the macaque brain have a highly nonuniform

distribution within the cortex and the connections be-

tween nodes are hierarchically organised [6]. Given that

the human brain shares network homologies with that of

the macaque [53],

this architecture would tend to

focusthe effects of neurodegenerative disease at particular

vulnerable hub regions (for example, in prefrontal cor-

tex and posterior cingulateprecuneus [1,59]). Much

more generally, it has been shown that highly connected

network elements are intrinsically more vulnerable to

extinction following perturbing events in a variety of

hierarchical systems, ranging from ecology to economics

[60]. In the context of neurodegenerative disease, extinc-

tion might be equated to destruction of highly connected

network elements after introduction of a pathogenic

protein and susceptibility from connectedness might,

for example, predict disproportionate vulnerability of

dominant hemisphere language hubs in the progressive

aphasias [43] and medial parietal hubs binding thedefault mode network in AD [1,4,15,55,59]. If functional

connections between brain regions are defined based on

the strength and direction of spontaneous activity cor-

relations, fMRI data suggest a fundamental dichotomy

between positive connections that are dominant within

a cerebral hemisphere versus negative connections that

are dominant between hemispheres [61]: negative inter-

hemispheric functional correlations will tend to establish

intrinsically asymmetric interhemispheric interactions

that could be exploited by neurodegenerative pathologies

(Figure 2).

It is unlikely a priori that any set of neuronal or neural

network

features

would

confer

vulnerability

uniquely

to

asingle molecular species. However, further specificity in

the profile of network involvement (in particular, whether

strong polarity of damage is expressed across the brain)

may be driven, in part, by functional characteristics of the

pathogenic protein itself.

Directional protein dysfunction drives network

asymmetries

Across the spectrum of potentially pathogenic proteins,

there is a basic distinction between toxic-gain-of-function

(deleterious effects of protein accumulation) and loss-of-

function (impaired physiological, signalling or trophic)

molecular effects [57,62]. The loss of function of a key

protein is likely to lead ultimately to the loss of function

of the affected network element and, therefore, might be

regarded in computational terms as inhibiting the affect-

ed element; the net computational effect of a toxic gain of

function is more difficult to predict. Large-scale network

asymmetries (i.e., asymmetric macroscopic atrophy pro-

files) might result from interaction of intrinsic connectivity

structure with a gradient of molecular effects across the

vulnerable network.

We envisage that, within an affected network, an overall

toxic gain of function will spread relatively uniformly,

whereas an overall loss-of-function effect will establish a

gradient of tissue loss due to attenuation of downstream

synaptic inputs. Such polarising network-level effects of

loss-of-function proteinopathies would be in line with a net

inhibitory action on damaged connections, because selec-

tive inhibition of network elements can generate highly

polarised network structures and self-amplifying network

activity patterns in computational models [54,61,63,64].

Proteinopathic effects would interact with (and may, in

part,

be

driven

by)

intrinsic,

ontogenetic

network

gradients[38,39]. Trophic effects modulate intercellular gradients in

normal morphogenesis and developmental disorders [65]

as well as in computational models [66]. Certain loss-of-

function effects could become self amplifying due to addi-

tional, catastrophic mechanisms that might be specific to

particular protein alterations: an example is GRN muta-

tions, which may inhibit neuronal repair processes leading

to accelerated collapse of network architecture [67].

Although it is unlikely that polarised protein effects

operate in pure form in the brain [57,62], for a given

disease process and disease stage, toxic gain-of-function

or loss-of-function effects may dominate at the network

level (Figure 1). Intracellularly, particular pathogenic pro-

teins have complementary loss-of-function and toxic-gain-of-function effects [62]. However, the overall primary bal-

ance of those effects across a neural network may depend

on specific molecular actions at key network elements (e.g.,

synapses) that act as the final common pathway for net-

work damage. Additional specificity may be conferred by

biochemical characteristics and conformational signatures

of protein subtypes within broad categories, such as tau

and Tar DNA-binding protein 43 (TDP-43) [24,49]. We

currently lack such specific information for most key path-

ogenic proteins in the neurodegenerative spectrum [62].

There is further substantial potential for interactions

among pathogenic proteins (for example, between tau

and

beta-amyloid

in

AD

[28]). Protein-specific

effects

mightmodulate intrinsic network connectivity properties, con-

tributing to phenotypic variation associated with particu-

lar proteins within a common network architecture [for

example, the relatively symmetric atrophy profile associ-

ated with microtubule-associated protein tau (MAPT)

mutations versus the strongly asymmetric profile associ-

ated with TDP-43 type C (TDPC) pathology [19] within

anterior temporal lobe networks [18]].

Temporal evolution and the problem of heterogeneity

A critical feature of neurodegenerative molecular nexopa-

thies is likely to be their pattern of evolution in time as well

as spatially within the brain. The rapidity of network

breakdown might depend on the relative proportions of

connection types affected by the pathological process, the

predominant involvement of longer-range connections cor-

responding to rapid spread and involvement of clustered

connections corresponding to slower spread, respectively.

This would fit with available data for certain neurodegen-

erative disorders. For example, patients with MAPT muta-

tions and relatively focal anterior temporal lobe damage

have, on average, slower rates of overall brain atrophy and

survive substantially longer compared with patients with

GRN mutations associated with widespread intrahemi-

spheric damage [68]; interhemispheric asymmetry

increases with advancing disease in association with


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GRN mutations [17]; but MAPT and GRN mutations pro-

duce similar local rates of atrophy within key structures

such as the hippocampus [69]. Taken together, such evi-

dence suggests that disease effects are preferentially am-

plified if long intrahemispheric fibre tracts are implicated.

The temporal evolution of atrophy profiles associated

with a particular proteinopathy may reveal a characteris-

tic

signature

of

network

involvement

that

unites

appar-ently disparate phenotypes (Figure 3). For example,

tauopathies in the FTLD spectrum (such as corticobasal

degeneration) may present with a behavioural syndrome

due to frontal lobe involvement, with a language syndrome

due to involvement of peri-Sylvian cortices in the dominant

hemisphere, with a parietal lobe syndrome or with atypical

parkinsonism: the nexopathy paradigm predicts phenotyp-

ic convergence over time due to progressive erosion of

core frontoparietal, frontotemporal, or frontosubcortical

networks implicated in particular tauopathies [18]. There

is substantial evidence for such phenotypic convergence in

the FTLD spectrum [18,70] and related overlap syndromes

such as FTD-ALS [71]; however, precise correlations with

particular brain networks have yet to be widely estab-

lished. Similarly, variant AD phenotypes have been inter-

preted as modulating a core temporoparietal-prefrontal

default mode network [15]. Phenotypic convergence

implies that initial stochastic insults anywhere in a vul-

nerable network will lead ultimately to a common signa-

ture of network breakdown, although the precise sequence

of network

involvement

will

tend

to

reflect

the

initial

locusof pathology within the network (Figure 3).

This concept of the differential involvement of a core

vulnerable network (with increasingly complete involve-

ment of the network over time) suggests one possible

solution to the apparent paradox of individual phenotypic

variation associated with particular proteinopathies [70].

The clinico-anatomical expression of a given proteinopathy

often varies between individuals as well as between syn-

dromic subgroups [15,27,43]. The molecular nexopathy

paradigm requires that the neuroanatomical profile of dis-

ease evolution is not random, but adheres to a spatiotempo-

ral template of network damage: the location of disease

onset within the vulnerable network may vary between

Box 2. Testing the paradigm: outstanding questions and future directions

Is diffusive protein spread a general mechanism of neurodegenera-

tion?

The strength of evidence for prion-like spread, permissive templat-

ing, and direct cellcell transmission varies among proteinopathies,

and has not been established for some (e.g., fused-in-sarcoma

protein) [98]. Protein spread could occur via mechanisms other than

network pathways (e.g., extracellular diffusion [26,27]). Nonprion

diseases have not been shown to have prion-like spontaneous

infectivity and, typically, evolve more slowly [86].

Hypothesis

Diffusive protein spread is a general mechanism of network disin-

tegration.

Key experiments

Inoculation and tracer studies in animal models [3133] and the

development of novel molecular model systems [77].

How do protein properties relate to profiles of network degenera-

tion?

Protein properties and expression profiles remain to be related in

detail to cell morphological features, dynamics of cellular transport

mechanisms, and intercellular interactions. For various pathogenic

proteins, the final net direction of effects (loss-of-function versus

toxic gain-of-function effects) remains contentious [62]. For several

neurodegenerative diseases, the pathogenic protein species or the

pathogenic form of the protein has not been unambiguously

determined [25].

Hypothesis

Network degeneration arises predictably from interactions of patho-

genic protein properties with specific network morphological and

functional characteristics.Key experiments

Computational modelling of artificial neural networks with biologi-

cally plausible properties [44]; development of model neural circuits

in vitro [99] and in vivo[38,39]; histomorphometric and immunola-

belling analyses of subcellular protein targets and putative connec-

tion vulnerabilities (e.g., dendritic versus axonal) [48,51]; correlative

phenotypic-histological studies; and cognitive science paradigms to

characterise network activity and architectures [27,30,100].

Are empirical patterns of disease evolution consistent with nexo-

pathy models?

Certain proteinopathies have specific macroanatomical signatures of

network disintegration [4,7,11,1318,2023] , but disease overlap and

heterogeneity are substantial. The problem of heterogeneity may be

resolved, in part, by mapping longitudinal profi les of disease

evolution, using neuroimaging tools that can capture convergent

structural and/or functional changes across the brain and over time

[7,8,11]. The molecular nexopathy paradigm makes specific predic-

tions about the sequence of regional evolution with particular

proteinopathies (Figures 2 and 3, main text). fMRI reflects synaptic

function and can assess functional connectivity of networks when

active and at rest [1,7], including potentially compensatory and

homeostatic responses [3,10,73]; in addition, diffusion tensor ima-

ging can assess structural connectivity of white matter pathways that

bind large-scale networks [4,5].

Hypothesis

Macroanatomical spatiotemporal network signatures arise predicta-

bly from underlying molecular lesions.

Key experiments

Longitudinal quantitative tracking of regional t issue damage in

different neurodegenerative diseases in large patient cohorts (in

particular, those with defined molecular lesions) derived from multi-

centre collaborative platforms [101]; connectivity metrics (e.g.,

dynamic causal modelling) to assess relations between network

elements (e.g., putative shorter- versus longer-range connections)

and dynamic, physiologically motivated techniques, such as magne-

toencephalography (MEG) [12]; development of new molecular

ligands (e.g., phosphorylated tau); and practical quantitative metrics

of network function and connectivity [1,2].

What are the implications for disease diagnosis, prognosis, and

treatment?

Besides predicting underlying proteinopathies, improved under-

standing of determinants of network disintegration would enablethe prediction and more accurate tracking of disease evolution.

Identification of specific neural network dysfunction pre-dating the

loss of structural integri ty may enable modulation of culprit

molecular deficits. Specific molecular treatments could be directed

at modifying protein mecha

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Trends in Neurosciences - October 2013