Matthieu Petit
email: matthieu.petit@univ-amu.fr

Lisa Michez

Jean-Manuel Raimundo

Tuhiti Malinowski

Philippe Dumas

An introduction to photocatalysis through methylene blue photodegradation

Keywords: numbers: 82.45.Jn, 82.50.-m, 82.65.+r, 77.84.Cg photocatalysis, titanium dioxide, T iO 2, Langmuir-Hinshelwood, methylene blue, degradation, redox reaction, dyes

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Context

The last IPCC (Intergovernemental Panel on Climate Change) synthesis report has confirmed the impact of mankind on the climate change and its impacts on the ecosystems, people and economics. However this report also emphasizes that there are several means to limit climate change and its consequences [START_REF]Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. The efficient use of solar energy, as a green energy source for various applications is one of these means that the scientific and industrial communities tend to develop: the solar power irradiating the surface of Earth (around 10 5 TW) is four orders of magnitude higher than the current global human energy consumption. So the photocatalysis belongs to this wide family of various techniques and technologies aiming at a sustainable development of our society. Reports on photocatalytic reactions date from the beginning of the 20th century: for example C. F. Goodeve and J. A. Kitchener described the "photosensitisation of solids" and the bleaching of dyes by T iO 2 in 1938 [START_REF] Goodeve | [END_REF]. The true boost of interest on photocatalysis occurred in 1972 with the re-publication in English of a previous report of the splitting of water in hydrogen and oxygen at the surface of T iO 2 under ultraviolet irradiation by A. Fujishima and K. Honda [3]. Nowadays advances in photocatalysis science and technology, as well as in industrial applications, point out the promising potential of photocatalysis for reducing the levels of greenhouse gases in the atmosphere, for green chemistry, degrading water pollutants, etc. Regarding students with majors in physics or chemistry, the main interest of photocatalysis lies in the understanding of the process and the ability to draw links between these fields: photo-and electrochemistry, material and surface sciences, solid physics and so on. Photocatalysis is actually an interdisciplinary domain.

Definition of some terms

So as to describe the photocatalytic process, we will use in this article some concepts that belong usually to the vocabulary of chemistry. We provide here simple definitions of these concepts:

• activation energy: it is the minimum energy needed to start a chemical reaction which transforms reactants to products. Therefore the activation energy is a potential barrier separating two energetic states formed by the reactants (starting state) and the products (final state).

• adsorption, physisorption, chemisorption and desorption: we would like to emphasize the distinction between the notions of adsorption of atoms or molecules on a surface, which may include physisorption (weak bonding, typically Van der Walls forces) and chemisorption (covalent bonding between the adsorbed molecules and the surface). The desorption of atoms or molecules from a surface is the release of these species from the surface (the previous bondings are broken). We wish to highlight the difference between the adsorption of molecules on a surface and the light absorption (photoabsorption) by the semiconductor material to potentially create electron/hole pairs. Several models can be used to describe the adsorption phenomena, like the Langmuir isotherm. These models basically give a relationship between the amount of species in a gas or liquid and the amount of these species adsorbed on a surface at a given temperature.

• reduction-oxidation (redox reactions): redox reactions are a family of chemical reactions involving an exchange of charges (electrons) between atoms or molecules.

If an exchange of charges takes place, it means that a potential difference exists between the various chemical species. Every chemical species has its own potential called the redox potential (in volt). It provides a measure of the ability of a species to give up (and thus be oxidized) or to acquire an electron (and thus be reduced). The redox potential is an intrinsic parameter of a given species. So as to be compared and forecast which chemical species will give or accept electrons from another species, the redox potential are organized on a scale. The origin of the scale is arbitrarily attributed to the hydrogen species (H 2 /H + ): the so-called standard hydrogen electrode (SHE) whose the redox potential is thus equal to zero.

• vacuum level: this is a notion of solid state physics. the vacuum level is the energy of an electron in a perfect vacuum meaning infinitely far away from any materials. This level is used as an absolute origin for the energy (or potential) of electrons.

• chemical or reaction kinetics: when a chemical reaction occurs, reactants "A" are transformed into products "B ". Such a transformation takes time. Reaction kinetics is the study of the rate "r " of the chemical reactions. r depends on the concentration of A and B and on k the reaction rate constant:

r = k[A] x [B] y (1)
x and y are called the partial orders of the reaction (and are integers). For example, if the reaction is of first order, x +y=1. It means that the rate depends only of the concentration of one reactant:

r = - d[A] dt = k[A] (2)
We will use this case to describe the photocatalytic degradation of methylene blue.

Definition of photocatalysis

Photocatalysis comes from two words: light and catalysis. Various definitions of "photocatalysis" have been suggested. One the most commonly used definitions refers to a chemical reaction induced by the absorption of light (photo-absorption) by a solid material (generally a semiconductor). The reaction occurs at the surface of the semiconductor which remains unchanged during and after the reaction. This semiconductor is called a photocatalyst. From a thermodynamically point of view, the catalysis and the photocatalysis are two different processes. A "simple" catalyst will enhance the reaction rate of an already thermodynamically allowed chemical reaction by reducing the activation energy. On the contrary, thanks to the energy brought by light, photocatalysis can promote reactions unfavourable on a thermodynamic point of view. This is the example of the photocatalytic splitting of water into hydrogen and oxygen. From this point of view catalysis and photocatalysis concepts are basically different [4,5].

Brief theoretical description

Overall steps

Photocatalysis can occur in liquid or gas phase. The whole photocatalysis process can be divided into five independent steps that are common to the heterogeneous catalysis as clearly described by J.M. Hermann [6]:

(i) Diffusion of the reactants in the fluid phase to the surface of the photocatalyst.

(ii) Adsorption of reactants on the surface of the photocatalyst: classical models like Freundlich or Langmuir isotherms can describe this step.

(iii) Reaction in the adsorbed phase. It is often basically a charge transfer between adsorbed reactants and the semiconductor: a so-called redox reaction. Light is absorbed by the semiconductor: electrons are "available" in the conduction band for the redox reaction.

(iv) Desorption of the products of the redox reaction (i.e release of the products from the surface of the photocatalyst).

(v) Draining of the products from the region close to the semiconductor to free the access to its surface for the remaining reactants.

The third step is the heart of the photocatalytic process. This is when the transformation of chemical species like degradation of pollutants takes place.

Interface between the semiconductors and the fluid phase

To explain and describe the redox reaction occurring at this step, we need to bring together the redox potential scale used to know the potential of the chemical reactants in the liquid or gas phase and the energy levels structure of the semiconductor. In this way, we must link electrochemistry and solid physics. This is done by analysing the properties of the liquid(gas)/solid interface. Such an interface can be handle in the same way as a p-n junction (chapter 4, ref. [START_REF] Kaneko | Photocatalysis: Science and Technology springer[END_REF]) with an energetic description of the electrolyte following the model developed by H. Gerischer [START_REF] Gerischer | [END_REF]9]. Therefore the relationship between the two energy scales is the following equation (eq.3) [10,11,12]:

E(eV ) = -qE(V ) -Φ (3)
E is the value of the energy relative to the vacuum level, E is the redox potential referenced to the SHE, q is the elementary charge and Φ is the absolute electrode potential of the redox couple (H 2 /H + ) on which is based the SHE. It means that Φ is the value of the SHE potential compared to the vacuum level. Its value is experimentally determined and is equal to about 4.5 eV. Thanks to this common scale between redox couples and semiconductors energy levels it is possible to know if a redox reaction is favourable between a given semiconductors and reactants.

Langmuir-Hinshelwood (LH) model

The LH model is often used to quantify the photocatalytic process even if there are some discussions over its relevance and the use of it according to a given photocatalytic process. It is not the purpose of this article to present these discussions but we recommend the reader to read the paper of B. Othani [4]. During the photocatalytic process there is a transformation of the reactants adsorbed onto the surface of the semiconductor, the concentrations of these chemical species vary, hence these processes are kinetic reactions. The LH model takes into account the phenomenon relative to the adsorption on the semiconductor surface and the kinetic reactions [13]. The main equation of the LH model is eq.4:

1 v LH = 1 k + 1 kK × 1 C i (4)
where v LH is the rate of the reaction (the photocatalytic rate), k is the rate constant of the reaction of the adsorbed reactants on the semiconductors surface with e -or h + created by photoabsorption, K is the adsorption equilibrium constant (Langmuir isotherms) and C i is the initial concentration of reactants before the beginning of the photocatalysis. Then it is easy to check the validity of the LH model to describe a photocatalytic process by drawing 1 v LH versus 1 C i and obtaining a straight line.

Method and implementation

Equipment

To provide evidences of the photocatalytic effect in the framework of our practical course, we use methylene blue (MB) (CAS number 7220-79-3) as the organic molecules to degrade. MB is non-toxic hence it is suitable for an educational lab work. Methylene blue absorbs light in the visible range, therefore the measurements of its concentration can easily be determined using the Beer-Lambert law (eq.5):

A(λ) = log I(λ) I 0 (λ) = -ǫl[BM] (5)
A is the absorbance at a given wavelength λ, I 0 (λ) represents the incident light intensity, I(λ) the light intensity transmitted trough the MB solution, ǫ is the molar attenuation coefficient of MB (the coefficient of light absorption by a liquid solution of MB), l the path length of the beam of light through the material sample and finally [MB] the concentration of methylene blue in the solution. To measure the light spectrum and intensity, we use an educational version of the USB-650 Red-Tide spectrophotometer from Ocean Optics [START_REF]Ocean Optics I[END_REF]. Titanium dioxide (T iO 2 , CAS number 13463-67-7) is used as the semiconductor acting as the photocatalyst. We used T iO 2 nanopowder with an average size of 21 nm because according to ref [START_REF] Xu | [END_REF] the photocatalytic degradation increases especially for particles with sizes less than 30 nm. T iO 2 has a bandgap around 3-3.2 eV according to its phase (anatase or rutile). So the suitable wavelength light for the excitation of T iO 2 is in the UV range of the electromagnetic spectrum. T iO 2 is one of the most commonly used photocatalyst because of its chemical stability, non-toxicity, price and even if its bandgap lies in the UV part of the visible spectra which count for only 5% of the sunlight. The UV excitation light is a commercial UV energy saving lamp with a power of 20 W. The spectrum of the lamp is shown on fig. 1 b). MB solutions: Students prepare four MB solutions of different initial concentrations [MB] 0 in the range of 5 × 10 -7 to 10 -5 mol.l -1 with water as the solvent (fig. 1 a)). This range is determined according to the sensing capability of the spectrophotometer and on the other hand the concentration validity domain of the Beer-Lambert law. Then they set up four crystallisers with 10 mg of T iO 2 nanopowder in each and 50 ml of each initial concentration. The powder should be well mixed in water in order to avoid the aggregation of particles which can entail a decrease of the specific surface of the T i0 2 photocatalyst. A set of four control experiments (same experimental parameters but without T iO 2 particles) should also be prepared to ascertain the photocatalytic effect and disambiguate with other phenomena such as the photolysis of MB molecules. The photolysis is the degradation of the molecules directly by the sole effect of light. The Fig. 1 b) displays the spectrum of water as the reference for the measurement of the MB concentration via the absorbance. Then Fig. 1 c) presents the absorbance spectra of the four initial MB solutions with chosen concentrations of 5 × 10 -7 , 10 -6 , 5 × 10 -6 and 10 -5 mol.l -1 . The main absorption peak of MB is at 665 nm. Students should use this wavelength throughout the practical work to conduct the monitoring of the evolution of the absorbance versus time of irradiation to maximise the accuracy of the measures.

measurements process:

At an irradiation time t=0, the students put the four crystallisers under UV light and they follow the evolution of the concentration of MB versus the irradiation time. They choose a time interval t i (10 min for instance) and every t i they sample a small volume (2-3 ml) of the MB solutions ideally with a syringe. They performe the absorbance measurements on these volumes so as to follow the evolution of the MB concentrations versus time of irradiation. To increase the accuracy of the absorbance values, the sampled volumes of MB solutions should be centrifuged in order to remove T iO 2 particles from the solutions which might disrupt the spectroscopic measurements.

Results and discussion

T iO 2 characterisation, quantum size effect

The photocatalyst plays a key role in the photocatalytic process since it provides charges needed for the redox reactions by the absorption of light. Therefore the yield of the whole photocatalytic process is linked to the bandgap of the semiconductor. That is why we encourage the students to try to characterise the used semiconductor. X-ray diffraction (XRD) can be easily performed on the T iO 2 nanopowder. Fig. 2 shows the XRD diagram of the nanopowder recorded on a Philips PANanalytical XPert XRD system with a Cu electrode. The X-ray source is non monochromatic. The peaks identification shows that the powder is a mix of anatase and rutile which are two well-known forms of titanium dioxide. From the quantitative analysis of the XRD spectrum, this allows us to determine that there are 83% of anatase and 17% of rutile in the powder. Then the size of the nanoparticles of T iO 2 can be estimated from the XRD diagram by using the Scherrer equation (eq. 6). It links the size of the particles to the width of the XRD peaks [16]: τ is the mean size of a grain size (to be precise this the size of the crystalline domains which can be smaller or equal to a grain size), k is a dimensionless factor with a value around 0.9, λ is the X-ray wavelength (in our case the main wavelength is 1.5406 Å), H is the line broadening at half the maximum intensity (FWHM), s is the instrumental line broadening (evaluated to 0.03 • for our apparatus) and θ is the Bragg angle. All angles should be in radians.

(°)

τ = kλ √ H 2 -s 2 cos(θ) (6)
Using the XRD peak indexed A(101) on Fig. 2 at a position of 25.24 • , the estimated average size of the T iO 2 nanoparticles is found to be 20.2 nm. The supplier provides a value of 21 nm, therefore this is very pertinent (product ref 718467 Aldrich [START_REF] Aldrich | Online[END_REF]). Because the particles of T iO 2 are nanometer-sized, students with a background in nanoscience may think about discussing a possible quantum size effect on the bandgap of these nanoparticles. Changing the bandgap energy will change the absorbed light and impact of the photocatalytic degradation rate through a possible variation of a number of electron/hole pairs created. Quantum size effects generally occur for semiconductor particles of a size in the range of 10 to 100 Å due to quantum confinement. It might entail an energy shift ∆E of the bandgap which can be calculated with the following approximated equation (eq.7) [START_REF] Linsebigler | [END_REF]:

∆E = 2 π 2 2r 2 1 m * e + 1 m * h - 1.786q 2 ǫr -0.248 q 4 2ǫ 2 h 2 m * e + m * h m * e m * h (7)
r is the nanoparticle radius, q is the elementary charge of the electron, m * e , m * h are the effective masses of electrons and holes, ǫ is the dielectric constant and h the Planck's constant. This equation is rather complex but the purpose here is simply to get a relationship between the small size of the particles and a possible energetic effect on the bandgap without going into solid physics details. Using the values of the parameters for T iO 2 listed in table 1, ∆E is evaluated to 0.02 eV. ∆E is insignificant in our context since the corresponding change in absorbed light wavelength will be around 2 nm.

MB concentration versus time of UV irradiation

The evolution of the MB concentration for the four prepared solutions is presented in fig. 3 on a logarithmic scale. The accuracy of the concentrations measurements is subdued at low concentrations because of the limitation of the sensitivity of our UV-VIS spectrophotometer for very low absorbances. From the linear relationship between ln([MB]) and t observed on fig. 3, the reaction rate of MB degradation is of apparent first order. On this point readers should refer to the comment made by Herrman in [13], section 2.5 regarding the apparent contradiction on the increase of the reaction rate with the decrease of the initial concentration. Avoiding the confusion between the reaction rate and the conversion rate solves this contradiction. The first one depends on the initial concentration wherea the second one does not. Using a first order reaction, the integration of the reaction rate gives (eq. 8):

-d[MB] dt = k r [MB] ⇒ ln ([MB]) = ln ([MB] 0 ) -k r t (8)
By fitting the experimental data of fig. 3, students can extract the values of the kinetic constants k r for the four experiments. The fitted values are given in table 2.

LH model

Moreover the photocatalytic degradation rate v LH is estimated from k r and the LH model can be verified by plotting 1/v LH versus 1/[MB] 0 (fig. 4). The linear relationship between 1/v LH and 1/[MB] 0 is fully in agreement with eq.4. The correlation factor of the linear fitting is equal to 0.96. It is a bit low but the impact of the last experimental point at the lowest MB concentration is significant. As discussed above, it comes from the limitation of our UV-VIS spectrophotometer in the low range concentration of MB solutions. The value of K obtained by the linear fitting is 5.9 × 10 4 l.mol -1 and it is typical of the degradation of organic molecules soluble in water.

MB degradation pathway

The photocatalytic degradation of MB does not result from a direct redox reaction between the T iO 2 nanoparticles and the MB molecules. The photocatalytic degradation pathway of MB in water has been proposed by Houas & al [20]. The electrons generated in the T iO 2 by the UV light either recombine with the holes of the valence band or react with the adsorbed oxygen on T iO 2 surface. In the latter case, oxygen ions are created and react in turn with the adsorbed water molecules. Hydroxyl radicals OH • and hydroxyl groups are formed. Eventually the MB molecules are degraded by the reactions with the radicals. The establishment of the whole degradation pathway by the students is not the goal of this practical work. However students can comment on the feasibility of the degradation of MB by T iO 2 by drawing the energetic diagram with the different levels positions of anatase, rutile and MB by using eq.3 (fig. 5).

From this diagram it can be concluded that the direct charge transfers between the different phases of T iO 2 and MB molecules are unlikely. Therefore the photocatalytic degradation of MB by T iO 2 will need intermediate steps involving OH • radicals to be processed.

Conclusion

In this paper we described a practical work consisting in the photodegradation of MB by T iO 2 nanoparticles. This lab work only requires a simple experimental set-up which allows us to provide evidences of the significance of the photocatalysis. However, this phenomenon is rather complex and requires several notions from chemistry and physics. A full and informational explanation of the phenomenon must be made, and the report must include the following : diffusion, adsorption, redox reactions, excitation of semiconductors by light absorption and other aspects of the photocatalysis process. We have thus discussed the properties of the photocatalyst in terms of materials science using XRD diffraction and considering a potential quantum size effect on the T iO 2 bandgap because of the size of the nanoparticles. Then we checked the validity of the main model developed to describe the photocatalysis effects, the Langmuir-Hinshelwood model and eventually we commented on the photodegradation pathway of MB by analysing the respective energetic levels positions of the photocatalyst and the organic molecules. This analyse indicate that a direct charge transfer between T iO 2 and MB molecules is unlikely so the photodegradation pathway may use intermediate steps like formation of hydroxyl radicals. It is a lab work that allows students to draw links between several different science domains that have been historically explored at different places and times. To go further in the photocatalytic processes, students can look at the different means developed to enhance the photocatalysis rate such as the improvements of the semiconductor photoelectrode. As an example involving nanoscience, we can cite the socalled plasmonic photocatalysis where metal nanoparticles added to the semiconductors improved the photocatalytic performance through localised surface plasmon resonance

Figure 1 .

 1 Figure 1. (colour online) a) Scheme of the experimental set-up. b) UV-VIS spectrum of the light source and the solvent (water). c) Absorbance spectra of the four initial MB concentrations.

Figure 2 .

 2 Figure 2. XRD diagram of the T iO 2 nanopowder used as a photocatalyst.

Figure 3 .

 3 Figure 3. Evolution of the methylene blue concentration [MB] versus the irradiation time for the four initial solutions.

+06B

  = -9,59818e+06 +/-2,14567e+07 A = 7,60156e+01 +/-1,90962e+01

Figure 4 .

 4 Figure 4. Verification of the LH model.

- 9 0Figure 5 .

 95 Figure 5. Energy diagram with the positions of the MB redox potential, CB and VB of anatase and rutile [21].

Table 1 .

 1 Values of parameters used to predict the shift of the energy bandgap due to quantum size effect in the T iO 2 nanoparticles (anatase)

	f or T iO 2 Values
	r	10 nm
	m * e m0	0.095 [19]
	m * h m0	0.200 [19]
	ǫ ǫ0	90

Table 2 .

 2 Results coming from the fits of fig.3and calculated values for the LH model[M B] 0 mol.l -1 k r (eV)

			1
			vLH
	5 × 10 -7 10 -6 5 × 10 -6 10 -5	0.0199 0.0319 0.0157 0.0094	8.69 × 10 7 3.13 × 10 7 1.18 × 10 7 1.06 × 10 7


Martin Dichgans

Joanna Wardlaw
email: joanna.wardlaw@ed.ac.uk

Eric Smith

Vera P Zietemann

Sudha Seshadri

Geert Perminder Sachdev

Jan Biessels

Franz Fazekas

Oscar Benavente

Leonardo Pantoni

Metacohorts Consortium

A Alonso

R Al-

Shahi Salman

F Arba

H-J Bae

C Brayne

H Chabriat

C Chen

C Cordonnier

C Decarli

M Duering

L Feng

S Greenberg

M Ihara

E Jouvent

R Kalaria

S-Y Kim

J-S Lim

R I Lindley

J Linn

R Malik

B Mazoyer

V Mok

B Norrving

C Ritchie

R Sacco

R Schmidt

L Sposato

N Sprigg

B Stephan

R Swartz

M Van Boxtel

J Van Der Grond

R Van Oos- Tenbrugge

M Vernooij

D Werring

W Whiteley

Bath

METACOHORTS for the study of vascular disease and its contribution to cognitive decline and neurodegeneration: An initiative of the Joint Programme for Neurodegenerative Disease Research

Keywords: Dementia, Cerebrovascular disease, Small vessel disease, Neurodegeneration, Cohorts, Survey

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Worldwide, nearly 36 million people are estimated to be living with dementia. This is expected to triple by 2050. Cerebrovascular disease causes up to 45% of all dementias alone or in conjunction with Alzheimer's disease (AD) [START_REF] Hachinski | Stroke and potentially preventable dementias proclamation: updated World Stroke Day Proclamation[END_REF][START_REF] O'brien | Vascular dementia[END_REF]. Despite vascular risk factor reduction being an achievable target for public health intervention in many countries, and some recent evidence of success in preventing dementia [START_REF] Ngandu | A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial[END_REF], knowledge about vascular contributions to dementia remains modest.

Many studies, from the early 1990s onward [START_REF] Tatemichi | Dementia in stroke survivors in the Stroke Data Bank cohort. Prevalence, incidence, risk factors, and computed tomographic findings[END_REF], have demonstrated that cognitive impairment and dementia are both common and under-recognized after stroke [START_REF] Pendlebury | Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: a systematic review and meta-analysis[END_REF]. The concept of "vascular cognitive impairment" was introduced in 1994 [START_REF] Hachinski | Vascular dementia: a radical redefinition[END_REF], covering a spectrum of cognitive impairment after stroke to cognitive impairment in association with otherwise asymptomatic cerebrovascular disease. The most common vascular contributor to dementia is cerebral small vessel disease (SVD) [START_REF] Pantoni | Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges[END_REF], a condition that affects perforating vessels, thence white and gray matter, and accelerates neurodegenerative processes. Vascular dementia reflects the global effects of vascular disease on the brain, not just of multiple individual infarcts. [START_REF] Baezner | Association of gait and balance disorders with age-related white matter changes: the LADIS study[END_REF][START_REF] Ahmad | Are white matter abnormalities associated with "unexplained dizziness[END_REF] It results in stroke, cognitive decline and dementia, plus neuropsychiatric symptoms, gait, balance [START_REF] Baezner | Association of gait and balance disorders with age-related white matter changes: the LADIS study[END_REF][START_REF] Ahmad | Are white matter abnormalities associated with "unexplained dizziness[END_REF], and continence problems [START_REF] Hachinski | Little strokes, big trouble[END_REF], necessitating a larger framework for targeted, comprehensive studies [START_REF] Hachinski | National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards[END_REF].

In 2006, the National Institute for Neurological Disorders and Stroke and the Canadian Stroke Network convened a multidisciplinary research group to recommend standards for the study of vascular cognitive impairment [START_REF] Hachinski | National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards[END_REF]. In 2013 the Alzheimer's Association convened an expert working group, which summarized the state of vascular cognitive impairment science and identified areas where new knowledge is needed [START_REF] Snyder | Vascular contributions to cognitive impairment and dementia including Alzheimer's disease[END_REF]. However, despite strong and unanimous evidence for the major burden of vascular cognitive impairment on both patients and their caregivers [START_REF] Lodder | Poststroke cognition and the fight against the hard problem: vascular neurologists, enter the arena![END_REF], most dementia research largely overlooks vascular disease as a cause. In part, this reflects that clinicians and researchers working on dementia, stroke, physical, or psychiatric manifestations are still too often segregated. "Stroke" and "dementia" (both syndromes, not pathological diagnoses) present to different clinical specialists (Fig. 1); stroke specialists underrecognize the cognitive impact of stroke, whereas dementia specialists under-recognize vascular inputs to dementia pathophysiology. This separation also affects research and funding initiatives, for example, vascular disease was rarely mentioned in a report on 169 European studies considered relevant to neurodegenerative disease research [START_REF] Jpnd Action | Longitudinal cohort studies in neurodegeneration[END_REF]. Better diagnostic criteria for the different cognitive profiles of vascular and AD are also needed [START_REF] Sachdev | Diagnostic criteria for vascular cognitive disorders: a VASCOG statement[END_REF].

The recognition of an important role for cerebrovascular disease in dementia opens major therapeutic opportunities. Vascular risk factor reduction and stroke prevention may already be reducing dementia incidence [START_REF] Ngandu | A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial[END_REF][START_REF] Norton | Potential for primary prevention of Alzheimer's disease: an analysis of populationbased data[END_REF]. Increased government and public concern about dementia, as well as better grouping of codes for different cerebrovascular disease presentations in the revised International Classification of Disease (ICD) codes version 11 (ICD-11, release 2018, http://www.who.int/classifications/icd/ revision/en/), will help advance understanding of cerebrovascular disease and its impact on neurodegeneration.

Here, we report on an initiative funded by the JPND to promote efficient use of available data in which we identified information, relevant to vascular disease, available in different types of studies that could provide large, statistically robust, generalizable data sets, and create platforms for future mechanistic, epidemiological research, or clinical trials [START_REF]Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies[END_REF]. We used the exemplar survey data to identify major gaps in knowledge, methodological issues and suggest priority actions to advance the field.

Method

We convened a group of experts in stroke and cerebrovascular disease, AD, epidemiology, psychology, neuroimaging, and clinical trials (Appendix). We designed a survey aiming to capture information about data available in cohorts relevant to vascular contributions to neurodegeneration. A "relevant cohort" could comprise patients with stroke/transient ischaemic attack (TIA), or suspected cognitive impairment or dementia, or healthy subjects, from a hospital or geographical population, and would have information on vascular disease and/or risk factors, and one or more of the following: cognitive data, long-term outcomes (including physical function and mood), neuroimaging including biomarkers of vascular disease and/or neurodegeneration, physiological measures (e.g., blood pressure, vascular stiffness), or biomarker samples with a relevant vascular link. The study could be completed or ongoing, cross-sectional or longitudinal, observational, or a clinical trial. The minimum sample for inclusion was 50 participants, with no age or geographical limits.

The survey (Supplementary Material), designed for online delivery, sought information on whether participants were healthy or recruited from a stroke or memory or other relevant clinic or participated in a clinical trial. Data were collected on demographics, medical history, risk factors, cognition, brain imaging, physiological measures, comorbidities at inclusion, duration and frequency of follow-up, follow-up assessments, outcome events, whether the study was completed or ongoing, availability of bio-or genetic samples for further analysis, interest of investigators in data sharing, and whether approvals for sharing were already in place.

The survey was piloted by three members of the expert group (JMW, MD, and ES), before being distributed widely. It ran from November 15, 2014 until August 31, 2015 with updates for ongoing studies to November 2015. We initially invited participation from investigators of studies in Europe through the JPND Vascular Disease group, relevant studies listed in the JPND report [START_REF] Jpnd Action | Longitudinal cohort studies in neurodegeneration[END_REF], networks, and studies known to them, for example, Dementia Platform UK, the German Center for Neurodegenerative Diseases (DZNE), and "Constances" in France; however, investigators based in North America, Australasia, and the Asia Pacific Region also expressed interest and were included. We recognized that the survey was unlikely to capture all studies but aimed to capture a broad sample, particularly from the vascular disease perspective (including clinical trials), as these are underrepresented in other dementia initiatives [START_REF] Jpnd Action | Longitudinal cohort studies in neurodegeneration[END_REF][START_REF] Sachdev | COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups[END_REF][START_REF] Lees | Cognitive and mood assessment in stroke research: focused review of contemporary studies[END_REF][START_REF] Bath | Use of ordinal outcomes in vascular prevention trials: Comparison with binary outcomes in published trials[END_REF].

We performed descriptive statistics and meta-analyses (random effects methods) [START_REF] Neyeloff | Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis[END_REF]. For detailed analyses of cognition in relation to stroke, we used studies that collected data on stroke and cognition from subjects without prestroke dementia in community-based studies or in subjects with stroke (hospital-based post-stroke cognitive impairment cohorts). Responses were received from 68 investigators (some provided data on several studies). Samples were updated to include ongoing recruitment to December 01, 2015. Five incomplete responses were removed from further analysis (for full details, see Supplementary Material).

Fifty-five experts (Appendix) discussed the data to identify knowledge gaps requiring new data, implications of ICD-11 disease codes (http://www.who.int/classifications/icd/revision/ en/), agree early targets for shared data analysis, and plan future analyses of existing data and new research initiatives.

Results

The survey collected data on a total of 96 studies, including 167,064 participants, or 667,064 with UK Biobank [START_REF]Virtual International Stroke Trials Archive (VISTA)-Cognition[END_REF] (186,000 and 686,000, respectively including target samples in ongoing studies; Table 1; Supplementary Table 1). The sample size ranged from 41 to 29,852 (excluding UK Biobank). The mean age was 72, range 15 to 106 years. There were 84 observational studies (11 cross sectional and 73 longitudinal) and 12 randomized clinical trials. The main types of studies overlapped (some recruited from several sources by various methods, Table 2) but, in general, most studies could be attributed to the following categories: community-based cohorts including population studies (32 studies, of which 28 were suitable for analyzing incident post-stroke dementia, sample size .600,000 subjects), hospital-based stroke clinics (i.e., stroke and TIA services, 26 studies, 12 suitable for analyzing incident post-stroke dementia, w4700 subjects), hospital-based memory clinics (15 studies, w20,000 subjects), and randomized clinical trials (12 trials, w20,000 subjects); 38 studies were ongoing (recruiting or long-term follow-up, Table 2). Some studies recruiting from mixed sources (Table 2, Supplementary Table 1) were not included in detailed analysis in the following section (or in Table 1), yet provide other relevant information (details in Supplementary Material). The longest duration of follow-up so far was more than 5 years (Fig. 2). Sixty-seven studies were based in Europe, 17 in North America, and 12 in the Asia Pacific Region (excluding 2 incomplete entries).

Most cohorts (w86/96) did neither appear in the JPND report of 169 cohort studies [START_REF] Jpnd Action | Longitudinal cohort studies in neurodegeneration[END_REF] nor overlap by more than 20% with other recent initiatives, for example, Cohort Studies of Memory in an International Consortium (COSMIC) [START_REF] Sachdev | COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups[END_REF], Virtual International Stroke Trials Archive (VISTA) Cognition [START_REF]Virtual International Stroke Trials Archive (VISTA)-Cognition[END_REF], or the Consortium of Studies of Post-Stroke Cognitive Decline and Dementia (STROKOG; [START_REF]Consortium of Studies of Post-Stroke Cognitive Decline and Dementia. Consortium of Studies of Post-Stroke Cognitive Decline and Dementia (STROKOG)[END_REF]). This lack of overlap indicates a gap in information about vascular disease in neurodegeneration when viewed from "traditional" neurodegenerative perspectives and shows that there is a large amount of data available for sharing and meta-analyses if it could be brought together efficiently and effectively.

. Community cohorts

Community-based (including population-based) cohorts are the best way to determine the relative contribution of vascular and other pathologies to the development of dementia and cognitive aging. They permit assessment of risk factor levels before the development of cognitive impairment or dementia, and hence, risk factor measurement is less likely to be affected by disease or its treatment. These cohorts often have repeated measures, starting in midlife, so, the impact of cumulative exposures, including during specific ages, can be explored. In contrast, clinical studies usually recruit from one extreme of the population distribution of vascular susceptibility; these studies may generate hypotheses that can be tested in population-based cohorts.

We gathered data from a representative sample of 32 community-based cohorts (Supplementary Table 1, Supplementary Fig. 1; 28 suitable for analysis) that defined the extent of vascular compromise, and structural brain injury in each person using serial brain imaging, and also measured global and domain-specific cognitive performance, mood, and physical function. Most studies prospectively followed their participants using health record linkage, questionnaires, or repeated examinations, to detect progression to cognitive impairment, stroke, or dementia. Most studies include biobanking, and a few have prospective postmortem brain banks. The community-based studies were either geographically population-based or recruited through advertisement and other strategies.

Most studies were conducted in the past three decades in North America and Europe, studied older participants (mean age 70 years), and used brain magnetic resonance imaging (MRI). Sample size ranged from around 100 to 500,000 participants (median: 1400; Q1-Q3: 400-9500), with imaging planned for w150,000. However, there are limitations. The imaging protocols, hence sensitivity to vascular pathology, varied, particularly in the older studies. Vascular risk factor assessment covered common risk factors, but interim TIA, clinical stroke, and stroke subtype were ascertained with varying degrees of rigor ranging from surveillance for incident events with direct participant examination and consensus review by study investigators, through medical records linkage, to self-reported events. Data on lipids, inflammatory markers, and renal function were missing from about half the studies. There was considerable variation in methods and timing used to assess vascular and cognitive outcomes. Data from a wider age span starting in youth to mid adulthood, diverse race, ethnic, and geographic origins, but using common protocols for cognition, physical function, minimum standard physiological measures, and MRI, are needed.

Post-stroke cognitive impairment cohorts

In hospital-based series, about 20% of stroke patients have dementia after stroke, and the cumulative incidence of dementia after the first year is about 3% pa [START_REF] Pendlebury | Stroke-related dementia: rates, risk factors and implications for future research[END_REF]. The survey identified 26 hospital-based cohorts recruiting from stroke/TIA 6 other services (Table 2). Twelve had data suitable for analysis comprising studies that recruited patients presenting to hospital with ischemic stroke or TIA, followed longitudinally with cognitive and other measures. These studies collectively included .4134 subjects currently (planned .4700), and nearly 90% have structural neuroimaging. Most assessed educational attainment (although few assessed premorbid intelligence quotient), most used the Montreal Cognitive Assessment (MoCA) and all collected details of vascular disease and vascular risk factors (Supplementary Fig. 2). Of note, several cohorts include amyloid-positron emission tomography imaging, thus enabling assessment of the interactions between vascular and amyloid pathology in cognitive decline.

These data, if combined, would help overcome many gaps in knowledge remaining from previous post-stroke cognitive impairment studies [START_REF] Pendlebury | Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: a systematic review and meta-analysis[END_REF][START_REF] Makin | Cognitive impairment after lacunar stroke: systematic review and meta-analysis of incidence, prevalence and comparison with other stroke sub-types[END_REF]: poor generalizability due to small sample and inclusion of high-functioning ischemic, nondysphasic, stroke patients, with an informant; or various entry restrictions, for example, inclusion of TIAs only, or first-only strokes, rather than any stroke. The variety of cognitive, physical, and physiological assessment tools and lack of prestroke cognition or contemporaneous mood data restrict comparisons. There is little information on concomitant AD pathology, or on biomarkers of vascular dementia, or pathology specimens to determine true proportions of vascular disease, and imaging acquisitions vary. As with population studies, agreed standards for future studies would increase research efficiency.

Memory clinics

Patients attending a memory clinic represent a highly relevant population to study vascular contributions to cognitive decline and dementia. Most patients attending memory clinics have vascular lesions co-occurring with other pathologies, in particular, Alzheimer-type processes. However, there is limited evidence from longitudinal studies and randomized controlled trials (RCTs) in memory clinic-based cohorts to determine how much the vascular lesions contribute to cognitive profiles, predict prognosis, or should influence treatment. Extrapolation of observations from, for example, population-based studies, may not be valid because disease predictive factors in a relatively healthy population may not necessarily predict disease progression among individuals affected by the disease, or vice versa.

We identified 15 cohorts that included memory clinic patients (Table 2, Supplementary Fig. 3), some providing data only on memory [START_REF] Aalten | The Dutch Parelsnoer Institute-Neurodegenerative diseases; methods, design and baseline results[END_REF], whereas others included other clinical presentations [START_REF] Inzitari | Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LA-DIS (leukoaraiosis and disability) study cohort[END_REF]. Cohort sizes were generally modest, with 8 of 15 cohorts including 200 patients, although baseline data are available on 19,144 patients of mean age of 73 years. All studies collected data on demographics, risk factors for vascular disease including education. Cognitive test results and neuroimaging (mostly MRI or computed tomography) were available from most patients in all cohorts. However, diagnostic criteria for mild cognitive impairment (MCI) and dementia, and its subtypes, varied across cohorts. Moreover, although most of the studies collected longitudinal data, both timing and content of follow-up varied substantially. Unfortunately, substantial gaps in knowledge remain, such as the extent to which different pathologies may have differential prognostic impact in different stages of the dementia process. For example, larger studies at different disease stages across multiple clinics would help to determine if white matter hyperintensity (WMH) burden is indeed a stronger predictor of progressive brain atrophy in people with MCI and early AD than in later stages [START_REF] Barnes | Vascular and Alzheimer's disease markers independently predict brain atrophy rate in Alzheimer's Disease Neuroimaging Initiative controls[END_REF][START_REF] Kandiah | Association between white matter hyperintensity and medial temporal atrophy at various stages of Alzheimer's disease[END_REF]. Further studies are needed to determine how much cooccurring pathologies affect risk-benefit ratios of treatments that are typically used to reduce vascular risk, such as antithrombotic drugs. For example, randomized trials of aspirin in patients with AD observed rates of intracerebral hemorrhage that were much higher than those in people without AD [START_REF] Thoonsen | Aspirin in Alzheimer's disease: increased risk of intracerebral hemorrhage: cause for concern?[END_REF].

Physical function

Gait and balance disorders are common in elderly people, increasing rapidly from around 15% at the age of 60 years to .50% at age of 80 years [START_REF] Snijders | Neurological gait disorders in elderly people: clinical approach and classification[END_REF][START_REF] Verghese | Epidemiology of gait disorders in community-residing older adults[END_REF][START_REF] Mahlknecht | Prevalence and burden of gait disorders in elderly men and women aged 60-97 years: a population-based study[END_REF]. They are often multifactorial and increase falls, institutionalization, and mortality [START_REF] Snijders | Neurological gait disorders in elderly people: clinical approach and classification[END_REF][START_REF] Verghese | Epidemiology of gait disorders in community-residing older adults[END_REF][START_REF] Callisaya | Progression of white matter hyperintensities of presumed vascular origin increases the risk of falls in older people[END_REF]. For example, Parkinson's disease, impairs gait, and balance [START_REF] Bennett | Prevalence of parkinsonian signs and associated mortality in a community population of older people[END_REF], but vascular cerebral disorders also disturb gait and may contribute to Parkinsonian symptoms [START_REF] Buchman | Cerebrovascular disease pathology and parkinsonian signs in old age[END_REF][START_REF] De Laat | Cerebral white matter lesions and lacunar infarcts contribute to the presence of mild parkinsonian signs[END_REF], particularly in SVD where gait is the second commonest symptom after cognitive disturbance [START_REF] Okroglic | Clinical symptoms and risk factors in cerebral microangiopathy patients[END_REF][START_REF] Pantoni | The significance of cerebral white matter abnormalities 100 years after Binswanger's report[END_REF]. The Leukoaraiosis and Disability in the Elderly Study (LADIS) showed that gait and balance were correlated with WMH severity [START_REF] Baezner | Association of gait and balance disorders with age-related white matter changes: the LADIS study[END_REF]. As gait represents a complex higher order form of motor functioning, impaired gait and cognition are closely intertwined [START_REF] Snijders | Neurological gait disorders in elderly people: clinical approach and classification[END_REF].

However, gait and balance were rarely assessed in population-based or hospital-based post-stroke or memory studies. The survey found very limited information, but such details were poorly captured in the questionnaire. For example, none of five studies from general geriatric clinics mentioned recording gait, walking, or movement. Under "other," no study mentioned these words either. Seven other studies mentioned "gait" (Supplementary Table 1, ABC1936, ABC1921, CASPER, ONDRI, PURE-MIND, RUN DMC, STRIDE) although we recognize that some studies that did not specifically mention gait do collect such data. This suggests that problems of gait and balance are under-recognized compared with other features of vascular neurodegeneration and hence are poorly assessed in vascular-focused clinics for older people, despite representing a major problem for older people, their families, hospitals, and social services.

Clinical trials

Many acute stroke and stroke prevention RCTs have not collected cognitive data because of the following: (1) they focused on the physical consequences of stroke; (2) cognitive testing was considered too laborious and not applicable to participants whose vision, speech, or hand function were impaired; or (3) there was no informant, thus excluding significant proportions of patients from testing [START_REF] Pendlebury | Methodological factors in determining risk of dementia after transient ischemic attack and stroke: (II) effect of attrition on follow-up[END_REF].

The survey collected data from 12 RCTs, testing treatments for acute ischemic or hemorrhagic stroke or secondary prevention of ischemic stroke (Supplementary Table 1). The sample size ranged from 41 to 4750, total current sample 20,035 (planned sample 22,314), of which 12,439 will have detailed neuroimaging. The mean participant age is 71.6 years, and 58.5% are men. Most trials consistently recorded baseline vascular risk factors including blood pressure, and outcomes such as recurrent vascular events and functional outcome assessed using the modified Rankin Scale. However, cognitive tests varied (eight used the mini-mental state examination [MMSE], one the MoCA, five the Telephone Interview of Cognitive Assessment (TICS), and two a more detailed assessment), none tested premorbid intelligence quotient although four trials recorded educational attainment, few assessed mood, and none corrected for imaging features such as WMH burden (a predictor of post-stroke cognitive impairment). The latest follow-up was at 12 months in all but two trials (latest assessment 24 and 36 months in one trial each), substantially shorter than that in the other study types (Fig. 2).

An individual patient data meta-analysis of cognition after stroke in these trials, which are typical of many stroke treatment or prevention trials, would be hampered by lack of consistency in cognitive measures and of long-term data, despite providing exemplary vascular risk factor and vascular outcome assessments. Inadequate attention has been given to assessing cognition after stroke in RCTs to date. Agreement on pragmatic and rapid ways to assess important cognitive domains such as executive function and processing speed, not just memory, and to correct for premorbid cognition, depression, and WMH burden on imaging, are essential to advance understanding of cognitive trajectories after stroke. There is an opportunity to progress by including cognitive tests in ongoing multicentre stroke trials where feasible as pragmatic methods are becoming available.

Methods for assessing vascular effects on cognition and neurodegeneration

Vascular disease requires different methods compared with other types of neurodegeneration or dementia research. Two key methods, which differ substantially in their requirements for vascular disease and neurodegenerative pathologies such as AD, are the assessment of neuroimaging and cognition. Integrated cerebrovascular disease codes are essential to bridge clinical presentations. All are discussed here.

Imaging, protocols, and analysis methods

In the 1990s, landmark neuroepidemiological studies showed that clinically silent cerebrovascular lesions detected only on MRI, including lacunes and WMH of presumed vascular origin, were associated with cognitive impairment and an increased risk of future stroke and dementia [START_REF] Vermeer | Silent brain infarcts: a systematic review[END_REF][START_REF] Debette | The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis[END_REF]. More recent studies have incorporated advanced imaging modalities that interrogate physiological and molecular changes-such as structural and functional connectivity with diffusion tensor imaging and functional MRI, cerebral perfusion, and molecular markers such as amyloid deposition-with larger sample sizes to increase statistical power for subgroup analyses and to predict clinical events.

Our synthesis of cohort studies identified many participants in community-dwelling settings and clinical studies on stroke who have cognitive data and undergone or will undergo neuroimaging, predominantly brain MRI (Table 1, Supplementary Table 1). We identified five major areas where there are currently limitations, gaps in knowledge, or unrealized opportunities for harmonization and collaboration of neuroimaging methods.

First, vascular lesion definitions and terminology require standardization, to enable cross-cohort comparisons and meta-analysis. This need has largely been met by the recent STandards for ReportIng Vascular ChangEs Neuroimaging (STRIVE) [START_REF] Tuladhar | Relationship between white matter hyperintensities, cortical thickness, and cognition[END_REF]; however, updates will become necessary for new neuroimaging methods that bring new imaging markers or increased sensitivity of known markers.

Second, to harmonize and compare findings across studies, full details of neuroimaging acquisition and analysis methods should be reported. New studies could adopt successful, validated methods recommended by STandards for ReportIng Vascular ChangEs Neuroimaging or used previously if the full methodological details were available. Imaging protocols could be shared through a single, publicly available website.

Third, reliability and accuracy of lesion classification would be improved through sharing of (exemplary) MRI data across cohorts with appropriate anonymization. For visual rating, a shared MRI repository could be used to train new raters using expert consensus as the gold standard. For computational analysis, for example, of MRI WMH, a repository could allow developers access to MRI images showing a range of lesions, from different vendors and field strengths, to derive or validate processing methods.

Fourth, there is great need for integrating information on vascular and neurodegenerative pathology from cohorts recruited through different settings, leveraging the expertise of stroke and dementia specialists in vascular and neurodegenerative disease. Integrating data across geographic and race/ethnic backgrounds would also help to more reliably identify and explore differences in subclinical vascular brain injury.

Fifth, more collaboration would enhance innovative methods for neuroimaging post-processing and data analysis. One example is the increasing emphasis on integrated data analysis to determine total SVD burden and effects on brain connectivity, neurodegeneration, and cognition (Fig. 3). Advances in machine learning and graph theorybased network analysis provide new opportunities to accelerate image analysis for large-scale studies. A multidisci-plinary approach including neuroepidemiologists and clinical researchers on the one hand, and computer scientists, mathematicians and biomedical engineers on the other hand, is required.

Cognition

There are particular challenges in the assessment of cognition in patients with cerebrovascular diseases, rendering detailed neuropsychological approaches (typically used in studies of dementia) impractical. Fatigue is common after stroke, limiting patient tolerance of prolonged tests. Patients may have dysphasia, impaired hand function, or visual deficits, making some tests impossible, even if comprehension is preserved. Depression and apathy are common in SVD and affect cognitive test performance. Many brief cognitive screening tests focus on memory, although vascular disease, in particular SVD, typically results in subcortical cognitive impairments, for example, loss of frontal and executive function [START_REF] Pantoni | Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges[END_REF][START_REF] De Groot | Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study[END_REF], and may occur in a stepwise manner reflecting sudden vascular events.

The survey shows huge variability in cognitive outcome measures in stroke/TIA patients (Table 1, Supplementary Material). About 25% of studies used a diagnosis of dementia or MCI, another 25% used a single cognitive test (most commonly MoCA, MMSE, or the revised Addenbrooke's cognitive examination); less than 10% assessed the premorbid (i.e., optimal early adulthood) cognitive status; and few assessed cognition immediately before the stroke. Of cognitive domains assessed in these studies, there was an almost equal distribution among memory, executive functions, reaction time, visuospatial function, with many accounting also for depression and anxiety.

Longitudinal observational studies included patients with different cognitive impairment or dementia diagnoses, but of note, about half the studies did not assign a specific dementia type and the diagnostic criteria for MCI, AD, vascular cognitive impairment (VCI), and dementia varied. The most commonly used criteria were the National Institutes of Aging-Alzheimer's Association for MCI and AD, Diagnostic and Statistical Manual of Mental Disorders, IV Edition for dementia, and the American Heart Association/American Stroke Association for VCI. However, with the exception of the widely used Diagnostic and Statistical Manual of Mental Disorders, IV Edition criteria for dementia, most studies used widely differing criteria for other categories of cognitive disorders, perhaps reflecting the difficulties and complexity of cognitive assessment in vascular disease. Most community-based and longitudinal observational studies used the MMSE, which is insensitive to vascular cognitive decline. A stepwise approach to determining the cognitive test approach to vascular disease is suggested in Table 3.

The importance of assessing cognitive profiles (without worsening the complexity of categorization) is emphasized by recent findings in SVD patients of memory loss (a cortical dysfunction) [START_REF] Pantoni | Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges[END_REF][START_REF] Tuladhar | Relationship between white matter hyperintensities, cortical thickness, and cognition[END_REF], suggesting that SVD affects not just white and deep gray matter but also the (connected) cerebral cortex (Fig. 3) [START_REF] Tuladhar | Relationship between white matter hyperintensities, cortical thickness, and cognition[END_REF][START_REF] Duering | Incident subcortical infarcts induce focal thinning in connected cortical regions[END_REF][START_REF] Duering | Acute infarcts cause focal thinning in remote cortex via degeneration of connecting fiber tracts[END_REF]. Lower connectivity within cerebral networks was associated with cognitive impairment and dementia [START_REF] Lawrence | Structural network efficiency is associated with cognitive impairment in small-vessel disease[END_REF][START_REF] Tuladhar | Structural network efficiency predicts conversion to dementia[END_REF]; WMHs were associated with less brain activation in the frontal cortex on fludeoxyglucose-positron emission tomography [START_REF] Lo | Vascular burden and Alzheimer disease pathologic progression[END_REF][START_REF] Haight | Dissociable effects of Alzheimer disease and white matter hyperintensities on brain metabolism[END_REF][START_REF] Tullberg | White matter lesions impair frontal lobe function regardless of their location[END_REF]. Mood disorders and apathy are common after stroke, affect cognitive test performance (and more fundamentally, patient participation in research), and may reflect impaired connectivity. Integrating the results from different cohorts that investigate these underlying mechanisms and consequences is essential to understand the full impact of vascular disease on brain function and progression toward the complete spectrum of cognitive impairments.

Relevance and mapping to next generation disease coding, ICD-11

Accurate and uniformly applied diagnoses are essential in health care and research. The World Health Organization has the main responsibility for the global classification systems, a core constitutional task. ICD-10 was published about 25 years ago. Major advances in the understanding of diseases have occurred since then, making ICD-10 outdated in several areas. The revision of ICD-10 into ICD-11 is currently in its final stage.

A major change from ICD-10 to ICD-11 is that cerebrovascular diseases will no longer be split across different chapters, but will constitute "one single section" in Diseases of the Nervous System. ICD-11 will also, for the first time, include definitions of all cerebrovascular diagnostic codes including definitions of transient ischemic attack and the different main types of stroke. It will also encompass cerebrovascular diseases not causing acute neurological dysfunction: silent cerebral infarcts, cerebral microbleeds, and silent white matter abnormalities associated with vascular disease. The term "silent" denotes that these entities have not caused acute neurologic symptoms (and hence are not "strokes") but are important for brain function, affect prognosis, and should not be regarded only as incidental imaging findings.

The final ICD-11 classification is expected to be approved for governmental use by the World Health Assembly for release in 2018, but the prefinal beta draft is officially available at the World Health Organization website [START_REF]ICD-11 Beta Draft[END_REF]. For several research purposes, it is recommended that the ICD-11 terminology and definitions be considered and may be applied already at this stage.

Discussion

Our initiative identified more than 90 cohort studies, including over 660,000 participants, many outside current neurodegeneration data initiatives, most with consent for data sharing, providing substantial scope for data mining. We acknowledge that our survey is incomplete. However, we consider it sufficiently representative to draw important conclusions. The segregation of stroke and dementia remains prevalent 10 years after the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network (NINDS-CSN) standards [START_REF] Hachinski | National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards[END_REF], in spite of recognition that larger frameworks and better diagnostic criteria for dementias are urgently needed [START_REF] Hachinski | Stroke and potentially preventable dementias proclamation: updated World Stroke Day Proclamation[END_REF][START_REF] Hachinski | Stroke and vascular cognitive impairment: a transdisciplinary, translational and transactional approach[END_REF]. Even among the survey respondents (likely "cerebrovascular disease enthusiasts"), there was a large gap between "stroke" and "dementia," and sparse overlap with the JPND report [START_REF] Jpnd Action | Longitudinal cohort studies in neurodegeneration[END_REF]. Although stroke clinic-based studies and RCTs were trying to collect at least some cognitive data, the methods for testing cognition in such environments are suboptimal. Meanwhile, the memory clinic-based cohorts collected relatively little information on vascular disease. Undoubtedly, the role of vascular disease in neurodegeneration remains under-recognized, and under-funded [START_REF]MRC workshop on neurovascular ageing in health and disease: interplay of the CNS and vascular system[END_REF], a situation that can no longer be justified: vascular risk factor reduction prevents stroke and may also prevent dementia [START_REF] Ngandu | A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial[END_REF] further evidenced by declining dementia incidence paralleling declining stroke incidence [START_REF] Norton | Potential for primary prevention of Alzheimer's disease: an analysis of populationbased data[END_REF]. Fortunately, perspectives may be evolving. A recent call for new conceptual formulations of AD and dementia cites the need to account for mixed pathologies and known risk factors (many of which are also stroke risk factors) [START_REF] Khachaturian | The special topics section of Alzheimer's & Dementia[END_REF]. Furthermore, ICD-11 should help identify all cerebrovascular disease presentations. Standardized diagnostic workup and data collection would facilitate studies on diagnosis, prognosis, and treatment of vascular factors in a memory clinic setting, and similarly, studies of cognition, gait, and balance in a stroke clinic setting (Table 4). "Transnosological" research units, integrating specialists in neurovascular and neurodegenerative disorders would facilitate a global approach to dementia prevention. These survey data provide a framework for addressing interactions between the two leading causes of cognitive decline and dementia: vascular disease and neurodegeneration. Epidemiological studies and RCTs are highly complementary when viewed as large data sets en masse. Observational studies indicate that the most critical period for elevated blood pressure with regard to cognitive decline is midlife, whereas blood pressure-lowering trials mostly included older patients with follow-up periods too short to detect an effect. Population studies inform hospital-based post-stroke dementia studies (and vice versa), often have repeated measures gathered over many years, enabling the impact of cumulative exposures, and of exposure during specific ages, to be explored. Important early life information is present in these studies, for example, birth weight, childhood cognition, socioeconomic data, for subjects now aged 50 to 70 years, enabling assessment of early life factors on cerebrovascular disease and dementia risk. Capturing information on both vascular and neurodegenerative disease from mixed sources improves generalizability (e.g., RUN DMC; FUTURE; Lund Stroke Registry, Supplementary Table 1). Combining studies that focus on populations in different epidemiological "windows" relative to the expression of disease enhances mechanisms' discovery and can relate systemic disease risk (obesity, metabolic, and cardiovascular disease) to cerebrovascular disease and dementia. Cohort meta-analyses would help clarify long-term event rates, their prediction, risk factors, and variation between populations and improve design of RCTs. Existing studies may provide well-phenotyped "trial ready" subjects with prospective consent for future research. The challenges involved in harmonization and analysis of large, diverse data sets are substantial (Table 4), but methods to overcome this are ongoing [START_REF] Mathers | Guidelines for biomarkers of healthy ageing[END_REF], and the potential rewards are huge. Work already ongoing as a result of this initiative is listed in Supplementary Table 2.

Agreeing on a unified cognitive assessment, which can be applied easily in cerebrovascular disease, is sensitive to relevant domains and relevant to patients, could have as much impact on identifying treatment to prevent VCI as the Rankin Scale [START_REF] Rankin | Cerebral vascular accidents in patients over the age of 60. II. Prognosis[END_REF] has had on finding acute stroke treatments: without the common language for functional outcome provided by the Rankin scale, it is arguable that stroke units, thrombolysis, hemicraniectomy, and thrombectomy would not have become guideline acute stroke interventions in as little as 20 years. Currently, most stroke RCTs, with few exceptions [START_REF] Pearce | Effects of long-term blood pressure lowering and dual antiplatelet treatment on cognitive function in patients with recent lacunar stroke: a secondary analysis from the SPS3 randomised trial[END_REF], do not assess cognition. The evaluation of cognition in stroke patients is complex, difficult, with no "best cognitive test". The 2006 collaborative consensus [START_REF] Hachinski | National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards[END_REF] proposed three cognitive protocols with different lengths, one being a brief test for use in large observational studies and RCTs. Pragmatic, rapid, validated, tools sensitive to cognitive domains affected by vascular disease early on, are required, like the MoCA [START_REF] Chiti | Use of Montreal Cognitive Assessment in patients with stroke[END_REF]. Online cognitive tests, for example, the UK Biobank Cognitive Testing Enhancement, are too complex for many stroke patients. In any case, a stepwise approach is needed to assess vascular effects on neurodegeneration (Table 3). Simple, sensitive, cognitive scales for use in telephone interviews, validated in patients with cerebrovascular disease, are needed (Table 4) [START_REF] Castanho | Telephone-based screening tools for mild cognitive impairment and dementia in aging studies: a review of validated instruments[END_REF].

Several large national initiatives will address dementia prevention in line with the 2013 G8 Dementia Summit. These draw largely on healthy or presymptomatic disease populations and offer new opportunities for systematic, prospective evaluations of people at scale, and often longterm sample biobanking, genetics, and imaging, enabling some powerful study designs. These include the Rhineland study (Germany, DZNE, n 5 40,000), the Canadian Longitudinal Study on Aging (50,000 individuals), the Canadian Alliance for Healthy Hearts and Minds and Prospective Urban Rural Epidemiological MIND (PURE-MIND, 11,200 persons), and the UK Biobank [START_REF] Sudlow | UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age[END_REF] (500,000 people aged 40-70, 100,000 with detailed imaging). These long-term initiatives are complemented by several national and regional efforts to establish disease-based cohorts, for example, the Canadian Consortium on Neurodegeneration in Aging (1400 persons; AD, mixed dementia, MCI, and VCI), or to combine existing cohorts, for example, the DPUK [START_REF]Dementias Platforms UK (DPUK)[END_REF], (29 UK community cohorts), Cohort Studies of Memory in an International Consortium (COSMIC) [START_REF] Sachdev | COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups[END_REF], Virtual International Stroke Trials Archive (VISTA) Cognition [START_REF]Virtual International Stroke Trials Archive (VISTA)-Cognition[END_REF], and STROKOG [START_REF]Consortium of Studies of Post-Stroke Cognitive Decline and Dementia. Consortium of Studies of Post-Stroke Cognitive Decline and Dementia (STROKOG)[END_REF]. Other regions should be encouraged and are creating large repositories of data-Asia Pacific Region, Central and America [START_REF] Sposato | Program for the epidemiological evaluation of stroke in Tandil, Argentina (PREVISTA) study: rationale and design[END_REF], Russia, Africa [START_REF] Akinyemi | Profile and determinants of vascular cognitive impairment in African stroke survivors: the CogFAST Nigeria Study[END_REF], and Australasia [START_REF] Sachdev | COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups[END_REF].

Governments, funders, and the public recognize the importance of sharing publicly funded data. Data from combined analyses of cohorts would provide larger samples, more robust data on individual cognitive and physical outcomes, and the interplay between brain and body to maintain healthy, active populations into old age. The 2015 World Stroke Proclamation on preventable dementias [START_REF] Hachinski | Stroke and potentially preventable dementias proclamation: updated World Stroke Day Proclamation[END_REF] has been endorsed by several international Alzheimer's, neurological, psychiatric, and heart associations. Funding for cerebrovascular disease research should more closely match that spent on dementia or cardiac disease [START_REF]MRC workshop on neurovascular ageing in health and disease: interplay of the CNS and vascular system[END_REF]. Researchers should work together to operationalize assessment of vascular effects on neurodegeneration; stroke should move from "stroke-related" to "anything vascular related including cognition or other effects" [START_REF]ICD-11 Beta Draft[END_REF]; and dementia should move from AD to "any disorder, arising in or outside the brain, that progressively diminishes cognitive function".

Fig. 1 .

 1 Fig.1. Approaches to tackling vascular factors in neurodegenerative disease. The challenge is to integrate the different clinical presentations when attempting to recognize more completely the interactions between vascular disease and neurodegeneration and thence improve prevention and treatment.

Fig. 2 .

 2 Fig. 2. Duration of follow-up by study type and available information. Note some community-based studies have .5 years of follow-up.

Fig. 3 .

 3 Fig. 3. Dynamic effects of small vessel disease on the brain: (A) Periventricular and deep white matter hyperintensity (WMH; orange) can increase in size (red), occasionally shrink, and lead to atrophy of white matter. (B) Acute small subcortical infarcts (dashed black line) may cavitate and shrink (black area), develop into a WMH (orange) or disappear. Distant effects (blue) involve thinning of connected cortex and degeneration of projection fibers.

Table 3

 3 Choosing tests to measure cognition in studies and trials dealing with vascular diseases: a step-based process 1) Decide to assess cognition (mandatory) 2) Decide whether to assess a) diagnostic outcome measure (e.g., dementia, cognitive decline, mild cognitive impairment) and/or b) cognitive measures (i.e., use domain-specific cognitive tests) 4) If b, decide which domains to assess, and 5) Which tests to use.

Table 1

 1 Summary of types and amount of data available in cohorts recorded in the survey that were analyzed in detail Association Internationale pour la Recherch e et l'Enseignement en Neurosciences; ASA, American Stroke Association; CT, computed tomography; DSM, Diagnostic and Statistical Manual of Mental Disorders; ICD, International Classification of Disease; MoCA, Montreal Cognitive Assessment; MCI, mild cognitive impairment; MI, myocardial infarction; MMSE, mini-mental state examination; MRI, magnetic resonance imaging; NIA-AA, National Institutes of Aging-Alzheimer's Association; NINDS, National Institute for Neurological Disorders and Stroke; TIA, transient ischaemic attack; TICS, Telephone Interview of Cognitive Assessment.

			Hospital-based
		Community-based	cohorts from	Hospital-based cohorts
		cohorts	stroke services	from memory clinics	Clinical trials	All
	Number of studies
	Total/completed recruitment/	28/22/15	12/8/5	16/8/4	12/7/5	68/45/29
	completed follow-up
	Current number of patients
	Total/with imaging*	583.851/23.388	4.134/3.529	19.144/5.982	20.035/12.050	627.164/44.949
	Planned sample size
	Total/with imaging data	.600.000/.150.000 4.702/4.289	21.353/8.153	22.314/12.439	w655.000/w172.000
	Mean age (y)	71	70	73	71.6	72
	Male sex (%)	46	56	51	58.5	46
	Number of studies with
	Clinical diagnosis of stroke supported
	by neuroimaging
	MRI/CT/MRI or CT	6/1/4	5/4/3	4/0/2	3/2/6	18/7/15
	Baseline information on risk factors
	Hypertension/diabetes mellitus/	26/26/22/26/27/27	12/12/12/12/12/11 16/16/16/16/15/16	10/10/10/9/8/4	64/64/60/63/62/58
	hypercholesterolemia/smoking/
	medication/education
	Follow-up assessment
	After months 3/6/12/24/36/48/60	1/2/6/10/10/5/6	9/6/9/3/6/3/6	0/4/14/9/7/1/0	7/4/5/2/2/0/0	17/16/34/24/25/9/12
	Functional outcomes
	mRS/BI/SIS/EuroQol/SF36/ADL or	3/2/0/1/2/5	7/7/1/2/2/2	4/4/1/3/0/4	8/3/1/7/1/0	22/16/3/13/5/11
	IADL
	Vascular outcomes
	Stroke/TIA/MI/Vascular death	17/14/16/15	10/7/7/8	14/12/10/9	9/8/9/7	50/41/42/39
	Cognitive outcomes
	MCI/Dementia/MoCA or ACE-R/	7/15/4/17/16/18/15/16 7/9/7/10/8/7/4/7	8/11/6/12/14/14/10/14 1/2/1/8/6/4/4/4/4 23/37/18/47/44/43/33/41
	MMSE/TICS/Memory/Executive/
	Reaction time/Visuospatial
	Psychiatric outcomes
	Depression/anxiety	18/12	9/7	14/7	7/0	48/26
	Mobility outcomes
	Gait/balance/manual dexterity	1/0/0	1/0/0	1/0/0	0/0/0	3/0/0
	Criteria used for a diagnosis of MCI
	DSM-V/AHA or ASA/Petersen/	1/1/4/3/2	2/1/3/0/1	0/2/2/6/3	0/0/0/0/6	3/4/9/9/12
	NIA-AA/other
	Criteria used for a diagnosis of
	dementia
	DSM-IV/DSM-V/ICD-10/other	7/3/3/3	5/1/1/0	10/0/0/3	1/0/0/6	23/4/4/12
	Criteria used for diagnosis of
	vascular CI
	NINDS-AIREN/AHA or ASA/other 8/4/2	1/1/1	7/4/1	0/0/0	16/9/4
	Criteria used for a diagnosis of AD
	NIA-AA clinical/DSM-V/DSM-V/	5/5/0/2/6	1/4/1/0/0	8/2/1/4/2	0/0/0/0/0	14/11/2/6/8
	NINCDS-ADRDA/other
	Stored sample
	DNA/blood	26/20	7/6	13/14	3/3	49/43

Abbreviations: ACE-R, revised Addenbrooke's cognitive examination; AD, Alzheimer's disease; AHA, American Heart Association; AIREN, NOTE. For studies not included in detailed analysis and full details of all studies, see Supplementary Table 1. *Number includes UK Biobank of 500,000 recruited, 100,000 expected to have brain and other imaging. For 11 cross-sectional and 17 longitudinal studies not listed in Table 1, see Supplementary Material.

Table 2

 2 Summary of 84 observational cohort studies by study setting

	Setting

Abbreviation: TIA, transient ischaemic attack NOTE. Of 84 observational studies, 11 are cross sectional, and 73 are longitudinal. Data on 12 clinical trials are not included.

Table 4

 4

	Recommendations for research
	Recommendation	Reason 1	Reason 2	Reason 3
	General	Vascular and neurodegenerative	Secondary neurodegeneration due to	Vascular damage can manifest as
		pathologies are closely related;	vascular insults is an important	progressive cognitive, behavioral
		vascular pathology is an integral	contributor to accumulating	or sensorimotor dysfunction, that
		part of the pathological spectrum	structural brain damage and brain	is, not just stroke.
		of AD, and vascular disease can	dysfunction.
		play an important primary or
		secondary role to other pathology
		in neurodegeneration and
		dementia.
	Integrated approaches are needed	Vascular neurodegenerative disorders	These clinics should integrate to	Clinical practice and research should
		may present to many different	avoid overlooking the multifaceted	assess risk factors, clinical,
		clinics but are underpinned by a	effects of vascular disease on	cognitive, imaging, and physical
		common vascular disorder.	cognition, psychiatric symptoms,	function.
			and physical function.
	Vascular disease is a dynamic and	Apparently small lesions that may	Small lesions are also evidence of a	Vascular lesions are not small,
	far-reaching process	precipitate clinical presentations	global brain disease and should be	individually trivial lesions, without
		have remote effects on other parts	treated as a progressive, global	clinical meaningfulness.
		of the brain, which increase	pathology.
		neurological and cognitive
		dysfunction.
	Always assess vascular risk factors,	Cerebrovascular disease and AD	As an absolute minimum, routinely	Pragmatic approaches can be suitable
	disease burden, and outcomes	share multiple risk factors, for	assess history of cerebrovascular,	and avoid overburdening
		example, smoking, hypertension,	peripheral vascular, cardiovascular	researchers and participants.
		hyperglycemia, diabetes, and	disease, blood pressure, smoking,	Follow-up should continue long
		obesity. Vascular risk factors may	exercise, occupation, and diet,	term.
		have a greater impact in midlife	blood lipids, blood glucose.
		than old age.
	Cognitive assessments should be	Need to be applicable to vascular	Adapted to reflect their specific	Assess executive function and
	performed in, and relevant to,	patients and the environment in	cognitive deficits and physical	processing speed in addition to
	vascular disease	which they typically present.	limitations.	memory.
		To avoid mistaking lifelong stable	Long-term outcome events, rates, and	Socioeconomic factors have major
		traits for late life change, routinely	timings of decline in cognitive and	influence on vascular disease
		assess prior cognitive ability (or	physical function are needed to	beyond that attributed to vascular
		proxy measures, e.g., educational	power clinical trials and inform	risk factors alone and should be
		attainment) in any studies of	patients and health services more	assessed routinely.
		cognition and vascular disease or	effectively.
		other dementias.
	Assess physical function across	Gait, balance, and continence are	Simple tests such as "timed up and
	several domains routinely	often affected and should be	go" are valuable to assess physical
		assessed routinely in suspected	function.
		vascular cognitive impairment.
	Use standard, validated data	Agreed core standard data (clinical,	Agreed standards are available, for	Imaging can identify "silent" and
	collection that accounts for	cognitive, imaging, biomarkers,	example, NINDS-CSN Vascular	symptomatic vascular disease if
	vascular disease	and so forth) and definitions would	Cognitive Impairment	the right sequences are used.
		facilitate future data sharing and	Harmonization Standards; or
		meta-analyses.	STRIVE standards for
			neuroimaging.
	Encourage postmortem brain tissue	Brain tissue from subjects well	More research is needed on the	Tissue-imaging analysis of individual
	collection	phenotyped in life, including brain	interaction of AD with	lesions is needed to understand
		regions commonly affected by	cerebrovascular pathology, the	pathological mechanisms.
		vascular disease, are not widely	consequences for function of brain
		available; storing samples frozen,	networks, and ultimately how
		and in paraffin, would facilitate	these pathologies evolve and
		protein, and gene as well as	combine to cause clinical
		histological assessments.	consequences.
	Make better use of existing cohort	Study registration and public	Cohorts that assess cerebrovascular	Open data initiatives and databanks
	data	availability of protocols would	disease and include molecular	would encourage sharing of
		facilitate identification of novel	imaging to assess AD pathology	existing cohort data.
		and ongoing studies for meta-	(e.g., by PET amyloid imaging)
		analyses.	will help understand joint
			pathologies.

Abbreviations: AD, Alzheimer's disease; PET, positron emission tomography.

METACOHORTS Consortium / Alzheimer's & Dementia -(2016) 1-14

Acknowledgments

The following funders supported the work: Joint Programme for Neurodegenerative Disease (JPND) Research, specifically the UK Medical Research Council, the Deutsches Zentrum f€ ur Neurodegenerative Erkrankungen (DZNE), and the Canadian Institutes of Health Research (CIHR). The Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) through the Pools Engagement in Europe (PEER) funding from the Scottish Funding Council. The Therese Pei Fong Chow Research Centre for Prevention of Dementia (in memory of Donald H K Chow). The authors thank the Siemens Foundation, Munich, Germany, for providing the workshop venue and catering. F.-E.D.L. acknowledges VIDI Innovation Grant from ZonMW ref 016.126.351. P.M.M. acknowledges generous support from the Edmond J Safra Foundation and Lily Safra and the Imperial College Health Trust BRC. P.M.W.B. is Stroke Association Professor of Stroke Medicine. C.de.C. acknowledges support from Centre Grant NIH P30 AG 010129. MD, JMW, GJB, RVO acknowledge EU Horizon 2020 SVDs@Target grant agreement No 666881. In the short term, the main source of information about these cohorts is Supplementary Table 1, while work continues to enable a platform to improve accessibility and searching for study data. Author contributions. Obtaining funding: JMW, MD. Project management and administration: JMW, MD, ES. Design and testing of survey: MD, ES, JMW, KS. Survey distribution: ES, MD, JMW, KS, CC, VM. Data collection: all authors. Data analysis: VZ, KS, JMW. Manuscript preparation: JMW, MD, ES, VZ, SS, PS, GJB, FF, LP, FEdeL, BN, PM, MD, WW. Preparation of figures: MD, FEdeL, VZ, MD, KS. Critical comment and data checking: all authors. Final approval to submit: all authors.

the submitted work, S Black reports institutional grants from Pfizer, GE Healthcare, Eli Lilly, Elan/Transition Therapeutics, Roche, Cognoptix, and personal fees from Pfizer, GE Healthcare, Eli Lilly, Eisai, Boehringer Ingelheim, Novartis. R Bordet reports grants from French Minister of Health, Fondation Coeur et Art ere, during the conduct of the study. I Deary reports grants from Age UK, UK Medical Research Council, UK Biotechnology and Biological Sciences Research Council, during the conduct of the study. F-E de Leeuw reports grants from VIDI innovational grant (ZonMW), during the conduct of the study. F Doubal reports grants from JPND (Medical Research Council and Canadian Institutes of Health Research), The Stroke Association and Garfield Weston Foundation, during the conduct of the study. KP Ebmeier reports grants from UK Medical Research Council, The HDH Wills 1965 Charitable Trust, Gordon Edward Small's Charitable Trust, National Institute of Health Research, Alzheimer Research UK, and personal fees from Eli Lily, GE, and grants from Various Pharmaceutical Companies, outside the submitted work. M Ewers received grants from the European Commission, Alzheimer Forschung Initiative and LMU. R Frayne reports grants from CIHR, during the conduct of the study; grants from CIHR, outside the submitted work. J O'Brien reports personal fees from GE Healthcare, TauRx, Cytox, grants and personal fees from Avid/Lilly, outside the submitted work. T Quinn is a founding member of VISTA cognition, a not for profit resource that collates individual patient level data relating to cognition and stroke. P Sachdev reports grants from NHMRC Program Grant ID 568969, during the conduct of the study. K Shuler reports grants from JPND (Medical Research Council), grants from Scottish Funding Council PEER SINAPSE, during the conduct of the study. E Smith reports grants from Canadian Institutes of Health Research, during the conduct of the study and from the Heart and Stroke Foundation of Canada, outside the submitted work. A Thomas reports grants from NIHR BRU in Lewy Body Dementia, during the conduct of the study. A Viswanathan reports personal fees from Roche Pharmaceuticals, outside the submitted work. JM Wardlaw reports grants from JPND (Medical Research Council and Canadian Institutes of Health Research), and Scottish Funding Council PEER SINAPSE, during the conduct of the study.

Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jalz.2016.06.004.