Anne-Sophie Sophie Colas
email: anne-sophie.colas@ifsttar.fr

Denis Garnier

Jean-Claude Claude Morel

Yield design modelling of dry joint retaining structures

Keywords: Dry joint masonry, retaining walls, yield design, scale-down experiments

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Introduction

Masonry structures have received great interest over the past few decades, mainly due to the growing need for evaluation, maintenance and repair of historical architecture. Part of these masonry constructions were built dry or have experienced a loss of mortar due to aging and can now be considered as dry masonry structures.

A large number of studies have been dedicated to monumental constructions, but recent literature on retaining masonry structures is quite sparse.

Modelling on masonry can be divided in two categories :

• macro-modelling where the masonry is considered as continuous and homogeneous and subjected to a classical behaviour law of mechanics of continuous media [START_REF] Heyman | The stone skeleton[END_REF][START_REF] Mola | Analysis, diagnosis and preservation of ancient monuments: the St Mark's Basilica in Venice[END_REF][START_REF] Lourenço | A plane stress softening plasticity model for orthotropic materials[END_REF]; this approach provides immediate information on the structure but fails to take into account the characteristics of masonry internal behaviour;

• micro-modelling where the masonry is considered as heterogeneous; simulations differ depending on whether the medium is considered as continuous [START_REF] Page | Finite element model for masonry, A.S.C[END_REF][START_REF] Lotfi | Interface model applied to fracture of masonry structures[END_REF][START_REF] Orduña | Cap model for limit analysis and strengthening of masonry structures[END_REF] or discrete [START_REF] Lemos | Discrete element modelling of historical structures[END_REF][START_REF] Rafiee | Application of the NSCD method to analyse the dynamic behaviour of stone arched structures[END_REF]; this approach supplies plentiful information on the behaviour of the masonry but proves quite complex and time-consuming, and thus does not fit for practical purposes.

On the other hand, experimental studies are usually rare because difficult to undertake : in the literature can be found laboratory tests on periodic masonry [START_REF] Lourenço | Dry joint stone masonry walls subjected to in-plane combined loading[END_REF] as well as recent on-site experiments on dry-stone retaining walls [START_REF] Villemus | Experimental assessment of dry stone retaining wall stability on a rigid foundation[END_REF][START_REF] Colas | Full-scale field trials to assess dry-stone retaining wall stability[END_REF][START_REF] Mundell | Behaviour of drystone retaining structures[END_REF].

The Department of Civil Engineering and Building (DGCB) of ENTPE concentrates on civil engineering materials and structures. It has been involved in the simulation of dry-stone masonry since 1998 with two theses dedicated to this theme [START_REF] Villemus | Étude des murs de soutènement en maçonnerie de pierres sèches[END_REF][START_REF] Colas | Mécanique des murs de soutènement en pierre sèche : Modélisation par le calcul à la rupture et expérimentation échelle 1[END_REF]. The present work is part of this research field.

This paper presents theoretical and experimental simulations to assess the stability of dry masonry retaining structures. First, a model based on yield design homogenization for dry masonry will be presented : this model enables to take into account the heterogeneity of the masonry while maintaining a pragmatic process. Then the simulation will evaluated on 2D scale-down experiments, with different parametric configurations in order to test its robustness and to apprehend dry masonry phenomenology. The widespread use of the model on full-scale periodic dry joint and dry-stone retaining constructions will finally be discussed. As a conclusion, future perspectives expanding on this work will be exposed.

Yield design modelling of dry joint retaining structures

The present work relies on yield design [START_REF] Salençon | An introduction to the yield design theory and its application to soils mechanics[END_REF]; this theory enables to evaluate the ultimate bearing capacity of a structure, solely knowing its geometry, loading mode and yield criterion. This method was first devoted to soil mechanics, but expanding on this work, it has been proved that yield design could be applied to masonry [START_REF] De Buhan | A homogenization approach to the ultimate strength of brick masonry[END_REF][START_REF] Corfdir | Analyse de la stabilité des ouvrages en gabions cellulaires par la théorie du calcul à la rupture[END_REF][START_REF] Sab | Yield design of thin periodic plates by a homogenization technique and an application to masonry walls[END_REF]. The following section describes the procedure to model a dry joint retaining wall using this method.

Hypotheses

The system under investigation is constituted by the masonry retaining structure and its backfill. Three kinds of parameters of this system are now required to set up yield design.

h h s l B C O A λ 1 λ 2 γ m α γ s β α C s = 0 φ m φ s

Geometry

The wall is of height h and of thickness at the top l, with a batter λ 1 and a counter-slope λ 2 (Fig. 1). The wall is assumed to be founded onto rigid bedrock, and the bed joints are inclined with an angle α from horizontal. The backfill will be considered as infinitely long, of height h s , and its surface forms an angle β with horizontal.

Loading mode

This system is only subjected to the respective unit weights of the wall γ m and the soil γ s .

Yield criterion

The yield criterion of the system depends on the wall and soil constituent materials.

The wall macroscopic yield criterion is calculated by a homogenization method for periodic media developed on by de Buhan and de Felice [START_REF] De Buhan | A homogenization approach to the ultimate strength of brick masonry[END_REF]. The joints will be assumed to have a purely frictional Mohr-Coulomb criterion, only depending on the block friction angle φ m , and the stones will be considered as infinitely resistant. The homogenization process (Fig. 2) enables to undertake a macroscopic stability assessment of the wall, now considered as a homogenized continuous medium. The backfill submits to a purely frictional Mohr-Coulomb criterion, which friction angle will be noted as φ s . It has been decided that the cohesion of the soil would not be taken into account (C s = 0) in order to simplify calculations.

Σ 22 Σ 12 Σ 11 (-1,0,0) (-f,1,-1/f) (-f,-1,-1/f) (f,0,-2m)
On the other hand, this hypothesis makes our design calculations better for safety.

The contact zone between the wall and its backfill is modelled by a Mohr-Coulomb criterion which friction angle equals φ s , the backfill friction angle. This hypothesis can be justified considering the roughness of the back face of the wall; it will be validated further on by the experimental tests.

Yield mechanism

The yield design upper-bound theorem consists in making the balance between the work of external force and the maximum resisting work for every kinematically admissible virtual velocity field.

In this study, the wall is intended to break from its toe along a failure line, which forms an angle of Ψ m from foundation (Fig. 3). The lower part of the wall remains fixed whereas the upper trapezium is given a velocity v m .

The backfill is intended to follow a failure cone, which is given a velocity v s .

Two different virtual velocity fields will then be considered :

• a translation χ m in the wall and a translation χ s in the soil (Fig. 3a);

• a rotation v m in the wall and a shearing v s in the soil (Fig. 3b).

Ultimate backfill height

The ultimate backfill height h + s the wall can bear is the minimal height verifying that the work of external forces W e is lower than the maximum resisting work W mr ; this critical height only depends on the three kinds of parameters described above: Therefore, this method succeeds in taking into account the possible internal failure in the wall, and proves indeed easy to carry out, since requiring no programming and only few parameters.

h + s = f (h, l, λ 1 , λ 2 , α, β, γ m , γ s , φ m , φ s ) (1)
Ψ m Ψ s v m = χ m v s = χ s Ψ m v m = χ m v s = χ s Ψ s X 2 X 1 X ′ 2 X ′ 1 Ψ m v m v s Ψ s Ψ m v m v s Ψ s X 2 X 1 X ′ 2 X ′ 1 X 2 X 1 (a) (b)

2D scale-down experiments of dry joint retaining structures

The physical approach aims at assessing the consistence of the model. As they are quite easy to undertake and to repeat, they represent an attractive tool to test various parametric configurations. The campaign consists in the experiment of 30 cm high masonry structures built with brick and wood blocks and backfilled until failure with Schneebeli rods. These tests do not respect scaling effects, thus the scale-down models will be considered as fullfledged constructions but they can be used to evaluate dry joint masonry phenomenology and to prepare full-scale experiments.

Experimental protocol 3.1.1. Constitutive elements characteristics

In these experiments, it has been decided to represent the backfill soil by a Schneebeli material [START_REF] Schneebeli | Une mécanique pour les terres sans cohésion[END_REF]. This designation refers to a set of rolls of different diameters which behaviour is similar to that of pulverulent soils but acting solely in two dimensions. The analogic backfill is thus constituted of small cylinders of duralium which are 3 to 5 mm of diameter and 6 cm long.

Wilson-Jones [START_REF] Wilson-Jones | Ouvrages renforcés par des géosynthétiques dans un modèle analogique plan[END_REF] determined the soil friction angle φ s = 25 • using 30×30 cm Casagrande shear tests.

The walls are made of plane-parallel blocks of the same length (6 cm) as that of the rolls and of section 2×1 cm. Two different types of materials were explored in order to evaluate the joint influence of wall unit weight γ m and friction angle φ m . The block friction angle was determined with 10 × 10 cm Casagrande shear tests.

Geometrical and physical characteristics of the wall and the backfill are recorded in Table 1.

Experimental device

The scale-down models are self standing walls based on a rigid foundation of same material as that of the wall : they are built in staggered rows with the small elements previously described laid dry (Fig. 4). A minimum of five

Brick Wood

Wall height h (cm) 27.5

Wall thickness l (cm) 9 11

Wall batter λ 1 (%) 0, 11, 16 0, 9, 12

Wall counter-slope λ 1 (%) 0

Joint inclination α ( • ) -12, -9, -6, 0, 6 -6, 0, 6, 16 blocks in the wall thickness is ensured in order to validate the use of homogenization. Each wall is then backfilled with 1 cm high layers of Schneebeli rods until failure. The backfill is sufficiently long (65 cm) so that it can be considered as semi-infinite to prevail from side effects.

Backfill slope β ( • ) 0, 10

Parametric analysis

Twenty-five tests were undertaken on varying geometrical and physical configurations of the wall and/or the backfill. For each type of block, the influence of the joint inclination α, the wall batter λ 1 , and the backfill slope β was experienced. Each test is conducted with the same geometrical characteristics, except for the parameter tested (in italic in Table 1). Finally, the experimental failure height is compared to the ultimate height given by yield design.

This paper focuses on the first parametric test on the influence of joint inclination α on brick walls (Fig. 5); details on the other tests can be found in Colas et al. [START_REF] Colas | 2D modelling of a dry joint masonry wall retaining a pulverulent backfill[END_REF]. In this experiment, models are built with vertical faces and leaning joints (from -12 to 6 • ), and then loaded with a horizontal backfill until failure. Two different configurations have been tested for the back face of the wall:

• a blank face, which will be used for further experiments;

• a face covered with rolls, which ensures that the interface friction angle is equal to the soil internal friction angle.

This first experiment shows good qualitative agreement with yield design modelling, as the simulation succeeds in predicting the evolution of the ultimate height as well as the type of failure of the wall. Brick walls slide for α under -12 • and overturn for α above -6 • : for α = -8 • , the failure mode combines sliding and overturning as predicted by yield design.

It has to be noted that the error rate is quite high when α is low: this configuration gets the wall very unstable and encourages errors due to experimental manipulation. This difference can also be accounted for by an overestimation of the brick friction angle.

Comparing tests with and without rolls at the interface shows that experimental results are closer to simulation predictions when interface are covered with rolls. The soil/structure friction angle may be lower than the soil internal friction angle. Yet, the low difference between the two configurations led us to validate the interface friction angle equal to φ s . The five other experiments confirm the good qualitative agreement between simulation and experiments. They indeed show that yield design succeeds in predicting experimental results with an error rate around 10%. Further details can be found in Colas et al. [START_REF] Colas | 2D modelling of a dry joint masonry wall retaining a pulverulent backfill[END_REF]. Figure 6 presents theoretical ultimate heights depending on experimental results. It can be seen that the scatter plot is globally above the first bissector, meaning that theoretical predictions are higher than experimental results: this is quite coherent with the principle of upper-bound yield design theory which provides an upperbound limit of the ultimate height. On the other hand, the data are quite close to the first bissector, thus validating the simulation presented here.

The furthermost points are those corresponding to the experiment on joint inclination for brick walls, for the reasons previously described.

Experiments show close agreement with theoretical predictions. The ultimate backfill height as well as the type of failure estimated by yield design correspond to those found by physical models with an error rate around 10%, thus corroborating the hypothesis adopted for the wall/backfill interaction.

These results also show that the model is able to take into account different materials and geometry. This experimental campaign enables the validation of the yield design simulation and help to prepare a full-scale field trial.

Application to full-scale dry joint masonry structures

The yield design simulation was developed to assess various types of dry joint retaining structures. Validation on 2D scale-models shows the robustness of the model toward parametric variations.

The quantitative results obtained in section 3 cannot be used to describe full-scale structures as the experiments did not respect scale effects. Yet, the qualitative observations enable to describe dry joint periodic structure phenomenology. As a consequence of our parametric tests, the following trends can be identified:

• the inclination of bed joints toward the back face of the wall can prevent it from an early sliding;

• a batter on the wall front face reinforces its stability; besides, battered walls tend to fail by sliding rather than overturning;

• a growing slope of the backfill makes the wall unstable.

The yield design simulation presented above is meant to be used as a pragmatic tool to design dry-stone retaining wall. Dry-stone masonry consists in fitting interlocking stones without mortar to build a wall or a vault.

It is a widely expanded form of construction, and an important heritage can be found all around the world. However, no structural design method has been validated until recently.

Simulating dry-stone construction by a regular and periodic medium makes it possible to take into account the strong heterogeneity of the structure while maintaining a pragmatic process. This hypothesis can be justified as regard to the apparent regularity of well-built dry-stone masonry (Fig. 7): actually, dry-stone construction practices recommend to build linear bed joints and to use small blocks of stone called pins to prevent blocks from rotating. Yet, the block irregularity leads to an important presence of void in the structure that can be taken into account in the simulation by a decrease of the wall unit weight. Villemus et al. [START_REF] Villemus | Experimental assessment of dry stone retaining wall stability on a rigid foundation[END_REF] have measured the void percentage by weighing experimental dry-stone walls after testing : they estimated the percentage around 25% for walls built with large blocks of smooth limestone and 32% for walls constituted of thin blocks of schist.

Nevertheless, it is necessary to validate the model by comparisons with experimental data. The strong heterogeneity of the masonry and the specificity of the soil/structure interaction make it important to undertake fullscale experiments to provide qualitative as well as quantitative results. Thus experimental evaluation is meant to corroborate the qualitative observations presented here, provide complementary information-as for instance the wall void percentage, and finally validate the model as a practical tool to design dry joint retaining structures. The authors have thus undertaken on site experiments on full-scale drystone walls (Fig. 8). The 2D scale-down experiments have been used to prepare the full-scale field trial, which had to be well-targeted considering its cost and its complexity. The aim of this campaign was to lead a dry-stone wall to overturn by means of pulverulent backfill. The bed joints of the wall were inclined toward the back face in order to prevent sliding. Indeed, the backfill was laid on its natural slope (maximum slope) in order to favour the wall failure. The wall geometry was designed using the model presented above. The experiments have been achieved [START_REF] Colas | Full-scale field trials to assess dry-stone retaining wall stability[END_REF]; comparisons with theoretical predictions are in process [START_REF] Colas | Assessing the 2D behaviour of dry-stone retaining walls by full-scale experiments and yield design simulation[END_REF].

Conclusions and perspectives

This study has presented a pragmatic method to assess dry joint retaining structures thanks to yield design. A model based on yield design homogenization combined to its upper-bound kinematic approach has been established and then tested on 2D scale-down experiments. Comparing experimental results to theoretical predictions have proved the robustness of the model, thus validating the hypotheses taken into account. Indeed, it has provided interesting information on dry joint structure phenomenology. The scale-down experiments prove very interesting as they provide useful information while being relatively easy to undertake and to repeat. Yet, the results can be affected by the reduced size of the elements which make the experiment very sensitive to manipulation errors. On the other hand, the importance of scale effects on this type of structures prevents from using the quantitative results obtained to described full-scale constructions. Thus, the model needs to be confronted to experiments on full-scale structures to be validated.

Further perspectives on this work includes tests of the model on experimental data, and more especially on the results of full-scale field trials on dry-stone walls [START_REF] Villemus | Experimental assessment of dry stone retaining wall stability on a rigid foundation[END_REF][START_REF] Colas | Full-scale field trials to assess dry-stone retaining wall stability[END_REF].

Figure 1 :

 1 Figure 1: Dry-joint retaining wall modelling: hypotheses of geometry, loading and yield criterion.

Figure 2 :

 2 Figure 2: Yield criterion of homogenized dry joint periodic masonry depending on the block slenderness ratio m and the tangent of the block friction angle f = tan φ m .

Figure 3 :

 3 Figure 3: Virtual velocity fields : wall and backfill translations (a), wall rotation and backfill shearing (b).

  , 15, 20 0, 5, 10, 20 Wall unit weight γ m (kN/m 3 ) 18.4 7.1 Backfill unit weight γ b (kN/m 3 ) 22.5 Wall friction angle φ m ( • ) 33 30 Backfill friction angle φ b ( • ) 25 Interaction friction angle φ b ( • ) 25

Figure 4 :

 4 Figure 4: Experimental device : example of a dry joint wall of wood (a) and test on a brick wall backfilled with Schneebeli rods (b).

Figure 5 :

 5 Figure 5: Theoretical and experimental ultimate backfill heights of brick walls (γ m = 18.4 kN/m 3 , φ m = 33 • ) depending on joint inclination α (λ 1 = 0%, β = 0 • ).

Figure 6 :

 6 Figure 6: Outcome of the experimental campaign on 2D scale-models backfilled with Schneebeli rods.

Figure 7 :

 7 Figure 7: Comparison between dry-stone (a) and theoretical periodic masonry (b).

Figure 8 :

 8 Figure 8: Full-scale field trials of dry-stone walls: preparation before experimentation (a) and overturning of the wall (b).

Table 1 :

 1 Physical and geometrical characteristics of the system (in italic, the parameters which have been tested).


MSc Marion Mortamais
email: marion.mortamais@inserm.fr

PhD Sylvaine Artero

PhD Karen Ritchie

Cerebral white matter hyperintensities in the prediction of cognitive decline and incident dementia

HAL is

Introduction

Alzheimer"s disease (AD), defined as a neurodegenerative process, is usually considered the most common form of dementia, followed by vascular dementia (VaD), related to cerebral vascular lesions (ischemic, or hemorrhagic, or single or multiples infarcts) . However, in autopsy series, an overlap between the pathological characteristics of AD (tangles and neuritic plaques) and vascular pathology has frequently been observed in demented subjects [START_REF] Ince | Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales[END_REF][START_REF] Schneider | Mixed brain pathologies account for most dementia cases in community-dwelling older persons[END_REF][START_REF] Snowdon | Brain infarction and the clinical expression of Alzheimer disease. The Nun Study[END_REF], thus making it difficult to clinically differentiate the two entities. Moreover, epidemiological and clinical studies in the last two decades have suggested that the underlying biological characteristics of the two disorders may be interdependent such that increased vascular risk factors (diabetes, hypertension, dyslipidemia, cardiopathies, lifestyle) are also risk factors for AD [START_REF] Silvestrini | Cerebrovascular assessment for the risk prediction of Alzheimer's disease[END_REF][START_REF] Tolppanen | Midlife vascular risk factors and Alzheimer's disease: evidence from epidemiological studies[END_REF]. While to date no imaging study has compared the frequency of vascular disorder and AD in cohorts with dementia, longitudinal community-based postmortem brain series suggest that a mixed pathological basis occurs in over 60% of cases [START_REF] Ince | Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales[END_REF][START_REF] Schneider | Mixed brain pathologies account for most dementia cases in community-dwelling older persons[END_REF]. Moreover, given the insensitivity of standard neuropathological analyses to microvascular disease, this is likely to be an underestimation.

The dichotomization between pure neurodegenerative and pure vascular forms of dementia is therefore currently being questioned, and a reformulation of the diagnostic criteria for AD has been proposed [START_REF] Mckhann | The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease[END_REF]. It is still not clear whether vascular lesions are directly involved in the development of AD, or whether they may lower the burden of AD pathology necessary to produce clinical symptoms of dementia [START_REF] Esiri | Cerebrovascular disease and threshold for dementia in the early stages of Alzheimer's disease[END_REF][START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Van Der Flier | Interaction of medial temporal lobe atrophy and white matter hyperintensities in AD[END_REF]. Estimating the contribution of cerebrovascular disease in cognitive decline is important for the understanding of the etiology of dementia, and because vascular risk factors represent modifiable factors and potential therapeutic targets [START_REF] Valenzuela | Antihypertensives for combating dementia? A perspective on candidate molecular mechanisms and population-based prevention[END_REF]. Progress in neuroimaging has provided relevant means to estimate in vivo cerebrovascular burden, accumulated throughout life. Pathology in small cerebral arteries, which cannot be imaged directly, is typically measured by cerebral white matter hyperintensities (WMH) appearing as hyperintense areas on T2 weighted magnetic resonance imaging (MRI) scans (including FLAIR) and are commonly found in the elderly [START_REF] Ylikoski | White matter hyperintensities on MRI in the neurologically nondiseased elderly. Analysis of cohorts of consecutive subjects aged 55 to 85 years living at home[END_REF]. Pathological correlates of these hyperintense areas include myelin pallor, loss of myelin and axons, and mild gliosis [START_REF] Fazekas | Pathologic correlates of incidental MRI white matter signal hyperintensities[END_REF][START_REF] Gouw | Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations[END_REF]. Such lesions may cause cognitive impairment by disrupting cortical connections mediated by specific white matter tracts [START_REF] Smith | Correlations between MRI white matter lesion location and executive function and episodic memory[END_REF]. The etiology of WMH is still not fully understood, but WMH are thought to mainly result from pathological changes in small vessels [START_REF] Pantoni | Pathogenesis of leukoaraiosis: a review[END_REF][START_REF] Roman | Subcortical ischaemic vascular dementia[END_REF] leading to chronic hypoperfusion of white matter and disruption of the blood-brain barrier with leakage of plasma into white matter [START_REF] O'sullivan | Patterns of cerebral blood flow reduction in patients with ischemic leukoaraiosis[END_REF][START_REF] Topakian | Blood-brain barrier permeability is increased in normal-appearing white matter in patients with lacunar stroke and leucoaraiosis[END_REF].

WMH could represent a non-invasive method to assess vascular risk in epidemiologic studies, or as a surrogate marker in clinical trials [START_REF] Richard | Vascular care in patients with Alzheimer disease with cerebrovascular lesions slows progression of white matter lesions on MRI: the evaluation of vascular care in Alzheimer's disease (EVA) study[END_REF][START_REF] Schmidt | White matter lesion progression in LADIS: frequency, clinical effects, and sample size calculations[END_REF]. Numerous studies have investigated the association between WMH and cognition, with conflicting results. The present review examines evidence from published longitudinal studies assessing the relationship between WMH and 1) risk of dementia in the general population, 2) risk of transition from mild cognitive impairment (MCI) to dementia and 3) cognitive decline without dementia in the general population.

Methods

Study selection for the review

We reviewed the PubMed data base from January 1990 to March 2013. A combination of search strategies using MeSH terms and other search terms (keyword search) were used. In summary, the search covered the following terms: white matter, periventricular, subcortical, leukoaraiosis, dementia, cognition, MRI, and longitudinal studies. The detailed search strategy is reported in the Appendix.

Reference lists of relevant articles were also examined.

In this review, we included studies with assessment of WMH at baseline and with longitudinal data on cognition. We retained studies investigating the association of WMH with 1) the risk of dementia in the general population, 2) the risk of conversion to dementia in the MCI population, and 3) cognitive decline in the general population.

We reviewed titles and abstracts of identified articles which were published in English. For those potentially meeting the inclusion criteria, the full paper was reviewed. If several publications were found for the same cohort and the same outcome, we retained the study with the longest follow-up, or the highest number of participants if duration of follow-up was similar.

From the selected studies, information relating to the following characteristics was collected: number of participants, mean age, duration of follow-up, quantification method of WMH, outcome definition (all types of dementia versus AD, VaD, mixed dementia (MD), and others; neuropsychological tests used to assess cognitive decline), and number of events observed during the follow-up period. Hazards Ratio (HR), Odds Ratio (OR), and adjustment variables were extracted when available.

Results

Selected studies

Overall 824 references were initially identified from the initial searches. Studies with cross-sectional data on cognition or with MRI at the end of follow-up instead of at baseline were not included. Studies on WMH in high risk subjects such as patients with monogenic cerebrovascular disease (CADASIL), vascular risk, stroke or depression were excluded, as well as studies on the association of WMH with cognitive decline in already demented or MCI individuals. Finally, duplicates [START_REF] De Groot | Periventricular cerebral white matter lesions predict rate of cognitive decline[END_REF][START_REF] Ikram | Brain tissue volumes in relation to cognitive function and risk of dementia[END_REF][START_REF] Kuller | Determinants of vascular dementia in the Cardiovascular Health Cognition Study[END_REF][START_REF] Rosano | Focal atrophy and cerebrovascular disease increase dementia risk among cognitively normal older adults[END_REF][START_REF] Vermeer | Silent brain infarcts and the risk of dementia and cognitive decline[END_REF] were also discarded. After the initial screening, 23 articles were retrieved for full text review. We included one additional paper [START_REF] Bombois | Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients[END_REF] from the hand search of the reference list of these 23 articles. We finally included 24 articles.

WMH and risk of dementia in the general population

Results from the five population-based studies investigating the association between WMH and the risk of dementia are shown in Table 1. Overall, the association was significant for all types of dementia, and a meta-analysis [START_REF] Debette | The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and metaanalysis[END_REF] carried out on three of these five studies (Debette et al., 2010;[START_REF] Kuller | Risk factors for dementia in the cardiovascular health cognition study[END_REF][START_REF] Prins | Cerebral white matter lesions and the risk of dementia[END_REF] provided an HR of 2.9 (1. 3-6.3). Two studies distinguished between periventricular and deep (or subcortical) WMH (PWMH and DWMH respectively): Prins et al. showed that the association with risk of dementia was significant for PWMH only, whereas Meguro et al. found that these locations were both significantly associated with risk of dementia. Kuller et al. and Meguro et al. reported specific significant associations between WMH and risk of dementia other than AD. While Meguro et al. found no association with AD, Kuller et al. showed a slightly lower than for VaD and mixed dementia, but significant HR (1.5 (1.17-1.99)) in the association between WMH and risk of AD, which is in agreement with other studies [START_REF] Brickman | Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community[END_REF]Debette et al., 2010;[START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF] in which AD cases were the most frequent.

WMH and risk of dementia in MCI subjects

Results from studies investigating the association between WMH and the risk of dementia in MCI patients are shown in Table 2. Nine of the 12 studies assessed the relationship between WMH and risk of all types of dementia; all finding no significant association [START_REF] Bombois | Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients[END_REF][START_REF] Clerici | Does vascular burden contribute to the progression of mild cognitive impairment to dementia?[END_REF][START_REF] Decarli | Memory impairment, but not cerebrovascular disease, predicts progression of MCI to dementia[END_REF][START_REF] Devine | Do cerebral white matter lesions influence the rate of progression from mild cognitive impairment to dementia[END_REF][START_REF] Geroldi | Medial temporal atrophy but not memory deficit predicts progression to dementia in patients with mild cognitive impairment[END_REF][START_REF] Kantarci | Risk of dementia in MCI: combined effect of cerebrovascular disease, volumetric MRI, and 1H MRS[END_REF][START_REF] Korf | Medial temporal lobe atrophy on MRI predicts dementia in patients with mild cognitive impairment[END_REF][START_REF] Smith | Magnetic resonance imaging white matter hyperintensities and brain volume in the prediction of Mild Cognitive Impairment and dementia[END_REF][START_REF] Tapiola | MRI of hippocampus and entorhinal cortex in mild cognitive impairment: a follow-up study[END_REF]. Three studies [START_REF] Defrancesco | Impact of white matter lesions and cognitive deficits on conversion from mild cognitive impairment to Alzheimer's disease[END_REF][START_REF] Staekenborg | Progression of mild cognitive impairment to dementia: contribution of cerebrovascular disease compared with medial temporal lobe atrophy[END_REF][START_REF] Van Straaten | Periventricular white matter hyperintensities increase the likelihood of progression from amnestic mild cognitive impairment to dementia[END_REF] investigated the specific relationship between WMH and risk of AD: total WMH load was not significantly associated with risk of AD in any of these studies, and of the two studies [START_REF] Staekenborg | Progression of mild cognitive impairment to dementia: contribution of cerebrovascular disease compared with medial temporal lobe atrophy[END_REF][START_REF] Van Straaten | Periventricular white matter hyperintensities increase the likelihood of progression from amnestic mild cognitive impairment to dementia[END_REF] distinguishing between PWMH and DWMH, only one [START_REF] Van Straaten | Periventricular white matter hyperintensities increase the likelihood of progression from amnestic mild cognitive impairment to dementia[END_REF] showed a significant association between PWMH and risk of AD. Conversely, total WMH load [START_REF] Bombois | Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients[END_REF][START_REF] Staekenborg | Progression of mild cognitive impairment to dementia: contribution of cerebrovascular disease compared with medial temporal lobe atrophy[END_REF], and PWMH and DWMH [START_REF] Staekenborg | Progression of mild cognitive impairment to dementia: contribution of cerebrovascular disease compared with medial temporal lobe atrophy[END_REF] were significantly associated with risk of dementia other than AD.

WMH and cognitive decline in the general population

Results from studies investigating the association between WMH and cognitive decline in the general population are shown in Table 3. Among studies testing the relationship between WMH and global cognitive decline, results were discrepant: five studies [START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Inaba | White matter lesions on brain magnetic resonance imaging scan and 5year cognitive decline: the Honolulu-Asia aging study[END_REF][START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF][START_REF] Silbert | Cognitive impairment risk: white matter hyperintensity progression matters[END_REF][START_REF] Smith | Magnetic resonance imaging white matter hyperintensities and brain volume in the prediction of Mild Cognitive Impairment and dementia[END_REF] found a significant association, while the other 2 did not (Debette et al., 2010;[START_REF] Kuller | Relationship between ApoE, MRI findings, and cognitive function in the Cardiovascular Health Study[END_REF]. Among studies with positive results, studies distinguishing between PWMH and DWMH showed significant associations between PWMH and global cognitive decline [START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF][START_REF] Silbert | Cognitive impairment risk: white matter hyperintensity progression matters[END_REF], while negative results were reported for DWMH [START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF]. Regarding specific cognitive domains, a significant association was found for PWMH and decline in processing speed and executive functions [START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF], but not reaching significance for verbal fluency and memory [START_REF] Christensen | Education, atrophy, and cognitive change in an epidemiological sample in early old age[END_REF][START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF]. Conversely, Christensen et al. did not find a significant association between WMH and processing speed. However, little cognitive change is observed in this sample, in which participants are relatively young and have high levels of education. The neuropsychological tests used in these studies are, however, too limited in scope to conclude domain specific effects, and further research is required using functional imaging to ensure persons with WMH process information in the same way as those without.

Discussion

In this review, we examined the extent to which WMH may predict dementia or cognitive decline in both the general population and in MCI patients. Overall WMH load appears to be a significant predictor of all types of dementia in the general population, but not in MCI patients. This may of course partly reflect the inadequacy of MCI criteria. The association between WMH and risk of VaD or mixed dementia seems to be the most consistent irrespective of the population. Regarding cognitive decline, results are discrepant for global decline, but suggest the possibility of a specific relationship between WMH and decline in executive functions and processing speed, supporting findings from cross-sectional studies [START_REF] Murray | Functional impact of white matter hyperintensities in cognitively normal elderly subjects[END_REF][START_REF] Tullberg | White matter lesions impair frontal lobe function regardless of their location[END_REF].

The findings of this review show above all that the strength of the relationship between WMH and cognition varies according to the population and the cognitive dimension under consideration. As adequate estimations of reliability between visual scale ratings and automatic methods of WMH quantification have been reported [START_REF] Olsson | White Matter Lesion Assessment in Patients with Cognitive Impairment and Healthy Controls: Reliability Comparisons between Visual Rating, a Manual, and an Automatic Volumetrical MRI Method-The Gothenburg MCI Study[END_REF][START_REF] Valdes Hernandez Mdel | Close correlation between quantitative and qualitative assessments of white matter lesions[END_REF] it is unlikely that heterogeneity in the different WMH measurement methods over the different studies constitutes a significant cause of inconsistency. A number of alternative hypotheses may be postulated to explain the differences between studies:

1) The relationship between WMH and cognition is confounded by cognitive reserve

People may differ in their capacity to compensate for the deleterious effect of WMH, as has already been observed for some people with extensive AD histopathology (senile plaques and neurofibrillary tangles) who did not exhibit cognitive impairment before death [START_REF] Bennett | Education modifies the relation of AD pathology to level of cognitive function in older persons[END_REF]. The concept of "cognitive reserve" has been proposed to explain how neurodegenerative changes that are similar in nature and extent, may give rise to considerable variation in terms of cognitive consequences [START_REF] Stern | What is cognitive reserve? Theory and research application of the reserve concept[END_REF]. This may be defined as individual ability to make flexible and efficient use of available neuronal networks or active reserve [START_REF] Steffener | Exploring the neural basis of cognitive reserve in aging[END_REF], and differential capacity of the brain itself to cope with pathology or passive reserve.

Although one study did not find direct evidence to support the cognitive reserve hypothesis [START_REF] Christensen | Education, atrophy, and cognitive change in an epidemiological sample in early old age[END_REF], several others support the notion that reserve may influence the relationship between WMH and some cognitive domains [START_REF] Brickman | White matter hyperintensities and cognition: testing the reserve hypothesis[END_REF][START_REF] Dufouil | Influence of education on the relationship between white matter lesions and cognition[END_REF][START_REF] Murray | The balance between cognitive reserve and brain imaging biomarkers of cerebrovascular and Alzheimer's diseases[END_REF][START_REF] Nebes | The relation of white matter hyperintensities to cognitive performance in the normal old: education matters. Neuropsychology, development, and cognition[END_REF][START_REF] Saczynski | White matter lesions and cognitive performance: the role of cognitively complex leisure activity[END_REF][START_REF] Vemuri | Cognitive reserve and Alzheimer's disease biomarkers are independent determinants of cognition[END_REF] and in dementia [START_REF] Skoog | Head size may modify the impact of white matter lesions on dementia[END_REF] . The latter study was, however, cross-sectional [START_REF] Skoog | Head size may modify the impact of white matter lesions on dementia[END_REF], and used head size as a proxy of cognitive reserve, which is assumed to reflect the passive model. Moreover, WMH were estimated with CT scans which are less sensitive than MRI in detecting WMH.

In the Esprit Study [START_REF] Ritchie | Prevalence of DSM-IV psychiatric disorder in the French elderly population[END_REF], a cohort of people aged 65 years and over recruited from the electoral rolls in Montpellier (France), a significant interaction was found between WMH and education (a proxy of the active model of cognitive reserve); severe WMH significantly increasing the risk of developing MCI and dementia over a 7-year period in low educated participants, while subjects with higher education level were seen to be more likely to be resilient to the deleterious effects of severe WMH (Mortamais et al., 2013a).

Cognitive reserve could indeed balance the negative impact of pathological brain burden such as that of WMH on late life cognitive ability, acting through both protective and compensatory mechanisms. On the other hand, greater head size [START_REF] Coffey | Relation of education to brain size in normal aging: implications for the reserve hypothesis[END_REF], stronger myelination and more richly connected fiber tracts were observed in the white matter of highly educated people [START_REF] Teipel | White matter microstructure in relation to education in aging and Alzheimer's disease[END_REF], suggesting a link between the active and passive models. How cognitive reserve is implemented is still unclear, but this hypothesis suggests several avenues for dementia prevention. Inconsistencies between observations of the association between WMH and cognitive decline have to date not taken into account the notion of cognitive reserve, although most have adjusted by education, which is, however, a poor proxy for active reserve only.

2) The risk conferred by WMH may vary across the life-span with "vulnerability windows" determined by age and comorbidity

The observations obtained to date suggest that WMH are poor predictors of transition to dementia once cognitive impairment is present. The prevalence of WMH increases with advancing age [START_REF] Ylikoski | White matter hyperintensities on MRI in the neurologically nondiseased elderly. Analysis of cohorts of consecutive subjects aged 55 to 85 years living at home[END_REF] and it has been suggested that their relationship with vascular risk factors becomes less clear [START_REF] Breteler | Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study[END_REF][START_REF] O'sullivan | Hypertensive target-organ damage in the very elderly[END_REF][START_REF] Van Dijk | Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study[END_REF]. As observed for the pathological features of AD [START_REF] Haroutunian | Role of the neuropathology of Alzheimer disease in dementia in the oldest-old[END_REF][START_REF] Savva | Age, neuropathology, and dementia[END_REF], the importance of WMH in cognitive decline may change with advancing age. The few studies which have examined the relationship between WMH and cognition in the oldest old [START_REF] Firbank | Neuroimaging predictors of death and dementia in a cohort of older stroke survivors[END_REF][START_REF] Skoog | A population study of apoE genotype at the age of 85: relation to dementia, cerebrovascular disease, and mortality[END_REF] have indeed found no association in terms of either prevalence or incidence of dementia. This could reflect the fact that WMH accumulation stands out in younger subjects where it is less frequent, but at higher ages is indistinguishable from "normal" ageing-related cumulation not related to neurodegenerative disease.

These findings suggest that the association between increasing WMH volume and cognitive deterioration is less apparent with advancing age either due to loss of effect or masked by comorbidities which constitute risk factors in themselves.

3) WMH location may differentially determine risk

The assumption of much research in this area is that the impact on cognitive functioning is largely determined by the extent of WMH damage, whereas as is the case for other types of brain lesion, localization may be a more important factor.

WMH may cause cognitive impairment by disrupting cortical connections that are mediated by specific white matter tracts [START_REF] Smith | Correlations between MRI white matter lesion location and executive function and episodic memory[END_REF]. For instance, the strong association found between WMH and executive functioning would appear to be principally due to the presence of WMH in the frontal lobes [START_REF] Chen | Regional quantification of white matter hyperintensity in normal aging, mild cognitive impairment, and Alzheimer's disease[END_REF], prefrontal cortex and their associated cortical-cortical and cortical-subcortical connectivity [START_REF] Brickman | Regional white matter and neuropsychological functioning across the adult lifespan[END_REF]. As noted in the above review, periventricular WMH seem to better anticipate both dementia and cognitive impairment than deep WMH. Findings concerning this categorization remain controversial, and as De Carli et al. ( 2005) have pointed out, may simply reflect the capacity of these two locations to reflect total WMH volume.

Independently of periventricular or subcortical locations, conflicting results have been reported concerning the extent and spatial distribution of WMH in different brain regions in patients with MCI or dementia. While some studies did not find a particular regional distribution of WMH in AD [START_REF] Chen | Regional quantification of white matter hyperintensity in normal aging, mild cognitive impairment, and Alzheimer's disease[END_REF][START_REF] Gootjes | Regional distribution of white matter hyperintensities in vascular dementia, Alzheimer's disease and healthy aging[END_REF][START_REF] Holland | Spatial distribution of white-matter hyperintensities in Alzheimer disease, cerebral amyloid angiopathy, and healthy aging[END_REF], others found significantly higher WMH in parietal and posterior regions in AD [START_REF] Brickman | Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community[END_REF][START_REF] Yoshita | Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD[END_REF]. In both MCI and normal ageing white matter deterioration shows antero-posterior progression [START_REF] Artero | Neuroanatomical localisation and clinical correlates of white matter lesions in the elderly[END_REF][START_REF] Gao | Possible retrogenesis observed with fiber tracking: an anteroposterior pattern of white matter disintegrity in normal aging and Alzheimer's disease[END_REF]. The association between WMH in the parietal and posterior regions with the risk of MCI or dementia could be thus confounded by total WMH load. In the Esprit study, we observed that total WMH volume and percentage of WMH in the temporal region were the best predictors of progression to MCI and dementia. Specifically, severe total WMH load with a high proportion of hyperintensities in the temporal region was significantly associated with the risk of developing MCI or dementia [START_REF] Mortamais | Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia[END_REF]. The association between WMH and risk of MCI/dementia therefore appears to depend on both the extent and location of WMH, and further research is needed to determine which particular white matter structure in the temporal region is involved. This particular spatial distribution was observed in healthy subjects, before the onset of clinical symptoms, and may therefore facilitate the detection of patients at risk of MCI or dementia.

4) The impact of WMH on cognition is determined by other concurrent structural brain changes in aging and in AD

If the link between atrophy and HSB seems independent of age [START_REF] Appelman | White matter lesions and brain atrophy: more than shared risk factors? A systematic review[END_REF], it is not yet clear whether they are independent of other common risk factors, including vascular risk factors. In addition, their pathophysiological processes may be interdependent: ischemia due to cerebrovascular disease indeed damages the axons which correspond to cortical neurons and may be the cause of neuronal loss by retrograde degeneration. Whatever are the mechanisms that link brain atrophy and WMH, it seems necessary to consider the overall atrophy as potential confounding factor in studies investigating the relationship between cognition and WMH, in order to determine the specific impact of WMH regardless of this parameter which is also related to age and concomitant with WMH.

Furthermore, the fact that brain regions where WMH cluster in people who will develop cognitive deterioration colocalize to the distribution of AD pathology [START_REF] Braak | Neuropathological stageing of Alzheimer-related changes[END_REF], and that the associations between WMH and cognition persist after adjusting for vascular risk factors [START_REF] Bombois | Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients[END_REF][START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Inaba | White matter lesions on brain magnetic resonance imaging scan and 5year cognitive decline: the Honolulu-Asia aging study[END_REF][START_REF] Kuller | Risk factors for dementia in the cardiovascular health cognition study[END_REF] suggests that, in addition to its ischemic origin, WMH may have other etiologies. Other potential mechanisms have been suggested such as Wallerian degeneration that occurs secondary to neuronal loss [START_REF] Leys | Could Wallerian degeneration contribute to "leuko-araiosis" in subjects free of any vascular disorder[END_REF], or amyloid angiopathy [START_REF] Chen | Regional quantification of white matter hyperintensity in normal aging, mild cognitive impairment, and Alzheimer's disease[END_REF]. Alternatively, microvascular white matter disease may impair amyloid clearance and contribute consequently to βamyloid deposition in AD [START_REF] Grimmer | White matter hyperintensities predict amyloid increase in Alzheimer's disease[END_REF].

Other studies have, however, found no relationship between WMH and progression of AD-specific pathology [START_REF] Lo | Vascular burden and Alzheimer disease pathologic progression[END_REF]. Moreover, the association between WMH and cognition is not affected when adjusted for hippocampal volume or medial temporal lobe atrophy [START_REF] Bombois | Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients[END_REF][START_REF] Brickman | Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community[END_REF][START_REF] Mortamais | Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia[END_REF][START_REF] Silbert | Cognitive impairment risk: white matter hyperintensity progression matters[END_REF], hallmarks of neurodegeneration in AD on MRI, suggesting that the vascular contribution to dementia does exist and is probably additive with AD pathology [START_REF] Godin | Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study[END_REF][START_REF] Van Der Flier | Interaction of medial temporal lobe atrophy and white matter hyperintensities in AD[END_REF].

Conclusion

WMH appear to be early predictors of dementia. However, the strength of the association between WMH and cognition appears to be modulated by cognitive reserve, age and the spatial distribution of lesions. These factors should be taken into account in epidemiological studies investigating the contribution of vascular risk with WMH in dementia, or in clinical trials using WMH as surrogate marker.

There are however some limits in the use of WMH as a marker of vascular burden. In addition to their ischemic origin, WMH may be the result of co-occurring morbidity.

Appendix

The search strategy was carried out in two steps with the PubMed Advanced Search Builder. Results: 65 publications.

Funding

The ESPRIT Project is financed by the regional government of Languedoc-Roussillon, the Agence Nationale de la Recherche (ANR) and an unconditional grant from Novartis. This study is also supported by France Alzheimer. The follow-up at ten years is financed by the Fonds de coopération Alzheimer (FCA) and the ANR programme Longvie (ANR-07-LVIE-00301).

Further

  research is needed to disentangle the possible etiologies of WMH, in order to elucidate to what extent WMH actually reflect vascular risk and hence evaluate the likely efficacy of interventions specifically targeting WMH reduction.

  matter) OR periventricular) OR subcortical) OR leukoaraiosis[MeSH Terms]) AND (((((dementia[MeSH Terms]) OR alzheimer disease[MeSH Terms]) OR cognition[MeSH Terms]) OR cognition disorders[MeSH Terms])) AND (imaging, magnetic resonance[MeSH Terms]) AND ((((((longitudinal studies[MeSH Terms]) OR cohort studies[MeSH Terms]) OR follow up studies[MeSH Terms]) OR prospective studies[MeSH Terms]) OR risk factors[MeSH Terms])) AND ("1990/01/01"[Date -Publication] : "2013/03/01"[Date -Publication]). Results: 759 publications. 2) Second step This second step was carried out in order to select the more recent studies which MeSH Terms are not yet registered in PubMed (in process). ((white matter lesions[Title/Abstract]) OR (white matter hyperintensity[Title/Abstract])) AND (dementia[Title/Abstract]) AND ("2012/01/01"[Date -Publication] : "2013/03/01"[Date -Publication]).

Table 1 .

 1 Association between WMH and risk of dementia in the general population. Prospective studies, with assessment of WMH at baseline. VaD, vascular dementia; AD, Alzheimer"s disease; MD, mixed dementia; apoe, apolipoprotein E; PWMH, periventricular white matter hyperintensities; DWMH, deep white matter hyperintensities; SD, standard deviation; NS, no significant; DLB, dementia with Lewy bodies.

	27

Adjustment on age, sex, and infarcts on MRI.

Abbreviations : WMH, white matter hyperintensities ;

Table 3 .

 3 Association between WMH and cognitive decline in the general population. Prospective studies, with assessment of WMH at baseline. Adjustment on age, education, sex, low 3MSE at years 5 to 6, apoe 4 genotype infarcts, clinical and subclinical CVD at baseline, high ventricular volume, High sulci width, ethnicity. Decrease of 0.035 (0.003-0.066) point/year in MMSE score for PWMH -Significant decline for Stroop naming Test and Letter Digit Substitution Test for PWMH, (Processing speed, executive functions). No association with DWMH.

	Study	Follow-up	WMH quantification	Cognitive decline	Results
	Sample size (n)	period	methods	evaluation
	Mean age
	Cardiovascular Health	3-7 years Semi-quantitative (grade	Global decline (3MSE)	OR=1.4 (1.1-1.9) for a 3MSE score<80 at years 5
	Study (Kuller et al., 1998) n=3469 ≥ 65 years old		ranges 0 to 9). Dichotomization (> 3 vs. ≤3)		to 6. OR=1.20 (0.98-1.47) for a 3MSE score decrease ≤ 5.
	Rotterdam Scan Study	5.2 years	Semi-quantitative pour	Global decline (MMSE) +	Per SD increment
	(Prins et al., 2005) n=832 71 years old		PWMH (grade ranges 0 to 9). Quantitative for DWMH. PWMH et DWMH : variables continuous.	Processing speed, executive functions and (Stroop Test, Letter-Digit Substitution Task, Verbal Fluency Test, 15-word verbal learning test).	-Adjustment on age, sex, education and the interaction of age
					with time.
	General population	5.1 years	Quantitative.	Global decline: conversion	HR=3.30 (1.33-8.22) for severe WMH
	(Smith et al., 2008) n=67		(WMH volume/ intracranial volume)*100.	to MCI (CDR=0.5)	adjustment on apoe 4 genotype, age, sex, education,
	71.2 years old		Dichotomization: severe	n=26	smoking, CDR sum of boxes
			WMH > (mean % + 1 SD).
	Oregon Brain Aging	9.5 years	Quantitative.	Global decline: conversion	HR=1.04 (1.00-1.07) for increasing total WMH
	(Silbert et al., 2009) n=98 ≥ 65 years old		Continuous.	to persistent cognitive n=53 impairment (CDR≥0.5 for 2 consecutive follow-up).	HR=1.06 (1.01-1.10) for increasing PWMH Adjustment on age, hypertension, MMSE, APOE 4 genotype, intracranial and hippocampal volume.