PhD Muralidharan Sargurupremraj

PhD Aicha Soumare

PhD Joshua C Bis

PhD Ida Surakka

MSc Tuuli Jurgenson

PhD Pierre Joly

Maria J Knol

Ruiqi Wang

PhD Qiong Yang

PhD Claudia L Satizabal

Maria J Knol Msc

MSc Alexander Gudjonsson

PhD Aniket Mishra

PhD Vincent Bouteloup

MD Chia-Ling Phuah

PhD Cornelia M Van Duijn

PhD Carlos Cruchaga

PhD Carole Dufouil

MD Geneviève Chêne

MD Oscar Lopez

MD Bruce M Psaty

MD Christophe Tzourio

MD Philippe Amouyel

MD Hieab H Adams

PhD Hélène Jacqmin-Gadda

MD Mohammad Arfan Ikram

PhD Vilmundur Gudnason

PhD Lili Milani

MD Bendik S Winsvold

MD Kristian Hveem

MD, DPhil Paul M Matthews

MD W T Longstreth

MD Sudha Seshadri

PhD Lenore J Launer

MD Stéphanie Debette

Complexities of cerebral small vessel disease, blood pressure, and dementia relationship: new insights from genetics

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

Introduction

As life expectancy rises worldwide, the prevalence of dementia is expected to reach 75 million by 2030. [START_REF] Prince | Recent global trends in the prevalence and incidence of dementia, and survival with dementia[END_REF][START_REF] Wang | Global, regional, and national life expectancy, allcause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015[END_REF] Devising strategies to prevent or delay its occurrence is therefore a major public health priority. As has been documented over decades, it is now widely recognized by the scientific community that a majority of dementia cases, including Alzheimer's disease (AD) in the population are, in fact, due to a combination of vascular and neurodegenerative lesions. [START_REF] Viswanathan | Vascular risk factors and dementia How to move forward? VIEWS & REVIEWS[END_REF][START_REF] Zlokovic | Neurovascular pathways to neurodegeneration in Alzheimer's disease and other disorders[END_REF][START_REF] Skoog | 15-year longitudinal study of blood pressure and dementia[END_REF][START_REF] Nichols | The prevalence, correlation, and co-occurrence of neuropathology in old age: harmonisation of 12 measures across six community-based autopsy studies of dementia[END_REF] A large majority (80%) of patients with clinically diagnosed AD are found to have cerebrovascular lesions on post-mortem examinations. [START_REF] Toledo | Contribution of cerebrovascular disease in autopsy confirmed neurodegenerative disease cases in the National Alzheimer's Coordinating Centre[END_REF] Epidemiological and clinical studies have shown that stroke patients have at least a doubling of their risk for incident dementia. [START_REF] Savva | Epidemiological studies of the effect of stroke on incident dementia: A systematic review[END_REF][START_REF] Levine | Trajectory of Cognitive Decline After Incident Stroke[END_REF] At the population level, covert cerebral small vessel disease (cSVD), detectable on brain imaging in the absence of clinical stroke, is thought to be the main pathological substrate underlying the vascular contribution to cognitive decline and dementia, [START_REF] Wardlaw | Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration[END_REF] with nearly half of dementia cases exhibiting overlap of AD neuropathology with cSVD. [START_REF] Iadecola | The Pathobiology of Vascular Dementia[END_REF] White matter hyperintensity burden (WMH) is the most common magnetic resonance imaging (MRI) feature of covert cSVD. Evidence from observational studies has established strong associations of WMH with increased stroke and dementia risk, including AD, [START_REF] Debette | Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury[END_REF] yet with no proof of causality. Recently, a putative causal relation between WMH and AD has been suggested in a preliminary Mendelian randomization (MR) analysis that used genetic instruments as proxies for WMH volume, thus leveraging the natural randomization of genetic variation at conception to mitigate risks of confounding and reverse causation as seen in observational studies. [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] Intriguingly, however, while high blood pressure is by far the strongest risk factor for WMH and easily accessible to efficient therapy, several MR studies [START_REF] Burgess | Are Mendelian randomization investigations immune from bias due to reverse causation[END_REF] have reported inverse associations of genetically predicted blood pressure levels [START_REF] Evangelou | Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits[END_REF] with AD. These associations were observed both in datasets using standard AD diagnostic criteria (IGAP) [START_REF] Østergaard | Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study[END_REF][START_REF] Larsson | Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis[END_REF][START_REF] Andrews | Causal Associations Between Modifiable Risk Factors and the Alzheimer's Phenome[END_REF] and in studies using self-reported parental history as a proxy for AD diagnosis (UK Biobank). [START_REF] Sproviero | High Blood Pressure and Risk of Dementia: A Two-Sample Mendelian Randomization Study in the UK Biobank[END_REF] "Selective survivorship" [START_REF] Smit | Survival Bias in Mendelian Randomization Studies[END_REF] or age-dependent structural changes (arterial stiffness) [START_REF] Franklin | Hemodynamic Patterns of Age-Related Changes in Blood Pressure[END_REF] and neurodegenerative lesions in blood pressure regulated regions resulting in reverse causation have been discussed as possible hypotheses. [START_REF] Qiu | Decline in blood pressure over time and risk of dementia: A longitudinal study from the Kungsholmen project[END_REF][START_REF] Gregson | Blood pressure and risk of dementia and its subtypes: a historical cohort study with long-term follow-up in 2.6 million people[END_REF] These inconsistencies have led to many discussions about the causal role of vascular damage in AD, but an understanding of the contributions of specific vascular pathology is still limited. Indeed, understanding such causal relationships is crucial to prioritize interventions and target populations to prevent cognitive decline and dementia.

Based on the sharing of a large proportion of genetic risk variants between WMH and blood pressure (BP) traits, [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] we aim to address from a genetic epidemiologic perspective: 1) what are the putative causal associations of genetically defined different vascular pathologies to AD and all-cause-dementia; 2) what are the potential biases that may contribute to the MR associations.

Methods

The study design is summarized in Figure 1.

Analyses on summary level data

A comprehensive suite of MR-based analyses leveraging summary statistics of large GWAS was used to establish causality of associations between vascular traits (WMH, BP, stroke) and dementia and to test for alternative interpretations of causality. A P value < .017 correcting for 3 independent traits was considered significant.

Selection of genetic instruments for the vascular trait exposures in MR analyses

Independent genetic variants (single-nucleotide polymorphisms [SNPs]) that are genomewide significant (P < 5x10 -8 ) in large published GWAS and satisfying the instrumental variable definition [START_REF] Bowden | Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression[END_REF][START_REF] Swerdlow | Selecting instruments for Mendelian randomization in the wake of genome-wide association studies[END_REF] were considered as genetic instruments for each of the exposures. These were derived from GWAS of WMH on 50,970 participants, of stroke on 67,162/454,450 cases and controls, and of systolic blood pressure [SBP], diastolic blood pressure [DBP], and pulse pressure [PP] on up to 757,601 participants. [START_REF] Evangelou | Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits[END_REF][START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF][START_REF] Malik | Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes[END_REF] (eMethods). The Cragg-Donald F statistic was used to evaluate instrument strength (eMethods).

Dementia phenotypes used as outcomes in MR analyses

For the MR analyses, we used the GWAS summary statistics of clinically diagnosed lateonset AD (N=21,982/41,944 cases/controls) [START_REF] Kunkle | Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing[END_REF] and of the combination of clinical AD cases (n-cases=21,982) and proxy AD cases (n-cases=53,402) defined by parental history of dementia in the UK biobank (this combination being hereafter referred to as ADmeta, N=75,024/397844 cases/controls). [START_REF] Schwartzentruber | Genome-wide meta-analysis, finemapping and integrative prioritization implicate new Alzheimer's disease risk genes[END_REF] ADmeta is sometimes considered closer to a definition of all-cause-dementia than pure AD. [START_REF] Fongang | Genetic insights of all-cause and vascular dementia through genome-wide association studies[END_REF] In all instances AD diagnosis was based on clinical criteria and family history only, and not on neuropathology criteria (eMethods).

Suite of MR analyses

As a starting point the putative causal effect of a given risk factor (WMH, stroke, SBP, DBP, PP) on AD was estimated using a suite of instrumental variable analyses based on two-sample Mendelian randomization (2SMR). We first accounted for potential pleiotropic effects of genetic instruments (SNPs) directly on the outcome and that is uncorrelated with the exposure (uncorrelated pleiotropy) [START_REF] Smith | Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?[END_REF] using MR Egger, MR-RAPs, weighted median and mode based methods (eMethods). Second, we used MR-CAUSE to account for possible correlated pleiotropy, whereby genetic instruments are correlated with both exposure and outcome through the unmeasured confounders (eFigures 1-2 and eMethods). [START_REF] Morrison | Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics[END_REF] MR-CAUSE is a Bayesian approach that differentiates the causal model (𝛾) from the correlated-sharing (q) model based on the extent of the contribution of genetic instruments to the predicted effect. It provides a prediction accuracy (expected log pointwise posterior density, ELPD) for both models and their corresponding difference (ΔELPD=ELPD𝛾-ELPDq), which, if greater than zero, indicates that the causal model (𝛾) is a better fit than the correlated-sharing model (q) (eMethods). Third, for exposures for which MR-CAUSE suggested the causal model to be a better fit (ΔELPD > 0) but with significant residual effects in the sharing model (q), we performed multivariable MR conditioning for effects from potential confounders to confirm the putative causal relation using MVMR. [START_REF] Sanderson | An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings[END_REF] Finally, for exposures with significant MVMR association (P value < .013, for 4 independent traits) the following sensitivity analyses were conducted: i) using Qhet-MVMR, confounding due to potentially weak instruments was accounted for, and the effect direction was confirmed, [START_REF] Sanderson | Testing and Correcting for Weak and Pleiotropic Instruments in Two-Sample Multivariable Mendelian Randomisation[END_REF] and ii) causal direction among the multiple exposures was further determined using two-sample bidirectional MR (eMethods).

Analyses on individual level data from longitudinal cohort studies

We additionally conducted analyses on individual level data from prospective cohort studies to study the relation of genetically determined WMH burden, BP, and stroke with incident dementia outcomes in a longitudinal setting, while exploring the impact of potential selective survival bias. [START_REF] Swanson | A Practical Guide to Selection Bias in Instrumental Variable Analyses[END_REF]

Association analyses of weighted genetic risk scores for vascular traits with incident dementia

Analyses are based on genotype and phenotype information from 13 longitudinal cohorts (participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology [CHARGE], [START_REF] Psaty | Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: Design of prospective meta-analyses of genome-wide association studies from 5 cohorts[END_REF] and large biobanks (Trøndelag health study: HUNT, Estonian biobank: EstBB, and UK biobank: UKB). Nearly all cohorts were population-based, except MEMENTO (memory clinic patients with cognitive complaints and no dementia) and Knight ADRC. Together these cohorts included 157,698 unrelated participants of European origin, of whom 10,699 developed all-cause-dementia (which is more inclusive than ADmeta). Dementia diagnosis in these studies is based on standard criteria described in the eMethods along with the study design and participant selection. The mean age at dementia diagnosis across the cohorts is 71.4 years with a median duration of follow-up ranging between 3-25 years. Cox proportional hazard regression models were used to examine the association of genetic risk scores for the different exposures (WMH, stroke, BP traits) studied in the 2SMR analyses with incident all-cause-dementia. For each trait, we constructed an individual weighted genetic risk score (wGRS) using as weights the number of 'effect' alleles times the effect estimates (betas) of the respective genetic instruments constructed for a given exposure in the 2SMR analysis. [START_REF] Chouraki | Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease[END_REF] The wGRSs were standardized to have mean of 0 and a variance of 1, so that each unit change in the wGRS corresponds to one standard deviation (SD). Analyses were restricted to participants with at least one follow-up visit and no dementia at baseline. The Cox model with delayed entry included birth as time origin and age as the time scale and controlled for sex, education level, principal components of population stratification, and study-specific criteria (eTable 3). Data were censored at the age of dementia diagnosis for cases or age at the last follow-up for controls. Individual cohort-specific estimates were combined using a fixed-effects inverse variance weighted meta-analysis, implemented as an R (meta) package. Additional sensitivity analyses excluding individuals with a history of stroke at inclusion and adjusting for interim incident stroke were conducted (except in Knight ADRC where this information was not available).

Secondary analyses accounting for interval-censoring, competing risk of death, and dementia subtypes

These in-depth analyses were conducted in two large CHARGE cohorts (3C [Three city], AGES [Age, Gene/Environment Susceptibility -Reykjavik study]) with nearly identical characteristics (sample sizes, age distributions, and dementia ascertainment) (eMethods). We first explored whether survival bias during follow-up might affect our results using illness death models (IDMs) [START_REF] Touraine | SmoothHazard: An R Package for Fitting Regression Models to Interval-Censored Observations of Illness-Death Models[END_REF] accounting for interval-censoring of time-to-onset of dementia and competing risk of death. Second, we examined whether our vascular exposures of interest exhibit an association with different subtypes of incident dementia (all-cause-dementia, AD and vascular and/or mixed dementia, Supplementary Methods) at more liberal instrument selection thresholds using polygenic profile scores (PGSs), created by binning observations by p-value of the exposures in the original GWASs. A P value < .017 correcting for 3 independent traits was considered significant.

Results

Exploring causal relations of WMH, BP, and stroke with AD risk using GWAS summary-level data

The genetic instruments derived from GWAS of WMH, BP, and stroke strongly predicted the exposures, with a Cragg-Donald F statistic ranging between 22 and 65 (eTables 1-2). Using the inverse variance weighting method we found significant associations (P value < .017) of genetically determined larger WMH burden and lower BP (DBP, SBP, PP) levels with ADmeta (clinically diagnosed AD or parental dementia) risk (Figure 2, eTable 4a) and of lower DBP with clinically diagnosed AD risk (eFigure 3, eTable 5a). The complementary MR tools MR-RAPS, weighted-median and mode enabled us to robustly rule out uncorrelated pleiotropic effects (eTable 4b, 5b). The Bayesian MR-CAUSE method that accounts for correlated pleiotropy (Methods) supported a causal relation of WMH with both AD outcomes (clinical AD and ADmeta), with a posterior distribution of the causal model distinctively different from the sharing model (ΔELPD = 0.91 for AD; 0.50 for ADmeta) (eTable 6, eFigures 4-5). On the contrary, stroke and BP traits suggested a better fit of the sharing model with potential unmeasured confounders (ΔELPD < 0) than a causal model (eTable 6, eFigures 4-5). Notably, for WMH with AD and not for other exposure-outcome combinations, we observed the presence of a significant proportion of genetic instruments being shared with unmeasured confounders (q P value: 8.37x10 -9 , eFigure 5) along with a better fit of the causal model (ΔELPD > 0) (eTable 6). We, therefore, sought to confirm any putative causal association of WMH with AD in a multivariable analysis setting, adjusting for the effects of closely related traits using MVMR. Greater genetically predicted WMH burden was associated with a 27.8% increase in the probability of AD risk (OR: 1.28, CI:1.07-1.53, P=.008, per unit increase in WMH risk alleles) after accounting for PP effects (Figure 3,eTable 7). This represents a 16.5% increase in disease risk compared to the univariable estimates (OR:1.11, CI:0.95-1.31, P=. 19), with a consistent direction of effect. The effect of other exposures (stroke, BP traits) on AD remained non-significant using MVMR after adjusting for the closely related traits (eTable 7). Finally, a bidirectional MR analysis between the exposures showing significant MVMR results (WMH, PP) suggested a causal path of higher genetically predicted levels of PP with larger WMH burden (eTable 8).

Association of genetic risk scores for WMH, BP, and stroke with incident dementia using individual-level data

In a meta-analysis of thirteen longitudinal cohort studies, we observed a borderline significant association of increasing genetically predicted WMH burden with increased risk of incident all-cause-dementia (HR:1.02, CI:1.00-1.04, P=.06, per SD increase in WMH wGRS) (Figure 4, eTable 9). After adjusting for education and interim stroke, this association remained substantially unchanged (Figure 4). There was no significant heterogeneity across cohorts (I 2 : 7%, p=0.38; eFigure 6). Genetically determined BP traits and genetic liability to stroke failed to show significant associations with incident all-cause-dementia, with negative point estimates for stroke and SBP. Notably, all exposures showed at least a nominally significant association with increased risk for mortality, the most significant association being observed for SBP (eTable 9-10). In secondary analyses, using illness-death models (IDM) in two older population-based cohorts (3C, AGES, Methods), we ruled out potential biases related to competing risk of death during follow-up in the context of interval censoring. Indeed, per SD increase in genetically predicted WMH and BP levels, and genetic liability to stroke risk were not associated with incident all-cause-dementia in the IDM model, and the effect estimates were generally similar to those from the Cox model (eTable 11) in both cohorts. When examining the PGSs, where associations are binned according to significance of genetic instruments with less stringent instrument-significance thresholds (eMethods), we found that PGSs for WMH and stroke were significantly associated (P < .017) with increased all-causedementia risk in both cohorts (eTable 12-13, eFigures 7-8). In sensitivity analyses excluding prevalent stroke and adjusting for interim stroke, the WMH PGSs associations with dementia outcomes remained unchanged, while the stroke PGSs associations with dementia risk were markedly attenuated in both cohorts (eTable 13, eFigure 8). Meta-analyses of effect estimates from individual PGSs bins in 3C and AGES showed a significant association of WMH and stroke PGSs with increased risk of all-cause-dementia, AD, and (for stroke) vascular and/or mixed dementia (eTable 14). Finally, most of the PGSs for BP traits failed to show significant associations with dementia risk; the significant protective association observed between SBP/DBP PGSs and AD in the AGES cohort was attenuated in sensitivity analyses excluding prevalent stroke and adjusting for interim stroke (eTable 15).

Discussion

In this study capitalizing on a comprehensive MR workflow, large GWASs and numerous longitudinal cohort studies and biobanks, we report a putative causal association of genetically predicted WMH burden with increased risk of both clinically diagnosed AD [START_REF] Kunkle | Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing[END_REF] and ADmeta (AD and parental history of dementia). [START_REF] Schwartzentruber | Genome-wide meta-analysis, finemapping and integrative prioritization implicate new Alzheimer's disease risk genes[END_REF] The former association was strengthened after accounting for PP using multivariable MR. In contrast we observed protective effects of BP traits with ADmeta (all BP traits) and AD (DBP) risk using two-sample MR, [START_REF] Østergaard | Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study[END_REF][START_REF] Larsson | Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis[END_REF][START_REF] Andrews | Causal Associations Between Modifiable Risk Factors and the Alzheimer's Phenome[END_REF][START_REF] Sproviero | High Blood Pressure and Risk of Dementia: A Two-Sample Mendelian Randomization Study in the UK Biobank[END_REF] and provide evidence that these may at least partly be driven by the sharing of BP genetic instruments with unmeasured confounders. Genetic liability to stroke was not associated with AD or ADmeta. Next, using 13 large longitudinal cohorts and biobanks gathering 157,698 participants with prospective dementia surveillance (N=10,699 incident dementia cases), we report a similar, borderline significant association trend of WMH with increased risk of incident all-cause-dementia, while genetic instruments for BP traits and stroke showed no association. In a subset of population-based cohorts, polygenic scores (encompassing risk variants at less stringent significance thresholds than MR instruments) for WMH burden and stroke were associated with increased risk of incident all-cause-dementia, AD, and vascular and/or mixed dementia. While the association between stroke PGSs and all-cause-dementia attenuated markedly after adjusting for interim stroke, the WMH PGSs association with allcause-dementia remained significant.

Overall, out of all the vascular phenotypes considered (WMH, BP traits, stroke), genetic instruments for WMH appear to show the most robust associations with dementia risk, including ADmeta, AD, and all-cause-dementia. These MR findings suggest causal mechanisms and highlighting WMH as an important causal pathway to target for the prevention of dementia (Figure 5). Our results support association of extensive WMH burden with dementia and AD risks described in observational studies, [START_REF] Debette | Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury: A Systematic Review and Meta-analysis[END_REF][START_REF] Guo | White matter hyperintensities volume and cognition: A meta-analysis[END_REF][START_REF] Roseborough | White matter hyperintensities and longitudinal cognitive decline in cognitively normal populations and across diagnostic categories: A meta-analysis, systematic review, and recommendations for future study harmonization[END_REF][START_REF] Hu | White matter hyperintensities and risks of cognitive impairment and dementia: A systematic review and meta-analysis of 36 prospective studies[END_REF][START_REF] Debette | The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis[END_REF] providing additional strong evidence for a possible causal relation. This reinforces our earlier preliminary observations of a putative causal association of WMH with ADmeta, [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] and expands it to a larger ADmeta GWAS resource, [START_REF] Schwartzentruber | Genome-wide meta-analysis, finemapping and integrative prioritization implicate new Alzheimer's disease risk genes[END_REF] and, importantly also to a smaller and more conservative definition of only clinically diagnosed AD. [START_REF] Kunkle | Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing[END_REF] The fact that the latter association was more prominent after accounting for PP effects in a multivariable model, with a 16.5% increase in the disease risk compared to the univariable estimates, is intriguing. PP is a marker of the pulsatile component of BP and is correlated with measures of arterial stiffness, [START_REF] Niiranen | Relative Contributions of Pulse Pressure and Arterial Stiffness to Cardiovascular Disease[END_REF][START_REF] Safar | Arterial stiffness, pulse pressure, and cardiovascular disease-is it possible to break the vicious circle?[END_REF] which was suggested to promote both white matter pathology and amyloid deposition. [START_REF] Hughes | Pulse wave velocity is associated with beta-amyloid deposition in the brains of very elderly adults[END_REF]47 Interestingly, recent evidence for a causal relation of arterial stiffness with larger WMH burden was found to be reinforced after accounting for PP, [START_REF] Francis | GENOME-WIDE ASSOCIATIONS OF AORTIC DISTENSIBILITY SUGGEST CAUSAL RELATIONSHIPS WITH AORTIC ANEURYSMS AND BRAIN WHITE MATTER HYPERINTENSITIES[END_REF] in line with the present findings. Underlying mechanisms are speculative, but could potentially involve oxidative stress, implicated in BPassociated vascular damage [START_REF] Rodrigo | The role of oxidative stress in the pathophysiology of hypertension[END_REF] and also an early and prominent feature of aging and neurodegeneration. [START_REF] Kim | The Role of Oxidative Stress in Neurodegenerative Diseases[END_REF] Elevated PP may dysregulate brain endothelial cells and increase cellular production of oxidative and inflammatory molecules, which may in turn increased amyloid-β secretion by cerebral endothelial cells and induce blood-brain barrier breakdown. 51- 53 Interestingly, although WMH is known to be associated with increased risk of stroke, [START_REF] Debette | Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury[END_REF][START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] and stroke with a substantial increase in dementia incidence, [START_REF] Pendlebury | Prevalence, incidence, and factors associated with prestroke and post-stroke dementia: a systematic review and meta-analysis[END_REF][START_REF] Pendlebury | Incidence and prevalence of dementia associated with transient ischaemic attack and stroke: analysis of the populationbased Oxford Vascular Study[END_REF][START_REF] Koton | Association of Ischemic Stroke Incidence, Severity, and Recurrence With Dementia in the Atherosclerosis Risk in Communities Cohort Study[END_REF] associations of WMH PGSs with risk of dementia were unchanged after accounting for baseline and interim stroke, suggesting an independent effect of WMH on dementia risk.

High blood pressure is the strongest known risk factor for WMH and other MRI-markers of cSVD, with MR studies suggesting a causal relation of increasing genetically determined BP with WMH volume, even in persons without clinically defined hypertension. [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] Moreover, evidence from randomized controlled trials shows that WMH volume progression is slowed down by BP-lowering treatments in hypertensive individuals, [START_REF] Kjeldsen | Intensive blood pressure lowering prevents mild cognitive impairment and possible dementia and slows development of white matter lesions in brain: the SPRINT Memory and Cognition IN Decreased Hypertension (SPRINT MIND) study[END_REF][START_REF] Dufouil | Effects of blood pressure lowering on cerebral white matter hyperintensities in patients with stroke: the PROGRESS (Perindopril Protection Against Recurrent Stroke Study) Magnetic Resonance Imaging Substudy[END_REF][START_REF] De Havenon | Blood pressure, glycemic control, and white matter hyperintensity progression in type 2 diabetics[END_REF][START_REF] White | Effects of Intensive Versus Standard Ambulatory Blood Pressure Control on Cerebrovascular Outcomes in Older People (INFINITY)[END_REF][START_REF] Wardlaw | ESO Guideline on covert cerebral small vessel disease[END_REF] especially by intensive vs. standard BP-lowering. [START_REF] Wardlaw | ESO Guideline on covert cerebral small vessel disease[END_REF] Given the aforementioned associations of genetically determined WMH with dementia and AD it therefore appears "counterintuitive" to observe an inverse association of genetically determined high BP with lower risk of ADmeta and AD in our twosample MR analysis. It is however in line with earlier MR studies deriving instruments from earlier, smaller BP GWAS or using genetic proxies for the effect of BP-lowering drugs. [START_REF] Østergaard | Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study[END_REF][START_REF] Larsson | Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis[END_REF][START_REF] Andrews | Causal Associations Between Modifiable Risk Factors and the Alzheimer's Phenome[END_REF][START_REF] Sproviero | High Blood Pressure and Risk of Dementia: A Two-Sample Mendelian Randomization Study in the UK Biobank[END_REF][START_REF] Walker | Repurposing antihypertensive drugs for the prevention of Alzheimer's disease: a Mendelian randomization study[END_REF] Our sensitivity analyses suggest that this unexpected directionality of association might at least partly be explained by pleiotropic effects from unmeasured confounders (MR-CAUSE), prompting caution with applying methods designed only to remove or downweigh pleiotropic variants (e.g., weighted median based MR methods).

Moreover, while we saw suggestive evidence for selective survival during follow-up, given the late age of onset of dementia (85 years on average 63 ), the strong association of high BP and stroke with premature death in our longitudinal data and extensive evidence from other studies, [START_REF] Perkovic | The Burden of Blood Pressure-Related Disease[END_REF][START_REF] Miura | Relationship of Blood Pressure to 25-Year Mortality Due to Coronary Heart Disease, Cardiovascular Diseases, and All Causes in Young Adult Men[END_REF][START_REF] Forouzanfar | Global Burden of Hypertension and Systolic Blood Pressure of at Least 110 to 115 mm Hg, 1990-2015[END_REF][START_REF] Seshadri | Lifetime risk of stroke and dementia: current concepts, and estimates from the Framingham Study[END_REF] it is possible that the apparent protective effect of high BP on dementia risk could potentially reflect selective survival bias before entry into the study. Indeed, if the selection is a function of the exposure or the outcome, it could result in collider (index event) bias, [START_REF] Dudbridge | Adjustment for index event bias in genome-wide association studies of subsequent events[END_REF] leading to an association in the absence of a causal effect. [START_REF] Boef | Mendelian randomization studies in the elderly[END_REF][START_REF] Munafò | Collider scope: when selection bias can substantially influence observed associations[END_REF][START_REF] Cole | Illustrating bias due to conditioning on a collider[END_REF] While we did not see any evidence for selective survival during follow-up using the illness-death model in our longitudinal cohorts, we cannot formally rule out selective survival before study entry. Although non-significant, the association of genetically determined PP and DBP with incident all-cause-dementia had point estimates above 1 in the longitudinal cohort studies, which are likely less exposed to selective survival than the AD case-control GWAS used for the 2SMR analyses, although they also tend to overrepresent healthy individuals at inclusion (as for any voluntary participation). [START_REF] Delgado-Rodriguez | Bias[END_REF][START_REF] Manolio | New models for large prospective studies: is there a better way?[END_REF][START_REF] Fry | Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population[END_REF] Beyond these possible biases our results highlight the complexity of the relation between BP and dementia risk, with weak epidemiological evidence varying by age. [START_REF] Launer | Midlife blood pressure and dementia: the Honolulu-Asia aging study[END_REF][START_REF] Qiu | The age-dependent relation of blood pressure to cognitive function and dementia[END_REF][START_REF] Tzourio | Is Hypertension Associated With an Accelerated Aging of the Brain?[END_REF] Recent meta-analyses of clinical trials show evidence that antihypertensive medication reduces risk of secondary outcomes combining dementia with cognitive impairment, [START_REF] Ding | Antihypertensive medications and risk for incident dementia and Alzheimer's disease: a meta-analysis of individual participant data from prospective cohort studies[END_REF][START_REF] Hughes | Association of Blood Pressure Lowering with Incident Dementia or Cognitive Impairment: A Systematic Review and Meta-analysis[END_REF] but not dementia alone. In a meta-analysis of 6 population-based cohorts, antihypertensive medication was associated with a reduced risk of incident dementia and AD in individuals with clinically defined high BP at baseline. [START_REF] Ding | Antihypertensive medications and risk for incident dementia and Alzheimer's disease: a meta-analysis of individual participant data from prospective cohort studies[END_REF] However in another recent metaanalysis of 7 population-based cohorts, dementia risk appeared lower for older individuals with higher SBP levels, with more distinctly U-shaped associations for participants older than 75 years, which were not explained by SBP-associated changes in mortality risk. [START_REF] Van Dalen | Association of Systolic Blood Pressure With Dementia Risk and the Role of Age, U-Shaped Associations, and Mortality[END_REF] In contrast with BP measurements, which show high intra-individual variability, [START_REF] Parati | Assessment and management of bloodpressure variability[END_REF] WMH volume is also a more stable marker, reflecting white matter damage secondary to changes in structure or function of cerebral small vessels. Assuming that WMH at least partly mediates the association of BP with dementia in the population, WMH may better capture the brain damage caused by BP than BP itself. WMH and covert cSVD more broadly likely also reflects the impact of other parameters on white matter integrity, including other risk factors for cSVD such as cerebral amyloid angiopathy, or factors influencing the resilience of the brain white matter to vascular insults. Given the high prevalence of WMH in the general population in the absence of clinical stroke, [START_REF] Launer | Midlife blood pressure and dementia: the Honolulu-Asia aging study[END_REF][START_REF] Qiu | The age-dependent relation of blood pressure to cognitive function and dementia[END_REF][START_REF] Tzourio | Is Hypertension Associated With an Accelerated Aging of the Brain?[END_REF] our results highlight WMH as a major causal pathway to consider for the prevention of dementia (Figure 5).

Strengths and Limitations

Strengths of our study include the diversity and complementarity of the analytical approaches used, ranging from various state-of-the-art MR analyses, based on powerful published GWAS, to longitudinal analyses in large population-based cohort studies with prospective dementia ascertainment. We also acknowledge limitations. First, the GWASs used for the MR analyses have likely predominantly recruited patients with clinically diagnosed AD, thus leading to an underrepresentation of patients with mixed dementia, who likely represent the majority of AD cases in the population. Second, in our longitudinal analyses, the number of incident dementia cases remained modest, with some differences in the methods for dementia ascertainment, thus limiting power to detect associations. Third, we considered only one MRImarker for cSVD, WMH, for which there is most evidence for an association with dementia risk and the strongest genetic instruments. With increasing availability of larger GWAS for other MRI-cSVD markers (cerebral microbleeds, lacunes, perivascular spaces) future studies concomitantly assessing the impact of various genetically determined MRI-cSVD markers are warranted. [82][START_REF] Willey | White matter hyperintensity volume and impaired mobility among older adults[END_REF][START_REF] Rensma | Cerebral small vessel disease and risk of incident stroke, dementia and depression, and all-cause mortality: A systematic review and meta-analysis[END_REF][START_REF] Phuah | Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies[END_REF] Finally, validation of our findings in populations of non-European ancestry, as larger datasets become available, will be crucial.

Conclusions

In summary, our findings provide converging evidence that WMH is a leading vascular contributor to dementia risk and should be targeted in priority for the prevention of cognitive decline and dementia in the population. They also support WMH as a relevant surrogate marker for clinical trials testing interventions to prevent dementia by better controlling vascular risk. [START_REF] Wardlaw | ESO Guideline on covert cerebral small vessel disease[END_REF][START_REF] Brown | Rate of, and risk factors for, white matter hyperintensity growth: a systematic review and meta-analysis with implications for clinical trial design[END_REF] Our data also prompt caution when interpreting MR studies where the outcome of interest is a late-onset disease such as dementia, especially if the instrument for the exposure of interest shows a strong association with survival. They highlight the importance of combining several complementary epidemiological approaches to compensate for respective limitations and of combining different studies, cohorts and biobanks rather than drawing definitive conclusions on single datasets to minimize the impact of study-specific shortcomings and biases.

Figures:

Figure 1 :

 1 Figure 1: Study workflow

Figure 2 :

 2 Figure 2: Mendelian randomization results of vascular risk factors with ADmeta.

Figure 3 :

 3 Figure 3: Multivariable Mendelian randomization (MVMR) along with the univariable MR for AD as the outcome.

Figure 4 :

 4 Figure 4: Forest plot showing the meta-analysis results of risk factor wGRSs (per standard deviation increase) with incident ACD.

Figure 5: Central role of WMH with dementia outcomes. VaD: Vascular dementia, B: baseline, P(S): probability of survival bias. Thick background arrows indicate inferences made from observational studies, and solid coloured lines indicate inferences from univariable Mendelian randomization studies. Orange dots and dashed lines represent the multivariable MR setting.