Yunju Yang

Maria J Knol

Ruiqi Wang

Aniket Mishra

Dan Liu

Michelle Luciano

Alexander Teumer

Nicola Armstrong

Joshua C Bis

Min A Jhun

Shuo Li

Hieab H H Adams

Ahmad Nasir

Aziz

Mark E Bastin

Mathieu Bourgey

Jennifer A Brody

Stefan Frenzel

Rebecca F Gottesman

Norbert Hosten

Lifang Hou

Sharon L R Kardia

Valerie Lohner

Pascale Marquis

Susana Muñoz Maniega

Claudia L Satizabal

Farzaneh A Sorond

Maria C Valdés Hernández

Cornelia M Van Duijn

Meike W Vernooij

Katharina Wittfeld

Qiong Yang

Wei Zhao

Eric Boerwinkle

Daniel Levy

Ian J Deary

Jiyang Jiang

Karen A Mather

Thomas H Mosley

Bruce M Psaty

Perminder S Sachdev

Jennifer A Smith

Nona Sotoodehnia

Charles S Decarli

Monique M B Breteler

M Arfan Ikram

Hans J Grabe

Joanna Wardlaw

W T Longstreth

Lenore J Launer

Sudha Seshadri

Stephanie Debette

PhD Myriam Fornage
email: myriam.fornage@uth.tmc.edu

Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI

Keywords: epigenome-wide association study, white matter hyperintensities, cerebral small vessel disease, integrative cross-omics analysis, blood-brain barrier dysfunction

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

Abstract

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention.

We investigated the association between white matter hyperintensity burden and DNA methylation in blood at approximately 450,000 CpG sites in 9,732 middle-aged to older adults from 14 community-based studies. Single-CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities.

We identified 12 single-CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P=7.6x10 -8 ), was associated with F2 expression in blood (P=6.4x10 -5 ), and colocalized with FOLH1 expression in brain (posterior probability =0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single-CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P=0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis, and multi-omics colocalization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genomewide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug repositioning analysis indicated antihyperlipidemic agents, more specifically peroxisome proliferator-activated receptor alpha, as possible target drugs for white matter hyperintensities.

Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood brain barrier disruption. vessel disease (cSVD) and are part of the spectrum of brain vascular injury that impacts cognitive function, also known as vascular contributions to cognitive impairment and dementia (VCID). [START_REF] Pantoni | Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges[END_REF][START_REF] Wardlaw | Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies[END_REF] While the pathophysiology of WMH is little understood and likely heterogeneous, it likely has ischemic and neurodegenerative origins. [START_REF] Pantoni | Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges[END_REF] Historical pathology data suggested chronic ischemia resulting in demyelination and axonal loss as an underlying mechanism; however, neuroimaging data point to blood-brain barrier dysfunction, dysfunctional blood flow linked with impaired cerebrovascular autoregulation, vascular stiffness, periarteriolar inflammation, and more recently protein deposition (i.e. amyloid angiopathy). [START_REF] Wardlaw | Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies[END_REF] Genetics plays a significant role in WMH with a heritability estimated from 54 to 80% [START_REF] Carmelli | Evidence for genetic variance in white matter hyperintensity volume in normal elderly male twins[END_REF][START_REF] Atwood | Genetic variation in white matter hyperintensity volume in the Framingham Study[END_REF][START_REF] Kochunov | Analysis of genetic variability and whole genome linkage of whole-brain, subcortical, and ependymal hyperintense white matter volume[END_REF][START_REF] Turner | Heritability of leukoaraiosis in hypertensive sibships[END_REF][START_REF] Duperron | Burden of Dilated Perivascular Spaces, an Emerging Marker of Cerebral Small Vessel Disease, Is Highly Heritable[END_REF] ; however, the genetic variants identified in association studies explain only ~29% of WMH variance. [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF][START_REF] Jian | Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging[END_REF] Epigenetic changes such as DNA methylation (DNAm), which regulate gene expression, have emerged as another key component of the genetic architecture of complex traits. [START_REF] Handel | Epigenetics: molecular mechanisms and implications for disease[END_REF] Unlike DNA sequence variation, which remains unchanged throughout life, DNAm is plastic and highly sensitive to changes in the environment and aging. [START_REF] Handel | Epigenetics: molecular mechanisms and implications for disease[END_REF][START_REF] Jaenisch | Epigenetic regulation of gene expression: How the genome integrates intrinsic and environmental signals[END_REF] To date, its role in cSVD has received little attention. We hypothesized that there may be patterns of DNAm associated with WMH that are common across all populations. We also hypothesized that the interplay between genotype, epigenotype, and risk factor exposure underlies cSVD etiology and used an integrated analytic framework to identify such relationships.

Materials and methods

Overview

This study comprises five analytic parts to implicate novel genes and gene networks in WMH etiology (Figure 1). First, we performed an epigenome-wide association analysis to identify DNAm loci, both cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs), associated with WMH burden. The identified DNAm loci were then annotated for regulatory features, pathways, and association with other traits. Second, we investigated the contribution of genetic variation to variation in DNAm at the identified CpGs and used Mendelian randomization (MR) techniques to test for causal association with WMH burden and for the mediating role of expression of nearby genes. Third, we examined the role of DNAm at established WMH genome-wide association study (GWAS) loci. Fourth, we integrated gene expression and expression quantitative trait loci (eQTL) data to prioritize candidate genes associated with the identified CpGs. Lastly, we performed integrative cross-omics analyses to derive WMH-associated genes networks and their key drivers and to reposition drug targets.

Study subjects

The sample included 9,732 middle-aged to older adults of European (EA) and African ancestry (AA) from 14 community-based studies. Our discovery sample includes 5,715 subjects of European ancestry (EA, n=4,610) and of African ancestry (AA, n=1,105) from Atherosclerosis Risk in Communities (ARIC), [START_REF] Wright | The ARIC (Atherosclerosis Risk In Communities) Study: JACC Focus Seminar 3/8[END_REF] Biobanking and BioMolecular resources Research Infrastructure (BBMRI), [START_REF]BBMRI Stakeholder's Forum. BBMRI: A Step Closer -Stakeholder's Forum Report[END_REF] Cardiovascular Health Study (CHS), [START_REF] Fried | The Cardiovascular Health Study: design and rationale[END_REF] Coronary Artery Risk Development in Young Adults (CARDIA), [START_REF] Friedman | CARDIA: study design, recruitment, and some characteristics of the examined subjects[END_REF] Framingham Heart Study (FHS) offspring study, [START_REF] Dawber | The Framingham study. An epidemiological approach to coronary heart disease[END_REF][START_REF] Feinleib | The Framingham Offspring Study. Design and preliminary data[END_REF] Genetic Epidemiology Network of Arteriopathy (GENOA) study, [START_REF] Daniels | Familial aggregation of hypertension treatment and control in the Genetic Epidemiology Network of Arteriopathy (GENOA) study[END_REF] Lothian Birth Cohort (LBC) 1936, [START_REF] Wardlaw | Brain aging, cognition in youth and old age and vascular disease in the Lothian Birth Cohort 1936: rationale, design and methodology of the imaging protocol[END_REF][START_REF] Deary | The Lothian Birth Cohort 1936: a study to examine influences on cognitive ageing from age 11 to age 70 and beyond[END_REF] Rotterdam Study (RS), [START_REF] Ikram | Objectives, design and main findings until 2020 from the Rotterdam Study[END_REF][START_REF] Ikram | The Rotterdam Scan Study: design update 2016 and main findings[END_REF] and Study of Health in Pomerania (SHIP) [START_REF] Volzke | Cohort profile: the study of health in Pomerania[END_REF] . To replicate our findings, we accessed data on 3,398 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI), [START_REF] Khachaturian | Perspective on the Alzheimer's disease neuroimaging initiative: progress report and future plans[END_REF][START_REF] Petersen | Alzheimer's disease neuroimaging initiative (ADNI): clinical characterization[END_REF] FHS 3 rd generation study, [START_REF] Splansky | The third generation cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination[END_REF] the Older Australian Twin Study (OATS), [START_REF] Sachdev | Cognitive functioning in older twins: The Older Australian Twins Study[END_REF][START_REF] Sachdev | A comprehensive neuropsychiatric study of elderly twins: the Older Australian Twins Study[END_REF] and the Rhineland study [START_REF] Breteler | P2-135: The Rhineland study: a novel platform for epidemiologic research into Alzheimer disease and related disorders[END_REF] . Additionally, we included a secondary replication sample (n=619) from the BRIDGET consortium. [START_REF]BRIDGET: BRain Imaging, cognition, Dementia and next generation GEnomics[END_REF] Subjects with history of stroke or dementia were excluded. Details about participating studies and study-specific ethics statements are provided in Supplementary Data I. Each study obtained written informed consent from all participants and approval from the appropriate institutional review boards.

WMH burden measurements

Brain MRI was taken in the same or the closest subsequent visit to the visit in which DNAm was measured. In each study, MRI scans were performed and interpreted using standardized procedures without reference to demographic or clinical information. The field strength of the scanners used ranged mostly from 1.5 to 3.0 Tesla. T1-, T2-, and/or protondensity-weighted scans were obtained for all participants. The majority of the studies used fully automated segmentation method to quantify WMH burden. MRI procedures and WMH

DNAm profiling

DNAm levels were measured at ~450K CpGs from whole blood samples with the Illumina Infinium Human450 Methylation BeadChip in most participating cohorts. GENOA study measured methylation levels at ~27K CpGs with the Illumina Infinium HumanMethylation 27 BeadChip, entirely covered by the Human450 BeadChip. CARDIA, SHIP-TREND, ADNI, and Rhineland Study used the Illumina MethylationEPIC BeadChip with a denser coverage of CpGs (~850K). Each study independently performed quality control (QC) for DNAm data, complying with the agreed minimum QC guidelines; CpGs with more than 95% of samples with a detection P<0.01 and samples with more than 95% of CpGs with a detection P <0.01 were selected. DNAm values were then standardized using an intra-array normalization method. The BRIDGET Consortium measured DNAm levels using Hi-seq bisulfate sequencing, and DNAm sites with sample coverage less than 95% were excluded. Details of DNAm data collection and processing in participating studies are presented in Supplementary Data III.

Cohort-level epigenome-wide association analyses

We tested association between DNAm level (untransformed beta values) and WMH burden (ln(WMH+1)) using a linear mixed regression model by ancestry group adjusted for age, sex, study site if applicable, total (intra)cranial volume (cm 3 ), white blood cell proportion (%), [START_REF] Houseman | DNA methylation arrays as surrogate measures of cell mixture distribution[END_REF] and within-ancestry principal components (PCs) as fixed effects and technical covariates (i.e. plate, chip-position, row, and column) as random effects. In FHS, family structure is also adjusted as a random effect. Multi-ancestry studies with a small number of subjects in each ancestry, namely CHS and CARDIA, performed a pooled-ancestry analysis that also adjusted for ancestry group as fixed effects. Additionally, subgroup analyses by hypertension status were conducted. Hypertension was defined if either systolic or diastolic blood pressure (SBP or DBP) is greater than 140 mmHg or 90 mmHg, respectively, or if a subject was taking any antihypertensive medication at the time of MRI measurement. In the BRIDGET study, we tested the association of DNAm with an extreme-SVD phenotype defined as excessive WMH volume with or without brain infarcts accounting for age, sex, country, the sequencing read counts, and sample relatedness. [START_REF] Mishra | Association of variants in HTRA1 and NOTCH3 with MRI-defined extremes of cerebral small vessel disease in older subjects[END_REF] DNAm measurements and statistical models used in participating studies are

Epigenome-wide meta-analysis and replication analysis

We combined EWAS results based on sample-size-weighted z-score-based fixed-effect method in METAL [START_REF] Willer | METAL: fast and efficient meta-analysis of genomewide association scans[END_REF] because WMH was measured on different scales in the various cohorts and because our primary aim was to identify novel DNA methylation loci for WMH burden rather than estimate effect sizes of methylation probes. [START_REF] Pereira T V, Patsopoulos | Discovery properties of genome-wide association signals from cumulatively combined data sets[END_REF] Hypertensive and normotensive subgroup meta-analyses and ancestry-specific meta-analyses (excluding CHS and CARDIA) were also performed. Study-specific results were corrected for inflation during meta-analysis if inflation was detected (genomic inflation factor (λ)>1.0). An association was considered as significant if P is smaller than Bonferroni threshold (approximately 1.2x10 -7 ). A less stringent threshold was also set as 1.0x10 -5 to detect suggestive associations. CpGs on sex chromosomes were not considered because our analytic plan did not account for hemi-methylation on the X chromosome due to chromosome X inactivation in women. Cross-reactive CpGs reported by Chen et al. [START_REF] Chen Y An | Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray[END_REF] and those showing evidence of heterogeneity (Cochran Q P-value <0.05) were removed from the results post hoc. In the replication samples, associations for the identified CpGs were tested. CpGs were considered replicated if they were significant at the Bonferroni threshold (0.05/the number of the CpGs). We plotted epigenetic associations in cis (±50 kb) using R 'coMET' package. [START_REF] Martin | coMET: visualisation of regional epigenome-wide association scan results and DNA co-methylation patterns[END_REF]

Annotation of regulatory features and traits

We scored genomic positions of the identified CpGs according to RegulomeDB's [START_REF] Boyle | Annotation of functional variation in personal genomes using RegulomeDB[END_REF] ranking criteria ranging from one (likely to affect binding and linked to expression of a gene target) to five (minimal binding evidence) and also computed a probability score within a range from zero to one (the most likely to be a regulatory variant). CpGs at the locations with significant regulatory features (rank category one or two, and probability score 0.9) are discussed. We also identified enhancers or promoters mapped to CpGs using the database of genome-wide enhancer-to-gene or promoter-to-gene associations computed based on five elements: eQTLs, eRNA co-expression, transcription factor co-expression, capture Hi-C and gene target distance (GeneHancer DB). [START_REF] Fishilevich | GeneHancer: genome-wide integration of enhancers and target genes in GeneCards[END_REF] Identified CpGs were also searched in EWAS catalog [START_REF] Battram | The EWAS Catalog: A Database of Epigenome-wide Association Studies[END_REF] and EWAS atlas [START_REF] Li | EWAS Atlas: a curated knowledgebase of epigenome-wide association studies[END_REF] to identify associated traits reported in previous EWAS. Lastly, to examine possible correlations among the CpGs, Spearman correlations were calculated in 906 EA and 639

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AA subjects from the ARIC study.

DMR analysis

We performed a DMR analysis to identify a group of CpGs that collectively influence WMH burden using two specific methods, Comb-p [START_REF] Pedersen | Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values[END_REF] and DMRcate [START_REF] Peters | De novo identification of differentially methylated regions in the human genome[END_REF] , accounting for their spatial correlations. Briefly, Comb-p detects regional enrichment of low Ps at varying distance using the Stouffer-Liptak-Kechris correction for adjacent Ps. [START_REF] Pedersen | Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values[END_REF] DMRcate models Gaussian kernel smoothing within pre-defined distance (1Kbp in this study) and collapses contiguous significant CpGs (P <0.05) after multiple testing correction. DMR identified by both Comb-p (Šidák P <0.05) and DMRCate (FDR <0.05) was considered significant. To replicate, individual association Ps were pooled at each identified DMRs using DMRCate in the replication samples.

Gene set enrichment analysis of WMH-associated epigenetic Loci

Identified CpGs and DMRs were tested for enrichment in gene sets from MSigDB c5 gene ontology database [START_REF] Subramanian | Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles[END_REF][START_REF] Liberzon | The Molecular Signatures Database (MSigDB) hallmark gene set collection[END_REF] and KEGG pathway database [START_REF] Kanehisa | KEGG: kyoto encyclopedia of genes and genomes[END_REF] , using 'gsameth' and 'gsaregion' functions built in R 'missMethyl' package [START_REF] Phipson | missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform[END_REF] .

Shared epigenetics with BP

BP is an influential risk factor for WMH. [START_REF] Debette | Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury: A Systematic Review and Meta-analysis[END_REF][START_REF] Prins | White matter hyperintensities, cognitive impairment and dementia: an update[END_REF][START_REF] Prins | Cerebral small-vessel disease and decline in information processing speed, executive function and memory[END_REF] To investigate the shared epigenetics between WMH burden and BP, we performed a pairwise multivariate association test using summary statistics from a previous EWAS of SBP and DBP [START_REF] Richard | DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation[END_REF] . CpGs associated with both traits were tested against the null hypothesis H 0 : β WMH =β SBP or DBP =0. The test uses Z-scores for each trait and estimates multivariate test statistics accounting for the trait correlation calculated based on the null associations (trait-specific P>1x10 -5 ). This method is implemented in the 'metaUSAT' software. [START_REF] Ray | Methods for meta-analysis of multiple traits using GWAS summary statistics[END_REF] To avoid false positive associations driven entirely by one trait, we included CpGs showing significance (P<0.001) for both traits. Bonferroni threshold was set at 8.33x10 -3 (=0.05/6) based on the number of associations tested.

Heritability analysis and GWAS of WMH-associated CpGs

Inter-individual variation in DNAm may result from differences in environmental exposures, stochastic variation, or genetic influences. To examine the contribution of genetic

A C C E P T E D M A N U S C

Bi-directional MR analysis of the identified CpGs and WMH burden

To determine if the WMH-associated DNAm level is a causal factor for WMH burden (Forward-MR) or a secondary outcome of WMH burden (Reverse-MR), we performed a bidirectional two-sample MR analysis [START_REF] Pierce | Efficient design for Mendelian randomization studies: subsample and 2sample instrumental variable estimators[END_REF] for the identified CpGs with at least three instrumental variables (IVs). We identified methylation quantitative trait loci (mQTL) associations in-cis (±1Mb) from the FHS study (n=4,170) that had been validated using ARIC data (n=963). [START_REF] Huan | Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease[END_REF] Those mQTLs were clumped at linkage disequilibrium (LD) r 2 <0.05 for independence. For WMH, the UK biobank (UKBB) GWAS summary statistics (n=11,226) [START_REF] Traylor | Genetic variation in PLEKHG1 is associated with white matter hyperintensities (n = 11,226)[END_REF] was downloaded from the Cerebrovascular Disease Knowledge Portal (http://www.cerebrovascularportal.org/) on 01/09/2019. Reverse-MR analysis was performed using eight clumped genome-wide significant associations (LD r 2 <0.05). Since the FHS mQTL study shares only significant associations in cis, [START_REF] Huan | Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease[END_REF] we used the mQTL association statistics from ARIC EA subjects for reverse-MR analysis.

For each CpG in both directions, causal association was tested based on the IVW method in the R package 'TwoSampleMR'. [START_REF] Hemani | The MR-Base platform supports systematic causal inference across the human phenome[END_REF]

Mediating effect of in cis genes between CpGs and WMH burden

To investigate if expression of nearby genes mediates the relationship between the identified CpG and WMH burden, a two-step MR analysis was performed. We tested the directional relationships 1) from "the exposure (CpGs)" to "the mediator (gene expression)" (step 1) and 2) from "the mediator (gene expression)" to "the outcome (WMH burden) (step 2) using the identified mQTL IVs, the WMH GWAS associations, [START_REF] Traylor | Genetic variation in PLEKHG1 is associated with white matter hyperintensities (n = 11,226)[END_REF] and eQTL associations from the GTEx version eight brain eQTL data accessed via eQTL Catalogue (https://www.ebi.ac.uk/eqtl/) on 2020/11/12. Among available GTEx brain tissues, cortex (n=205), frontal cortex (n=175), cerebellum (n=209), cerebellar hemisphere (n=175), and caudate basal ganglia (n=194) were selected. MR association based on the IVW method was again tested and sensitivity analysis was also performed. Gene expression with IVW P<0.05 at both steps was considered as a potential mediator in the association between the identified CpG and WMH burden.

Cis-acting genes associated with the identified CpGs in blood

To functionally annotate the identified CpGs, we tested associations with gene expression in blood in long-range [START_REF] Huan | Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease[END_REF] cis-regions (±5Mb) in 1,966 and 728 EA subjects from FHS and RS, respectively. Expression of the nearest gene/ mRNA was regressed on DNAm β score at the CpG adjusting for age, sex, population structure, and family structure (FHS only), blood cell counts and technical covariates. Technical covariates and family structure were modeled as random effects. In sensitivity analyses, smoking status and BMI were added to the model. Estimates from two studies were then combined for each gene using the sample-sized based meta-analysis method in METAL [START_REF] Willer | METAL: fast and efficient meta-analysis of genomewide association scans[END_REF] .

Genes colocalizing with the identified CpGs in Brain

To investigate cis-acting genes colocalized with the identified CpGs in the brain, we performed a multiple-trait colocalization (moloc) analysis using brain QTL data. Prior to this analysis, we examined the inter-individual correlations between DNAm levels in whole blood and in prefrontal cortex at the identified CpGs, using publicly available data. [START_REF] Hannon | Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes[END_REF] For CpGs with significant correlation (P <0.05) between blood and prefrontal cortex, we tested the posterior probabilities for full-colocalization (PPFC) that multiple traits (DNAm, gene expression, and

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WMH burden) share causal variants at each locus, given the data. We used coloc priors of 1x10 -5 .

We identified EA-specific GWAS associations [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] and brain mQTL (n=543) and eQTL (n=534) associations accessed via http://mostafavilab.stat.ubc.ca/xqtl/. [START_REF] Ng | An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome[END_REF] If PPFC is greater than 0.7, we considered the gene is significantly colocalized with CpG and WMH burden. Moloc analysis was performed using the R package "moloc". 58

Epigenetic regulation of known GWAS loci

We next investigated the role of DNAm at established WMH GWAS loci, which may not have been detectable at the genome-wide significance threshold. Among 26 loci reported in the latest WMH GWAS, [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] we mapped 450K-array CpGs to 21 loci. EWAS associations at each of these 21 loci were pooled using the Brown's method (implemented in the package "poolr") adjusting for dependence among CpGs. [START_REF] Brown | A method for combining non-independent, one-sided tests of significance[END_REF] For dependency information, we calculated correlation among CpGs in the GWAS loci using ARIC methylation data (906 EA and 639 AA subjects). A GWAS locus with combined P was considered significant if P is smaller than Bonferroniadjusted threshold (0.05/number of loci tested).

Alternatively, we performed a moloc analysis at the 21 GWAS loci, again using the GWAS and brain QTL data. [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF][START_REF] Ng | An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome[END_REF] With the priors of 1x10 -5 , we considered genes with a PPFC greater than 70% as convincingly colocalized with DNAm and WMH burden.

Identification of biological pathways using multi-dimensional data integration

Integrating multi-omics associations for WMH may boost power to identify novel genes influencing WMH burden. We integrated genetic 8 , transcriptomic [START_REF] Lin | Whole blood gene expression and white matter Hyperintensities[END_REF] , and epigenetic genome-wide association studies of WMH using the R package 'mergeomics' (version 1.2). [START_REF] Shu | Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems[END_REF] To reduce noise in the GWAS data, the top 50% of genetic associations [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] were included and pruned at r 2 <0.5 based on HapMap3 LD information as recommended. [START_REF] Shu | Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems[END_REF] For transcriptomic associations, we used the recent WMH transcriptome-wide association study (TWAS) results. [START_REF] Lin | Whole blood gene expression and white matter Hyperintensities[END_REF] For epigenetic associations, we used our discovery EWAS. Markers were primarily mapped to the nearest genes.

For CpGs, cis-acting genes reported in the MesaEpiGenomics study [START_REF] Liu | Methylomics of gene expression in human monocytes[END_REF] were additionally annotated. For each GWAS, EWAS and TWAS, we tested marker-level enrichment with

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hierarchical permutation size of 20,000 based on biological pathways from pre-defined public databases: KEGG [START_REF] Kanehisa | KEGG: kyoto encyclopedia of genes and genomes[END_REF] , REACTOME [START_REF] Jassal | The reactome pathway knowledgebase[END_REF] , Biocarta 64 , and the gene ontology knowledgebase [START_REF] Carbon | The Gene Ontology resource: enriching a GOld mine[END_REF][START_REF] Ashburner | Gene ontology: tool for the unification of biology[END_REF] . Then, we meta-analyzed the enriched gene sets from association studies and identified the WMHassociated gene sets (FDR-adjusted P <0.05).

To describe the regulatory network of the identified gene sets and identify its local hub genes, we performed a weighted key driver analysis (wKDA) using the web-based software Mergeomics version 2.0. 67 Gene regulatory network was constructed using in-house brainspecific Bayesian network (minimum hub overlap 0.33 and directed edge type) [START_REF] Zhu | An integrative genomics approach to the reconstruction of gene networks in segregating populations[END_REF] and visualized via Cytoscape version 3.8.2. [START_REF] Shannon | Cytoscape: a software environment for integrated models of biomolecular interaction networks[END_REF] We also conducted an overlap-based drug repositioning analysis "PharmOmics" based on the identified key driver genes (FDR <0.05) to predict potential drugs or small molecules targeting WMH. [START_REF] Chen | PharmOmics: A Species-and Tissue-specific Drug Signature Database and Online Tool for Drug Repurposing[END_REF] PharmOmics comprises a curated drug signature database covering 941 drugs, constructed from transcriptomic data across >20 tissues from rat, human, and mouse. For our analysis, we selected drug signatures from relevant tissues (in vivo human transcriptome data in cardiovascular and nervous system, and in vitro transcriptome data from murine oligodendroglial precursor cells), and examined the overlap between these drug signature genes and key-driver genes from our identified WMH-associated gene sets.

Results

Identification of epigenetic changes associated with WMH burden

Study sample characteristics

In the discovery sample, the mean age ranges from 49.7 years in SHIP to 74

Novel DNAm loci are associated with WMH burden

In the discovery sample, we identified a novel epigenome-wide significant association between WMH burden and level of DNAm at cg24202936 (Z=5.38, P=7.58x10 -8 ) in SEPTIN7P11. Associations at cg24202936 in each study are presented in a forest plot (Supplementary Figure 1) and regional associations within 50 kb are presented with annotations (Supplementary Figure 2). At the suggestive significance threshold of 1x10 -5 , we identified 11 additional loci (Table 1). The associations remained significant (P <0.05/12=4.17x10 -3 ) after adjusting for BMI, smoking status, and SBP and DBP. Quantile-quantile (QQ) and Miami plots are presented in Supplementary Figure 3 and4. All subsequent analyses focus on these 12 CpGs, which are referred to as "target CpGs". None of the target CpGs associations were replicated in independent samples and a meta-analysis of the discovery and replication samples showed significant heterogeneity in many of the resulting associations, which was not present in the discovery cohorts (Supplementary Table 2). Target CpGs showed consistent associations with WMH in subgroup analyses by ancestry and hypertension status (Supplementary Table 3 and4).

Cg06450373 in CDH18 (P=6.48x10 -8 ) was identified in normotensive subjects (Supplementary Table 5); but not replicated. In a gene set enrichment analysis on discovered CpGs (P<1.0x10 -5 ), "cell-cell junction organization" was identified as the top pathway (P=1.32x10 -3 , false discovery rate (FDR)=0.32).

Annotated regulatory functions of target CpGs

We found significant regulatory features from RegulomeDB at the genomic positions of cg24202936 (rank 2b and score 0.93), and cg06809326 (rank 2b and score 0.91) (Supplementary (Supplementary Table 6). Previously reported EWAS traits associated with target CpGs are presented in Supplementary Table 7. In particular, cg24202936 was previously reported associated with HIV infection. [START_REF] Gross | Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA[END_REF] Cg06450373, cg031161214, cg01506471, and cg14547240 were correlated each other in both ancestries with weak to moderate r (0.23 to 0.55) (Supplementary Figure 5). In AA, cg23586595 showed weak but significant correlations with cg13476133 (r=0.32), cg03116124 (r=-0.42), and cg14547240 (r=-0.36). No correlated CpG (|r|>0.3) was identified for our top CpG, cg24202936, in both ancestries.

WMH-associated DMRs are enriched in immune response-related pathways

We identified 46 DMRs in associations with WMH burden (Supplementary Table 8).

Notably, one DMR was in SH3PXD2A, previously identified in genome-wide association studies (GWAS). [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF][START_REF] Persyn | Genome-wide association study of MRI markers of cerebral small vessel disease in 42,310 participants[END_REF][START_REF] Verhaaren | Multiethnic genome-wide association study of cerebral white matter hyperintensities on MRI[END_REF][START_REF] Armstrong | Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities[END_REF] Identified DMRs were enriched in several gene ontologies, including STAT (signal transducer and activator of transcription) family protein binding (FDR=4.91x10 -3 ) and defense response to virus (FDR=5.68x10 -3 ), which are related to the immune response (Supplementary Table 9). Of the 46 identified DMRs, PRMT1, ABAT, BHMT2, C11orf21, IZUMO1, C5orf66, ENPEP, SLC35F3, FBXO47, SLC45A4, KCTD16, KITLG, and UCN3 were replicated (Supplementary Table 8). Of note, ENPEP, SLC35F3, and SLC45A4 were previously reported in BP GWAS. [START_REF] Giri | Trans-ethnic association study of blood pressure determinants in over 750,000 individuals[END_REF][START_REF] Kichaev | Leveraging Polygenic Functional Enrichment to Improve GWAS Power[END_REF][START_REF] Sakaue | A cross-population atlas of genetic associations for 220 human phenotypes[END_REF][START_REF] Warren | Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk[END_REF][START_REF] Takeuchi | Interethnic analyses of blood pressure loci in populations of East Asian and European descent[END_REF][START_REF] Kato | Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians[END_REF][START_REF] Zhu | Genetic overlap of chronic obstructive pulmonary disease and cardiovascular disease-related traits: a large-scale genome-wide cross-trait analysis[END_REF]

Shared epigenetic loci between WMH and BP

At the Bonferroni-corrected threshold (P <8.33x10 -3 ), we identified six CpGs associated with both WMH burden and BP (Supplementary Table 10). For WMH-DBP, cg23291754 in MOBKL1A (P=2.38x10 -7 ) and cg24372586 in GNL1 (P=7.84x10 -7 ) were identified. For WMH-SBP, cg00711496 in CDC42BPB (P=1.99x10 -7 ), cg04987734 in C19orf76;PRMT1 (P=3.09x10 - 7 ), cg00934987 in SEPT4 (P=1.07x10 -6 ), and cg18770635 in KLHDC7B (P=1.68x10 -6 ) were identified.

Heritability of the WMH-associated CpGs

Significant h 2 meth was estimated for cg17417856 (40.4%, P=1.37x10 -8 ), cg06809326 (26.5%, P=1.03x10 -4 ), cg23586595 (24.2%, P=1.47x10 -3 ), cg17577122 (14.3%, P=2.80x10 -2 ), and cg24202936 (15.5%, P=1.34x10 -2 ) (Table 2). Additional adjustment for BMI and smoking

A C C E P T E D M A N U S C R I P T
status did not significantly modify these estimates. In GWAS of the target CpGs in the ARIC EA sample, we observed significant cis genetic influence on cg06809326, cg13476133, and cg24202936 (Supplementary Figure 6). This result agrees with a previous publication that included the same dataset. 53

Mendelian randomization analyses between target CpGs and WMH burden

Forward two-sample multiple IV MR analysis was performed for two target CpGs, cg06809326 and cg24202936, which have at least three independent cis-mQTL IVs in Huan T et al [START_REF] Huan | Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease[END_REF] (Supplementary Table 11). We found a marginally significant causal relationship from cg06809326 to WMH burden ( P=2.91x10 -2 ). Higher methylation level at the locus is associated with greater WMH burden (odds ratio (OR) [95% confidence interval (CI)]=1.39 [1.03, 1.87]).

Evidence was lacking for horizontal pleiotropy (P=0.41) or heterogeneity (P=0.42) (Supplementary Table 12). In reverse-MR analysis, evidence that WMH causally influence methylation levels at any of the target CpGs was lacking (Supplementary Table 12 and13).

Using the same three IVs, we also investigated whether cg6809326 is causally associated with expression of nearby genes (step 1). Two cis transcripts were annotated to this CpG in GTEx version eight data. [START_REF] Gtex | The GTEx Consortium atlas of genetic regulatory effects across human tissues[END_REF] They both encode a long noncoding RNA designated as CCDC144NL, and CCDC144NL-AS1 and we identified one IV for both transcripts. In all five brain tissues, we found evidence of causal association between cg06809326 and both CCDC144NL and CCDC144NL-AS1 (Supplementary Table 14). In step two, a marginal association between CCDC144NL and WMH burden was observed in caudate basal ganglia and cortex (step one P=1.11x10 -3 and step two P=3.94x10 -2 in caudate basal ganglia; step one P=1.21x10 -3 and step two P=4.28x10 -2 in cortex). [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] We estimated the combined effect of DNAm at each locus from our EWAS results at the 21 established GWAS loci. [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF] Consistent with our DMR results, CpGs at the GWAS locus SH3PXD2A were jointly associated with WMH (P=8.48x10 -3 ), but evidence of DNAm effects on WMH at other loci was lacking (Supplementary Table 15). We also conducted a multiple trait colocalization analysis (moloc) [START_REF] Giambartolomei | A Bayesian framework for multiple trait colocalization from summary association statistics[END_REF] of brain mQTL and expression QTL (eQTL) [START_REF] Ng | An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome[END_REF] , and WMHassociated single nucleotide polymorphisms (SNPs). At 17 out of the 21 GWAS loci, we

DNAm at established GWAS loci and WMH burden

A C C E P T E D M A N U S C R I P T
and ISLR) represent a sub-network of "extracellular matrix (ECM) organization, ECM-receptor interaction, focal adhesion, and collagen formation". Additionally, three related sub-networks, "smooth muscle contraction" with key driver TAGLN; "G-protein-coupled receptor (GPCR) ligand binding" with key drivers GAL, ECEL1, ESR1, and NTS; and "cytokine signaling in immune system" with key drivers IFIT1 and RTP4, make up the network (Figure 2 and Supplementary Table 20). We also identified an independent second network associated with "lipid and lipoprotein metabolism", with key driver gene KNG1. Genes included in each subnetwork are presented in Supplementary Table 21.

Overlap-based drug repositioning analysis of WMH-associated genes

Using drug signatures derived from in vivo cardiovascular and nervous system data, we predicted antihyperlipidemic drugs, including PPAR-α (peroxisome proliferator-activated receptor-alpha) agonist "fenofibrate", as the top therapeutic target. Using drug signatures derived from murine oligodendroglial precursor cells data, we predicted several small molecules, including a glycogen synthase kinase inhibitor and a phenylalanyl tRNA synthetase inhibitor that may have therapeutic potential for Alzheimer's disease [START_REF] Lauretti | Glycogen synthase kinase-3 signaling in Alzheimer's disease[END_REF] and autoimmune diseases [START_REF] Kwon | Aminoacyl-tRNA synthetases as therapeutic targets[END_REF] , respectively (Supplementary Table 22).

Discussion

This first EWAS of WMH burden in 9,732 middle-aged to older adults from 14 community-based cohorts identified several novel epigenetic loci. Although we could not independently replicate the association of single CpGs with WMH, likely due to a limited sample size and differences between the discovery and replication sample, functional annotation and bioinformatic analyses provided strong supportive evidence. Moreover, powerful DMR analyses identified 46 DMRs of which 13 were replicated. Integrative analyses of multi-omics information also suggested novel gene networks with key drivers and potential drug targets for WMH.

We identified a novel epigenetic locus, cg24204936, mapping to a pseudogene SEPTIN7P11. Functional integration revealed two candidate genes whose expression may be influenced by variation in DNAm at this locus: F2 in blood and FOLH1 in DLPFC. Prothrombin encoded by F2 plays an essential role in blood clot formation, angiogenesis, tissue repair and

A C C E P T E D M A N U S C R I P T
vascular integrity. A prothrombotic state or circulating prothrombin has been reported for symptomatic cSVD, [START_REF] Tomimoto | The Coagulation-Fibrinolysis System in Patients With Leukoaraiosis and Binswanger Disease[END_REF][START_REF] Wiseman | Blood Markers of Coagulation, Fibrinolysis, Endothelial Dysfunction and Inflammation in Lacunar Stroke versus Non-Lacunar Stroke and Non-Stroke: Systematic Review and Meta-Analysis[END_REF] WMH and stroke [START_REF] Nagai | Association of Prothrombotic Status With Markers of Cerebral Small Vessel Disease in Elderly Hypertensive Patients[END_REF][START_REF] Kario | Additional impact of morning haemostatic risk factors and morning blood pressure surge on stroke risk in older Japanese hypertensive patients[END_REF] . However, it remains unclear whether coagulation plays a major role in the etiology of WMH or is secondary to injury to the cerebral small vessels and white matter. [START_REF] Markus | Markers of Endothelial and Hemostatic Activation and Progression of Cerebral White Matter Hyperintensities[END_REF] FOLH1 encodes glutamate carboxypeptidase II that catalyzes the hydrolysis of N-acetylaspartylglutamate (NAAG). An elevated level of NAAG in the cerebrospinal fluid has been reported in two patients with almost complete absence of myelin in the central nervous system [START_REF] Wolf | Severe hypomyelination associated with increased levels of N-acetylaspartylglutamate in CSF[END_REF] and has been proposed as a diagnostic biomarker for rare diseases of the white matter. [START_REF] Mochel | Elevated CSF N-acetylaspartylglutamate suggests specific molecular diagnostic abnormalities in patients with white matter diseases[END_REF] An epigenetic locus mapping to PRMT1, which encodes a protein arginine N-methylase, was identified in single-CpG and DMR analyses and also as a shared epigenetics locus with BP.

The biological link between DNAm at PRMT1 and WMH burden may involve pathways related to endothelial dysfunction, which have previously been implicated in WMH etiology. [START_REF] Wardlaw | Small vessel disease: mechanisms and clinical implications[END_REF] PRMT1, a predominant member of the PRMT family, methylates histone and non-histone proteins to regulate various cellular functions. [START_REF] Wei | Protein arginine methylation of non-histone proteins and its role in diseases[END_REF] PRMT1 is essential for the development of neurons, astrocytes, and oligodendrocytes and is critical for myelin formation. [START_REF] Hashimoto | Severe Hypomyelination and Developmental Defects Are Caused in Mice Lacking Protein Arginine Methyltransferase 1 (PRMT1) in the Central Nervous System[END_REF] PRMTs also catalyze the formation of ADMA (asymmetric dimethylarginine), which reduces nitric oxide production, promotes endothelial dysfunction in the blood-brain barrier (BBB), and triggers the immune response in atherosclerosis. [START_REF] Wardlaw | Small vessel disease: mechanisms and clinical implications[END_REF][START_REF] Dowsett | ADMA: A Key Player in the Relationship between Vascular Dysfunction and Inflammation in Atherosclerosis[END_REF][START_REF] Watson | The transporter and permeability interactions of asymmetric dimethylarginine (ADMA) and L-arginine with the human bloodbrain barrier in vitro[END_REF] Higher ADMA levels have been repeatedly associated with cSVD and its monogenic form, CADASIL (Cerebral Autosomal Dominant Arteriopathy with Sub-cortical Infarcts and Leukoencephalopathy). [START_REF] Janes | ADMA as a possible marker of endothelial damage. A study in young asymptomatic patients with cerebral small vessel disease[END_REF][START_REF] Pikula | Association of plasma ADMA levels with MRI markers of vascular brain injury: Framingham offspring study[END_REF][START_REF] Guan | Analysis of risk factors in patients with leukoaraiosis[END_REF][100][101][102][103] Single-CpG association combined with functional genomic analyses and DMR analyses identified a novel epigenetic locus near CCDC144NL;CCDC144NL-AS1 (coiled-coil domain containing 144 family and its antisense RNA1). Cg06809326 is under strong cis-genetic control and brain expression of its nearest gene,CCDC144NL;CCDC144NL-AS1, may mediate the association between DNAm and WMH burden (Supplementary Figure 8). A TWAS of WMH using blood gene expression data [START_REF] Lin | Whole blood gene expression and white matter Hyperintensities[END_REF] did not report a significant association for CCDC144NL;CCDC144NL-AS1 expression, possibly due to its low expression in blood.

CCDC144NL-AS1 encodes a long non-coding mRNA transcript that controls expression of target genes by acting as a molecular sponge for various regulatory miRNAs. [104][105][106][107][108][109] In vitro studies have uncovered several of its target genes with potentially relevant function to cSVD. These include matrix metalloproteinases MMP2 and MMP9 108 ; F-actin and vimentin 110 ; and transforming growth factor beta (TGF-β)-activated kinase 1 (TAK1). 106 MMP2 and MMP9can damage the A central role of endothelial dysfunction, possibly resulting in a compromised BBB, in WMH burden 119 is further suggested by identified DNAm associations in genes involved in cell junctions. Claudins are integral membrane proteins that comprise tight junctions specifically in brain microvascular endothelial 120 cells and that regulate BBB permeability. 121 Claudin-5 mapped to cg17577122 is the most enriched tight junction protein in the BBB, and its dysfunction has been implicated in neurodegenerative and neuroinflammatory diseases, and cSVD. 122-126 A recent DMR analysis using DLPFC DNAm levels also identified CLDN5 to be associated with cognitive decline. 127 In normotensive subjects, we identified a CpG in cadherin 18 (CDH18) that encodes an adherens junction protein, which mediates calcium-dependent cell-cell adhesion.

CDH18 is also involved in cell junction organization process and in cell signaling pathways including G-proteins signaling together with F2. 128 Our DMR analysis, aggregated epigenetic associations using Brown's method, [START_REF] Brown | A method for combining non-independent, one-sided tests of significance[END_REF] and moloc analysis using brain QTL data consistently identified an epigenetic association at a known WMH GWAS locus, SH3PXD2A (SH3 and PX-domain-containing protein 2A). [START_REF] Sargurupremraj | Cerebral small vessel disease genomics and its implications across the lifespan[END_REF][START_REF] Persyn | Genome-wide association study of MRI markers of cerebral small vessel disease in 42,310 participants[END_REF][START_REF] Verhaaren | Multiethnic genome-wide association study of cerebral white matter hyperintensities on MRI[END_REF][START_REF] Armstrong | Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities[END_REF] Several genome-wide associations with WMH-related traits have also been reported at SH3PXD2A, including white matter microstructure 129 and stroke 130,131 . SH3PXD2A encodes an adaptor protein (TKS5) involved in the formation of podosomes that act as sites of close contact to as well as degradation of ECM. 132 Gene set enrichment of identified DNAm loci and integrative crossomics analyses collectively point to a central role of the ECM in WMH burden. One of the two WMH burden networks identified through the Mergeomics approach centered around key driver genes involved in ECM organization and function and the top associated module was "regulation of actin cytoskeleton". Notably, actin polymerization and disassembly of junctional proteins within microvascular endothelial cells were shown to play a key role in early BBB disruption in a murine model. vessel stroke. 134 Statin therapy for cSVD has also been regarded as promising since individuals with high WMH burden typically carry higher vascular risk factors. Few randomized clinical trials assessing the effect of lipid lowering on WMH progression have been conducted and they have generally provided mixed results. [135][136][137] While they suggest a possible role of statins, in particular rosuvastatin, in preventing WMH progression, the lack of high-quality data prevents strong evidence-based recommendation at this time. 138 It has been postulated that statins improve endothelial function and stabilize the BBB in cSVD. 139,140 Studies that investigated membrane proteins including phospholipid flippase (ATP11B) and aquaporin-4 showed that the loss of these proteins cause pathological features of cSVD including endothelial cell dysfunction with reduced tight junctions, nitric oxide, oligodendrocyte progenitor cell maturation block and microglial activation. 126,141 Finally, this study provides further emphasis concerning the long-observed perivascular inflammation as an additional crucial player in cSVD pathology and provides a possible explanation. Interestingly, gene set enrichment analyses identified a possible role of the defense response to viral infection with several DMR-associated genes related to interferon gamma signaling and the innate immune response (DTX3L-PARP9, BNIP3, and IFITM1). Our top associated CpG has been previously reported in an EWAS of chronic HIV infection [START_REF] Gross | Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA[END_REF] and our drug-repositioning analysis also identified a HIV antiviral as a possible drug target. Several studies have reported that people with HIV are at higher risk of an increased burden of WMH compared to uninfected controls. 142,143 Several limitations of our study must be acknowledged. First, many of our EWAS discoveries were not independently confirmed. Since a series of functional analyses showed biological relevance, we suspect that the lack of replication may stem from the limited size of the replication sample and from differences between the discovery and replication samples as hinted by the increased heterogeneity in the DNAm association observed in the meta-analysis (Supplementary Table 2). Indeed, variation in WMH burden was smaller in the replication studies minimizing the number of covariates in the models. Our primary goal was to identify novel DNAm loci associated with WMH burden and we cannot exclude the possibility that the identified loci may reflect, in part, variation in those risk factors. Fourth, the currently publicly available brain QTL data are limited to cis-regions of omics markers and, thus, our in-silico bioinformatics analyses were restricted only to the CpGs with substantial cis-acting genetic influence. For example, cg17417856 in PRMT1 had a strong heritability estimate (h 2 =0.40, P=1.37x10 -8 ) but was not followed-up because it was under polygenic control. Lastly, the study was conducted in blood and cell type-specific associations, most notably in brain, may have been missed. To extrapolate the findings in blood to brain, we assessed the correlation with DNAm in brain, and utilized available brain QTL data. Due to the difficulties of getting both brain DNAm and MRI data from a large population-based sample, an EWAS of WMH burden using brain DNAm may not be easy to achieve. However, findings from this large blood-based study may provide a basis for an epigenetic candidate gene study in the brain.

Abbreviations:

  Abbreviations: BBB = blood-brain barrier; CADASIL = Cerebral Autosomal Dominant Arteriopathy with Sub-cortical Infarcts and Leukoencephalopathy; cSVD = cerebral small vessel disease; DNAm = DNA methylation; WMH = cerebral white matter hyperintensities A C C E P T E D M A N U S C R I P T

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Introduction

  Cerebral white matter hyperintensities (WMH) on MRI are indicative of cerebral small

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  quantification in each study are detailed in Supplementary Data II.

  BBB by triggering recruitment of immune cells 111 and have been implicated in white matter injury and cSVD. 112 F-actin plays an important role in maintaining the shape of endothelial cells and the integrity of the BBB.113 Disturbed TGF-β signaling has been implicated in the pathogenesis of several monogenic forms of cSVD.[114][115][116][117] Deficiency of TAK1 in mouse brain endothelial cells resulted in endothelial cell death, small vessel rarefaction, and disruption of the BBB.118

  133

  Another network includes genes that function in lipid and lipoprotein metabolism and our overlap-based drug repositioning analyses suggested antihyperlipidemic drugs as potential drug targets. A recent MR analysis showed that genetically increased high-density lipoprotein cholesterol (HDL-C) level was associated with lower WMH volume and lower risk of small

Figure 1

 1 Figure 1 Overview of the study analytic scheme.

Figure 2 WMH

 2 Figure 2 WMH-associated Gene Networks. WMH-associated genes based on multi-molecular evidence are organized around the 19 key driver genes. a. WMH-associated network consisting of four sub-networks -extracellular matrix (ECM) organization (FMOD, COL3A1, SEPING1, SLC13A4, and ISLR); smooth muscle contraction (TAGLN); G-protein-coupled receptor (GPCR) ligand binding (GAL, ECEL1, ESR1, and NTS) and cytokine signaling in immune system (IFIT1 and RTP4) b. WMH-associated network of lipid and lipoprotein metabolism (KNG1). Key drivers and associated gene networks identified in the Mergeomics analysis are colored in orange (RGB: 255,166,127). Neighboring genes are grouped into networks and labelled in random colors.

  Figure 1 2 160x241 mm (.46 x DPI) 3

  Figure 2 160x158 mm (.46 x DPI) A C C E P T E D M A N U S C R I P T

  R I P T variation to variation in DNAm at the identified CpGs, we estimated the narrow sense heritability (h 2 meth ) in the FHS Offspring Cohort subjects (n=2,377) adjusting for age, sex, blood cell counts, PCs and technical covariates. Body mass index (BMI) and smoking status were additionally corrected in sensitivity analyses. To further identify genetic variants associated with DNAm levels at the WMH-associated CpGs, we performed GWAS in ARIC EA subjects (n=984). Genotypes were measured with Affymetrix 6.0 array and imputed from 1000 Genome phase one version three reference using MaCH v1.0.16. Variants were excluded if minor allele frequency (MAF)<0.01, sample call rate<95%, or imputation quality<0.3. The untransformed methylation beta value was tested for genetic association adjusting for age, sex, top 42 methylation PCs, and blood cell components.

  To validate the MR result, sensitivity analyses based on Downloaded from https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awac290/6659012 by Universite de Bordeaux user on 29 October 2022

	S C R I P T
	A N U
	M
	weighted median and MR Egger methods, and built-in tests for pleiotropy and heterogeneity were A C C E P T E D
	also performed. For existence of pleiotropy (MR egger intercept test P<0.05), the Egger
	regression estimate was assessed instead of the IVW estimate.

Table 6 )

 6

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. Cg24202936 resides near a transcriptional starting site (0.2 Kb upstream), and identified as a transcriptional factor binding site computationally annotated with 20 genes

  than in the discovery studies perhaps due to the younger age of the participants. The younger cohorts, CARDIA (n=277) with a mean age 53.9 years and SHIP (n=214) with a mean age 49.7 years, make up only 8.59% of the discovery sample; whereas the Rhineland Study with a mean age 54.1 years and FHS 3 rd generation cohort with a mean age of 47.1 years, make up over 86% of the replication sample. Replication of several WMH-associated loci identified through more powerful DMR analyses further underscore an underpowered replication study for single CpG associations. Additional studies are needed to confirm the findings presented here. Second, we conducted a subgroup analysis stratified by hypertension status, but statistical power in each stratum was limited. A more ideal design to study this and other modifiable risk factors of cSVD will be a longitudinal study or a stratified association study with a larger sample size. Similarly, our study was not sufficiently powered to examine ancestry-specific associations of DNAm with WMH and possible ancestry difference in epigenetic patterns could not be investigated. Third, we did not adjust for additional lifestyle factors or comorbidities to maximize our sample size by

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	A C C E P T E D

Table 2 Heritability estimates of WMH-associated CpGs

 2 meth : the narrow-sense heritability in an additive genetic model. S.E.: standard error Reduced model is adjusted for age, sex, blood cell counts, principal components of the ancestry and technical covariates. Full model is additionally adjusted for body mass index and smoking.

	CpG	Nearest Gene	Reduced model		Full Model
			h 2	meth	S.E.	P	h 2	meth	S.E.	P
	cg0150647	SDK1	0.02	0.07	0.38	0.01	0.07	0.42
	cg03116124	TRIM67	0.01	0.07	0.45	0.01	0.07	0.47
	cg06809326	CCDC144NL	0.26	0.07	1.03 × 10 -4*	0.27	0.07	9.51 × 10 -5*
	cg13476133	GCK	0.09	0.07	0.11	0.09	0.07	0.12
	cg14133539	FO × D4	0.08	0.07	0.14	0.07	0.07	0.17
	cg14547240	C1QTNF7	0.06	0.07	0.20	0.06	0.07	0.18
	cg17417856	PRMT1;ADM5	0.40	0.08	1.37 × 10 -8*	0.40	0.08	3.06 × 10 -8*
	cg17577122	CLDN5	0.14	0.08	2.80 × 10 -2	0.15	0.08	2.27 × 10 -2
	cg21547371	MUSTN1	0.00	-	0.50	0.00	0.50
	cg23054394	SPSB4	0.00	-	0.50	0.00	0.50
	cg23586595	PLAC8	0.24	0.08	1.47 × 10 -3*	0.23	0.08	2.51 × 10 -3*
	cg24202936	LOC441601	0.15	0.07	1.34 × 10 -2	0.16	0.07	1.17 × 10 -2
	h 2

* Significant after adjustment for multiple testing burden.

Table 3 Cis-Genes (±5Mb) whose expression is significantly associated with identified CpGs Z

 3 scores and P values from the reduced and full model are presented. Reduced model is adjusted for age, sex, blood cell counts, principal components of the ancestry and technical covariates. Full model is additionally adjusted for body mass index and smoking. PLAC8: placentaassociated 8 and F2: coagulation factor II.

	CpG	Gene	Region (hg19)	n	Z reduced	P reduced	Z full	P full
	cg23586595	PLAC8	4:84011211-84138405	2687	-5.13	2.98 × 10 -7	-5.11	3.27 × 10 -7
	cg24202936	F2	11:46740749-46761054	1963	-4.00	6.39 × 10 -5	-4.01	6.04 × 10 -5

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Acknowledgements

The authors thank the staff and participants of ARIC study, BBMRI, CARDIA, CHS, FHS, GENOA, LBC1936, RS, SHIP, ADNI, Rhineland Study, OATS, and BRIDGET for their pivotal contributions. We acknowledge collaborative contributions from the neuroCHARGE

Funding

We thank all study participants for contributing to this work. This project was largely supported by grant R01NS087541 from US National Institute of Neurological Disorders and Stroke with additional support from U01AG052409 and R01HL105756. A full set of studyspecific funding sources is provided in the Supplementary Data I.

Data availability

The data that support the findings of this study are included in this manuscript. Full EWAS summary statistics are available in dbGaP at phs000930.v9.p1.

identified significant colocalization evidence (PPFC >0.7) (Supplementary Table 16 and Supplementary Figure 7). At eight loci, the SNPs with the highest PPFC were the sentinel SNPs in the GWAS.

Candidate genes implicated by gene-expression associations with the target CpGs

At the Bonferroni threshold (6.93x10 -5 =0.05/722 cis-genes in ±5Mb of the target CpGs), we identified significant associations between cg23586595 and PLAC8 (P=2.98x10 -7 ), and between cg24202936 and F2 (P=6.39 x10 -5 ) (Table 3). Adjusting for additional covariates (smoking status and BMI) did not change these associations.

Cg24202936, cg01506471, and cg06809326 showed significant correlation estimates (|r|>0.3) between blood and brain (r=0.33, 0.87, and 0.57, respectively) (Supplementary Table 17) and, thus, were tested for colocalization. We found that mQTLs for cg24202936 and WMH GWAS SNPs colocalize with FOLH1 expression in dorsolateral prefrontal cortex (DLPFC) (PPFC=0.75) (Supplementary Table 18). Also, suggestive evidence existed for colocalization of cg06809326 mQTLs, CCDC144NL-AS1 eQTLs, and WMH SNPs (PPFC=0.69).

Integrative cross-omics analysis

Integrative cross-omics analysis identifies novel gene regulatory networks

At FDR <0.05, we identified 576 WMH-associated gene sets enriched from the integrated data of GWAS, EWAS, and TWAS out of 12,303 gene sets from curated databases. [START_REF] Kanehisa | KEGG: kyoto encyclopedia of genes and genomes[END_REF][START_REF] Jassal | The reactome pathway knowledgebase[END_REF][64][START_REF] Carbon | The Gene Ontology resource: enriching a GOld mine[END_REF][START_REF] Ashburner | Gene ontology: tool for the unification of biology[END_REF] Top associated gene-sets includes "regulation of actin cytoskeleton" (P=1.14x10 -45 , 211 genes), "telomeres, telomerase, cellular aging, and immortality" (P=1.10x10 -35 , 18 genes), "integrinmediated cell surface interactions" (P=3.17x10 -34 , 84 genes), "thrombin signaling through proteinase activated receptors" (P=1.41x10 -33 , 32 genes), and "Nef protein mediated CD4 downregulation" (P=4.70x10 -32 , nine genes). All enriched pathways with FDR P <0.05 are listed in Supplementary Table 19.

We derived two WMH burden-associated gene networks in brain. The first network is comprised of four sub-networks. Five key driver genes (FMOD, COL3A1, SERPING1, SLC13A4,

Supplementary material

Supplementary material is available at Brain online.


Kevin Grollier

Emmanuel Chefdeville

Arnaud De Zordo-Banliat

Bruce Pegot

Guillaume Dagousset

Emmanuel Magnier

Thierry Billard
email: thierry.billard@univ-lyon1.fr

Fe-mediated nucleophilic trifluoromethylselenolation of activated alkyl bromides via umpolung reactivity of trifluoromethyl tolueneselenosulfinate

Keywords: Fluorine, Selenium, Trifluoromethylselenolation, Iron F 3 CSe

Introduction

Because of the intrinsic properties of fluorine atom, fluorinated molecules generally possess particular characteristics [START_REF] Seppelt | The Curious World of Fluorinated Molecules[END_REF][START_REF] Tressaud | Fluorine A Paradoxical Element[END_REF][START_REF] Kirsch | Modern Fluoroorganic Chemistry[END_REF][START_REF] Smart | [END_REF]. Consequently, fluorinated compounds played these last years important role in various fields of applications from materials to life sciences [5][6][7][8][9][10][11][12][13][14][15][16][17][START_REF]Fascinating Fluoropolymers and Their Applications[END_REF][START_REF] Améduri | [END_REF]. In the objective to propose new substrates with dedicated properties, the development of new emerging fluorinated motifs known a rising interest this last decade [START_REF]Emerging Fluorinated Motifs: Synthesis, Properties and Applications[END_REF]. In particular, merging of trifluoromethyl group with heteroatoms known a certain craze. More specifically, trifluoromethylchalcogen motifs were particularly investigated, in partly due to their high Hansch-Leo lipophilicity parameters (pR(CF3O) = 1.04, (pR(CF3S) = 1.44, (pR(CF3Se) = 1.61) which contribute to enhance the bioavailability of molecules [START_REF] Kirsch | Modern Fluoroorganic Chemistry[END_REF][START_REF] Leo | [END_REF][22][23].

If CF3O and CF3S chemistry is now well described [24][25][26][27][28][29][30][START_REF] Toulgoat | Chemistry of OCF3, SCF3, and SeCF3 Functional Groups[END_REF], CF3Se group remains still less explored [START_REF] Toulgoat | Chemistry of OCF3, SCF3, and SeCF3 Functional Groups[END_REF][START_REF] Billard | When Fluorine Meets Selenium[END_REF][START_REF] Wang | [END_REF], maybe due to the toxicity generally associated with selenium [34,35]. However, selenium is also an indispensable trace element playing a crucial role in human physiology [36][37][START_REF]European Food Safety Authority[END_REF]. Furthermore, selenylated compounds find applications in various fields such as materials or life sciences [35,[39][40][41][42][START_REF]Organoselenium Compounds in Biology and Medicine: Synthesis, Biological and Therapeutic Treatments[END_REF][START_REF] Alcolea | [END_REF][45][46][47][48][49]. Moreover, recently, trifluoromethylselenolated derivatives of nonsteroidal anti-inflammatory have shown promising anticancer properties [50,51].

Consequently, development of new synthetic methods to efficiently introduce CF3Se onto organic substrates is highly required. In particular, late-stage direct trifluoromethylselenolation is particularly studied these last years [27,[START_REF] Toulgoat | Chemistry of OCF3, SCF3, and SeCF3 Functional Groups[END_REF][START_REF] Billard | When Fluorine Meets Selenium[END_REF][START_REF] Wang | [END_REF]. Among the various described approaches, nucleophilic reactions with CF3Se -anion are well investigated [27]. However, this anion suffers from various drawbacks: stability issues and tedious synthesis [START_REF] Billard | When Fluorine Meets Selenium[END_REF]52]. Therefore, new strategies to in situ generate this anion are necessary.

Results and discussion

We recently described trifluoromethyl tolueneselenosulfonate (1a) as a versatile reagent to perform trifluoromethylselenolation following various pathways [22,[53][54][55][56][57]. Thus, its umpolung reactivity was described through in situ generation of CF3Se -anion to perform SN2 reactions. This umpolung behavior is based either on the 2 electrons reduction of 1a with TDAE (tetrakis(dimethylamino) ethylene) [56] or on the transient generation of CF3SeI, which possesses an inverted polarity, in presence of an excess of TBAI (tetrabutylammonium iodide) [57] (Scheme 1).

Scheme 1. Previous umpolung reactivity of 1a.

Despite the efficiency of these methods, they require the use of sensitive TDAE or an excess of TBAI. Consequently, we decided to investigate a novel approach cheaper, cleaner and with an easier purification process. In particular, the reductive conditions, developed with TDAE, was reinvestigated by using other reducers. More specifically, a great interest was focused on inexpensive non-precious metals. Redox potential of 1a was previously measured in DMSO at -0.32 V (vs SHE) [54]. Such value led us to consider Zn (E 0 {Zn 2+ /Zn} = -0.76 V) and Fe (E 0 {Fe 2+ /Fe} = -0.45 V) as potential metallic reducer [START_REF]CRC Handbook of Chemistry and Physics[END_REF]. The conditions reaction were screened with benzyl bromide (2a) as model substrate (Table 1). a Yields determined by 19 F NMR with PhOCF3 as internal standard.

In presence of 3 equivalents of zinc powder, a good yield was obtained in 1 h at room temperature (entry 1). The same result was also obtained with 2 equivalents of Zn (entry 2)

whereas with only 1 equivalent, the yield dropped (entry 3). Interestingly, good result was observed in only 15 min of reaction (entry 4). Other solvents were tested but with highly disappointing results (entries 5-6). In view of these positive results, cheaper iron was then considered as reducing metal. With 2 equivalents of Fe in DMSO, a slightly lower yield was obtained (entry 7). In contrast to Zn, the use of only 1 equivalent provided also good result (entry 8). Finally, as expected, Fe appeared essential to the reaction (entry 9).

The optimal conditions with Fe in hand (entry 8), the scope of reaction was then investigated (Scheme 2).

Br F 3 CSe S O O 1a + 2a metal DMSO (0.1 M) RT SeCF 3 3a (1 equiv.) (1 equiv.)
Scheme 2. Fe-mediated trifluoromethylselenolation. Yields determined by 19 F NMR with PhOCF3 as internal standard. In parentheses, isolated yields.

Good yields were obtained with benzylic substrates, whatever the aromatic substituents (electron withdrawing or donating) (3a-j). The steric hindrance has only a slight influence (3b, 3i-j). Heteroaromatic benzylic substrates led also to good result (3k-l). The reaction is compatible with functional groups such as ester (3g) or nitro (3h, 3l) as well as aromatic chloride (3j). Cinnamyl bromide was efficiently trifluoromethylselenolated (3m) whereas geranyl bromide led only to medium yield (3n). Starting from bromo-acetophenone, medium result was obtained (3p), maybe due to an interaction between carbonyl and Fe. With non- activated substrates, a lower reactivity was observed (3q-r), bromoundecane staying unreactive (3r). On contrary to bromide derivatives, chloride ones were quite unreactive (3a, 3m, 3o).

Interestingly, because of the simplicity of the procedure, most of the final products can be isolated with satisfactory purity by a simple extraction.

Finally, the method was extended to a higher fluorinated homolog of 1a. Thus, nucleophilic heptafluoropropylselenolation, scarcely described, was performed with medium yield, but satisfactory in this series (Scheme 3). Scheme 3. Heptafluoropropylselenolation of benzyl bromide. Isolated yield.

Conclusion

This work contributes to demonstrate the high versatility of trifluoromethyl tolueneselenosulfinate as trifluoromethylselenolating reagent. With these results, a third method to initiate umpolung reactivity of this reagent is described. This approach is complementary of the previous ones and, in particular, allows a rapid way to obtain expected products, without further purifications, with satisfactory purity.

Experimental

General. Commercial reagents were used as supplied. Anhydrous solvents were used as supplied. NMR spectra were recorded on a Bruker AV 400 spectrometer at 400 MHz ( 1 H NMR), 376 MHz ( 19 F NMR) or on a Bruker AV 300 spectrometer at 300 MHz ( 1 H NMR), 282 MHz ( 19 F NMR). Multiplicities are indicated as follows: s (singlet), d (doublet), t (triplet), q (quartet), m (multiplet). All coupling constants were reported in Hz.

Typical procedure for the perfluororalkylselenolation of alkyl halides.

To a 10 mL tube equipped with a magnetic stir bar was weighted Fe (0.1 mmol, 1 equiv.). A solution of 1 (0.1 mmol, 1 equiv.) and 2 (0.1 mmol, 1 equiv.) in anhydrous DMSO (1 mL, 0.1 M) was added to the tube and the tube was rapidly sealed. The crude mixture was vigorously stirred at room temperature for 1 h. Conversion was checked by 19 F using PhOCF3 as internal standard (filtration of the sample on PTFE 0.45 µm filter was required). The crude mixture was partitioned between pentane or Et2O and water. The aqueous layer was extracted with pentane or Et2O two times, combined organic layers were washed with water and brine, dried over MgSO4, filtered and concentrated to dryness under moderate vacuum affording the desired product 3 or 4.

Synthesis of benzyl(trifluoromethyl)selane (3a).

Colorless oil. Characterization data match that reported in the literature [START_REF] Glenadel | [END_REF].

Synthesis of (1-phenylethyl)(trifluoromethyl)selane (3b).

Yellowish oil.

1 H NMR (300 MHz, Chloroform-d) δ 7.40 -7.23 (m, 5H), 4.79 (q, J = 7.1 Hz, 1H), 1.93 (qq, J(H,H) = 7.1, J(H,F) 0.7 Hz, 3H). 19 F NMR (282 MHz, Chloroform-d) δ -33.57 (s, 3F).

Characterization data match that reported in the literature [56].

Synthesis of (4-(tert-butyl)benzyl)(trifluoromethyl)selane (3c).

Colorless oil. Characterization data match that reported in the literature [60].

Synthesis of ([1,1'-biphenyl]-4-ylmethyl)(trifluoromethyl)selane (3d).

White solid. Characterization data match that reported in the literature [61].

Synthesis of (4-fluorobenzyl)(trifluoromethyl)selane (3e).

Yellowish oil. Characterization data match that reported in the literature [60].

Synthesis of (3-methoxybenzyl)(trifluoromethyl)selane (3f).

Yellowish oil.

1 H NMR (300 MHz, Chloroform-d) δ 7.24 (m, 1H), 6.93 (m, 1H), 6.88 (m, 1H), 6.82 (m, 1H), 4.22 (s, 2H), 3.81 (s, 3H). 19 F NMR (282 MHz, Chloroform-d) δ -34.52 (s, 3F).

Characterization data match that reported in the literature [62].

Synthesis of methyl 4-(((trifluoromethyl)selanyl)methyl)benzoate (3g).

Yellowish oil. Characterization data match that reported in the literature [56].

Synthesis of (4-nitrobenzyl)(trifluoromethyl)selane (3h)

Yellow oil. Characterization data match that reported in the literature [62].

Synthesis of (2-methylbenzyl)(trifluoromethyl)selane (3i).

Colorless oil.

1 H NMR (300 MHz, Chloroform-d) 7.27 (m, 1H), 7.23-7.13 (m, 3H), 4.28 (s, 2H), 2.40 (s, 3H). 19 F NMR (282 MHz, Chloroform-d) δ -34.49 (s, 3F).

Characterization data match that reported in the literature [60].

Synthesis of (2-chloro-4-methoxybenzyl)(trifluoromethyl)selane (XX)

Yellowish oil.

Synthesis of 2-(((trifluoromethyl)selanyl)methyl)pyridine (3k).

Synthetized From HBr salt. Yellowish oil.

1 H NMR (300 MHz, Chloroform-d) δ 8.54 (d, J = 4.8 Hz, 1H), 7.66 (td, J = 7.7, 1.8 Hz, 1H), 7.33 (d, J = 7.9 Hz, 1H), 7.19 (ddd, J = 7.6, 4.9, 1.1 Hz, 1H), 4.37 (s, 2H). 19 F NMR (282 MHz, Chloroform-d) δ -34.59 (s, 3F).

Characterization data match that reported in the literature [56].

Synthesis of 2-nitro-5-(((trifluoromethyl)selanyl)methyl)furan (3l).

Brownish oil. Characterization data match that reported in the literature [56].

Synthesis of cinnamyl(trifluoromethyl)selane (3m).

Colorless oil. Characterization data match that reported in the literature [62].

Synthesis of (E)-(3,7-dimethylocta-2,6-dien-1-yl)(trifluoromethyl)selane (3n)

. 19 F NMR (376 MHz, Chloroform-d) δ -34.06 (s, 3F).

Characterization data match that reported in the literature [63].

Synthesis of (3-phenylprop-2-yn-1-yl)(trifluoromethyl)selane (3o)

. 19 F NMR (376 MHz, Chloroform-d) δ -35.41 (s, 3F).

Characterization data match that reported in the literature [62].

Synthesis of 1-phenyl-2-((trifluoromethyl)selanyl)ethan-1-one (3p).

Yellowish oil. Characterization data match that reported in the literature [64].

Synthesis of phenethyl(trifluoromethyl)selane (3q).

Yellowish oil. Characterization data match that reported in the literature [62].

Synthesis of benzyl(perfluoropropyl)selane (4a)

Yellowish oil. Characterization data match that reported in the literature [START_REF] Glenadel | [END_REF].

1 H

 1 NMR (300 MHz, Chloroform-d) δ 7.37-7.27 (m, 5H), 4.24 (s, 2H)19 F NMR (282 MHz, Chloroform-d) δ -34.46 (s, 3F).

1 H

 1 NMR (300 MHz, Chloroform-d) δ 7.36 (m, 2H), 7.28 (m, 2H), 4.24 (s, 2H), 1.32 (s, 9H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.53 (s, 3F).

1 H

 1 NMR (300 MHz, Chloroform-d) δ 7.62 -7.55 (m, 4H), 7.50 -7.33 (m, 5H), 4.31 (s, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.93 (s, 3F).

1

  H NMR (300 MHz, Chloroform-d) δ 7.31 (m, 2H), 7.02 (m, 2H), 4.22 (s, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.38 (s, 3F), -114,11 (m, 1H).

1

  H NMR (300 MHz, Chloroform-d) δ 8.00 (m, 2H), 7.40 (m, 2H), 4.25 (s, 2H), 3.91 (s, 3H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.33 (s, 3F).

1 H

 1 NMR (300 MHz, Chloroform-d) δ = 8.22 (m, 2H), 7.52 (m, 2H), 4.28 (s, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.12 (s, 3F).

1 H

 1 NMR (500 MHz, Chloroform-d) δ 7.26 (d, J = 8.6 Hz, 1H), 6.94 (d, J = 2.6 Hz, 1H), 6.77 (dd, J = 8.5, 2.6 Hz, 1H), 4.26 (s, 2H), 3.79 (s, 3H).

1

  H NMR (300 MHz, Chloroform-d) δ = 7.26 (d, J = 3.7 Hz, 1H), 6.52 (d, J = 3.7 Hz, 1H), 4.18 (s, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.45 (s, 3F).

1 H

 1 NMR (300 MHz, Chloroform-d) δ = 7.37-7.21 (m, 5H), 6.55 (d, J = 15.6 Hz, 1H), 6.31 (dt, J = 15.5, 7.7 Hz, 1H), 3.82 (d, J = 7.7 Hz, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -33.79 (s, 3F).

1

  H NMR (300 MHz, Chloroform-d) δ = 7.97 (m, 2H), 7.63 (t, J = 7.4, 1.2 Hz, 1H), 7.51 (m, 2H), 4.63 (s, 2H).

1 H

 1 NMR (300 MHz, Chloroform-d) δ = 7.33 (m, 2H), 7.27 (m, 1H), 7.21 (m, 2H), 3.23 (m, 2H), 3.10 (m, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -34.10 (s, 3F).

1

  H NMR (300 MHz, Chloroform-d) δ 7.40 -7.27 (m, 5H), 4.29 (s, 2H).

19 F

 19 NMR (282 MHz, Chloroform-d) δ -79.73 (t, J = 9.2 Hz, 3F), -87.70 (m, 2F), -122.74 (t, J = 3.9 Hz, 2F).

Table 1 .

 1 Nucleophilic Trifluoromethylselenolation of 2a with 1a.

	Entry	Metal (equiv.)	Solvent	t (min)	3a (%) a
	1	Zn (3 equiv.)	DMSO	60	90
	2	Zn (2 equiv.)	DMSO	60	93
	3	Zn (1 equiv.)	DMSO	60	65
	4	Zn (2 equiv.)	DMSO	15	95
	5	Zn (2 equiv.)	CH3CN	15	0
	6	Zn (2 equiv.)	THF	15	11
	7	Fe (2 equiv.)	DMSO	15	86
	8	Fe (1 equiv.)	DMSO	60	83
	9	-	DMSO	60	0

  Hz), 115.34, 113.38, 55.69, 26.62 (d, J = 1.8 Hz).

	13 C NMR (126 MHz, Chloroform-d) δ 160.03, 134.88, 131.47, 126.54, 123.06 (q, J = 331.3
	19 F NMR (376 MHz, Chloroform-d) δ -34.28.
	HRMS (EI): calc. for [C9H8ClF3OSe] 303.9376, measured 3030.9366

Acknowledgments

This work was supported by a grant from the French National Research Agency (ANR 18-CE07-0039-01). The authors are grateful to the French National Research Agency, the CNRS and the French Ministry of Research for financial support. The French Fluorine Network (GIS-FLUOR) is also acknowledged for its support.


Kevin Grollier

Dr Clément A Ghiazza

Anis Tlili

Dr Thierry Billard

Maurice Médebielle
email: maurice.medebielle@univ-lyon1.fr

Julien C Vantourout
email: julien.vantourout@univ-lyon1.fr

Dr T Tlili

Dr M Billard

Dr J C Médebille

Vantourout

Electrochemical Trifluoromethylselenolation of Activated Alkyl Halides

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Introduction

Since 1954 and the discovery of fludrocortisone 1 (Scheme 1A), fluorine-containing molecules keep flourishing and have found applications in the fields of medicinal and agrochemical chemistry as well as material science. [1][2][3][4][5][6][7][8][9][10][11][START_REF]Fascinating Fluoropolymers and Their Applications[END_REF][START_REF] Améduri | [END_REF][14][15][16] Strikingly, about three out of the five top-selling drugs bear at least one fluorine atom with atorvastatin 2 (Lipitor) being the best-selling pharmaceutical (Scheme 1A). 3,17 This trend relies on the various effects that fluorine and fluorinecontaining substituents can convey on properties of organic compounds such as basicity, acidity, lipophilicity, stability, conformation, and electrostatic interactions. [START_REF] Kirsch | Modern Fluoroorganic Chemistry[END_REF][START_REF] Smart | [END_REF] Therefore, being able to modulate those properties is highly important and desirable. 3,8 In this context, new fluorine-containing motifs have been developed and their incorporation into structures has been widely investigated. [START_REF]Emerging Fluorinated Motifs: Synthesis, Properties and Applications[END_REF] If to date, the trifluoromethyl (CF3) is the most used fluoroalkyl group, trifluoromethyl chalcogens (OCF3, SCF3 and SeCF3) are of significant interest since their increased lipophilicity and steric hindrance can considerably alter the properties of organic molecules. [START_REF]Emerging Fluorinated Motifs: Synthesis, Properties and Applications[END_REF][START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF] Out of the three trifluoromethyl chalcogens, SeCF3 has received less attention [START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF][START_REF] Wang | [END_REF] as some Se-containing substrates are sensitive to air and present high toxicity. 23 However, selenium is a crucial trace element of the human machinery, 24-26 and selenolated compounds have found plethora of applications in multiple areas including life sciences and materials. [27][28][29][30][31][32][33] Therefore, several research groups recognized the potential of merging the CF3 group with selenium, especially in the context of drug design, 34,35 to incorporate SeCF3 moieties into organic structures. [START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF][START_REF] Wang | [END_REF] The direct formation of C(sp 2 )-SeCF3 bond formation has been extensively studied and elegant trifluoromethylselenolation methods for the functionalization of aryl compounds have been reported. [START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF][START_REF] Wang | [END_REF]36 Conversely, access to alkyl trifluoromethylselenylated entities has proven more challenging, and to date, only a few strategies have been described in the literature. [START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF][START_REF] Wang | [END_REF][23]37 The most expedient way to afford such compounds remains the direct nucleophilic substitution of activated alkyl species with the CF3Se -anion to forge the desired C(sp 3 )-SeCF3 bond (Scheme 1B). [START_REF] Toulgoat | Organofluorine Chemistry: Synthesis, Modeling, and Applications[END_REF][START_REF] Wang | [END_REF][23]37 Due to the synthetic challenge associated to the generation of the CF3Se -anion, several copper-based methodologies have been reported (Scheme 1B, a). [38][39][40] In 2003, Tyrra and co-workers reported the convenient synthesis of the airstable (Me4N)SeCF3 reagent 41 which was subsequently used as a trifluoromethyselenylating reagent with various electrophiles by the Zhang group (Scheme 1B, b). 42 Recently, Billard, Tlili and co-workers described efficient electrophilic and radical trifluoromethylselenolation reactions using bench-stable trifluoromethylselenotoluenesulfonate reagent 3 (TsSeCF3). [43][44][45][46][47] In 2019, the same group demonstrated that this reagent could be reduced by tetrakis(dimethylamino)ethylene (TDAE) to perform nucleophilic trifluoromethylselenolation reactions via in situ generation of the CF3Se -anion (Scheme 1B, c). 48 Despite the excellent yields obtained, sensitivity of TDAE encouraged the authors to develop a complementary way to achieve a similar umpolung approach. Replacing TDAE with tetrabutylammonium iodide (TBAI) allowed the in-situ formation of CF3SeI under non-reductive conditions (Scheme 1B, d). 49 The milder set of conditions afforded good to excellent yields with reactive electrophiles (benzylic, allylic or propargylic) but provided lower conversions with nonactivated substrates. More recently, they also reported a metal-based reductive approach that employs iron powder to reduce the TsSeCF3 reagent. 50 The reductive approaches rely on the low reduction potential of TsSeCF3 in polar solvents such as DMSO (-0.51 V/SCE) and DMF (-0.65 V/SCE). Therefore, we envisioned to use electrochemistry to replace the stoichiometric quantities of reducing or activating agents. Indeed, when it comes to manipulation of electrons, electrochemistry is certainly the easiest and most economical method to use. [51][52][53][54][55][56][57] The direct cathodic reduction of TsSeCF3 would in situ mildly generate the CF3Se -anion affording a set of conditions for the metalfree trifluoromethylselenolation of activated alkyl halides.

Results and Discussion

We started our investigation by using one equivalent of both TsSeCF3 3 and benzyl bromide 4 in dry DMSO under air at room temperature using NEt4BF4 as electrolyte. The electrochemical undivided cell was equipped with a graphite anode and a graphite cathode. A current of 5 mA was applied for 2 F.mol -1 affording 58% of the desired trifluoromethylselenolated product 5 (Scheme 2A, entry 1). Running the reaction under inert atmosphere did not improve the yield (Scheme 2A, entry 2). As expected (see cyclic voltammetry data, see SI for details), solvents dramatically impact the reaction outcome of the reaction with DMF delivering desired product 5 with an efficiency comparable to DMSO (Scheme 2A, entries 3-5). Changing the electrolyte to TBAPF6, TBABF4, KPF6 or LiClO4 slightly lowered the yield of the reaction (Scheme 2A, entries 6-9). Cathodic materials were also investigated but none of them improved the conversion to the desired product (Scheme 2A, entries 10-13 and see SI for more details). To avoid any unnecessary oxidation processes, zinc or magnesium sacrificial anodes were tested (Scheme 2A, entries 14-15). Yields obtained were good but significant product formation was observed in the absence of electricity due to direct reduction of TsSeCF3 3 by the metal. 50 To suppress this competitive pathway and to limit the generation of undesired metal salts, graphite was selected as the anode material. Interestingly, concentration had a significant impact on the reaction outcome. While concentrating the reaction was detrimental (Scheme 2A, entry 16), higher dilution proved beneficial and afforded compound 5 in 63% yield (Scheme 2A, entry 17). Using an excess of reagent 3 lowered the yield from 58% to 47% (Scheme 2A, entry 18). Increasing both the equivalent of benzyl bromide 4 and the number of electrons delivered to the system positively impact the yield of the reaction (Scheme 2A, entries 19 and 20). Finally, in the With the optimized electrochemical conditions in hands, we evaluated the scope and limitations of the reaction (Scheme 3). Good to excellent yields were obtained with benzylic starting materials bearing both electron withdrawing and donating groups on the aromatic component (5-10, 12 and 13). Noteworthy, heterocyclic moieties such as pyridine were tolerated under the reaction conditions (11). Orthosubstituted aromatic, allylic and propargylic halide compounds also proved competent and afforded good yields (12-15 and 19). Disappointingly, the reaction seems to be very sensitive to steric hindrance as illustrated by the low yield obtained for compound 18. In addition, aliphatic substrates only delivered low yields (17 and 20) except for activated α-bromo acetophenone which afforded quantitative amount of desired product 16. Chloride starting materials gave modest to moderate yields (5, 14 and 15). This observation matches with previous studies, where the Cl - anion proved better nucleophile than the CF3Se -anion. To further assess the scope of our electrochemical method, we undertaken a robustness test where our model reaction was doped with additives bearing different functional groups (Scheme 4). 58 At the end of the experiment, we measured the yield of the desired product 5 by [START_REF] Smart | [END_REF] F NMR and the amount of additive recovered by GCMS. Pleasingly, functional groups such as trifluoromethyl, silyl ether, and boronic esters as well as primary amide, unprotected aniline, free alcohol, and free carboxylic acid were tolerated affording moderate to good yields of 3 and high recovery of the corresponding additives. Noteworthy, the electrochemical protocol affords similar yields than the previously reported approaches that require stoichiometric quantities of reducing or activating agents. [43][44][45][46][47][48][49][50] Comparable limitations are also observed with non-activated alkyl halides delivering low yields of the desired products.

Through the course of our study, cyclic voltammetric measurements revealed that TsSCF3 owns a similar reduction potential (-0.58 V/SCE, see SI for details) to TsSeCF3 in DMSO (-0.51 V/SCE, see SI for details). Therefore, we attempted to use TsSCF3 as a trifluoromethylthiolation reagent under our electrochemical procedure. Unfortunately, compounds 21 and 22 were only obtained in low yields of 12% and 18%, respectively. The instability of the in-situ generated CF3S -anion could certainly explain the lower efficiency of the trifluoromethylthiolation process. 59,60 To gain insight into the reaction mechanism, several experiments were conducted (Scheme 4). All mechanistic events are described in a stepwise fashion (Scheme 4A and B): 1. TsSeCF3 reagent 3 is initially reduced leading to the formation of Ts -anion II (+ 0.36 V/SCE in DMSO) along with CF3Se • radical III (Scheme 4C, panel 1).

Scheme 4. Robustness test of the reaction. Yields for compound 5 were determined by [START_REF] Smart | [END_REF] F NMR using trifluoromethoxybenzene as internal standard. Yields for the additives were determined by GCMS using 1,3,5trimethoxybenzene as internal standard.

2. Radical III then reacts with TsSeCF3 reagent 3 to afford (SeCF3)2 I (Scheme 4C, kinetic profile and panel 2a). Indeed, we demonstrated that under the reaction conditions, after 0.5 F.mol -1 , TsSeCF3 3 was fully consumed, and dimer (SeCF3)2 I was formed in 44% along with 12% of desired product 5. In addition, running the electrolysis in a divided setup and in the absence of benzyl bromide 4, TsSeCF3 3 was quantitatively reduced to dimer I after only applying 0.5 F.mol -1 . 3. Dimer I can then be reduced to form the CF3Se -anion IV and CF3Se • radical III as highlighted by the cyclic voltammetry experiment described in panel 1. Reduction of dimer I occurs at -0.45 V/SCE in DMSO whereas oxidation of the CF3Se -anion IV is observed at + 0.04V/SCE in DMSO (Scheme 4C, panel 1). Formation of anion IV was further established by [START_REF] Smart | [END_REF] F NMR when reducing dimer III in a divided setup in the absence of benzyl bromide (Scheme 4C, panel 2b). 4. Radical III certainly reacts with TsSeCF3 reagent 3 to afford (SeCF3)2 I. However, direct dimerization of CF3Se • radical III cannot be ruled out.

Electrochemically generated CF3Se

-anion IV can react with starting material activated alkyl bromide 4 to afford desired product 5 (Scheme 4C, panel 2c). 6. Based on cyclic voltammetric data, both Ts -anion II (+ 0.36 V/SCE in DMSO) and CF3Se -anion IV (+ 0.04V/SCE in DMSO) can potentially be oxidized at the anode affording Ts • radical V and CF3Se • radical III respectively (Scheme 4C, panel 1). Ts • radical V is easily reduced and therefore competes with the productive reduction of dimer I, explaining why more electrons need to be passed through the system to achieve higher conversions. Ts • radical V was also trapped in a control experiment where the reaction was conducted in the presence styrene instead of benzyl bromide 4 affording both isomers of 1-methyl-4-(styrylsulfonyl)benzene (Scheme 4C, panel 3).

Based on these observations, it was envisioned to suppress the competing reduction of Ts • radical V by using a divided cell setup at a constant potential of -0.51 V/SCE corresponding to the reduction potential of TsSeCF3 (Scheme 4D and see SI for details). Under these conditions, compounds 5, 9, and 23 were obtained in 60%, 70% and 51% yield with only 1 F.mol -1 validating the aforesaid hypothesis. Noteworthy, based on the mechanistic pathway, a maximum yield of 50% should have been obtained under these conditions. However, Br -anion formed through the course of the reaction can react with TsSeCF3 reagent 3 to form dimer I. Therefore, as soon as product 5 is formed, the only required electrochemical event is the reduction of dimer I (Scheme 4C, Panel 4).

Conclusion

An electrochemical method for the metal-free trifluoromethylselenolation of activated alkyl halides has been developed which exhibits a broad scope and a high functional group tolerance. This transformation relies on the reduction of shelf-stable reagent TsSeCF3 to afford the reactive CF3Se -anion which can further react with alkyl halide substrates via a nucleophilic substitution type mechanism. The main limitation of this protocol is the need to use a divided cell setup to avoid the reduction of sensitive substrates. A combination of cyclic voltammetric and [START_REF] Smart | [END_REF] F NMR studies allowed to gain insight into the reaction mechanism. This new protocol reinforces the high versatility of TsSeCF3 reagent in accomplishing electrophilic, radical, or nucleophilic reactions, depending on the conditions. It also demonstrates that depending on the substrate classes, reductive electrochemical conditions can be complementary to methods that require stoichiometric quantities of reducing or activating agents.

Scheme 1 .

 1 Scheme 1. Introduction. (A) Fluorine-containing pharmaceuticals, (B) Nucleophilic trifluoromethylselenolations: State of the Art, and (C) This work: Electrochemical trifluoromethylselenolation.

Scheme 2 .

 2 Scheme 2. Optimization. a Yields were determined by 19 F NMR using trifluoromethoxybenzene as internal standard. Isolated yields are shown in brackets. b Reaction was run under argon atmosphere instead of air. c 1 F.mol -1 instead of 2 F.mol -1 .

Scheme 3 .

 3 Scheme 3. Scope of the reaction. Yields were determined by 19 F NMR using trifluoromethoxybenzene as internal standard. Isolated yields are shown in brackets. a 0.45 mmol scale using a 20 mL vial, 10 mA and 8 F.mol -1 . b Starting from the hydrobromide salt.

Scheme 5 .

 5 Scheme 5. Mechanistic study. (A) Proposed mechanism, (B) Summary of key mechanistic events, (C) Control experiments, and (D) Divided-cell setup.Yields were determined by[START_REF] Smart | [END_REF] F NMR using trifluoromethoxybenzene as internal standard. Isolated yields are shown in brackets. a For this step, the formation of CF3Se -anion along with Ts . radical cannot be ruled out and is discussed in the SI. b CF3Se -anion was first prepared in the divided cell then the halide was added to reaction mixture.

Acknowledgements

This work was supported by a grant from the French National Research Agency (ANR 18-CE07-0039-01). The NMR