White matter hyperintensities are associated with increased risk of dementia and cognitive decline. The current study investigates the relationship between white matter hyperintensities burden and patterns of brain atrophy associated with brain ageing and Alzheimer's disease in a large populatison-based sample (n = 2367) encompassing a wide age range (20-90 years), from the Study of Health in Pomerania. We quantified white matter hyperintensities using automated segmentation and summarized atrophy patterns using machine learning methods resulting in two indices: the SPARE-BA index (capturing age-related brain atrophy), and the SPARE-AD index (previously developed to capture patterns of atrophy found in patients with Alzheimer's disease). A characteristic pattern of age-related accumulation of white matter hyperintensities in both periventricular and deep white matter areas was found. Individuals with high white matter hyperintensities burden showed significantly (P < 0.0001) lower SPARE-BA and higher SPARE-AD values compared to those with low white matter hyperintensities burden, indicating that the former had more patterns of atrophy in brain regions typically affected by ageing and Alzheimer's disease dementia. To investigate a possibly causal role of white matter hyperintensities, structural equation modelling was used to quantify the effect of Framingham cardiovascular disease risk score and white matter hyperintensities burden on SPARE-BA, revealing a statistically significant (P < 0.0001) causal relationship between them. Structural equation modelling showed that the age effect on SPARE-BA was mediated by white matter hyperintensities and cardiovascular risk score each explaining 10.4% and 21.6% of the variance, respectively. The direct age effect explained 70.2% of the SPARE-BA variance. Only white matter hyperintensities significantly mediated the age effect on SPARE-AD explaining 32.8% of the variance. The direct age effect explained 66.0% of the SPARE-AD variance. Multivariable regression showed significant relationship between white matter hyperintensities volume and hypertension (P = 0.001), diabetes mellitus (P = 0.023), smoking (P = 0.002) and education level (P = 0.003). The only significant association with cognitive tests was with the immediate recall of the California verbal and learning memory test. No significant association was present with the APOE genotype. These results support the hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population. White matter hyperintensities also contribute to brain atrophy patterns in regions related to Alzheimer's disease dementia, in agreement with their known additive role to the likelihood of dementia. Preventive strategies reducing the odds to develop cardiovascular disease and white matter hyperintensities could decrease the incidence or delay the onset of dementia.

Background The burden of cerebral white matter hyperintensities (WMH) is associated with an increased risk of stroke, dementia, and death. WMH are highly heritable, but their genetic underpinnings are incompletely characterized. To identify novel genetic variants influencing WMH burden, we conducted a meta-analysis of multi-ethnic genome-wide association studies. Methods and Results We included 21,079 middle-aged to elderly individuals from 29 population-based cohorts, who were free of dementia and stroke and were of European (N=17,936), African (N=1,943), Hispanic (N=795), and Asian (N=405) descent. WMH burden was quantified on MRI either by a validated automated segmentation method or a validated visual grading scale. Genotype data in each study were imputed to the 1000 Genomes reference. Within each ethnic group, we investigated the relationship between each SNP and WMH burden using a linear regression model adjusted for age, sex, intracranial volume, and principal components of ancestry. A meta-analysis was conducted for each ethnicity separately and for the combined sample. In the European descent samples, we confirmed a previously known locus on chr17q25 (p=2.7×10−19) and identified novel loci on chr10q24 (p=1.6×10−9) and chr2p21 (p=4.4×10−8). In the multi-ethnic meta-analysis, we identified two additional loci, on chr1q22 (p=2.0×10−8) and chr2p16 (p=1.5×10−8). The novel loci contained genes that have been implicated in Alzheimer’s disease (chr2p21, chr10q24), intracerebral hemorrhage (chr1q22), neuroinflammatory diseases (chr2p21), and glioma (chr10q24, chr2p16). Conclusions We identified four novel genetic loci that implicate inflammatory and glial proliferative pathways in the development of white matter hyperintensities in addition to previously-proposed ischemic mechanisms.

I schemic stroke remains a leading cause of death and disability worldwide.1 Planning cost-effective preventive strategies requires precise knowledge of stroke risk factors. 2 Approximately 10% of ischemic strokes occur at ages <45 years, 3 with major long-term socioeconomic con sequences. 4 Stroke prevention results in greater quality-weighted life-yearBackground and Purpose-Although many stroke patients are young or middle-aged, risk factor profiles in these age groups are poorly understood. Methods-The Stroke in Young Fabry Patients (sifap1) study prospectively recruited a large multinational European cohort of patients with cerebrovascular events aged 18 to 55 years to establish their prevalence of Fabry disease. In a secondary analysis of patients with ischemic stroke or transient ischemic attack, we studied age-and sex-specific prevalences of various risk factors. Results-Among 4467 patients (median age, 47 years; interquartile range, 40-51), the most frequent well-documented and modifiable risk factors were smoking (55.5%), physical inactivity (48.2%), arterial hypertension (46.6%), dyslipidemia (34.9%), and obesity (22.3%). Modifiable less well-documented or potentially modifiable risk factors like high-risk alcohol consumption (33.0%) and short sleep duration (20.6%) were more frequent in men, and migraine (26.5%) was more frequent in women. Women were more often physically inactive, most pronouncedly at ages <35 years (18-24: 38.2%; 25-34: 51.7%), and had high proportions of abdominal obesity at age 25 years or older (74%). Physical inactivity, arterial hypertension, dyslipidemia, obesity, and diabetes mellitus increased with age. Conclusions-In this large European cohort of young patients with acute ischemic cerebrovascular events, modifiable risk factors were highly prevalent, particularly in men and older patients. These data emphasize the need for vigorous primary and secondary prevention measures already in young gain in younger patients than in elderly patients, but has received less attention.In the general population and in patient cohorts, risk factor profiles changed with increasing age. 5,6 Most studies of stroke patients aged <50 years were small and methodologically heterogeneous. [7][8][9][10] In the largest single-center study including 1008 ischemic stroke patients aged 15 to 49 years, 7 the most common risk factors were dyslipidemia (60%), smoking (44%), and arterial hypertension (39%), with accumulation in men and increasing age. However, only scarce data exist on the prevalence and risk potential of lifestyle risk factors such as physical inactivity, obesity, 7,8,11 body mass index, waist circumference, 12 and sleep pattern 13,14 in the young. The Stroke in Young Fabry Patients (sifap1) study 15 prospectively recruited a large multinational European cohort of patients aged 18 to 55 years with cerebrovascular event (CVE) to establish their prevalence of Fabry disease. In a secondary analysis of patients with ischemic stroke and transient ischemic attack (TIA), we investigate...

Background and Purpose-Strokes have especially devastating implications if they occur early in life; however, only limited information exists on the characteristics of acute cerebrovascular disease in young adults. Although risk factors and manifestation of atherosclerosis are commonly associated with stroke in the elderly, recent data suggests different causes for stroke in the young. We initiated the prospective, multinational European study Stroke in Young Fabry Patients (sifap) to characterize a cohort of young stroke patients. Methods-Overall, 5023 patients aged 18 to 55 years with the diagnosis of ischemic stroke (3396) *Drs Rolfs, Fazekas and Grittner contributed equally to this work. Authors contributions: Dr Rolfs has conceptualized, initiated, and designed and organized the study, has been involved in the recruitment of the patients, and wrote significant parts of the manuscript. Dr Fazekas was involved in the study planning and has done together with Drs Enzinger and Schmidt the analysis of all MRI scans; this group was mainly involved in the statistical analysis of the MRI data. Drs Martus, Grittner, Holzhausen have taken responsibility for all statistical analysis and for the data structure of the total data bank. Drs Dichgans, Böttcher, Tatlisumak, Tanislav, Jungehulsing, Putaala, Huber, Bodechtel, Lichy, Hennerici, Kaps, Meyer, Kessler have been most active in the recruitment of the patients, drafting the manuscript and significantly influencing the scientific discussion. Dr Heuschmann was involved in drafting the manuscript and influencing the scientific discussion. Dr Norrving chaired the steering and publication committees of sifap, has written parts of the manuscript, and has significantly influenced the scientific discussions. Drs Lackner and Paschke, H. Mascher, Dr Riess have been involved in the laboratory analyses. Dr Kolodny has mostly contributed to the discussion of the Fabry cases. Dr Giese assisted in writing and editing the manuscript. All authors have reviewed, critically revised and approved the final version of the manuscript.The sponsors of the study had no role in the study design, data collection, data analysis, interpretation, writing of the manuscript, or the decision to submit the manuscript for publication. The academic authors had unrestricted access to the derived dataset, and assume full responsibility for the completeness, integrity, and interpretation of the data, as well as writing the study report and the decision to submit for publication.†Listed in Appendix I in the online-only Data Supplement. Jeffrey L. Saver, MD, was guest editor for this article.

ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10−8; and LINC00539/ZDHHC20, p = 5.82 × 10−9. Both have been associated with blood pressure (BP)–related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10−25; p[SSBI] = 5.23 × 10−14 for hypertension), smoking (p[BI] = 4.4 × 10−10; p[SSBI] = 1.2 × 10−4), diabetes (p[BI] = 1.7 × 10−8; p[SSBI] = 2.8 × 10−3), previous cardiovascular disease (p[BI] = 1.0 × 10−18; p[SSBI] = 2.3 × 10−7), stroke (p[BI] = 3.9 × 10−69; p[SSBI] = 3.2 × 10−24), and MRI-defined white matter hyperintensity burden (p[BI] = 1.43 × 10−157; p[SSBI] = 3.16 × 10−106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.