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Objective: To describe clinical and genealogic features in a Swedish family with Alzheimer's disease with a double mutation of the amyloid precursor protein gene at codon 670/671 and to study the effects of anticipation and imprinting. Design: Interviews with relatives, clinical investigations of the diseased, pedigree analysis, studies of medical records, and comparison with other families affected by Alzheimer's disease with amyloid precursor protein mutations. Setting: The Alzheimer's Disease Research Centre, Department of Clinical Neuroscience, Section of Geriatric Medicine, Karolinska Institute, Huddinge (Sweden) University Hospital. Patients and Other Participants: Individuals with the amyloid precursor protein codon 670/671 mutation and their relatives (N=66). Results: The trait was traced through eight generations, and an autosomal dominant inheritance with very high penetrance was observed. Onset occurred between 44 and 61 years of age (mean, 53 years). The mean duration of disease was 8.5 years (range, 3 to 13 years). The earliest clinical manifestations were deficits in memory function and abstract reasoning. Myoclonic jerks and seizures were common symptoms late in the disease. Anticipation and imprinting effects were not found in this family. Conclusions: The disease in this family has a single origin—a double mutation in the amyloid precursor protein gene at codon 670/671 transmitted as an autosomal dominant trait. The wide range in age at onset and the clinical symptoms in this pedigree give a characteristic phenotype similar to that seen in some of the other pedigrees with amyloid precursor protein mutations.

An ELISA method has been developed to quantitate human porphobilinogen deaminase in erythrocyte lysate. The antiserum used in the assay was raised against the erythropoietic form of human porphobilinogen deaminase. The IgG fraction was characterized by use of immunoblotting technique, rocket immunoelectrophoresis and immunotitration and shown to be monospecific. The measuring range of the method was from 4 ng to 50 pg. Intra- and inter-assay coefficients of variation were 6% and 7%, respectively. Erythrocyte lysates from 97 apparently healthy individuals were assayed giving a mean erythrocyte porphobilinogen deaminase protein concentration of 150 +/- 28 SD (micrograms/g Hb) and a specific enzyme activity of 750 +/- 140 SD (nkat/g). Eight patients with acute intermittent porphyria were also investigated. A decreased concentration of enzyme protein, i.e. 84 +/- 13 SD (micrograms/g Hb) with a normal specific activity, was found.

It has previously been shown that immune complexes (IC) of a given biomarker with class M immunoglobulins (IgM) provide better performances compared to the unbound biomarker in a number of cancer entities. In the present work, we investigated IC of IgM-Abeta as a potential biomarker for Alzheimer's disease (AD). Abeta-IgM concentration has been measured in 75 plasma samples from patients with AD, individuals with mild cognitive impairment (MCI), and healthy age- and sex-matched controls (HC). To characterize the fractions associated with Abeta, pooled plasma samples were subjected to gel-filtration analysis. Size-separated fractions were analyzed for the presence of Abeta using a sandwich ELISA assay. A strong reactivity was observed in the high molecular weight IgM (>500 kDa) and 150 kDa (IgG) fractions indicating that blood Abeta is strongly associated with antibodies. Using an ELISA assay detecting Abeta-IgM complexes, we observed that high levels of Abeta-IgMs were detectable in HC and MCI patients; however, there was no significant difference to the AD group.

Background We here examined whether plasma desmosterol‐to‐cholesterol ratio (DES/CHO) is decreased in patients with Alzheimer's disease (AD) and investigated the association between plasma DES/CHO and longitudinal cognitive decline. Methods Plasma DES/CHO of AD patients and age‐matched controls in a Japanese cross‐sectional cohort was determined. Plasma DES/CHO at baseline and follow‐up visits was assessed in relation to cognitive decline in Japanese and Swedish longitudinal cohorts. Results Plasma DES/CHO was significantly reduced in Japanese AD patients and significantly correlated with Mini‐Mental State Examination (MMSE) score. The longitudinal analysis revealed that plasma DES/CHO in AD patients shows a significant decrease at follow‐up intervals. The decline in plasma DES/CHO is larger in the AD group with rapid progression than in that with slow progression. The changes in plasma DES/CHO significantly correlated with changes in the MMSE score. Conclusion Plasma DES/CHO is decreased in AD patients and may serve as a longitudinal surrogate marker associated with cognitive decline.

Structural variations are among the most frequent interindividual genetic differences in the human genome. The frequency and distribution of de novo somatic structural variants in normal cells is, however, poorly explored. Using age-stratified cohorts of 318 monozygotic (MZ) twins and 296 single-born subjects, we describe age-related accumulation of copy-number variation in the nuclear genomes in vivo and frequency changes for both megabase- and kilobase-range variants. Megabase-range aberrations were found in 3.4% (9 of 264) of subjects ≥60 years old; these subjects included 78 MZ twin pairs and 108 single-born individuals. No such findings were observed in 81 MZ pairs or 180 single-born subjects who were ≤55 years old. Recurrent region- and gene-specific mutations, mostly deletions, were observed. Longitudinal analyses of 43 subjects whose data were collected 7-19 years apart suggest considerable variation in the rate of accumulation of clones carrying structural changes. Furthermore, the longitudinal analysis of individuals with structural aberrations suggests that there is a natural self-removal of aberrant cell clones from peripheral blood. In three healthy subjects, we detected somatic aberrations characteristic of patients with myelodysplastic syndrome. The recurrent rearrangements uncovered here are candidates for common age-related defects in human blood cells. We anticipate that extension of these results will allow determination of the genetic age of different somatic-cell lineages and estimation of possible individual differences between genetic and chronological age. Our work might also help to explain the cause of an age-related reduction in the number of cell clones in the blood; such a reduction is one of the hallmarks of immunosenescence. © 2012 The American Society of Human Genetics.

The presenilin-1 (PS-1) gene on chromosome 14 carries mutations which cosegregate with early-onset familial Alzheimer's disease. We quantified PS-1 mRNA in post-mortem mid-temporal and superior frontal cortices from 14 Alzheimer's disease subjects, 9 non-demented controls and 5 subjects with other neurological diseases using solution hybridisation-RNase protection assay. APP and APLP2 mRNAs had previously been quantified in these samples (Johnston et al. (1996) Mol. Brain Res., in press) and subjects were apolipoprotein E (APOE) genotyped. There were no significant differences between PS-1 mRNA levels per pg total RNA in mid-temporal or superior frontal cortices of the Alzheimer's disease subjects, compared to controls. PS-1 mRNA levels corresponded to 10% of total APP and 30% of APLP2 mRNA levels, and were not significantly affected by age, post-mortem delay, tissue pH, or APOE genotype. PS-1 mRNA showed significant positive correlations with APP and APLP2 mRNA levels in mid-temporal cortex and with APP mRNA in superior frontal cortex. This may reflect a co-regulation of the expression of these genes, or the fact that they are expressed in similar neuronal populations.

OBJECTIVE: To study the association between self-reported sleep disturbances and dementia risk. METHODS: Self-reported sleep disturbances and established risk factors for dementia were measured in men at ages 50 (n = 1574) and 70 (n = 1029) years. Dementia incidence was determined by reviewing their patient history between ages 50 and 90 years. In addition, plasma levels of β-amyloid (Aβ) peptides 1-40 and 1-42 were measured at ages 70, 77, and 82 years. RESULTS: Cox regression demonstrated that men with self-reported sleep disturbances had a higher risk of developing dementia (+33%) and Alzheimer's disease (AD, +51%) than men without self-reported sleep disturbances (both P

Two unrelated families with acute intermittent porphyria (AIP), an autosomal dominant disease related to a defect in porphobilinogen deaminase (PBG-D, EC 4.1.3.8.), were studied with regard to three restriction fragment length polymorphisms (RFLPs) (MspI, PstI, BstNI) within the PBG-D gene. The results indicate that linkage analysis of RFLPs within the gene can be used as a complement to PBG-D analysis for the diagnosis of gene carriers in families with AIP.

The last few years have seen considerable advances in understanding the pathogenesis of Alzheimer’s disease (AD). In 1992, we identified a double mutation in exon 16 of the amyloid precursor protein (APP) gene in two large Swedish AD families that results in a double amino acid substitution at codons 670 and 671. A follow-up genealogical study of these two Swedish 670/671 families has indicated that they are related to a common founder. We recently performed a two-point linkage analysis of this extended pedigree and obtained a lod score of 7.62 at zero recombination. Furthermore, following the death of a demented carrier from this family, we obtained pathological confirmation of the clinical diagnosis of AD in this family. The discovery of the Swedish 670/671 mutation has provided strong evidence that the expression of an altered APP can cause AD and has significantly strengthened the case for the amyloid hypothesis of AD.

The number of nicotinic and muscarinic receptors and choline acetyltransferase (ChAT) activity were investigated in the temporal cortex of patients with Alzheimer's disease (AD) with different apolipoprotein E (APOE) genotypes. A significant reduction in the ChAT activity (P < 0.001) and in the number of nicotinic receptors (P < 0.001) was observed in the temporal cortex of AD brains independent of APOE genotype. The number of muscarinic receptors were unchanged in AD brains compared to control in both epsilon 4 and epsilon 3 carriers. A significant negative correlation (P < 0.001) was observed in AD brains between the histopathological dementia score and ChAT activity, which was independent of the APOE genotype. In this study the presence of the APOE epsilon 4 allele was not related to specific deficits in cholinergic activity in the temporal cortex of AD brains.

The influence of beta-amyloid on cholinergic neurotransmission was studied by measuring alterations in nicotinic acetylcholine receptors (nAChRs) in autopsy brain tissue from subjects carrying the Swedish amyloid precursor protein (APP) 670/671 mutation. Significant reductions in numbers of nAChRs were observed in various cortical regions of the Swedish 670/671 APP mutation family subjects (-73 to -87%) as well as in sporadic Alzheimer's disease (AD) cases (-37 to -57%) using the nicotinic agonists [3H]epibatidine and [3H]nicotine, which bind with high affinity to both alpha3 and alpha4 and to alpha4 nAChR subtypes, respectively. Saturation binding studies with [3H]epibatidine revealed two binding sites in the parietal cortex of AD subjects and controls. A significant decrease in Bmax (-82%) for the high-affinity site was observed in APP 670/671 subjects with no change in K(D) compared with controls (0.018 nM APP 670/671; 0.036 nM control). The highest load of neuronal plaques (NPs) was observed in the parietal cortex of APP 670/671 brains, whereas the number of [3H]nicotine binding sites was less impaired compared with other cortical brain regions. Except for a positive significant correlation between the number of [3H]nicotine binding sites and number of NPs in the parietal cortex, no strict correlation was observed between nAChR deficits and the presence of NPs and neurofibrillary tangles, suggesting that these different processes may be closely related but not strictly dependent on each other.

Background: Recent findings of a reduced cerebral metabolic rate of glucose (CMRGlu) in at-risk relatives of patients with Alzheimer disease (AD) who carry the apolipoprotein E ( APOE ) ϵ4 allele suggest a causative role for the E4 isoform in cognitive changes that lead to AD. It is not known whether ϵ4 allele—associated deficits exist in patients with clinical AD. Objective: To determine whether distinct patterns of cerebral hypometabolism exist in patients who carry the ϵ4 allele. Patients and Methods: Information on the CMRGlu and APOE genotype was available for 46 patients at a memory disorders clinic: 31 patients were diagnosed as having probable AD, 3 demented patients did not meet criteria for AD, and 12 patients had mild memory complaints. Positron emission tomography with the use of 18 F-fludeoxyglucose was used to calculate the CMRGlu in the frontal and temporoparietal regions of the cortex. Estimates were standardized to the sensorimotor area of the cortex. Linear regression models were constructed to relate the APOE genotype to the CMRGlu, adjusting for cognitive status (ie, the Mini-Mental State Examination score). Results: Distinct patterns of the CMRGlu did not emerge for patients with different APOE genotypes. Bilateral deficits in the CMRGlu were found in the patients with AD. Left-right asymmetry was found in 8 of 12 patients with mild memory complaints: 7 of 8 had CMRGlu ratios less than 0.85 in the left side of the temporoparietal region of the cortex. Conclusions: The APOE ϵ4 allele does not appear to be associated with specific deficits in brain metabolism in patients with AD despite evidence that the ϵ4 allele is associated with preclinical alterations. This finding is consistent with previous epidemiologic results that have demonstrated a higher risk for AD in carriers of the ϵ4 allele, but no change in the rate of progression of AD.

Apolipoprotein E (APOE) genotypes and cerebrospinal fluid (CSF) tau protein concentration were evaluated in patients suffering from semantic dementia, with the aim of determining whether these markers could help to differentiate this condition from Alzheimer's disease (AD) in early stages. By strictly following diagnostic criteria for semantic dementia, we found a clinically homogeneous group comprising eight patients from a total population of 621 subjects referred for dementia investigation. CSF tau protein concentrations were moderately increased with a small intraindividual variation 437+/-36 pg/ml (mean+/-SD) compared to healthy control individuals. APOE genotype distribution showed an over representation of the epsilon4 allele (69% epsilon3, 31% epsilon4 and no epsilon2), a pattern similar to that found in AD. These results indicate that semantic dementia is a rather uncommon but clinically distinct condition which shows a moderate increase of CSF tau protein levels and for which the epsilon4 allele is a risk factor.

We report the cloning of a novel gene (E5-1) encoded on chromosome 1 which has substantial nucleotide and amino-acid sequence similarity to the S182 gene on chromosome 14q24.3. Mutations, including three new missense mutations in the S182 gene, are associated with the AD3 subtype of early-onset familial Alzheimer's disease (AD). Both the E5-1 and the S182 proteins are predicted to be integral membrane proteins with seven membrane-spanning domains, and a large exposed loop between the sixth and seventh transmembrane domains. Analysis of the nucleotide sequence of the open reading frame (ORF) of the E5-1 gene led to the discovery of two missense substitutions at conserved amino-acid residues in affected members of pedigrees with a form of familial AD that has a later age of onset than the AD3 subtype (50-70 years versus 30-60 years for AD3). These observations imply that the E5-1 gene on chromosome 1 and the S182 gene on chromosome 14q24.3 are members of a family of genes (presenilins) with related functions, and indicates that mutations in conserved residues of E5-1 could also play a role in the genesis of AD. Our results also indicate that still other AD susceptibility genes exist.

Aggregated alpha-synuclein is the main component of Lewy bodies, intraneuronal deposits observed in Parkinson's disease and dementia with Lewy bodies. The objective of the study was to identify surface-exposed epitopes of alpha-synuclein in vitro and in vivo formed aggregates. Polyclonal immunoglobulin Y antibodies were raised against short linear peptides of the alpha-synuclein molecule. An epitope in the N-terminal region (1-10) and all C-terminal epitopes (90-140) were found to be exposed in an indirect enzyme-linked immunosorbent assay (ELISA) using recombinant monomeric, oligomeric, and fibrillar alpha-synuclein. In a phospholipid ELISA, the N-terminus and mid-region of alpha-synuclein (i.e., 1-90) were associated with phosphatidylserine and thus occluded from antibody binding. The antibodies that reacted most strongly with epitopes in the in vitro aggregates (i.e., 1-10 and epitopes between positions 90-140) also labeled alpha-synuclein inclusions in brains from transgenic (Thy-1)-h[A30P] alpha-synuclein mice and Lewy bodies and Lewy neurites in brains of patients with alpha-synucleinopathies. However, differences in reactivity were observed with the C-terminal antibodies when brain tissue from human and transgenic mice was compared. Taken together, the study shows that although similar epitopes are exposed in both in vitro and in vivo formed alpha-synuclein inclusions, structural heterogeneity can be observed between different molecular species.

Publisher's version (útgefin grein), Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We 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. Results: The 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. Conclusion: In 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., CHAP: R01-AG-11101, R01-AG-030146, NIRP-14-302587. SMART: This study was supported by a grant from the Netherlands Organization for Scientific Research–Medical Sciences (project no. 904-65–095). LBC: The authors thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. The LBC1936 is supported by Age UK (Disconnected Mind Programme grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), a center in the SINAPSE Collaboration (sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK Medical Research Council is acknowledged. Genotyping was supported by a grant from the BBSRC (ref. BB/F019394/1). PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). SCES and SiMES: National Medical Research Council Singapore Centre Grant NMRC/CG/013/2013. C.-Y.C. is supported by the National Medical Research Council, Singapore (CSA/033/2012), Singapore Translational Research Award (STaR) 2013. Dr. Kamran Ikram received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. Whole-body MRI was supported by a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. OATS (Older Australian Twins Study): OATS was supported by an Australian National Health and Medical Research Council (NHRMC)/Australian Research Council (ARC) Strategic Award (ID401162) and by a NHMRC grant (ID1045325). OATS was facilitated via access to the Australian Twin Registry, which is supported by the NHMRC Enabling Grant 310667. The OATS genotyping was partly supported by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. NOMAS: The Northern Manhattan Study is funded by the NIH grant “Stroke Incidence and Risk Factors in a Tri-Ethnic Region” (NINDS R01NS 29993). TASCOG: NHMRC and Heart Foundation. AGES: The study was funded by the National Institute on Aging (NIA) (N01-AG-12100), Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament), with contributions from the Intramural Research Programs at the NIA, the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Neurological Disorders and Stroke (NINDS) (Z01 HL004607-08 CE). ERF: The ERF study as a part of European Special Populations Research Network (EUROSPAN) was supported by European Commission FP6 STRP grant no. 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by a joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). Exome sequencing analysis in ERF was supported by the ZonMw grant (project 91111025). Najaf Amin is supported by the Netherlands Brain Foundation (project no. F2013[1]-28). ARIC: The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F. FHS: This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (contracts no. N01-HC-25195 and no. HHSN268201500001I), and its contract with Affymetrix, Inc. for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the NIA (R01s AG033040, AG033193, AG054076, AG049607, AG008122, and U01-AG049505) and the NINDS (R01-NS017950, UH2 NS100605). Dr. DeCarli is supported by the Alzheimer's Disease Center (P30 AG 010129). ASPS: The research reported in this article was funded by the Austrian Science Fund (FWF) grant nos. P20545-P05, P13180, and P20545-B05, by the Austrian National Bank Anniversary Fund, P15435, and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND) (jpnd.eu). LLS: The Leiden Longevity Study has received funding from the European Union's Seventh Framework Programme (FP7/2007–2011) under grant agreement no. 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), UnileverColworth, and by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). CHS: This CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC15103, and HHSN268200960009C and grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, and R01HL130114 from the NHLBI with additional contribution from NINDS. Additional support was provided through R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/NWO project no. 050-060-810. The Rotterdam Study is funded by Erasmus MC Medical Center and Erasmus MC University, Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. M.A.I. is supported by an NWO Veni grant (916.13.054). The 3-City Study: The 3-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. S.D. is supported by a starting grant from the European Research Council (SEGWAY), a grant from the Joint Programme of Neurodegenerative Disease research (BRIDGET), from the European Union's Horizon 2020 research and innovation programme under grant agreements No 643417 & No 640643, and by the Initiative of Excellence of Bordeaux University. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the Labex DISTALZ, and the Centre National de Génotypage. ADGC: The Alzheimer Disease Genetics Consortium is supported by NIH. NIH-NIA supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute, P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant NS39764, NIMH MH60451, and by GlaxoSmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232, the Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council [MRC], local NHS trusts, and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England [HEFCE], Alzheimer's Research Trust [ART], BRACE, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, and Universitat de Barcelona). ADNI: Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, and K01 AG030514. Support was also provided by the Alzheimer's Association (LAF, IIRG-08-89720; MAP-V, IIRG-05-14147) and the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. SiGN: Stroke Genetic Network (SiGN) was supported in part by award nos. U01NS069208 and R01NS100178 from NINDS. Genetics of Early-Onset Stroke (GEOS) Study was supported by the NIH Genes, Environment and Health Initiative (GEI) grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). METASTROKE: ASGC: Australian population control data were derived from the Hunter Community Study. This research was funded by grants from the Australian National and Medical Health Research Council (NHMRC Project Grant ID: 569257), the Australian National Heart Foundation (NHF Project Grant ID: G 04S 1623), the University of Newcastle, the Gladys M Brawn Fellowship scheme, and the Vincent Fairfax Family Foundation in Australia. E.G.H. was supported by a Fellowship from the NHF and National Stroke Foundation of Australia (ID: 100071). J.M. was supported by an Australian Postgraduate Award. BRAINS: Bio-Repository of DNA in Stroke (BRAINS) is partly funded by a Senior Fellowship from the Department of Health (UK) to P.S., the Henry Smith Charity, and the UK-India Education Research Institutive (UKIERI) from the British Council. GEOS: Genetics of Early Onset Stroke (GEOS) Study, Baltimore, was supported by GEI Grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488), and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to the Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). HPS: Heart Protection Study (HPS) (ISRCTN48489393) was supported by the UK MRC, British Heart Foundation, Merck and Co. (manufacturers of simvastatin), and Roche Vitamins Ltd. (manufacturers of vitamins). Genotyping was supported by a grant to Oxford University and CNG from Merck and Co. J.C.H. acknowledges support from the British Heart Foundation (FS/14/55/30806). ISGS: Ischemic Stroke Genetics Study (ISGS)/Siblings With Ischemic Stroke Study (SWISS) was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000954-06. ISGS/SWISS used samples and clinical data from the NIH-NINDS Human Genetics Resource Center DNA and Cell Line Repository (ccr.coriell.org/ninds), human subjects protocol nos. 2003-081 and 2004-147. ISGS/SWISS used stroke-free participants from the Baltimore Longitudinal Study of Aging (BLSA) as controls. The inclusion of BLSA samples was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000015-50, human subjects protocol no. 2003-078. The ISGS study was funded by NIH-NINDS Grant R01 NS-42733 (J.F.M.). The SWISS study was funded by NIH-NINDS Grant R01 NS-39987 (J.F.M.). This study used the high-performance computational capabilities of the Biowulf Linux cluster at the NIH (biowulf.nih.gov). MGH-GASROS: MGH Genes Affecting Stroke Risk and Outcome Study (MGH-GASROS) was supported by NINDS (U01 NS069208), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research 0775010N, the NIH and NHLBI's STAMPEED genomics research program (R01 HL087676), and a grant from the National Center for Research Resources. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research resources. Milan: Milano–Besta Stroke Register Collection and genotyping of the Milan cases within CEDIR were supported by the Italian Ministry of Health (grant nos.: RC 2007/LR6, RC 2008/LR6; RC 2009/LR8; RC 2010/LR8; GR-2011-02347041), FP6 LSHM-CT-2007-037273 for the PROCARDIS control samples. WTCCC2: Wellcome Trust Case-Control Consortium 2 (WTCCC2) was principally funded by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z and WT084724MA). The Stroke Association provided additional support for collection of some of the St George's, London cases. The Oxford cases were collected as part of the Oxford Vascular Study, which is funded by the MRC, Stroke Association, Dunhill Medical Trust, National Institute of Health Research (NIHR), and the NIHR Biomedical Research Centre, Oxford. The Edinburgh Stroke Study was supported by the Wellcome Trust (clinician scientist award to C.L.M.S.) and the Binks Trust. Sample processing occurred in the Genetics Core Laboratory of the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh. Much of the neuroimaging occurred in the Scottish Funding Council Brain Imaging Research Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), Division of Clinical Neurosciences, University of Edinburgh, a core area of the Wellcome Trust Clinical Research Facility, and part of the SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence) collaboration (sinapse.ac.uk), funded by the Scottish Funding Council and the Chief Scientist Office. Collection of the Munich cases and data analysis was supported by the Vascular Dementia Research Foundation. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 666881, SVDs@target (to M.D.) and no. 667375, CoSTREAM (to M.D.); the DFG as part of the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and the CRC 1123 (B3) (to M.D.); the Corona Foundation (to M.D.); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain) (to M.D.); the e:Med program (e:AtheroSysMed) (to M.D.) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement no. Health-F2-2013-601456) (to M.D.). M.F. and A.H. acknowledge support from the BHF Centre of Research Excellence in Oxford and the Wellcome Trust core award (090532/Z/09/Z). VISP: The GWAS component of the Vitamin Intervention for Stroke Prevention (VISP) study was supported by the US National Human Genome Research Institute (NHGRI), grant U01 HG005160 (PI Michèle Sale and Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S. Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the US Public Health Service, NINDS, Bethesda, MD. Control data obtained through the database of genotypes and phenotypes (dbGAP) maintained and supported by the United States National Center for Biotechnology Information, US National Library of Medicine. WHI: Funding support for WHI-GARNET was provided through the NHGRI GARNET (grant no. U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the GEI (U01 HG004424). R.L. is a senior clinical investigator of FWO Flanders. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.