Publications by authors named "Claudia L Satizabal"

64 Publications

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Nat Commun 2021 06 7;12(1):3417. Epub 2021 Jun 7.

Servei de Neurologia, Hospital Universitari i Politècnic La Fe, Valencia, Spain.

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.
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http://dx.doi.org/10.1038/s41467-021-22491-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184987PMC
June 2021

Association of Midlife Depressive Symptoms with Regional Amyloid-β and Tau in the Framingham Heart Study.

J Alzheimers Dis 2021 ;82(1):249-260

Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA.

Background: Depressive symptoms predict increased risk for dementia decades before the emergence of cognitive symptoms. Studies in older adults provide preliminary evidence for an association between depressive symptoms and amyloid-β (Aβ) and tau accumulation. It is unknown if similar alterations are observed in midlife when preventive strategies may be most effective.

Objective: The study aim was to evaluate the association between depressive symptoms and cerebral Aβ and tau in a predominately middle-aged cohort with examination of the apolipoprotein (APOE) ɛ4 allele as a moderator.

Methods: Participants included 201 adults (mean age 53±8 years) who underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Depressive symptoms were evaluated with the Center for Epidemiological Studies Depression Scale (CES-D) at the time of PET imaging, as well as eight years prior. Associations between depressive symptoms at both timepoints, as well as depression (CES-D≥16), with regional Aβ and tau PET retention were evaluated with linear regression adjusting for age and sex. Interactions with the APOE ɛ4 allele were explored.

Results: Depressive symptoms and depression were not associated with PET outcomes in the overall sample. However, among APOE ɛ4 allele carriers, there was a significant cross-sectional association between depressive symptoms and increased tau PET uptake in the entorhinal cortex (β= 0.446, SE = 0.155, p = 0.006) and amygdala (β= 0.350, SE = 0.133, p = 0.012).

Conclusion: Although longitudinal studies are necessary, the results suggest that APOE ɛ4 carriers with depressive symptoms may present with higher susceptibility to early tau accumulation in regions integral to affective regulation and memory consolidation.
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http://dx.doi.org/10.3233/JAD-210232DOI Listing
September 2021

Blood biomarkers for dementia in Hispanic and non-Hispanic White adults.

Alzheimers Dement (N Y) 2021 9;7(1):e12164. Epub 2021 Apr 9.

Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases University of Texas Health Science Center San Antonio Texas USA.

Introduction: The study evaluated if blood markers reflecting diverse biological pathways differentiate clinical diagnostic groups among Hispanic and non-Hispanic White adults.

Methods: Within Hispanic (n = 1193) and non-Hispanic White (n = 650) participants, serum total tau (t-tau), neurofilament light (NfL), ubiquitin carboxyl-terminal hydrolase LI, glial fibrillary acidic protein (GFAP), soluble cluster of differentiation-14, and chitinase-3-like protein 1 (YKL-40) were quantified. Mixed-effects partial proportional odds ordinal logistic regression and linear mixed-effects models were used to evaluate the association of biomarkers with diagnostic group and cognition, adjusting for age, sex, ethnicity, apolipoprotein E ε4, education, and site.

Results: T-tau, NfL, GFAP, and YKL-40 discriminated between diagnostic groups (receiver operating curve: 0.647-0.873). Higher t-tau (odds ratio [OR] = 1.671, 95% confidence interval [CI] = 1.457-1.917,  < .001), NfL (OR = 2.150, 95% CI = 1.819-2.542,  < .001), GFAP (OR = 2.283, 95% CI = 1.915-2.722,  < .001), and YKL-40 (OR = 1.288, 95% CI = 1.125-1.475,  < .001) were associated with increased likelihood of dementia relative to cognitively unimpaired and mild cognitive impairment groups. Higher NfL was associated with poorer global cognition (β = -0.455, standard error [SE] = 0.083,  < .001), semantic fluency (β = -0.410, SE = 0.133,  = .002), attention/processing speed (β = 2.880, SE = 0.801,  < .001), and executive function (β = 5.965, SE = 2.037,  = .003). Higher GFAP was associated with poorer global cognition (β = -0.345, SE = 0.092,  = .001), learning (β = -1.426, SE = 0.359,  < .001), and memory (β = -0.890, SE = 0.266,  < .001). Higher YKL-40 (β = -0.537, SE = 0.186,  = .004) was associated with lower memory scores. Interactions with ethnicity were observed for learning (NfL, GFAP, YKL-40), memory (NfL, GFAP), and semantic fluency (NfL; interaction terms < .008), which were generally no longer significant in a demographically matched subset of Hispanic and non-Hispanic White participants.

Discussion: Blood biomarkers of neuronal/axonal and glial injury differentiated between clinical diagnostic groups in a bi-ethnic cohort of Hispanic and non-Hispanic Whites. Our results add to the growing literature indicating that blood biomarkers may be viable tools for detecting neurodegenerative conditions and highlight the importance of validation in diverse cohorts.
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http://dx.doi.org/10.1002/trc2.12164DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8033409PMC
April 2021

Multiomics integrative analysis identifies allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis.

Aging (Albany NY) 2021 Apr 12;13(7):9277-9329. Epub 2021 Apr 12.

Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) ε4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analysed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by haplotype ( and ). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterised a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in and AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.
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http://dx.doi.org/10.18632/aging.202950DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064208PMC
April 2021

MarkVCID cerebral small vessel consortium: I. Enrollment, clinical, fluid protocols.

Alzheimers Dement 2021 04 21;17(4):704-715. Epub 2021 Jan 21.

Alzheimer's Clinical and Translational Research Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.

The concept of vascular contributions to cognitive impairment and dementia (VCID) derives from more than two decades of research indicating that (1) most older individuals with cognitive impairment have post mortem evidence of multiple contributing pathologies and (2) along with the preeminent role of Alzheimer's disease (AD) pathology, cerebrovascular disease accounts for a substantial proportion of this contribution. Contributing cerebrovascular processes include both overt strokes caused by etiologies such as large vessel occlusion, cardioembolism, and embolic infarcts of unknown source, and frequently asymptomatic brain injuries caused by diseases of the small cerebral vessels. Cerebral small vessel diseases such as arteriolosclerosis and cerebral amyloid angiopathy, when present at moderate or greater pathologic severity, are independently associated with worse cognitive performance and greater likelihood of dementia, particularly in combination with AD and other neurodegenerative pathologies. Based on this evidence, the US National Alzheimer's Project Act explicitly authorized accelerated research in vascular and mixed dementia along with frontotemporal and Lewy body dementia and AD itself. Biomarker development has been consistently identified as a key step toward translating scientific advances in VCID into effective prevention and treatment strategies. Validated biomarkers can serve a range of purposes in trials of candidate interventions, including (1) identifying individuals at increased VCID risk, (2) diagnosing the presence of cerebral small vessel disease or specific small vessel pathologies, (3) stratifying study participants according to their prognosis for VCID progression or treatment response, (4) demonstrating an intervention's target engagement or pharmacodynamic mechanism of action, and (5) monitoring disease progression during treatment. Effective biomarkers allow academic and industry investigators to advance promising interventions at early stages of development and discard interventions with low success likelihood. The MarkVCID consortium was formed in 2016 with the goal of developing and validating fluid- and imaging-based biomarkers for the cerebral small vessel diseases associated with VCID. MarkVCID consists of seven project sites and a central coordinating center, working with the National Institute of Neurologic Diseases and Stroke and National Institute on Aging under cooperative agreements. Through an internal selection process, MarkVCID has identified a panel of 11 candidate biomarker "kits" (consisting of the biomarker measure and the clinical and cognitive data used to validate it) and established a range of harmonized procedures and protocols for participant enrollment, clinical and cognitive evaluation, collection and handling of fluid samples, acquisition of neuroimaging studies, and biomarker validation. The overarching goal of these protocols is to generate rigorous validating data that could be used by investigators throughout the research community in selecting and applying biomarkers to multi-site VCID trials. Key features of MarkVCID participant enrollment, clinical/cognitive testing, and fluid biomarker procedures are summarized here, with full details in the following text, tables, and supplemental material, and a description of the MarkVCID imaging biomarker procedures in a companion paper, "MarkVCID Cerebral small vessel consortium: II. Neuroimaging protocols." The procedures described here address a range of challenges in MarkVCID's design, notably: (1) acquiring all data under informed consent and enrollment procedures that allow unlimited sharing and open-ended analyses without compromising participant privacy rights; (2) acquiring the data in a sufficiently wide range of study participants to allow assessment of candidate biomarkers across the various patient groups who might ultimately be targeted in VCID clinical trials; (3) defining a common dataset of clinical and cognitive elements that contains all the key outcome markers and covariates for VCID studies and is realistically obtainable during a practical study visit; (4) instituting best fluid-handling practices for minimizing avoidable sources of variability; and (5) establishing rigorous procedures for testing the reliability of candidate fluid-based biomarkers across replicates, assay runs, sites, and time intervals (collectively defined as the biomarker's instrumental validity). Participant Enrollment Project sites enroll diverse study cohorts using site-specific inclusion and exclusion criteria so as to provide generalizable validation data across a range of cognitive statuses, risk factor profiles, small vessel disease severities, and racial/ethnic characteristics representative of the diverse patient groups that might be enrolled in a future VCID trial. MarkVCID project sites include both prospectively enrolling centers and centers providing extant data and samples from preexisting community- and population-based studies. With approval of local institutional review boards, all sites incorporate MarkVCID consensus language into their study documents and informed consent agreements. The consensus language asks prospectively enrolled participants to consent to unrestricted access to their data and samples for research analysis within and outside MarkVCID. The data are transferred and stored as a de-identified dataset as defined by the Health Insurance Portability and Accountability Act Privacy Rule. Similar human subject protection and informed consent language serve as the basis for MarkVCID Research Agreements that act as contracts and data/biospecimen sharing agreements across the consortium. Clinical and Cognitive Data Clinical and cognitive data are collected across prospectively enrolling project sites using common MarkVCID instruments. The clinical data elements are modified from study protocols already in use such as the Alzheimer's Disease Center program Uniform Data Set Version 3 (UDS3), with additional focus on VCID-related items such as prior stroke and cardiovascular disease, vascular risk factors, focal neurologic findings, and blood testing for vascular risk markers and kidney function including hemoglobin A1c, cholesterol subtypes, triglycerides, and creatinine. Cognitive assessments and rating instruments include the Clinical Dementia Rating Scale, Geriatric Depression Scale, and most of the UDS3 neuropsychological battery. The cognitive testing requires ≈60 to 90 minutes. Study staff at the prospectively recruiting sites undergo formalized training in all measures and review of their first three UDS3 administrations by the coordinating center. Collection and Handling of Fluid Samples Fluid sample types collected for MarkVCID biomarker kits are serum, ethylenediaminetetraacetic acid-plasma, platelet-poor plasma, and cerebrospinal fluid (CSF) with additional collection of packed cells to allow future DNA extraction and analyses. MarkVCID fluid guidelines to minimize variability include fasting morning fluid collections, rapid processing, standardized handling and storage, and avoidance of CSF contact with polystyrene. Instrumental Validation for Fluid-Based Biomarkers Instrumental validation of MarkVCID fluid-based biomarkers is operationally defined as determination of intra-plate and inter-plate repeatability, inter-site reproducibility, and test-retest repeatability. MarkVCID study participants both with and without advanced small vessel disease are selected for these determinations to assess instrumental validity across the full biomarker assay range. Intra- and inter-plate repeatability is determined by repeat assays of single split fluid samples performed at individual sites. Inter-site reproducibility is determined by assays of split samples distributed to multiple sites. Test-retest repeatability is determined by assay of three samples acquired from the same individual, collected at least 5 days apart over a 30-day period and assayed on a single plate. The MarkVCID protocols are designed to allow direct translation of the biomarker validation results to multicenter trials. They also provide a template for outside groups to perform analyses using identical methods and therefore allow direct comparison of results across studies and centers. All MarkVCID protocols are available to the biomedical community and intended to be shared. In addition to the instrumental validation procedures described here, each of the MarkVCID kits will undergo biological validation to determine whether the candidate biomarker measures important aspects of VCID such as cognitive function. Analytic methods and results of these validation studies for the 11 MarkVCID biomarker kits will be published separately. The results of this rigorous validation process will ultimately determine each kit's potential usefulness for multicenter interventional trials aimed at preventing or treating small vessel disease related VCID.
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http://dx.doi.org/10.1002/alz.12215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8122220PMC
April 2021

MarkVCID cerebral small vessel consortium: II. Neuroimaging protocols.

Alzheimers Dement 2021 04 21;17(4):716-725. Epub 2021 Jan 21.

Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.

The MarkVCID consortium was formed under cooperative agreements with the National Institute of Neurologic Diseases and Stroke (NINDS) and National Institute on Aging (NIA) in 2016 with the goals of developing and validating biomarkers for the cerebral small vessel diseases associated with the vascular contributions to cognitive impairment and dementia (VCID). Rigorously validated biomarkers have consistently been identified as crucial for multicenter studies to identify effective strategies to prevent and treat VCID, specifically to detect increased VCID risk, diagnose the presence of small vessel disease and its subtypes, assess prognosis for disease progression or response to treatment, demonstrate target engagement or mechanism of action for candidate interventions, and monitor disease progression during treatment. The seven project sites and central coordinating center comprising MarkVCID, working with NINDS and NIA, identified a panel of 11 candidate fluid- and neuroimaging-based biomarker kits and established harmonized multicenter study protocols (see companion paper "MarkVCID cerebral small vessel consortium: I. Enrollment, clinical, fluid protocols" for full details). Here we describe the MarkVCID neuroimaging protocols with specific focus on validating their application to future multicenter trials. MarkVCID procedures for participant enrollment; clinical and cognitive evaluation; and collection, handling, and instrumental validation of fluid samples are described in detail in a companion paper. Magnetic resonance imaging (MRI) has long served as the neuroimaging modality of choice for cerebral small vessel disease and VCID because of its sensitivity to a wide range of brain properties, including small structural lesions, connectivity, and cerebrovascular physiology. Despite MRI's widespread use in the VCID field, there have been relatively scant data validating the repeatability and reproducibility of MRI-based biomarkers across raters, scanner types, and time intervals (collectively defined as instrumental validity). The MRI protocols described here address the core MRI sequences for assessing cerebral small vessel disease in future research studies, specific sequence parameters for use across various research scanner types, and rigorous procedures for determining instrumental validity. Another candidate neuroimaging modality considered by MarkVCID is optical coherence tomography angiography (OCTA), a non-invasive technique for directly visualizing retinal capillaries as a marker of the cerebral capillaries. OCTA has theoretical promise as a unique opportunity to visualize small vessels derived from the cerebral circulation, but at a considerably earlier stage of development than MRI. The additional OCTA protocols described here address procedures for determining OCTA instrumental validity, evaluating sources of variability such as pupil dilation, and handling data to maintain participant privacy. MRI protocol and instrumental validation The core sequences selected for the MarkVCID MRI protocol are three-dimensional T1-weighted multi-echo magnetization-prepared rapid-acquisition-of-gradient-echo (ME-MPRAGE), three-dimensional T2-weighted fast spin echo fluid-attenuated-inversion-recovery (FLAIR), two-dimensional diffusion-weighted spin-echo echo-planar imaging (DWI), three-dimensional T2*-weighted multi-echo gradient echo (3D-GRE), three-dimensional T -weighted fast spin-echo imaging (T2w), and two-dimensional T2*-weighted gradient echo echo-planar blood-oxygenation-level-dependent imaging with brief periods of CO inhalation (BOLD-CVR). Harmonized parameters for each of these core sequences were developed for four 3 Tesla MRI scanner models in widespread use at academic medical centers. MarkVCID project sites are trained and certified for their instantiation of the consortium MRI protocols. Sites are required to perform image quality checks every 2 months using the Alzheimer's Disease Neuroimaging Initiative phantom. Instrumental validation for MarkVCID MRI-based biomarkers is operationally defined as inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility. Assessments of these instrumental properties are performed on individuals representing a range of cerebral small vessel disease from mild to severe. Inter-rater reliability is determined by distribution of an independent dataset of MRI scans to each analysis site. Test-retest repeatability is determined by repeat MRI scans performed on individual participants on a single MRI scanner after a short (1- to 14-day) interval. Inter-scanner reproducibility is determined by repeat MRI scans performed on individuals performed across four MRI scanner models. OCTA protocol and instrumental validation The MarkVCID OCTA protocol uses a commercially available, Food and Drug Administration-approved OCTA apparatus. Imaging is performed on one dilated and one undilated eye to assess the need for dilation. Scans are performed in quadruplicate. MarkVCID project sites participating in OCTA validation are trained and certified by this biomarker's lead investigator. Inter-rater reliability for OCTA is assessed by distribution of OCTA datasets to each analysis site. Test-retest repeatability is assessed by repeat OCTA imaging on individuals on the same day as their baseline OCTA and a different-day repeat session after a short (1- to 14-day) interval. Methods were developed to allow the OCTA data to be de-identified by the sites before transmission to the central data management system. The MarkVCID neuroimaging protocols, like the other MarkVCID procedures, are designed to allow translation to multicenter trials and as a template for outside groups to generate directly comparable neuroimaging data. The MarkVCID neuroimaging protocols are available to the biomedical community and intended to be shared. In addition to the instrumental validation procedures described here, each of the neuroimaging MarkVCID kits will undergo biological validation to determine its ability to measure important aspects of VCID such as cognitive function. The analytic methods for the neuroimaging-based kits and the results of these validation studies will be published separately. The results will ultimately determine the neuroimaging kits' potential usefulness for multicenter interventional trials in small vessel disease-related VCID.
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http://dx.doi.org/10.1002/alz.12216DOI Listing
April 2021

The cortical origin and initial spread of medial temporal tauopathy in Alzheimer's disease assessed with positron emission tomography.

Sci Transl Med 2021 01;13(577)

Massachusetts General Hospital, Boston, MA 02114, USA.

Advances in molecular positron emission tomography (PET) have enabled anatomic tracking of brain pathology in longitudinal studies of normal aging and dementia, including assessment of the central model of Alzheimer's disease (AD) pathogenesis, according to which TAU pathology begins focally but expands catastrophically under the influence of amyloid-β (Aβ) pathology to mediate neurodegeneration and cognitive decline. Initial TAU deposition occurs many years before Aβ in a specific area of the medial temporal lobe. Building on recent work that enabled focus of molecular PET measurements on specific TAU-vulnerable convolutional temporal lobe anatomy, we applied an automated anatomic sampling method to quantify TAU PET signal in 443 adult participants from several observational studies of aging and AD, spanning a wide range of ages, Aβ burdens, and degrees of clinical impairment. We detected initial cortical emergence of tauopathy near the rhinal sulcus in clinically normal people and, in a subset with longitudinal 2-year follow-up data ( = 104), tracked Aβ-associated spread of TAU from this site first to nearby neocortex of the temporal lobe and then to extratemporal regions. Greater rate of TAU spread was associated with baseline measures of both global Aβ burden and medial temporal lobe TAU. These findings are consistent with clinicopathological correlation studies of Alzheimer's tauopathy and enable precise tracking of AD-related TAU progression for natural history studies and prevention therapeutic trials.
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http://dx.doi.org/10.1126/scitranslmed.abc0655DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978042PMC
January 2021

Slow-Wave Sleep and MRI Markers of Brain Aging in a Community-Based Sample.

Neurology 2021 03 22;96(10):e1462-e1469. Epub 2020 Dec 22.

From the Framingham Heart Study (A.-A.B., A.S.B., J.R.R., C.L.S., J.M.Z., S.S., M.P.P. J.J.H.); Department of Neurology (A.-A.B., A.S.B., C.L.S., S.S., J.J.H.), Boston University School of Medicine; Department of Biostatistics (A.S.B., J.J.H. ), Boston University School of Public Health, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (V.M., C.L.S., S.S., J.J.H.), and Department of Population Health Sciences (J.J.H.), University of Texas Health Sciences Center, San Antonio; Centre for Advanced Research in Sleep Medicine (E.S.), Hôpital du Sacré-Coeur de Montréal, CIUSSS-NIM; Department of Neuroscience (E.S.), Université de Montréal, Quebec, Canada; Department of Neurology (C.D., P.M.), and School of Medicine and Imaging of Dementia and Aging Laboratory, Center for Neuroscience (P.M.), University of California, Davis, Sacramento; Division of Sleep and Circadian Disorders (S.R., D.J.G.), Brigham & Women's Hospital; Beth Israel Deaconess Medical Center (S.R., D.J.G.); Division of Sleep Medicine Harvard Medical School, Boston, MA; VA Boston Healthcare System (D.J.G.), Boston, MA; Turner Institute for Brain and Mental Health (M.P.P.), School of Psychological Sciences, Monash University, Melbourne, VIC, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Boston, MA.

Objective: To test the hypothesis that reduced slow-wave sleep, or N3 sleep, which is thought to underlie the restorative functions of sleep, is associated with MRI markers of brain aging, we evaluated this relationship in the community-based Framingham Heart Study Offspring cohort using polysomnography and brain MRI.

Methods: We studied 492 participants (age 58.8 ± 8.8 years, 49.4% male) free of neurological diseases who completed a brain MRI scan and in-home overnight polysomnography to assess slow-wave sleep (absolute duration and percentage of total sleep). Volumes of total brain, total cortical, frontal cortical, subcortical gray matter, hippocampus, and white matter hyperintensities were investigated as a percentage of intracranial volume, and the presence of covert brain infarcts was evaluated. Linear and logistic regression models were adjusted for age, age squared, sex, time interval between polysomnography and MRI (3.3 ± 1.0 years), ε4 carrier status, stroke risk factors, sleeping pill use, body mass index, and depression.

Results: Less slow-wave sleep was associated with lower cortical brain volume (absolute duration, β [standard error] = 0.20 [0.08], = 0.015; percentage, 0.16 [0.08], = 0.044), lower subcortical brain volume (percentage, 0.03 [0.02], = 0.034), and higher white matter hyperintensities volume (absolute duration, -0.12 [0.05], = 0.010; percentage, -0.10 [0.04], = 0.033). Slow-wave sleep duration was not associated with hippocampal volume or the presence of covert brain infarcts.

Conclusion: Loss of slow-wave sleep might facilitate accelerated brain aging, as evidence by its association with MRI markers suggestive of brain atrophy and injury. Alternatively, subtle injuries and accelerated aging might reduce the ability of the brain to produce slow-wave sleep.
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http://dx.doi.org/10.1212/WNL.0000000000011377DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055313PMC
March 2021

The genetics of circulating BDNF: towards understanding the role of BDNF in brain structure and function in middle and old ages.

Brain Commun 2020 28;2(2):fcaa176. Epub 2020 Oct 28.

Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, 78229 TX, USA.

Brain-derived neurotrophic factor (BDNF) plays an important role in brain development and function. Substantial amounts of BDNF are present in peripheral blood, and may serve as biomarkers for Alzheimer's disease incidence as well as targets for intervention to reduce Alzheimer's disease risk. With the exception of the genetic polymorphism in the gene, Val66Met, which has been extensively studied with regard to neurodegenerative diseases, the genetic variation that influences circulating BDNF levels is unknown. We aimed to explore the genetic determinants of circulating BDNF levels in order to clarify its mechanistic involvement in brain structure and function and Alzheimer's disease pathophysiology in middle-aged and old adults. Thus, we conducted a meta-analysis of genome-wide association study of circulating BDNF in 11 785 middle- and old-aged individuals of European ancestry from the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES), the Framingham Heart Study (FHS), the Rotterdam Study and the Study of Health in Pomerania (SHIP-Trend). Furthermore, we performed functional annotation analysis and related the genetic polymorphism influencing circulating BDNF to common Alzheimer's disease pathologies from brain autopsies. Mendelian randomization was conducted to examine the possible causal role of circulating BDNF levels with various phenotypes including cognitive function, stroke, diabetes, cardiovascular disease, physical activity and diet patterns. Gene interaction networks analysis was also performed. The estimated heritability of BDNF levels was 30% (standard error = 0.0246, -value = 4 × 10). We identified seven novel independent loci mapped near the gene and in , , , (two single-nucleotide polymorphisms) and . The expression of was associated with neurofibrillary tangles in brain tissues from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). Seven additional genes (, , , , , and ) were identified through expression and protein quantitative trait loci analyses. Mendelian randomization analyses indicated a potential causal role of BDNF in cardioembolism. Lastly, Ingenuity Pathway Analysis placed circulating BDNF levels in four major networks. Our study provides novel insights into genes and molecular pathways associated with circulating BDNF levels and highlights the possible involvement of plaque instability as an underlying mechanism linking BDNF with brain neurodegeneration. These findings provide a foundation for a better understanding of BDNF regulation and function in the context of brain aging and neurodegenerative pathophysiology.
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http://dx.doi.org/10.1093/braincomms/fcaa176DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734441PMC
October 2020

Cerebral small vessel disease genomics and its implications across the lifespan.

Nat Commun 2020 12 8;11(1):6285. Epub 2020 Dec 8.

University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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http://dx.doi.org/10.1038/s41467-020-19111-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722866PMC
December 2020

Association of circulating metabolites in plasma or serum and risk of stroke: Meta-analysis from seven prospective cohorts.

Neurology 2020 Dec 2. Epub 2020 Dec 2.

Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands;

Objective: To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings.

Methods: We investigated the association of metabolites with risk of stroke in seven prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by Nuclear Magnetic Resonance (H-NMR) technology. The relationship between metabolites and stroke was assessed using Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately.

Results: The analyses revealed ten significant metabolite associations. Amino acid histidine (hazard ratio (HR) per standard deviation (SD) = 0.90, 95% confidence interval (CI): 0.85, 0.94; = 4.45×10), glycolysis-related metabolite pyruvate (HR per SD = 1.09, 95% CI: 1.04, 1.14; = 7.45×10), acute phase reaction marker glycoprotein acetyls (HR per SD = 1.09, 95% CI: 1.03, 1.15; = 1.27×10), cholesterol in high-density lipoprotein (HDL) 2 and several other lipoprotein particles were associated with risk of stroke. When focusing on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD = 1.12, 95% CI: 1.05, 1.19; 4.13×10) and total and free cholesterol in large HDL particles.

Conclusions: We found association of amino acids, glycolysis-related metabolites, acute phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke.
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http://dx.doi.org/10.1212/WNL.0000000000011236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055347PMC
December 2020

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
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http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

Growth Differentiation Factor 15 and NT-proBNP as Blood-Based Markers of Vascular Brain Injury and Dementia.

J Am Heart Assoc 2020 10 14;9(19):e014659. Epub 2020 Sep 14.

Framingham Heart Study Framingham MA.

Background GDF15 (growth differentiation factor 15) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) may offer promise as biomarkers for cognitive outcomes, including dementia. We determined the association of these biomarkers with cognitive outcomes in a community-based cohort. Methods and Results Plasma GDF15 (n=1603) and NT-proBNP levels (n=1590) (53% women; mean age, 68.7 years) were measured in dementia-free Framingham Offspring cohort participants at examination 7 (1998-2001). Participants were followed up for incident dementia. Secondary outcomes included Alzheimer disease dementia, magnetic resonance imaging structural brain measures, and neurocognitive performance. During a median 11.8-year follow-up, 131 participants developed dementia. On multivariable Cox proportional-hazards analysis, higher circulating GDF15 was associated with an increased risk of incident all-cause and Alzheimer disease dementia (hazard ratio [HR] per SD increment in natural log-transformed biomarker value, 1.54 [95% CI, 1.22-1.95] and 1.37 [95% CI, 1.03-1.81], respectively), whereas higher plasma NT-proBNP was also associated with an increased risk of all-cause dementia (HR, 1.32; 95% CI, 1.05-1.65). Elevated GDF15 was associated with lower total brain and hippocampal volumes, greater white matter hyperintensity volume, and poorer cognitive performance. Elevated NT-proBNP was associated with greater white matter hyperintensity volume and poorer cognitive performance. Addition of both biomarkers to a conventional risk factor model improved dementia risk classification (net reclassification improvement index, 0.25; 95% CI, 0.05-0.45). Conclusions Elevated plasma GDF15 and NT-proBNP were associated with vascular brain injury on magnetic resonance imaging, poorer neurocognitive performance, and increased risk of incident dementia in individuals aged >60 years. Both biomarkers improved dementia risk classification beyond that of traditional clinical risk factors, indicating their potential value in predicting incident dementia.
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http://dx.doi.org/10.1161/JAHA.119.014659DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7792414PMC
October 2020

Association of common genetic variants with brain microbleeds: A genome-wide association study.

Neurology 2020 12 10;95(24):e3331-e3343. Epub 2020 Sep 10.

From the Departments of Epidemiology (M.J.K., H.H.H.A., D.V., S.J.v.d.L., P.Y., M.W.V., N.A., C.M.v.D., M.A.I.), Radiology and Nuclear Medicine (H.H.H.A., P.Y., A.v.d.L., M.W.V.), and Clinical Genetics (H.H.H.A.), Erasmus MC University Medical Center, Rotterdam, the Netherlands; Stroke Research Group, Department of Clinical Neurosciences (D.L., M.T., J.L., D.J.T., H.S.M.), University of Cambridge, UK; Department of Neurology (J.R.J.R., C.L.S., J.J.H., A.S.B., C.D., S. Seshadri), Boston University School of Medicine; The Framingham Heart Study (J.R.J.R., C.L.S., J.J.H., A.S.B., S. Seshadri), MA; Department of Biostatistics (A.V.S.), University of Michigan, Ann Arbor; Icelandic Heart Association (A.V.S., S. Sigurdsson, V.G.), Kopavogur, Iceland; Brown Foundation Institute of Molecular Medicine, McGovern Medical School (M.F.), and Human Genetics Center, School of Public Health (M.F.), University of Texas Health Science Center at Houston; Clinical Division of Neurogeriatrics, Department of Neurology (E.H., L.P., R.S.), Institute for Medical Informatics, Statistics and Documentation (E.H.), and Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry (Y.S., H.S.), Medical University of Graz, Austria; Center of Cerebrovascular Diseases, Department of Neurology (J.L.), West China Hospital, Sichuan University, Chengdu; Stroke Research Centre, Queen Square Institute of Neurology (I.C.H., D.W., H.H., D.J.W.), University College London, UK; Department of Neurosurgery (I.C.H.), Klinikum rechts der Isar, University of Munich, Germany; Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology (M.L., D.C.M.L., M.E.B., I.J.D., J.M.W.), and Centre for Clinical Brain Sciences, Edinburgh Imaging, UK Dementia Research Institute (M.E.B., J.M.W.), University of Edinburgh, UK; Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Department of Cardiology (S.T., J.v.d.G., J.W.J.), Section of Molecular Epidemiology, Biomedical Data Sciences (E.B.v.d.A., M.B., P.E.S.), Leiden Computational Biology Center, Biomedical Data Sciences (E.B.v.d.A.), Department of Radiology (J.v.d.G.), and Einthoven Laboratory for Experimental Vascular Medicine (J.W.J.), Leiden University Medical Center, the Netherlands; Department of Neurology (A.-K.G., N.S.R.), Massachusetts General Hospital, Harvard Medical School, Boston; Memory Aging and Cognition Center (S.H., C.C.), National University Health System, Singapore; Department of Pharmacology (S.H., C.C.) and Saw Swee Hock School of Public Health (S.H.), National University of Singapore and National University Health System, Singapore; Pattern Recognition & Bioinformatics (E.B.v.d.A.), Delft University of Technology, the Netherlands; Department of Biostatistics (S.L., J.J.H., Q.Y., A.S.B.), Boston University School of Public Health, MA; Department of Radiology (C.R.J., K.K.), Mayo Clinic, Rochester, MN; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.L.S., S. Seshadri), UT Health San Antonio, TX; Department of Medicine, Division of Geriatrics (B.G.W., T.H.M), and Memory Impairment and Neurodegenerative Dementia (MIND) Center (T.H.M.), University of Mississippi Medical Center, Jackson; Singapore Eye Research Institute (C.Y.C., J.Y.K., T.Y.W.); Department of Neuroradiology (Z.M., J.M.W.), NHS Lothian, Edinburgh; Institute of Cardiovascular and Medical Sciences (D.J.S.), College of Medical, Veterinary and Life Sciences, University of Glasgow, UK; Division of Cerebrovascular Neurology (R.F.G.), Johns Hopkins University, Baltimore, MD; Department of Neuroradiology (A.D.M.), Atkinson Morley Neurosciences Centre, St George's NHS Foundation Trust, London, UK; Department of Neurology (C.D.), University of California at Davis; Nuffield Department of Population Health (C.M.v.D.), University of Oxford, UK; Laboratory of Epidemiology and Population Sciences (L.J.L.), National Institute on Aging, Baltimore, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik, Iceland.

Objective: To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

Methods: We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.

Results: BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the region reached genome-wide significance for its association with BMB (lead rs769449; odds ratio [OR] [95% confidence interval (CI)] 1.33 [1.21-1.45]; = 2.5 × 10). ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; = 1.0 × 10) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; = 0.68). ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.

Conclusions: Genetic variants in the region are associated with the presence of BMB, most likely due to the ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
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http://dx.doi.org/10.1212/WNL.0000000000010852DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836652PMC
December 2020

Cardiovascular health, genetic risk, and risk of dementia in the Framingham Heart Study.

Neurology 2020 09 20;95(10):e1341-e1350. Epub 2020 Jul 20.

From the Departments of Biostatistics (G.M.P., A.S.B., V.X., A.L.D.) and Epidemiology (R.S.V.), Boston University School of Public Health; Boston University and NHLBI's Framingham Heart Study (A.S.B., C.L.S., V.X., R.S.V., A.L.D., S.S.), Framingham; Department of Neurology (A.S.B., C.L.S., A.L.D., S.S.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (C.L.S., S.S.), University of Texas Health Sciences Center, San Antonio; Sections of Preventive Medicine & Epidemiology and Cardiology (V.X., R.S.V.), Department of Medicine, Boston University, MA; Melbourne Dementia Research Centre (M.P.P.), The Florey Institute for Neuroscience and Mental Health; Faculty of Medicine, Dentistry, and Health Sciences (M.P.P.), University of Melbourne, Parkville; Centre for Human Psychopharmacology (M.P.P.), Swinburne University of Technology, Hawthorn, Australia; and Harvard T.H. Chan School of Public Health (M.P.P.), Boston, MA.

Objective: To determine the joint role of ideal cardiovascular health (CVH) and genetic risk on risk of dementia.

Methods: We categorized CVH on the basis of the American Heart Association Ideal CVH Index and genetic risk through a genetic risk score (GRS) of common genetic variants and the ε4 genotype in 1,211 Framingham Heart Study (FHS) offspring cohort participants. We used multivariable Cox proportional hazards regression models to examine the association between CVH, genetic risk, and incident all-cause dementia with up to 10 years of follow-up (mean 8.4 years, 96 incident dementia cases), adjusting for age, sex, and education.

Results: We observed that a high GRS (>80th percentile) was associated with a 2.6-fold risk of dementia (95% confidence interval [CI] of hazard ratio [HR] 1.23-5.29; = 0.012) compared with having a low GRS (<20th percentile); carrying at least 1 ε4 allele was associated with a 2.3-fold risk of dementia compared with not carrying an ε4 allele (95% CI of HR 1.49-3.53; = 0.0002), and having a favorable CVH showed a 0.45-fold lower risk of dementia (95% CI of HR 0.20-1.01; = 0.0527) compared to having an unfavorable CVH when all 3 components were included in the model. We did not observe an interaction between CVH and GRS ( = 0.99) or ε4 ( = 0.16).

Conclusions: We observed that both genetic risk and CVH contribute additively to dementia risk.
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http://dx.doi.org/10.1212/WNL.0000000000010306DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538213PMC
September 2020

Twenty-seven-year time trends in dementia incidence in Europe and the United States: The Alzheimer Cohorts Consortium.

Neurology 2020 08 1;95(5):e519-e531. Epub 2020 Jul 1.

From the Department of Epidemiology (F.J.W., L.B.C., R.W., D. Blacker, D. Bos, J.G., A.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Departments of Epidemiology (F.J.W., D. Bos, S.K.L.D., M.A.I., M.K.I., A.H.), Radiology and Nuclear Medicine (D. Bos), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (L.B.C.), Massachusetts General Hospital, Boston; Department of Infectious Disease Epidemiology (R.A., F.d.W., C. Hadjichrysanthou, K.M.-M., M.M.W.), School of Public Health, Imperial College London, UK; Neuropsychiatry and Epidemiology and Clinical Research (C. Berr), INSERM, UMR 1061 Montpellier, Universite de Montpellier, France; Boston University School of Medicine (A.B., M.P.P., C.L.S., S.S.); Framingham Heart Study (A.B., M.P.P., C.L.S., S.S.), MA; Department of Biostatistics (A.B., K.L.D.-P.), Boston University School of Public Health, MA; Cardiovascular Health Research Unit, Departments of Medicine (J.C.B., B.M.P.) and Epidemiology and Health Services (B.M.P.), University of Washington, Seattle; Department of Psychiatry (D. Blacker), Massachusetts General Hospital, Charlestown; University of Cambridge (C. Brayne), UK; Bordeaux Population Health Research Center (J.-F.D., S.D., C.D., L.G., C. Helmer), INSERM, UMR 1219, University of Bordeaux; Department of Neurology (S.D.), Memory Clinic, Bordeaux University Hospital, France; McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; Icelandic Heart Association (V.G.), Kopavogur; Faculty of Medicine (V.G.), University of Iceland, Reykjavik; Institute of Neuroscience and Physiology (E.J., S.K., I.S., H.W., A.Z.), Sahlgrenska Academy, University of Gothenburg, Sweden; Department of Epidemiology, Graduate School of Public Health (L.H.K.), and Departments of Neurology and Psychiatry (O.L.L.), University of Pittsburgh, PA; Laboratory of Epidemiology and Population Sciences (L.L., O.M.), National Institute on Aging, Bethesda, MD; Institute of Health and Society (F.E.M., B.C.M.S.), Newcastle University, Newcastle upon Tyne, UK; MIND Center (T.H.M.), University of Mississippi Medical Center, Jackson; Melbourne Dementia Research Centre (M.P.P.), The Florey Institute for Neuroscience and Mental Health, Melbourne, Australia; Kaiser Permanente Washington Health Research Institute (B.M.P.), Seattle; and The Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.L.S., S.S.), UT Health San Antonio, TX.

Objective: To determine changes in the incidence of dementia between 1988 and 2015.

Methods: This analysis was performed in aggregated data from individuals >65 years of age in 7 population-based cohort studies in the United States and Europe from the Alzheimer Cohort Consortium. First, we calculated age- and sex-specific incidence rates for all-cause dementia, and then defined nonoverlapping 5-year epochs within each study to determine trends in incidence. Estimates of change per 10-year interval were pooled and results are presented combined and stratified by sex.

Results: Of 49,202 individuals, 4,253 (8.6%) developed dementia. The incidence rate of dementia increased with age, similarly for women and men, ranging from about 4 per 1,000 person-years in individuals aged 65-69 years to 65 per 1,000 person-years for those aged 85-89 years. The incidence rate of dementia declined by 13% per calendar decade (95% confidence interval [CI], 7%-19%), consistently across studies, and somewhat more pronouncedly in men than in women (24% [95% CI 14%-32%] vs 8% [0%-15%]).

Conclusion: The incidence rate of dementia in Europe and North America has declined by 13% per decade over the past 25 years, consistently across studies. Incidence is similar for men and women, although declines were somewhat more profound in men. These observations call for sustained efforts to finding the causes for this decline, as well as determining their validity in geographically and ethnically diverse populations.
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http://dx.doi.org/10.1212/WNL.0000000000010022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455342PMC
August 2020

Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities.

Stroke 2020 07 10;51(7):2111-2121. Epub 2020 Jun 10.

Department of Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, CA.

Background And Purpose: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.

Methods: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.

Results: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (), 10q23.1 (), and 10q24.33 ( In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 () and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: (2q32.1), (3q27.1), (5q27.1), and (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.

Conclusions: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
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http://dx.doi.org/10.1161/STROKEAHA.119.027544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365038PMC
July 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Incident prolonged QT interval in midlife and late-life cognitive performance.

PLoS One 2020 25;15(2):e0229519. Epub 2020 Feb 25.

Department of Epidemiology and Biostatistics, George Washington University Milken Institute of Public Health, Washington, DC, United States of America.

Background: Measures of cardiac ventricular electrophysiology have been associated with cognitive performance in cross-sectional studies. We sought to evaluate the association of worsening ventricular repolarization in midlife, as measured by incident prolonged QT interval, with cognitive decline in late life.

Methods: Midlife QT interval was assessed by electrocardiography during three study visits from 1965/68 to 1971/74 in a cohort of Japanese American men aged 46-68 at Exam 1 from the Honolulu Heart Study. We defined incident prolonged QT as the QT interval in the upper quartile at Exam 2 or 3 after QT interval in lower three quartiles at Exam 1. Cognitive performance was assessed at least once using the Cognitive Abilities Screening Instrument (CASI), scored using item response theory (CASI-IRT), during four subsequent visits from 1991/93 to 1999/2000 among 2,511 of the 4,737 men in the Honolulu-Asia Aging Study otherwise eligible for inclusion in analyses. We used marginal structural modeling to determine the association of incident prolonged QT with cognitive decline, using weighting to account for confounding and attrition.

Results: Incident prolonged QT interval in midlife was not associated with late-life CASI-IRT at cognitive baseline (estimated difference in CASI-IRT: 0.04; 95% CI: -0.28, 0.35; p = 0.81), or change in CASI-IRT over time (estimated difference in annual change in CASI-IRT: -0.002; 95%CI: -0.013, 0.010; p = 0.79). Findings were consistent across sensitivity analyses.

Conclusions: Although many midlife cardiovascular risk factors and cardiac structure and function measures are associated with late-life cognitive decline, incident prolonged QT interval in midlife was not associated with late-life cognitive performance or cognitive decline.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229519PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041789PMC
May 2020

Circulating ceramide ratios and risk of vascular brain aging and dementia.

Ann Clin Transl Neurol 2020 02 16;7(2):160-168. Epub 2020 Jan 16.

Framingham Heart Study, Framingham, Massachusetts.

Background: We determined the association between ratios of plasma ceramide species of differing fatty-acyl chain lengths and incident dementia and Alzheimer's disease (AD) dementia in a large, community-based sample.

Methods: We measured plasma ceramide levels in 1892 [54% women, mean age 70.1 (SD 6.9) yr.] dementia-free Framingham Offspring Study cohort participants between 2005 and 2008. We related ratios of very long-chain (C24:0, C22:0) to long-chain (C16:0) ceramides to subsequent risk of incident dementia and AD dementia. Structural MRI brain measures were included as secondary outcomes.

Results: During a median 6.5 year follow-up, 81 participants developed dementia, of whom 60 were diagnosed with AD dementia. In multivariable Cox-proportional hazards analyses, each standard deviation (SD) increment in the ratio of ceramides C24:0/C16:0 was associated with a 27% reduction in the risk of dementia (HR 0.73, 95% CI 0.56-0.96) and AD dementia (HR 0.73, 95% CI 0.53-1.00). The ratio of ceramides C22:0/C16:0 was also inversely associated with incident dementia (HR per SD 0.75, 95% CI 0.57-0.98), and approached statistical significance for AD (HR 0.73, 95% CI 0.53-1.01, P = 0.056). Higher ratios of ceramides C24:0/C16:0 and C22:0/C16:0 were also cross-sectionally associated with lower white matter hyperintensity burden on MRI (-0.05 ± 0.02, P = 0.02; -0.06 ± 0.02, P = 0.003; respectively per SD increase), but not with other MRI brain measures.

Conclusions: Higher plasma ratios of very long-chain to long-chain ceramides are associated with a reduced risk of incident dementia and AD dementia in our community-based sample. Circulating ceramide ratios may serve as potential biomarkers for predicting dementia risk in cognitively healthy adults.
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http://dx.doi.org/10.1002/acn3.50973DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034495PMC
February 2020

Association of CD14 with incident dementia and markers of brain aging and injury.

Neurology 2020 01 9;94(3):e254-e266. Epub 2019 Dec 9.

From the Harvard T.H. Chan School of Public Health (M.P.P.), Boston; Department of Neurology (J.J.H., A.S.B., C.L.S., H.J.A., S.S.), Boston University School of Medicine; Framingham Heart Study (M.P.P., J.J.H., A.S.B., C.D., E.R.M., C.L.S., H.J.A., D.L., S.S.), MA; Centre for Human Psychopharmacology (M.P.P.), Swinburne University of Technology; Melbourne Dementia Research Centre (M.P.P.), The Florey Institute for Neuroscience and Mental Health & The University of Melbourne, Australia; Department of Biostatistics (J.J.H., A.S.B.), Boston University School of Public Health, MA; Department of Neurology (C.D.), School of Medicine & Imaging of Dementia and Aging Laboratory, Center for Neuroscience, University of California Davis, Sacramento; Departments of Epidemiology (H.H.H.A.) and Radiology and Nuclear Medicine (H.H.H.A.), Erasmus MC, Rotterdam, the Netherlands; Department of Epidemiology (A.P.R., W.T.L., B.M.P.), Fred Hutchinson Cancer Research Center (A.P.R.), Department of Neurology (W.T.L.), Cardiovascular Health Research Unit, Department of Medicine (B.M.P., J.C.B.), and Department of Health Services (B.M.P.), University of Washington, Seattle; Human Genetics Center, Department of Epidemiology (M.F.), Human Genetics & Environmental Sciences, School of Public Health (M.F.), and The Brown Foundation Institute of Molecular Medicine, Research Center for Human Genetics (M.F.), University of Texas Health Science Center, Houston; Departments of Pathology and Laboratory Medicine (R.P.T.) and Biochemistry (R.P.T.), Larner College of Medicine, University of Vermont, Burlington; Department of Neurology (O.L.), School of Medicine, University of Pittsburgh, PA; Kaiser Permanente Washington Health Research Institute (B.M.P.), Seattle; The Population Sciences Branch of the National Heart, Lung and Blood Institute (D.L.), NIH, Bethesda, MD; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio; Department of Neurology (E.R.M.), Brigham & Women's Hospital; and Harvard Medical School (E.R.M.), Boston, MA.

Objective: To test the hypothesis that the inflammatory marker plasma soluble CD14 (sCD14) associates with incident dementia and related endophenotypes in 2 community-based cohorts.

Methods: Our samples included the prospective community-based Framingham Heart Study (FHS) and Cardiovascular Health Study (CHS) cohorts. Plasma sCD14 was measured at baseline and related to the incidence of dementia, domains of cognitive function, and MRI-defined brain volumes. Follow-up for dementia occurred over a mean of 10 years (SD 4) in the FHS and a mean of 6 years (SD 3) in the CHS.

Results: We studied 1,588 participants from the FHS (mean age 69 ± 6 years, 47% male, 131 incident events) and 3,129 participants from the CHS (mean age 72 ± 5 years, 41% male, 724 incident events) for the risk of incident dementia. Meta-analysis across the 2 cohorts showed that each SD unit increase in sCD14 was associated with a 12% increase in the risk of incident dementia (95% confidence interval 1.03-1.23; = 0.01) following adjustments for age, sex, ε4 status, and vascular risk factors. Higher levels of sCD14 were associated with various cognitive and MRI markers of accelerated brain aging in both cohorts and with a greater progression of brain atrophy and a decline in executive function in the FHS.

Conclusion: sCD14 is an inflammatory marker related to brain atrophy, cognitive decline, and incident dementia.
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http://dx.doi.org/10.1212/WNL.0000000000008682DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108812PMC
January 2020

Mid-life and late-life vascular risk factor burden and neuropathology in old age.

Ann Clin Transl Neurol 2019 12 5;6(12):2403-2412. Epub 2019 Nov 5.

Framingham Heart Study, Framingham, Massachusetts.

Objective: To determine whether vascular risk factor burden in mid- or late-life associates with postmortem vascular and neurodegenerative pathologies in a community-based sample.

Methods: We studied participants from the Framingham Heart Study who participated in our voluntary brain bank program. Overall vascular risk factor burden was calculated using the Framingham Stroke Risk Profile (FSRP). Mid-life FSRP was measured at 50 to 60 years of age. Following death, brains were autopsied and semi-quantitatively assessed by board-certified neuropathologists for cerebrovascular outcomes (cortical infarcts, subcortical infarcts, atherosclerosis, arteriosclerosis) and Alzheimer's disease pathology (Braak stage, cerebral amyloid angiopathy, and neuritic plaque score). We estimated adjusted odds ratios between vascular risk burden (at mid-life and before death) and neuropathological outcomes using logistic and proportional-odds logistic models.

Results: The median time interval between FSRP and death was 33.4 years for mid-life FSRP and 4.4 years for final FSRP measurement before death. Higher mid-life vascular risk burden was associated with increased odds of all cerebrovascular pathology, even with adjustment for vascular risk burden before death. Late-life vascular risk burden was associated with increased odds of cortical infarcts (OR [95% CI]: 1.04 [1.00, 1.08]) and arteriosclerosis stage (OR [95% CI]: 1.03 [1.00, 1.05]). Mid-life vascular risk burden was not associated with Alzheimer's disease pathology, though late-life vascular risk burden was associated with increased odds of higher Braak stage (OR [95% CI]: 1.03 [1.01, 1.05]).

Interpretation: Mid-life vascular risk burden was predictive of cerebrovascular but not Alzheimer's disease neuropathology, even after adjustment for vascular risk factors before death.
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http://dx.doi.org/10.1002/acn3.50936DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6917310PMC
December 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

A genome-wide association study identifies genetic loci associated with specific lobar brain volumes.

Commun Biol 2019 2;2:285. Epub 2019 Aug 2.

17Department of Biomedical Data Sciences, Statistical Genetics, Leiden University Medical Center, Leiden, 2333ZA the Netherlands.

Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications ( and ), or close to genes causing Mendelian brain-related diseases ( and ). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.
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http://dx.doi.org/10.1038/s42003-019-0537-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677735PMC
April 2020

Circulating IGFBP-2: a novel biomarker for incident dementia.

Ann Clin Transl Neurol 2019 09 2;6(9):1659-1670. Epub 2019 Aug 2.

Framingham Heart Study, Framingham, Massachusetts.

Objective: To determine the association between plasma insulin-like growth factor binding protein 2 (IGFBP-2) and cognitive outcomes.

Methods: We measured plasma IGFBP-2 levels in 1596 (53% women, mean age 68.7 [SD 5.7] years) dementia-free Framingham Offspring cohort participants between 1998 and 2001. Multivariable Cox proportional hazards models related plasma IGFBP-2 to subsequent risk of incident dementia and Alzheimer's disease. MRI brain measures and cognitive performance were included as secondary outcomes.

Results: During a median follow-up of 11.8 (Q1, Q3: 7.1, 13.3) years, 131 participants developed incident dementia, of whom 98 were diagnosed with Alzheimer's disease. The highest tertile of IGFBP-2, compared to the lowest tertile, was associated with an increased risk of incident all-cause dementia (hazard ratio [HR] 2.89, 95% CI 1.63-5.13) and Alzheimer's disease (HR 3.63, 95% CI 1.76-7.50) in multivariable analysis. Higher circulating IGFBP2 levels were also cross-sectionally associated with poorer performance on tests of abstract reasoning but not with MRI-based outcomes. After adding plasma IGFBP-2 levels to a conventional dementia prediction model, 32% of individuals with dementia were correctly assigned a higher predicted risk, while 8% of individuals without dementia were correctly assigned a lower predicted risk (overall net reclassification improvement index, 0.40, 95% CI 0.22-0.59).

Interpretation: Elevated circulating IGFBP-2 levels were associated with an increased risk of both all-cause dementia and Alzheimer's disease. Addition of IGFBP2 plasma levels to a model of traditional risk factors significantly improved dementia risk classification. Manipulation of insulin-like growth factor signaling via IGFBP-2 may be a promising therapeutic target for dementia.
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http://dx.doi.org/10.1002/acn3.50854DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6764739PMC
September 2019

Plasma total-tau as a biomarker of stroke risk in the community.

Ann Neurol 2019 09 29;86(3):463-467. Epub 2019 Jul 29.

Framingham Heart Study, Framingham, MA.

Higher plasma total-tau level is associated with incident dementia, but its relationship with stroke risk is unknown. In this prospective community-based study, we evaluated plasma total-tau level as a biomarker of stroke risk in 2,794 Framingham Heart Study participants. Persons with plasma total-tau levels in the top quintile, versus the bottom 4, had an increased risk of incident stroke over a mean follow-up of 8.3 years (hazard ratio = 2.01; 95% confidence interval = 1.32-3.08) following adjustments for age, sex, and stroke risk factors. Our findings demonstrate that plasma total-tau relates to the risk of stroke in a community sample. ANN NEUROL 2019;86:463-467.
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http://dx.doi.org/10.1002/ana.25542DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297542PMC
September 2019

Corticosteroids and Regional Variations in Thickness of the Human Cerebral Cortex across the Lifespan.

Cereb Cortex 2020 03;30(2):575-586

Bordeaux Population Health Research Center, INSERM UMR, University of Bordeaux, Bordeaux 33076, France.

Exposures to life stressors accumulate across the lifespan, with possible impact on brain health. Little is known, however, about the mechanisms mediating age-related changes in brain structure. We use a lifespan sample of participants (n = 21 251; 4-97 years) to investigate the relationship between the thickness of cerebral cortex and the expression of the glucocorticoid- and the mineralocorticoid-receptor genes (NR3C1 and NR3C2, respectively), obtained from the Allen Human Brain Atlas. In all participants, cortical thickness correlated negatively with the expression of both NR3C1 and NR3C2 across 34 cortical regions. The magnitude of this correlation varied across the lifespan. From childhood through early adulthood, the profile similarity (between NR3C1/NR3C2 expression and thickness) increased with age. Conversely, both profile similarities decreased with age in late life. These variations do not reflect age-related changes in NR3C1 and NR3C2 expression, as observed in 5 databases of gene expression in the human cerebral cortex (502 donors). Based on the co-expression of NR3C1 (and NR3C2) with genes specific to neural cell types, we determine the potential involvement of microglia, astrocytes, and CA1 pyramidal cells in mediating the relationship between corticosteroid exposure and cortical thickness. Therefore, corticosteroids may influence brain structure to a variable degree throughout life.
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http://dx.doi.org/10.1093/cercor/bhz108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444740PMC
March 2020

Temporal Trends in Ischemic Stroke Incidence in Younger Adults in the Framingham Study.

Stroke 2019 06 14;50(6):1558-1560. Epub 2019 May 14.

From the Boston University School of Medicine, MA (H.J.A., J.J.H., C.L.S., J.R.R., C.S.K., A.S.B., S.S.).

Background and Purpose- Stroke at midlife has a disproportionately large impact on disability-adjusted life-years lost. Ischemic stroke incidence may be increasing at this age. We investigated long-term trends in ischemic stroke incidence and changes in stroke risk factors in a community sample stratified by stroke onset at middle and older age. Methods- In the Framingham Study, surveillance for incident stroke is ongoing since 1948. We examined age-adjusted and sex-adjusted 10-year incidence of ischemic stroke using Cox models in persons aged 35 to 54 and ≥55 years at start of follow-up. Tests for linear trend were performed over 4 epochs, controlling for the distance in time between intervals. Further, we calculated the mean 10-year risk of stroke at each epoch and for both age groups, based on vascular risk factors from the Framingham Stroke Risk Profile. Results- There were 153, 197, 176, and 165 incident ischemic strokes within each epoch beginning in 1962 (n=3966), 1971 (n=5779), 1987 (n=5133), and 1998 (n=6964). Most ischemic strokes at midlife (n=71) were because of atherosclerotic brain infarction (n=50) or cardioembolism (n=19). Using the risk in the 1962 epoch as the reference, the risk of ischemic stroke at midlife did not significantly decline (hazard ratio, 0.87; 95% CI, 0.74-1.02; P trend =0.09). Incidence of ischemic stroke declined in the older group (hazard ratio, 0.82; 95% CI, 0.77-0.88; P trend <0.001). Between epochs 1 and 4, the average 10-year risk of stroke, as estimated by the Framingham Stroke Risk Profile, declined by 0.7% at midlife and 1.1% at older age. Conclusions- Long-term rates of ischemic stroke declined in our community sample; the decline was greater in older as compared with younger adults. Early prevention, focused on modification of cardiovascular risk factors, is important to see sustained declines in stroke incidence and mortality at midlife.
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http://dx.doi.org/10.1161/STROKEAHA.119.025171DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538454PMC
June 2019

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Nat Commun 2019 May 1;10(1):2068. Epub 2019 May 1.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
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http://dx.doi.org/10.1038/s41467-019-10160-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494826PMC
May 2019

Full exploitation of high dimensionality in brain imaging: The JPND working group statement and findings.

Alzheimers Dement (Amst) 2019 Dec 30;11:286-290. Epub 2019 Mar 30.

Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands.

Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme-Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.
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http://dx.doi.org/10.1016/j.dadm.2019.02.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441785PMC
December 2019
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