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BackgroundDementia shows sex difference in its epidemiology. Childbirth, a distinctive experience of women, is associated with the risk for various diseases. However, its association with the risk of dementia in women has rarely been studied.MethodsWe harmonized and pooled baseline data from 11 population-based cohorts from 11 countries over 3 continents, including 14,792 women aged 60 years or older. We investigated the association between parity and the risk of dementia using logistic regression models that adjusted for age, educational level, hypertension, diabetes mellitus, and cohort, with additional analyses by region and dementia subtype.ResultsAcross all cohorts, grand multiparous (5 or more childbirths) women had a 47% greater risk of dementia than primiparous (1 childbirth) women (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.10-1.94), while nulliparous (no childbirth) women and women with 2 to 4 childbirths showed a comparable dementia risk to primiparous women. However, there were differences associated with region and dementia subtype. Compared to women with 1 to 4 childbirths, grand multiparous women showed a higher risk of dementia in Europe (OR = 2.99, 95% CI = 1.38-6.47) and Latin America (OR = 1.49, 95% CI = 1.04-2.12), while nulliparous women showed a higher dementia risk in Asia (OR = 2.15, 95% CI = 1.33-3.47). Grand multiparity was associated with 6.9-fold higher risk of vascular dementia in Europe (OR = 6.86, 95% CI = 1.81-26.08), whereas nulliparity was associated with a higher risk of Alzheimer disease (OR = 1.91, 95% CI 1.07-3.39) and non-Alzheimer non-vascular dementia (OR = 3.47, 95% CI = 1.44-8.35) in Asia.ConclusionParity is associated with women's risk of dementia, though this is not uniform across regions and dementia subtypes.

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data.

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure.

Background: Parental history of dementia appears to increase the risk of dementia, but there have been inconsistent results. We aimed to investigate whether the association between parental history of dementia and the risk of dementia are different by dementia subtypes and sex of parent and offspring. Methods: For this cross‐sectional study, we harmonized and pooled data for 17,194 older adults from nine population‐based cohorts of eight countries. These studies conducted face‐to‐face diagnostic interviews, physical and neurological examinations, and neuropsychological assessments to diagnose dementia. We investigated the associations of maternal and paternal history of dementia with the risk of dementia and its subtypes in offspring. Results: The mean age of the participants was 72.8 ± 7.9 years and 59.2% were female. Parental history of dementia was associated with higher risk of dementia (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.15–1.86) and Alzheimer's disease (AD) (OR = 1.72, 95% CI = 1.31–2.26), but not with the risk of non‐AD. This was largely driven by maternal history of dementia, which was associated with the risk of dementia (OR = 1.51, 95% CI = 1.15–1.97) and AD (OR = 1.80, 95% CI = 1.33–2.43) whereas paternal history of dementia was not. These results remained significant when males and females were analyzed separately (OR = 2.14, 95% CI = 1.28–3.55 in males; OR = 1.68, 95% CI = 1.16–2.44 for females). Conclusions: Maternal history of dementia was associated with the risk of dementia and AD in both males and females. Maternal history of dementia may be a useful marker for identifying individuals at higher risk of AD and stratifying the risk for AD in clinical trials. [ABSTRACT FROM AUTHOR]

Background: Ankle-brachial index (ABI), an indicator of atherosclerosis or arterial stiffness, has been associated with Alzheimer's disease (AD) dementia and related cognitive impairment. Nevertheless, only limited information is available regarding its contribution to brain alterations leading to cognitive decline in late-life. Objective: We aimed to investigate the relationship of ABI with in vivo AD pathologies and cerebrovascular injury in cognitively impaired older adults. Methods: Total 127 cognitively impaired (70 mild cognitive impairment and 57 AD dementia) individuals, who participated in an ongoing prospective cohort study, were included. All participants underwent comprehensive clinical and neuropsychological assessment, ABI measurement, apolipoprotein E (APOE) ɛ4 genotyping, and multi-modal brain imaging including [11C] Pittsburgh Compound B (PiB)-positron emission tomography (PET) and [18F] fludeoxyglucose (FDG)-PET, and MRI. Results: General linear model analysis showed significant relationship between ABI strata (low ABI: <1.00, normal ABI: 1.00–1.29, and high ABI: ≥1.30) and AD-signature region cerebral glucose metabolism (AD-CM), even after controlling age, sex, clinical dementia rating–sum of box, and APOE ɛ4 positivity (p = 0.029). Post hoc comparison revealed that low ABI had significantly lower AD-CM than middle and high ABI, while no difference of AD-CM was found between middle and high ABI. There was no significant difference of global Aβ deposition, AD-signature region cortical thickness, and white matter hyperintensity volume between the three ABI strata. Conclusion: Our findings suggest that lower ABI, likely related to atherosclerosis, may contribute to the aggravation of AD-related regional neurodegeneration in cognitively impaired older adults. [ABSTRACT FROM AUTHOR]

Background: There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults. Methods: We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses. Results: The COVID-19 pandemic was associated with increased depressive symptoms in older adults [ b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18–5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic. Conclusions: The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic. Aims: This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations. Materials and Methods: The participants, ages 65–85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta GWAS study by Jansen and colleagues. Results: We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models. Discussion: In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC. Conclusion: This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenoty pic associations that support deep systematic understanding of AD pathogenesis. [ABSTRACT FROM AUTHOR]

Este estudio analiza la relación entre el volumen del cerebelo de adultos normales en la tercera década de la vida (20-29 años) y varios factores psicológicos. El volumen del cerebelo de 118 sujetos (media de edad 23 ± 2,6 años), incluyendo 58 varones (media de edad 24 ± 2,8 años) y 60 mujeres (media de edad, 21,9 ± 2,1 años), fue medido utilizando la imagen por resonancia magnética (IRM). Todos los participantes completaron los siguientes tests: Cuestionario de 90 Síntomas (SCL-90-R), Cuestionario de Personalidad de Tipo A, El cuestionario de Ansiedad Estado Korean YZ, El Cuestionario de 16 Factores de la Personalidad (16PF), y la Escala Autoadministrada de Depresión (EAD). Utilizando regresión linear, se analizó la relación entre el volumen del cerebelo y factores psicológicos. Sin considerar las diferencias entre géneros, en cuanto crecía la tendencia hacia la personalidad tipo A y se incrementaba el estado de ansiedad y la fuerza del superego, disminuía el volumen del cerebelo. Cuando se incrementaba la fuerza del ego, se incrementaba el volumen del cerebelo. Cuando se consideraban las diferencias de género, cuando incrementaba la ansiedad fóbica y ambición en varones, disminuía el volumen del cerebelo. En mujeres, cuando incrementaba la hostilidad, tensión y la ansiedad estado, disminuía el volumen del cerebelo.

Background: The recruitment of monocytes to the brain plays an important role in the development of depression. However, the association between plasma biomarkers of monocyte trafficking and depression is unclear. This study is aimed to examine the effects of plasma monocyte chemoattractant protein 1 (MCP-1), intercellular adhesion molecule 1 (ICAM-1), and vascular cell adhesion molecule 1 (VCAM-1) on the risk of depression.Methods: Data were acquired from an ongoing prospective cohort study involving randomly sampled, community-dwelling Korean older adults, which has been followed every 2 years. We included 1539 euthymic older adults (age = 68.2 [5.6] years; 51.7% were women) without a history of major psychiatric disorders and dementia and neurological diseases. Geriatric psychiatrists diagnosed incident depression through a structured interview using the Korean version of the Mini-International Neuropsychiatric Interview.Results: Depression had developed in 134 (8.7%) participants during the follow-up period of 5.7 (0.8) years. The high-plasma MCP-1 tertile group showed twofold higher risk of depression than the low-plasma MCP-1 tertile group (hazards ratio = 2.00, 95% confidence interval = 1.27-3.13, p = .003). The association between high levels of plasma MCP-1 and future risk of depression was significant in the middle-plasma ICAM-1 and VCAM-1 tertile groups; the high-plasma MCP-1 tertile group showed about fourfold higher risk of depression than the low-plasma MCP-1 tertile group.Conclusions: Molecules involved in monocyte trafficking may be good candidates as diagnostic biomarkers and/or therapeutic targets for late-life depression. [ABSTRACT FROM AUTHOR]

Objective: The effects of mood disorders on mortality may be mediated by their effects on the risk of dementia, and interventions to reduce the occurrence of dementia may reduce their overall mortality. This study aimed to investigate the direct effects of depressive and bipolar disorders on the 6-year risk of mortality and also their indirect effects on mortality due to their effect on the risk of dementia. Methods: A total of 5101 Koreans were selected from a community-based prospective cohort study, and 6-year risks of mortality and dementia in participants with depressive and bipolar disorders were estimated by Cox proportional hazard analysis. The direct and indirect effects of depressive and bipolar disorders on the risk of mortality were estimated using structural equation modeling. Results: The depressive and bipolar disorder groups showed 51% and 85% higher 6-year mortality, and 82% and 127% higher risk of dementia, respectively, compared to euthymic controls. The effects of depressive and bipolar disorders on mortality were mainly mediated by their effects on the risk of dementia in a structural equation model. The direct effects of each mood disorder on mortality were not significant. Conclusion: Both depressive and bipolar disorders increased the risks of mortality and dementia, and the effects of mood disorders on mortality were mainly mediated through dementia. As dementia occurs later in life than mood disorders, measures to prevent it may effectively reduce mortality in individuals with a history of mood disorders, as well as being more feasible than attempting to control other causes of death. [ABSTRACT FROM AUTHOR]