scholarly journals Gray Matter Age Prediction as a Biomarker for Risk of Dementia

2019 ◽  
Vol 116 (42) ◽  
pp. 21213-21218 ◽  
Author(s):  
Johnny Wang ◽  
Maria J. Knol ◽  
Aleksei Tiulpin ◽  
Florian Dubost ◽  
Marleen de Bruijne ◽  
...  
Keyword(s):  
Gray Matter ◽  
Proportional Hazards ◽  
Early Stage ◽  
Hippocampal Volume ◽  
Cox Proportional Hazards ◽  
Intracranial Volume ◽  
Age Gap ◽  
Incident Dementia ◽  
Brain Age ◽  
Age Prediction

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and APOE ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05–1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06–1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.

scholarly journals Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study

2019 ◽  
Author(s):  
Johnny Wang ◽  
Maria J. Knol ◽  
Aleksei Tiulpin ◽  
Florian Dubost ◽  
Marleen de Bruijne ◽  
...  
Keyword(s):  
Grey Matter ◽  
Proportional Hazards ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Chronological Age ◽  
Population Based Study ◽  
Age Gap ◽  
Incident Dementia ◽  
Brain Age ◽  
Age Prediction

Key PointsQuestionIs the gap between brain age predicted from MRI and chronological age associated with incident dementia in a general population of Dutch adults?FindingsBrain age was predicted using a deep learning model, using MRI-derived grey matter density maps. In a population based study including 5496 participants, the observed gap was significantly associated with the risk of dementia.MeaningThe gap between MRI-brain predicted and chronological age is potentially a biomarker for dementia risk screening.AbstractImportanceThe gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link.ObjectiveWe aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps.DesignData was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016.SettingThe Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands.ParticipantsAt baseline, 5496 dementia- and stroke-free participants (mean age 64.67±9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66±2.46 years of follow-up, 159 people developed dementia.Main outcomes and measuresWe built a convolutional neural network (CNN) model to predict brain age based on its MRI. Model prediction performance was measured in mean absolute error (MAE). Reproducibility of prediction was tested using the intraclass correlation coefficient (ICC) computed on a subset of 80 subjects. Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for years of education, ApoEε4 allele carriership, grey matter volume and intracranial volume. Additionally, we computed the attention maps of CNN, which shows which brain regions are important for age prediction.ResultsMAE of brain age prediction was 4.45±3.59 years and ICC was 0.97 (95% confidence interval CI=0.96-0.98). Logistic regression and Cox proportional hazards models showed that the age gap was significantly related to incident dementia (odds ratio OR=1.11 and 95% confidence intervals CI=1.05-1.16; hazard ratio HR=1.11 and 95% CI=1.06-1.15, respectively). Attention maps indicated that grey matter density around the amygdalae and hippocampi primarily drive the age estimation.Conclusion and relevanceWe show that the gap between predicted and chronological brain age is a biomarker associated with risk of dementia development. This suggests that it can be used as a biomarker, complimentary to those that are known, for dementia risk screening.

scholarly journals Association Between Informant-Reported Sleep Disturbance and Incident Dementia: An Analysis of the National Alzheimer’s Coordinating Center Uniform Data Set

2020 ◽  
pp. 073346482096720
Author(s):  
Woojung Lee ◽  
Shelly L. Gray ◽  
Douglas Barthold ◽  
Donovan T. Maust ◽  
Zachary A. Marcum
Keyword(s):  
Older Adults ◽  
Sleep Disturbance ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Cognitive Screening ◽  
Cognitive Level ◽  
Data Set ◽  
Cox Proportional Hazards Models ◽  
Incident Dementia ◽  
Normal Cognition

Informants’ reports can be useful in screening patients for future risk of dementia. We aimed to determine whether informant-reported sleep disturbance is associated with incident dementia, whether this association varies by baseline cognitive level and whether the severity of informant-reported sleep disturbance is associated with incident dementia among those with sleep disturbance. A longitudinal retrospective cohort study was conducted using the uniform data set collected by the National Alzheimer’s Coordinating Center. Older adults without dementia at baseline living with informants were included in analysis. Cox proportional hazards models showed that participants with an informant-reported sleep disturbance were more likely to develop dementia, although this association may be specific for older adults with normal cognition. In addition, older adults with more severe sleep disturbance had a higher risk of incident dementia than those with mild sleep disturbance. Informant-reported information on sleep quality may be useful for prompting cognitive screening.

Diet Inflammatory Index and Dementia Incidence: A Population-Based Study

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012973
Author(s):  
Sokratis Charisis ◽  
Eva Ntanasi ◽  
Mary Yannakoulia ◽  
Costas A Anastasiou ◽  
Mary H Kosmidis ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Community Dwelling ◽  
Dietary Interventions ◽  
Clinical Criteria ◽  
Inflammatory Index ◽  
Incident Dementia ◽  
Dementia Incidence ◽  
Increased Risk

Background and objectives:Aging is characterized by a functional shift of the immune system towards a proinflammatory phenotype. This derangement has been associated with cognitive decline and has been implicated in the pathogenesis of dementia. Diet can modulate systemic inflammation; thus, it may be a valuable tool to counteract the associated risks for cognitive impairment and dementia. The present study aimed to explore the associations between the inflammatory potential of diet, assessed using an easily applicable, population-based, biomarker-validated diet inflammatory index (DII), and the risk for dementia in community-dwelling older adults.Methods:Individuals from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) were included in the present cohort study. Participants were recruited through random population sampling, and were followed for a mean of 3.05 (SD=0.85) years. Dementia diagnosis was based on standard clinical criteria. Those with baseline dementia and/or missing cognitive follow-up data were excluded from the analyses. The inflammatory potential of diet was assessed through a DII score which considers literature-derived associations of 45 food parameters with levels of pro- and anti-inflammatory cytokines in the blood; higher values indicated a more pro-inflammatory diet. Consumption frequencies were derived from a detailed food frequency questionnaire, and were standardized to representative dietary intake normative data from 11 different countries. Analysis of dementia incidence as a function of baseline DII scores was performed by Cox proportional hazards models.Results:Analyses included 1059 individuals (mean age=73.1 years; 40.3% males; mean education=8.2 years), 62 of whom developed incident dementia. Each additional unit of DII was associated with a 21% increase in the risk for dementia incidence [HR=1.21 (1.03 – 1.42); p=0.023]. Compared to participants in the lowest DII tertile, participants in the highest one (maximal pro-inflammatory diet potential) were 3 [(1.2 – 7.3); p=0.014] times more likely to develop incident dementia. The test for trend was also significant, indicating a potential dose-response relationship (p=0.014).Conclusions:In the present study, higher DII scores (indicating greater pro-inflammatory diet potential) were associated with an increased risk for incident dementia. These findings might avail the development of primary dementia preventive strategies through tailored and precise dietary interventions.

scholarly journals Increased Brain Age Gap Estimate (BrainAGE) in Young Adults After Premature Birth

2021 ◽  
Vol 13 ◽  
Author(s):  
Dennis M. Hedderich ◽  
Aurore Menegaux ◽  
Benita Schmitz-Koep ◽  
Rachel Nuttall ◽  
Juliana Zimmermann ◽  
...  
Keyword(s):  
Premature Birth ◽  
Brain Aging ◽  
Structural Mri ◽  
Full Term ◽  
Intracranial Volume ◽  
Age Gap ◽  
Increased Risk ◽  
Aging Rates ◽  
Brain Age ◽  
Premature Born

Recent evidence suggests increased metabolic and physiologic aging rates in premature-born adults. While the lasting consequences of premature birth on human brain development are known, its impact on brain aging remains unclear. We addressed the question of whether premature birth impacts brain age gap estimates (BrainAGE) using an accurate and robust machine-learning framework based on structural MRI in a large cohort of young premature-born adults (n = 101) and full-term (FT) controls (n = 111). Study participants are part of a geographically defined population study of premature-born individuals, which have been followed longitudinally from birth until young adulthood. We investigated the association between BrainAGE scores and perinatal variables as well as with outcomes of physical (total intracranial volume, TIV) and cognitive development (full-scale IQ, FS-IQ). We found increased BrainAGE in premature-born adults [median (interquartile range) = 1.4 (−1.3–4.7 years)] compared to full-term controls (p = 0.002, Cohen’s d = 0.443), which was associated with low Gestational age (GA), low birth weight (BW), and increased neonatal treatment intensity but not with TIV or FS-IQ. In conclusion, results demonstrate elevated BrainAGE in premature-born adults, suggesting an increased risk for accelerated brain aging in human prematurity.

scholarly journals Reliable longitudinal brain age prediction in stroke patients: Associations with cognitive function and response to cognitive training

2019 ◽  
Author(s):  
Geneviève Richard ◽  
Knut Kolskår ◽  
Kristine M. Ulrichsen ◽  
Tobias Kaufmann ◽  
Dag Alnæs ◽  
...  
Keyword(s):  
Cognitive Training ◽  
Outcome Prediction ◽  
Cognitive Intervention ◽  
Chronological Age ◽  
Double Blind Study ◽  
Stroke Patients ◽  
Brain Morphometry ◽  
Age Gap ◽  
Brain Age ◽  
Age Prediction

AbstractCognitive deficits are important predictors for outcome, independence and quality of life after stroke, but often remain unnoticed and unattended because other impairments are more evident. Computerized cognitive training (CCT) is among the candidate interventions that may alleviate cognitive difficulties, but the evidence supporting its feasibility and effectiveness is scarce, partly due to the lack of tools for outcome prediction and monitoring. Magnetic resonance imaging (MRI) provides candidate markers for disease monitoring and outcome prediction. By integrating information not only about lesion extent and localization, but also regarding the integrity of the unaffected parts of the brain, advanced MRI provides relevant information for developing better prediction models in order to tailor cognitive intervention for patients, especially in a chronic phase.Using brain age prediction based on MRI based brain morphometry and machine learning, we tested the hypotheses that stroke patients with a younger-appearing brain relative to their chronological age perform better on cognitive tests and benefit more from cognitive training compared to patients with an older-appearing brain. In this randomized double-blind study, 54 patients who suffered mild stroke (>6 months since hospital admission, NIHSS<7 at hospital discharge) underwent 3-weeks CCT and MRI before and after the intervention. In addition, patients were randomized to one of two groups receiving either active or sham transcranial direct current stimulation (tDCS). We tested for main effects of brain age gap (estimated age – chronological age) on cognitive performance, and associations between brain age gap and task improvement. Finally, we tested if longitudinal changes in brain age gap during the intervention were sensitive to treatment response. Briefly, our results suggest that longitudinal brain age prediction based on automated brain morphometry is feasible and reliable in stroke patients. However, no significant association between brain age and both performance and response to cognitive training were found.

scholarly journals Bi-directional association between epilepsy and dementia

Neurology ◽  
2020 ◽  
Vol 95 (24) ◽  
pp. e3241-e3247 ◽  
Author(s):  
Maria Stefanidou ◽  
Alexa S. Beiser ◽  
Jayandra Jung Himali ◽  
Teng J. Peng ◽  
Orrin Devinsky ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Secondary Analysis ◽  
Cox Proportional Hazards ◽  
Dementia Risk ◽  
Incident Dementia ◽  
Heart Study ◽  
Allele Status ◽  
Ε4 Allele ◽  
Nested Case Control

ObjectiveTo assess the risk of incident epilepsy among participants with prevalent dementia and the risk of incident dementia among participants with prevalent epilepsy in the Framingham Heart Study (FHS).MethodsWe analyzed prospectively collected data in the Original and Offspring FHS cohorts. To determine the risk of developing epilepsy among participants with dementia and the risk of developing dementia among participants with epilepsy, we used separate, nested, case–control designs and matched each case to 3 age-, sex- and FHS cohort–matched controls. We used Cox proportional hazards regression analysis, adjusting for sex and age. In secondary analysis, we investigated the role of education level and APOE ε4 allele status in modifying the association between epilepsy and dementia.ResultsA total of 4,906 participants had information on epilepsy and dementia and dementia follow-up after age 65. Among 660 participants with dementia and 1,980 dementia-free controls, there were 58 incident epilepsy cases during follow-up. Analysis comparing epilepsy risk among dementia cases vs controls yielded a hazard ratio (HR) of 1.82 (95% confidence interval 1.05–3.16, p = 0.034). Among 43 participants with epilepsy and 129 epilepsy-free controls, there were 51 incident dementia cases. Analysis comparing dementia risk among epilepsy cases vs controls yielded a HR of 1.99 (1.11–3.57, p = 0.021). In this group, among participants with any post–high school education, prevalent epilepsy was associated with a nearly 5-fold risk for developing dementia (HR 4.67 [1.82–12.01], p = 0.001) compared to controls of the same educational attainment.ConclusionsThere is a bi-directional association between epilepsy and dementia. with either condition carrying a nearly 2-fold risk of developing the other when compared to controls.

scholarly journals Illiteracy, dementia risk, and cognitive trajectories among older adults with low education

Neurology ◽  
2019 ◽  
Vol 93 (24) ◽  
pp. e2247-e2256 ◽  
Author(s):  
Miguel Arce Rentería ◽  
Jet M.J. Vonk ◽  
Gloria Felix ◽  
Justina F. Avila ◽  
Laura B. Zahodne ◽  
...  
Keyword(s):  
Older Adults ◽  
Cognitive Decline ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Independent Effect ◽  
Growth Curve Models ◽  
Cox Proportional Hazards Models ◽  
Dementia Risk ◽  
Incident Dementia ◽  
Low Education

ObjectiveTo investigate whether illiteracy was associated with greater risk of prevalent and incident dementia and more rapid cognitive decline among older adults with low education.MethodsAnalyses included 983 adults (≥65 years old, ≤4 years of schooling) who participated in a longitudinal community aging study. Literacy was self-reported (“Did you ever learn to read or write?”). Neuropsychological measures of memory, language, and visuospatial abilities were administered at baseline and at follow-ups (median [range] 3.49 years [0–23]). At each visit, functional, cognitive, and medical data were reviewed and a dementia diagnosis was made using standard criteria. Logistic regression and Cox proportional hazards models evaluated the association of literacy with prevalent and incident dementia, respectively, while latent growth curve models evaluated the effect of literacy on cognitive trajectories, adjusting for relevant demographic and medical covariates.ResultsIlliterate participants were almost 3 times as likely to have dementia at baseline compared to literate participants. Among those who did not have dementia at baseline, illiterate participants were twice as likely to develop dementia. While illiterate participants showed worse memory, language, and visuospatial functioning at baseline than literate participants, literacy was not associated with rate of cognitive decline.ConclusionWe found that illiteracy was independently associated with higher risk of prevalent and incident dementia, but not with a more rapid rate of cognitive decline. The independent effect of illiteracy on dementia risk may be through a lower range of cognitive function, which is closer to diagnostic thresholds for dementia than the range of literate participants.

Effect of Pregnancy on Overall Survival After the Diagnosis of Early-Stage Breast Cancer

2001 ◽  
Vol 19 (6) ◽  
pp. 1671-1675 ◽  
Author(s):  
Shari Gelber ◽  
Alan S. Coates ◽  
Aron Goldhirsch ◽  
Monica Castiglione-Gertsch ◽  
Gianluigi Marini ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Proportional Hazards ◽  
Comparison Group ◽  
Early Stage ◽  
Pregnant Patient ◽  
Subsequent Pregnancy ◽  
Cox Proportional Hazards ◽  
Early Stage Breast Cancer ◽  
Study Group ◽  
The Impact

PURPOSE: To evaluate the impact of subsequent pregnancy on the prognosis of patients with early breast cancer. PATIENTS AND METHODS: One hundred eight patients who became pregnant after diagnosis of early-stage breast cancer were identified in institutions participating in International Breast Cancer Study Group (IBCSG) studies. Fourteen had relapse of breast cancer before their first subsequent pregnancy. The remaining 94 patients (including eight who relapsed during pregnancy) formed the study group reported here. A comparison group of 188 was obtained by randomly selecting two patients, matched for nodal status, tumor size, age, and year of diagnosis from the IBCSG database, who were free of relapse for at least as long as the time between breast cancer diagnosis and completion of pregnancy for each pregnant patient. Survival comparison used Cox proportional hazards regression models. RESULTS: Overall 5- and 10-year survival percentages (± SE) measured from the diagnosis of early-stage breast cancer among the 94 study group patients were 92% ± 3% and 86% ± 4%, respectively. For the matched comparison group survival was 85% ± 3% at 5 years and 74% ± 4% at 10 years (risk ratio, 0.44; 95% confidence interval, 0.21 to 0.96; P = .04). CONCLUSION: Subsequent pregnancy does not adversely affect the prognosis of early-stage breast cancer. The superior survival seen in this and other controlled series may merely reflect a healthy patient selection bias, but is also consistent with an antitumor effect of the pregnancy.

Chronic diarrhoea and risk of rheumatoid arthritis: findings from the French E3N-EPIC Cohort Study

Rheumatology ◽  
2020 ◽  
Vol 59 (12) ◽  
pp. 3767-3775 ◽  
Author(s):  
Yann Nguyen ◽  
Xavier Mariette ◽  
Carine Salliot ◽  
Gaëlle Gusto ◽  
Marie-Christine Boutron-Ruault ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Dietary Habits ◽  
Early Stage ◽  
Gastrointestinal Disorder ◽  
Cox Proportional Hazards ◽  
Hazard Ratio ◽  
Gastrointestinal Disorders ◽  
Chronic Diarrhoea ◽  
Increased Risk ◽  
Nutrition Study

Abstract Objectives To assess the relationship between gastrointestinal disorders and the risk of further development of RA. Methods The Etude Epidémiologique auprès des femmes de la Mutuelle générale de l’Education Nationale-European Prospective Investigation into Cancer and Nutrition Study is a French prospective cohort including 98 995 healthy women since 1990. Participants completed mailed questionnaires on their lifestyles and health-related information. Gastrointestinal disorders were assessed in the third questionnaire (sent in 1993). Hazard ratios and 95% CIs for incident RA were estimated using Cox proportional hazards regression models with age as the time scale. Models were age adjusted, and then additionally adjusted for known risk factors of RA such as smoking, and for potential cofounders. Results Among 65 424 women, 530 validated incident RA cases were diagnosed after a mean (s.d.) of 11.7 (5.9) years after study baseline. In comparison with no gastrointestinal disorder, chronic diarrhoea was associated with an increased risk of developing RA during follow-up (hazard ratio = 1.70, 95% CI 1.13, 2.58), independently of dysthyroidism or dietary habits. The association was stronger among ever-smokers (hazard ratio = 2.21, 95% CI 1.32, 3.70). There was no association between RA risk and constipation or alternating diarrhoea/constipation. Conclusion Chronic diarrhoea was associated with an increased risk of subsequent RA development, particularly among ever-smokers. These data fit with the mucosal origin hypothesis of RA, where interaction between intestinal dysbiosis and smoking could occur at an early stage to promote emergence of autoimmunity, followed years later by clinical disease.

The effect of language skills on dementia in a Swedish longitudinal cohort

2016 ◽  
Vol 6 (1-2) ◽  
pp. 190-204 ◽  
Author(s):  
Jessica K. Ljungberg ◽  
Patrik Hansson ◽  
Rolf Adolfsson ◽  
Lars-Göran Nilsson
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Longitudinal Cohort ◽  
Proportional Hazards Regression ◽  
Time Period ◽  
Incident Dementia ◽  
Frequency Of Use ◽  
Longitudinal Effects ◽  
E4 Allele ◽  
Using Data

Abstract Recent findings indicate that bilingualism delay the onset of dementia. Using data from the Betula longitudinal cohort study on memory, health and aging (www.betula.su.se) the issue of a possible protective effect of bilingualism was addressed. Monolingual (n = 736) and bilingual (n = 82) participants (≥ 60 years) without dementia at inclusion were followed for incident dementia over a time-period up to 10 years. In total, 112 participants developed dementia. Analyses were performed with Cox proportional hazards regression adjusted for age, sex, and presence/absence of the Apolipoprotein E (APOE) ɛ4 allele, with dementia outcome as the dependent variable. Results showed no delayed onset of dementia in bilinguals compared to monolinguals. However, because of the findings from a study using participants from the same population showing beneficial longitudinal effects of bilingualism on episodic memory; we argue that our results may depend on the frequency of use of the second language after retirement.

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