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Abstract White matter hyperintensities index structural abnormalities in the cerebral white matter, including axonal damage. The latter may promote atrophy of the cerebral cortex, a key feature of dementia. Here, we report a study of 51,065 individuals from 10 cohorts demonstrating that higher white matter hyperintensity volume associates with lower cortical thickness. The meta-GWAS of white matter hyperintensities-associated cortical ‘atrophy’ identifies 20 genome-wide significant loci, and enrichment in genes specific to vascular cell types, astrocytes, and oligodendrocytes. White matter hyperintensities-associated cortical ‘atrophy’ showed positive genetic correlations with vascular-risk traits and plasma biomarkers of neurodegeneration, and negative genetic correlations with cognitive functioning. 15 of the 20 loci regulated the expression of 54 genes in the cerebral cortex that, together with their co-expressed genes, were enriched in biological processes of axonal cytoskeleton and intracellular transport. The white matter hyperintensities-cortical thickness associations were most pronounced in cortical regions with higher expression of genes specific to excitatory neurons with long-range axons traversing through the white matter. The meta-GWAS-based polygenic risk score predicts vascular and all-cause dementia in an independent sample of 500,348 individuals. Thus, the genetics of white matter hyperintensities-related cortical atrophy involves vascular and neuronal processes and increases dementia risk.

Abstract Background The accumulation of amyloid-β (Aβ) peptide in the brain is a hallmark of Alzheimer’s disease (AD), occurring years before symptom onset. Current methods for quantifying in vivo amyloid load involve invasive or costly procedures, limiting accessibility. Early detection of amyloid positivity in non-demented individuals is crucial for aiding early AD diagnosis and for initiating anti-amyloid immunotherapies at early stages. This study aimed to develop and validate predictive models to identify brain amyloid positivity in non-demented patients, using routinely collected clinical data. Methods Predictive models for amyloid positivity were developed using data from 853 non-demented participants in the MEMENTO cohort. Amyloid levels were measured potentially repeatedly during study course through Positron Emision Tomography or CerebroSpinal Fluid analysis. The probability of amyloid positivity was modelled using mixed-effects logistic regression. Predictors included demographic information, cognitive assessments, visual brain MRI evaluations of hippocampal atrophy and lobar microbleeds, AD-related blood biomarkers (Aβ42/40 and P-tau181), and ApoE4 status. Models were subjected to internal cross-validation and external validation using data from the Amsterdam Dementia Cohort. Performance also was evaluated in a subsample that met the main criteria of the Appropriate Use Recommendations (AUR) for lecanemab. Results The most effective model incorporated demographic data, cognitive assessments, ApoE status, and AD-related blood biomarkers, achieving AUCs of 0.82 [95%CI 0.81-0.82] in MEMENTO sample and 0.90 [95%CI 0.86-0.94] in the external validation sample. This model significantly outperformed a reference model based solely on demographic and cognitive data, with an AUC difference in MEMENTO of 0.10 [95%CI 0.10-0.11]. A similar model without ApoE genotype achieved comparable discriminatory performance. MRI markers did not improve model performance. Performances in AUR of lecanemab subsample were comparable. Conclusion A predictive model integrating demographic, cognitive, and blood biomarker data offers a promising method to help identify amyloid status in non-demented patients. ApoE genotype and brain MRI data were not necessary for strong discriminatory ability, suggesting that ApoE genotyping may be deferred when assessing the risk-benefit ratio of immunotherapies in amyloid-positive patients who desire treatment. The integration of this model into clinical practice could reduce the need for lumbar puncture or PET examinations to confirm amyloid status.

Abstract Neurofilament light chain (NfL) levels in circulation have been established as a sensitive biomarker of neuro-axonal damage across a range of neurodegenerative disorders. Elucidation of the genetic architecture of blood NfL levels could provide new insights into molecular mechanisms underlying neurodegenerative disorders. In this meta-analysis of genome-wide association studies (GWAS) of blood NfL levels from eleven cohorts of European ancestry, we identify two genome-wide significant loci at 16p12 (UMOD) and 17q24 (SLC39A11). We observe association of three loci at 1q43 (FMN2), 12q14, and 12q21 with blood NfL levels in the meta-analysis of African-American ancestry. In the trans-ethnic meta-analysis, we identify three additional genome-wide significant loci at 1p32 (FGGY), 6q14 (TBX18), and 4q21. In the post-GWAS analyses, we observe the association of higher NfL polygenic risk score with increased plasma levels of total-tau, Aβ-40, Aβ-42, and higher incidence of Alzheimer’s disease in the Rotterdam Study. Furthermore, Mendelian randomization analysis results suggest that a lower kidney function could cause higher blood NfL levels. This study uncovers multiple genetic loci of blood NfL levels, highlighting the genes related to molecular mechanism of neurodegeneration.

Abstract Background Cognitive complaints are often regarded as an early sign of Alzheimer’s disease (AD) but may also occur in several other conditions and contexts. This study examines the correlates of cognitive complaint trajectories over a 5-year period in individuals who shared similar objective cognitive trajectories. Methods We analyzed a subsample (n = 1748) of the MEMENTO cohort, consisting of individuals with subjective cognitive decline or mild cognitive impairment at baseline. Participants were stratified based on their latent MMSE trajectory over a 5-year period: “high and increasing,” “subtle decline,” and “steep decline.” Within each of the three strata, we used a latent-class longitudinal approach to identify distinct trajectories of cognitive complaints. We then used multiple logistic regressions to examine the association between these complaint trajectories and several factors, including AD biomarkers (blood pTau/Aβ42 ratio, cortical thickness, APOE genotype), anxiety, depression, social relationships, a comorbidity-polypharmacy score, and demographic characteristics. Results Among participants with high and increasing MMSE scores, greater baseline comorbidity-polypharmacy scores (odds ratio (OR) = 1.30, adjusted p = 0.03) were associated with higher odds of moderate and increasing cognitive complaints (as opposed to mild and decreasing complaints). Baseline depression and social relationships also showed significant associations with the complaint pattern but did not survive correction for multiple comparisons. Among participants with subtle decline in MMSE scores, greater baseline depression (OR = 1.76, adjusted p = 0.02) was associated with higher odds of moderate and increasing cognitive complaints (versus mild and decreasing). Similarly, baseline comorbidity-polypharmacy scores and pTau/Aβ42 ratio exhibited significant associations, but they did not survive correction. Among participants with a steep decline in MMSE scores, greater baseline comorbidity-polypharmacy scores increased the odds of moderate complaints (versus mild, OR = 1.38, unadjusted p = 0.03, adjusted p = 0.32), but this effect did not survive correction for multiple comparisons. Conclusions Despite similar objective cognitive trajectory, there is heterogeneity in the subjective perception of these cognitive changes. This perception was explained by both AD-related and, more robustly, non-AD-related factors. These findings deepen our understanding of the multifaceted nature of subjective cognitive complaints in individuals at risk for dementia and underscore the importance of considering a range of factors when interpreting cognitive complaints.

Abstract Background Alzheimer’s disease and related dementia (ADRD) are characterized by multiple and progressive anatomo-clinical changes including accumulation of abnormal proteins in the brain, brain atrophy and severe cognitive impairment. Understanding the sequence and timing of these changes is of primary importance to gain insight into the disease natural history and ultimately allow earlier diagnosis. Yet, modeling changes over disease course from cohort data is challenging as the usual timescales (time since inclusion, chronological age) are inappropriate and time-to-clinical diagnosis is available on small subsamples of participants with short follow-up durations prior to diagnosis. One solution to circumvent this challenge is to define the disease time as a latent variable. Methods We developed a multivariate mixed model approach that realigns individual trajectories into the latent disease time to describe disease progression. In contrast with the existing literature, our methodology exploits the clinical diagnosis information as a partially observed and approximate reference to guide the estimation of the latent disease time. The model estimation was carried out in the Bayesian Framework using Stan. We applied the methodology to the MEMENTO study, a French multicentric clinic-based cohort of 2186 participants with 5-year intensive follow-up. Repeated measures of 12 ADRD markers stemmed from cerebrospinal fluid (CSF), brain imaging and cognitive tests were analyzed. Results The estimated latent disease time spanned over twenty years before the clinical diagnosis. Considering the profile of a woman aged 70 with a high level of education and APOE4 carrier (the main genetic risk factor for ADRD), CSF markers of tau proteins accumulation preceded markers of brain atrophy by 5 years and cognitive decline by 10 years. However we observed that individual characteristics could substantially modify the sequence and timing of these changes, in particular for CSF level of A $$\beta _{42}$$ β 42 . Conclusion By leveraging the available clinical diagnosis timing information, our disease progression model does not only realign trajectories into the most homogeneous way. It accounts for the inherent residual inter-individual variability in dementia progression to describe the long-term anatomo-clinical degradations according to the years preceding clinical diagnosis, and to provide clinically meaningful information on the sequence of events. Trial registration clinicaltrials.gov, NCT01926249. Registered on 16 August 2013.

Abstract The utility of brain magnetic resonance imaging (MRI) for predicting dementia is debated. We evaluated the added value of repeated brain MRI, including atrophy and cerebral small vessel disease markers, for dementia prediction. We conducted a landmark competing risk analysis in 1716 participants of the French population‐based Three‐City Study to predict the 5‐year risk of dementia using repeated measures of 41 predictors till year 4 of follow‐up. Brain MRI markers improved significantly the individual prediction of dementia after accounting for demographics, health measures, and repeated measures of cognition and functional dependency (area under the ROC curve [95% CI] improved from 0.80 [0.79 to 0.82] to 0.83 [0.81 to 0.84]). Nonetheless, accounting for the change over time through repeated MRIs had little impact on predictive abilities. These results highlight the importance of multimodal analysis to evaluate the added predictive abilities of repeated brain MRI for dementia and offer new insights into the predictive performances of various MRI markers. Highlights We evaluated whether repeated brain volumes and cSVD markers improve dementia prediction. The 5‐year prediction of dementia is slightly improved when considering brain MRI markers. Measures of hippocampus volume are the main MRI predictors of dementia. Adjusted on cognition, repeated MRI has poor added value over single MRI for dementia prediction. We utilized a longitudinal analysis that considers error‐and‐missing‐prone predictors, and competing death.

Abstract Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer’s disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10–311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10–09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10–10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10–09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10–08, MAF = 0.006, sex-interaction P = 9.8 × 10–07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10–08, MAF = 0.004, sex-interaction P = 1.3 × 10–03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

Accurate prediction of disease progression in Alzheimer’s disease (AD) is necessary for optimal recruitment of patients to clinical trials. Here, the authors present AD Course Map, a statistical model which helps to predict disease progression in participants, thus decreasing the required sample size for a hypothetical trial.

Abstract Background Isolated subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are the prodromal phases of dementia with Lewy bodies (DLB). MEMENTO is a nationwide study of patients with SCI and MCI with clinic, neuropsychology, biology, and brain imaging data. We aimed to compare SCI and MCI patients with symptoms of prodromal DLB to others in this study at baseline. Methods Participants of the French MEMENTO cohort study were recruited for either SCI or MCI. Among them, 892 were included in the Lewy sub-study, designed to search specifically for symptoms of DLB. Probable prodromal DLB diagnosis (pro-DLB group) was done using a two-criteria cutoff score among the four core clinical features of DLB. This Pro-DLB group was compared to two other groups at baseline: one without any core symptoms (NS group) and the one with one core symptom (1S group). A comprehensive cognitive battery, questionnaires on behavior, neurovegetative and neurosensory symptoms, brain 3D volumetric MRI, CSF, FDG PET, and amyloid PET were done. Results The pro-DLB group comprised 148 patients (16.6%). This group showed more multidomain (59.8%) MCI with slower processing speed and a higher proportion of patients with depression, anxiety, apathy, constipation, rhinorrhea, sicca syndrome, and photophobia, compared to the NS group. The pro-DLB group had isolated lower P-Tau in the CSF (not significant after adjustments for confounders) and on brain MRI widening of sulci including fronto-insular, occipital, and olfactory sulci (FDR corrected), when compared to the NS group. Evolution to dementia was not different between the three groups over a median follow-up of 2.6 years. Conclusions Patients with symptoms of prodromal DLB are cognitively slower, with more behavioral disorders, autonomic symptoms, and photophobia. The occipital, fronto-insular, and olfactory bulb involvement on brain MRI was consistent with symptoms and known neuropathology. The next step will be to study the clinical, biological, and imaging evolution of these patients. Trial registration Clinicaltrials.gov , NCT01926249

Abstract Background This work aimed to investigate the potential pathways involved in the association between social and lifestyle factors, biomarkers of Alzheimer’s disease and related dementia (ADRD), and cognition. Methods The authors studied 2323 participants from the Memento study, a French nationwide clinical cohort. Social and lifestyle factors were education level, current household incomes, physical activity, leisure activities, and social network from which two continuous latent variables were computed: an early to midlife (EML) and a latelife (LL) indicator. Brain magnetic resonance imaging (MRI), lumbar puncture, and amyloid-positron emission tomography (PET) were used to define three latent variables: neurodegeneration, small vessel disease (SVD), and AD pathology. Cognitive function was defined as the underlying factor of a latent variable with four cognitive tests. Structural equation models were used to evaluate cross-sectional pathways between social and lifestyle factors and cognition. Results Participants’ mean age was 70.9 years old, 62% were women, 28% were apolipoprotein-ε4 carriers, and 59% had a Clinical Dementia Rating (CDR) score of 0.5. Higher early to midlife social indicator was only directly associated with better cognitive function (direct β = 0.364 (0.322; 0.405), with no indirect pathway through ADRD biomarkers (total β = 0.392 (0.351; 0.429)). In addition to a direct effect on cognition (direct β = 0.076 (0.033; 0.118)), the association between latelife lifestyle indicator and cognition was also mostly mediated by an indirect effect through lower neurodegeneration (indirect β = 0.066 (0.042; 0.090) and direct β = − 0.116 (− 0.153; − 0.079)), but not through AD pathology nor SVD. Conclusions Early to midlife social factors are directly associated with higher cognitive functions. Latelife lifestyle factors may help preserve cognitive functions through lower neurodegeneration.

A meta-analysis of genome-wide association studies of circulating total-tau levels identifies loci specific to European or African American ancestries, providing further insight to the genetic etiology of neurological diseases.

IntroductionThe impact of multi-domain preventive interventions on older adults, in particular on those with higher risk to develop Alzheimer's disease (AD), could be beneficial, as it may delay cognitive decline. However, the precise mechanism of such positive impact is not fully understood and may involve brain reserve and adaptability of brain functional connectivity (FC).MethodsTo determine the effect of multidomain interventions (involving physical activity, cognitive training, nutritional counseling alone or in combination with omega-3 fatty acid supplementation and vs. a placebo) on the brain, longitudinal FC changes were assessed after 36 months of intervention on 100 older adults (above 70 year-old) with subjective cognitive complaints.ResultsNo global change in FC was detected after uni or multidomain preventive interventions. However, an effect of omega-3 fatty acid supplementation dependent on cognitive decline status was underlined for frontoparietal, salience, visual and sensorimotor networks FC. These findings were independent of the cortical thickness and vascular burden.DiscussionThese results emphasize the importance of patient stratification, based on risk factors, for preventive interventions.

Known genetic loci account for only a fraction of the genetic contribution to Alzheimer’s disease. Here, the authors have performed a large genome-wide meta-analysis comprising 409,435 individuals to discover 6 new loci and demonstrate the efficacy of an Alzheimer’s disease polygenic risk score.

OBJECTIVES:. Studies comparing outcomes of ICU patients admitted for either COVID-19 or seasonal influenza are limited. Our objective was to describe baseline clinical profiles, care procedures, and mortality outcomes by infection status (influenza vs COVID-19) of patients who received invasive mechanical ventilation in the ICU. DESIGN:. Retrospective observational study. SETTING:. Data were extracted from the Assistance Publique—Hopitaux de Paris database from September 1, 2016, to April 20, 2021. It includes data from the 39 university hospitals. PATIENTS:. A total of 752 influenza adult patients and 3,465 COVID-19 adult patients received invasive mechanical ventilation in one of the ICUs of the Paris area university hospitals, France. INTERVENTION:. The characteristics and outcome by infection status were compared. Factors associated with mortality were assessed using Cox proportional hazard models after controlling for potential confounders, including infection status. MEASUREMENTS AND MAIN RESULTS:. The median age at admission to the ICU was 67 (interquartile range [IQR], 57–77) and 63 yr (IQR, 54–71 yr) for influenza and COVID-19 patients, respectively. At ICU admission, COVID-19 patients were more frequently obese, more frequently had diabetes mellitus or high blood pressure, and were less likely to have chronic heart failure, chronic respiratory disease, chronic kidney failure, or active cancer than influenza patients. The overall survival at 90 days was 57% for COVID-19 patients and 66% for influenza patients (p < 0.001). In a multivariable Cox model, higher age, organ transplant, severe acute respiratory syndrome coronavirus 2 infection, and chronic kidney failure were associated with shorter survival, whereas obesity and high blood pressure were associated with longer survival after invasive ventilation. CONCLUSIONS:. COVID-19 and influenza patients requiring mechanical ventilation in the ICU differed by many characteristics. COVID-19 patients showed lower survival independently of potential confounders.

Data on 2,045 non-demented individuals with memory complaints were drawn from the Memento cohort study to examine the association between Apolipoprotein E ε4 allele (APOE4) and regional brain gray matter volumes. Linear regression was used to examine the association of APOE4 and measures of regional gray matter volumes in cross-sectional analysis and change therein using longitudinal analyses based on two brain MRI performed at baseline and at two-year follow-up. Overall, in analyses adjusted for age, sex, and intracranial volume, the presence of APOE4 was associated with lower total gray matter volume at baseline and with a higher atrophy rate over the follow-up. The hippocampus and entorhinal cortex were the two gray matter regions most associated with APOE4. Further adjustment for cardiovascular risk factors had little impact on these associations. There was an interaction between age, APOE4 status and total brain volume atrophy rate, with evidence of an earlier age at onset of atrophy in hippocampal volume in APOE4 carriers compared to non-carriers. Those results are in accordance with the role of medial temporal structures in the greater risk of dementia observed in people carrying the APOE4 allele.

Summary: Background: The identification of modifiable risk factors for Alzheimer's disease is paramount for early prevention and the targeting of new interventions. We aimed to assess the associations between health conditions diagnosed in primary care and the risk of incident Alzheimer's disease over time, up to 15 years before a first Alzheimer's disease diagnosis. Methods: In this agnostic study of French and British health records, data from 20 214 patients with Alzheimer's disease in the UK and 19 458 patients with Alzheimer's disease in France were extracted from The Health Improvement Network database. We considered data recorded from Jan 1, 1996, to March 31, 2020 in the UK and from Jan 4, 1998, to Feb 20, 2019, in France. For each Alzheimer's disease case, a control was randomly assigned after matching for sex and age at last visit. We agnostically tested the associations between 123 different diagnoses of the International Classification of Diseases, 10th revision, extracted from health records, and Alzheimer's disease, by running a conditional logistic regression to account for matching of cases and controls. We focused on three time periods before diagnosis of Alzheimer's disease, to separate risk factors from early symptoms and comorbidities. Findings: Unadjusted odds ratios (ORs) and 95% CIs for the association between Alzheimer's disease and various health conditions were estimated, and p values were corrected for multiple comparisons. In both the British and French studies, ten health conditions were significantly positively associated with increased Alzheimer's disease risk, in a window of exposure from 2–10 years before Alzheimer's disease diagnosis, comprising major depressive disorder (UK OR 1·34, 95% CI 1·23–1·46; France OR 1·73, 1·57–1·91), anxiety (UK OR 1·36, 1·25–1·47; France OR 1·50, 1·36–1·65), reaction to severe stress and adjustment disorders (UK OR 1·40, 1·24–1·59; France OR 1·83, 1·55–2·15), hearing loss (UK OR 1·19, 1·11–1·28; France OR 1·51, 1·21–1·89), constipation (UK OR 1·31, 1·22–1·41; France OR 1·59, 1·44–1·75), spondylosis (UK OR 1·26, 1·14–1·39; France OR 1·62, 1·44–1·81), abnormal weight loss (UK OR 1·47, 1·33–1·63; France OR 1·88, 1·56–2·26), malaise and fatigue (UK OR 1·23, 1·14–1·32; France OR 1·59, 1·46–1·73), memory loss (UK OR 7·63, 6·65–8·76; France OR 4·41, 3·07–6·34), and syncope and collapse (UK OR 1·23, 1·10–1·37; France OR 1·57, 1·26–1·96). Depression was the first comorbid condition associated with Alzheimer's disease, appearing at least 9 years before the first clinical diagnosis, followed by anxiety, constipation, and abnormal weight loss. Interpretation: These results from two independent primary care databases provide new evidence on the temporality of risk factors and early signs of Alzheimer's disease that are observable at the general practitioner level. These results could guide the implementation of new primary and secondary prevention policies. Funding: Agence Nationale de la Recherche.

Objective Describe demographical, social and psychological correlates of willingness to receive a COVID-19 vaccine.Setting Series of online surveys undertaken between March and October 2020.Participants A total of 25 separate national samples (matched to country population by age and sex) in 12 different countries were recruited through online panel providers (n=25 334).Primary outcome measures Reported willingness to receive a COVID-19 vaccination.Results Reported willingness to receive a vaccine varied widely across samples, ranging from 63% to 88%. Multivariate logistic regression analyses reveal sex (female OR=0.59, 95% CI 0.55 to 0.64), trust in medical and scientific experts (OR=1.28, 95% CI 1.22 to 1.34) and worry about the COVID-19 virus (OR=1.47, 95% CI 1.41 to 1.53) as the strongest correlates of stated vaccine acceptance considering pooled data and the most consistent correlates across countries. In a subset of UK samples, we show that these effects are robust after controlling for attitudes towards vaccination in general.Conclusions Our results indicate that the burden of trust largely rests on the shoulders of the scientific and medical community, with implications for how future COVID-19 vaccination information should be communicated to maximise uptake.

Abstract Background Socioeconomic level of residential environment was found to influence cognitive performance. However, individuals from the same place of residence may be affected differently. We aim to investigate for the first time the influence of individual activity space on the association between neighborhood socioeconomic status (NSES) and the risk of dementia. Methods In the frame of the Three-City cohort, a French population-based study, we followed longitudinally (12 years) 7009 participants aged over 65. The activity space (i.e., the spatial area through which a person moves daily) was defined using two questions from Lawton’s Instrumental Activities of Daily Living scale (“Goes shopping independently”,“Travels alone”), and one question about mobility restriction. The survival analysis was performed using a Cox marginal model that takes into account intra-neighborhood correlations and includes a large number of potential confounders. Results Among people with a limited activity space (n = 772, 11%), risk of dementia is increased in subjects living in a deprived area (characterized by high GINI index or low median income) compared to those living in more favored. Conclusion This study shows that the individual activity space modifies the association between NSES and the risk of dementia providing a more complete picture of residential inequalities. If confirmed in different populations, these findings suggest that people with limited activity space and living in a deprived neighborhood are particularly at risk and should be targeted for prevention.

Abstract Background The natural history and disease mechanisms of Alzheimer’s disease and related disorders (ADRD) are still poorly understood. Very few resources are available to scrutinise patients as early as needed and to use integrative approaches combining standardised, repeated clinical investigations and cutting-edge biomarker measurements. Methods In the nationwide French MEMENTO cohort study, participants were recruited in memory clinics and screened for either isolated subjective cognitive complaints (SCCs) or mild cognitive impairment (MCI; defined as test performance 1.5 SD below age, sex and education-level norms) while not demented (Clinical Dementia Rating [CDR]

Abstract Introduction Subjective cognitive complaints may be a signature of preclinical stage Alzheimer's disease. However, the link between subjective cognitive and non‐cognitive complaints and brain alterations remains unclear. Methods The relationship between cognitive and non‐cognitive complaints and brain biomarkers, measured by structural magnetic resonance imaging, was investigated in 2056 participants of the MEMENTO cohort of outpatients, who were dementia‐free at baseline. We assessed whether the cognitive status at inclusion or the presence of the apolipoprotein E gene variant (APOE) ε4 could modulate the association between the intensity of complaints and brain lesions. Results Smaller hippocampal volume was associated with higher memory complaints and discomfort in daily life. In APOE ε4 carriers, smaller whole‐brain white matter and gray matter volumes and gyrification indices in several regions of interest of the parietal and temporal lobes, in the entorhinal and the para‐hippocampal gyrus, were associated with higher memory complaint score. Conclusions The intensity of subjective complaints in not only memory but discomfort in daily life was associated with brain degeneration markers. The presence of APOE ε4 modulated the relationships between subjective memory complaints and brain alterations.

Abstract Objective To assess progression of semantic loss in early stages of cognitive decline using semantic and letter fluency performance, and its relation with Alzheimer's disease (AD)‐specific neurodegeneration using longitudinal multimodal neuroimaging measures. Methods Change in verbal fluency was analyzed among 2261 non‐demented individuals with a follow‐up diagnosis of no mild cognitive impairment (MCI), amnestic MCI (aMCI), non‐amnestic MCI (naMCI), or incident dementia, using linear mixed models across 4 years of follow‐up, and relations with magnetic resonance imaging (MRI; n = 1536) and 18F‐fluorodeoxyglucose brain positron emission tomography (18F‐FDG‐PET) imaging (n = 756) using linear regression models across 2 years of follow‐up. Results Semantic fluency declined—fastest in those at higher risk for AD (apolipoprotein E [APOE] e4 carriers, Clinical Dementia Rating score of .5, aMCI, or incident dementia)—while letter fluency did not except for those with incident dementia. Lower baseline semantic fluency was associated with an increase in white matter hyperintensities and total mean cortical thinning over time, and regionally with less hippocampal volume as well as more cortical thinning and reduced 18F‐FDG‐PET uptake in the inferior parietal lobule, entorhinal cortex, isthmus cingulate, and precuneus–posterior cingulate area. In contrast, baseline letter fluency was not associated with change in total nor regional neurodegeneration. Whole‐brain neurodegeneration over time was associated with faster decline in both fluencies, while AD‐specific regions were associated with a faster rate of decline in semantic but not letter fluency. Interpretation This study provides strong evidence of distinctive degeneration of semantic abilities early on in relation to both cognitive decline and AD‐specific neurodegeneration.

Introduction/purpose: In vivo detection of cerebral microbleeds (CMBs) from T2* gradient recalled echo (GRE) magnitude image suffers from low specificity, modest inter-rater reproducibility and is biased by its sensitivity to acquisition parameters. New methods were proposed for improving this identification, but they mostly rely on 3D acquisitions, not always feasible in clinical practice. A fast 2D phase processing technique for computing internal field maps (IFM) has been shown to make it possible to characterize CMBs through their magnetic signature in routine clinical setting, based on 2D multi-slice acquisitions. However, its clinical interest for CMBs identification with respect to more common images remained to be assessed. To do so, systematic experiments were undertaken to compare the ratings obtained by trained observers with several image types, T2* magnitude, Susceptibility Weighted Imaging reconstructions (SWI) and IFM built from the same T2*-weighted acquisition. Materials/methods: 15 participants from the MEMENTO multi-center cohort were selected: six subjects with numerous CMBs (20 ± 6 CMBs), five subjects with a few CMBs (2 ± 1 CMBs) and four subjects without CMB. 2D multi-slice T2* GRE sequences were acquired on Philips and Siemens 3T systems. After pilot experiments, T2* magnitude, Susceptibility Weighted Imaging (SWI) minimum intensity projection (mIP) on three slices and IFM were considered for the rating experiments. A graphical user interface (GUI) was designed in order to consistently display images in random order. Six raters of various background and expertise independently selected “definite” or “possible” CMBs. Rating results were compared with respect to a specific consensus reference, on both lesion and subject type points of view. Results: IFM yielded increased sensitivity and decreased false positives rate (FPR) for CMBs identification compared to T2* magnitude and SWI-mIP images. Inter-rater variability was decreased with IFM when identifying subjects with numerous lesions, with only a limited increase in rating time. IFM thus appears as an interesting candidate to improve CMBs identification in clinical setting. Keywords: Microbleeds, Magnetic susceptibility, Phase MRI, SWI

Background: Dementia is a prevalent condition, affecting 5–7% of people aged 60 years and older, and a leading cause of disability in people aged 60 years and older globally. We aimed to examine the association between alcohol use disorders and dementia risk, with an emphasis on early-onset dementia (1·7) in sensitivity analyses on dementia case definition (including Alzheimer's disease) or older study populations. Also, alcohol use disorders were significantly associated with all other risk factors for dementia onset (all p

BACKGROUND:Vascular risk factors have been proposed as important targets for the prevention of dementia. As lipid fractions represent easily modifiable targets, we examined the longitudinal relationship of baseline lipid fractions with 13-y incident dementia and its subtypes (Alzheimer disease [AD] and mixed or vascular dementia) in older community-dwelling persons. METHODS AND FINDINGS:Non-institutionalized persons aged 65+ y (n = 9,294) were recruited for the Three-City Study (3C Study), a population-based cohort study from the electoral rolls of the cities of Dijon, Bordeaux, and Montpellier, France, between March 1999 and March 2001. Follow-up examinations were performed every 2 y after the baseline assessment. The final study sample comprised 7,470 participants from the 3C Study (mean age ± standard deviation [SD] 73.8 ± 5.3 y, 61.0% women) who were prospectively followed up for up to 13 y. Fasting lipid fractions (triglycerides [TGs], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], total cholesterol [TC]) were studied as continuous variables, and results are reported per SD increase of each lipid fraction. Incident dementia and its subtypes were studied as censored variables using Cox models with age as time scale. Analyses were adjusted for sex, study center, and educational level, as well as vascular risk factors and apolipoprotein E (APOE) ε4 genotype. We corrected for multiple testing, yielding a significance threshold of 0.0169. p-Values above the significance threshold but less than 0.05 were considered nominally significant. During a mean (± SD) follow-up period of 7.9 ± 3.6 y, 779 participants developed incident dementia (n = 532 AD and n = 154 mixed or vascular dementia). Higher LDL-C and TC concentrations at baseline were associated with an increased risk of AD (hazard ratio [HR] per SD increase = 1.13 [95% CI 1.04-1.22], p = 0.0045, and HR = 1.12 [1.03-1.22], p = 0.0072, respectively). These associations were largely unchanged after adjustment for vascular risk factors and were attenuated after adjustment for APOEε4 (HR per SD increase = 1.12 [1.03-1.23], p = 0.0110, and HR = 1.12 [1.02-1.23], p = 0.0171, respectively). Higher TG concentrations at baseline were associated with an increased risk of all dementia (HR per SD increase = 1.11 [1.03-1.19], p = 0.0044) and mixed or vascular dementia (HR = 1.21 [1.04-1.41], p = 0.0163). However, these associations disappeared after adjusting for vascular risk factors (HR = 1.07 [0.98-1.17], p = 0.1374, and HR = 1.17 [0.96-1.42], p = 0.1206, respectively). Main limitations of the study include interval censoring of incident dementia cases, potential selective survival bias, and the fact that variation in lipid concentrations during follow-up could not be accounted for in the analyses. CONCLUSIONS:In a large population-based sample of older community-dwelling persons with up to 13 y of follow-up, we observed that higher LDL-C and TC concentrations were associated with an increased risk of AD. This result was independent of vascular risk factors and was attenuated after adjustment for APOEε4 carrier status. TG and HDL-C concentrations were not associated with risk of incident dementia or its subtypes after accounting for vascular risk factors.

Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance.Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included.In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model.There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.