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Background: Cerebrospinal fluid (CSF) biomarkers (Aβ peptides and tau proteins) improved the diagnosis of Alzheimer’s disease (AD) in research and clinical settings. We previously described the PLM-scale (Paris-Lille-Montpellier study), which combines Aβ42, tau, and phosphorylated ptau(181) biomarkers in an easy to use and clinically relevant way. The purpose of this work is to evaluate an optimized PLMR-scale (PLM ratio scale) that now includes the Aβ42/Aβ40 ratio to detect AD versus non-AD (NAD) participants in clinical routine of memory centers.Methods: Both scales were compared using 904 participants with cognitive impairment recruited from two independent cohorts (Mtp-1 and Mtp-2). The CSF Aβ42/Aβ40 ratio was measured systematically in Mtp-1, and only on biologically discordant cases in Mtp-2. Two different ELISA kit providers were also employed. The distribution of AD and NAD patients and the discrepancies of biomarker profiles were computed. Receiver Operating Characteristic curves were used to represent clinical sensitivity and specificity for AD detection. The classification of patients with the net reclassification index (NRI) was also evaluated.Results: Nine hundred and four participants (342 AD and 562 NAD) were studied; 400 in Mtp-1 and 504 in Mtp-2. For AD patients, the mean CSF Aβ42 and CSF Aβ42/40 ratio was 553 ± 216 pg/mL and 0.069 ± 0.022 pg/mL in Mtp-1 and 702 ± 335 pg/mL and 0.045 ± 0.020 pg/mL in Mtp-2. The distribution of AD and NAD differed between the PLM and the PLMR scales (p < 0.0001). The percentage AD well-classified (class 3) increased with PLMR from 38 to 83% in Mpt-1 and from 33 to 53% in Mpt-2. A sharp reduction of the discordant profiles going from 34 to 16.3% and from 37.5 to 19.8%, for Mtp-1 and Mtp-2 respectively, was also observed. The AUC of the PLMR scale was 0.94 in Mtp-1 and 0.87 in Mtp-2. In both cohorts, the PLMR outperformed CSF Aβ42 or Aβ42/40 ratio. The diagnostic performance was improved with the PLMR with an NRI equal to 44.3% in Mtp-1 and 28.8% in Mtp-2.Conclusion: The integration of the Aβ42/Aβ40 ratio in the PLMR scale resulted in an easy-to-use tool which reduced the discrepancies in biologically doubtful cases and increased the confidence in the diagnosis in memory center.

Background: Suicide rates are high among older adults and many conditions have been related to suicide in this population: chronic illnesses, physical disabilities, cancer, social isolation, mental disorders and neurocognitive disorders.Objectives: Among neurocognitive disorders, analysis of the relationships between dementia and suicidal behaviors led to conflicting results and some questions are still without answer. Particularly, it is not known whether (i) Alzheimer's disease (AD) increases the risk of suicidal ideation and suicide attempts (SA) or the frequency of death by suicide; (ii) the presence of suicidal ideation or SA in people older than 65 years of age is an early dementia sign; and (iii) amyloid load in frontal areas facilitates SA by modifying the decision-making pathway.Methods: Therefore, in this narrative review, we searched the PubMed database using the medical subject heading (MeSH) terms (“Suicide” AND “Depression”) OR (“Amyloid” OR “Dementia”) to identify recent (from 2000 to 2017) original studies on the links between suicidal behavior, dementia and brain amyloid load. We also explored the clinical and pathophysiological role of depression in these relationships.Results and Discussion: The findings from these studies suggest that late stage dementia could protect against suicidal ideation and SA. Conversely, the risk of complete suicide is increased during the early phase of cognitive decline.Conclusions: Serious cognitive impairment and decline of executive functions could protect against negative thoughts related to cognitive disability awareness and against suicide planning.Several factors, including brain amyloid load, could be involved in the increased suicide rate early after the diagnosis of dementia.

Objective: To determine the relationships between self-reported sleep profile and cortical amyloid load in elderly subjects without dementia.Methods: This cross-sectional study included 143 community-dwelling participants aged ≥70 years (median: 73 years [70–85]; 87 females) with spontaneous memory complaints but dementia-free. Sociodemographic characteristics, health status, neuropsychological tests, sleep, and 18F-florbetapir (amyloid) PET data were collected. The clinical sleep interview evaluated nighttime sleep duration, but also daytime sleep duration, presence of naps, and restless leg syndrome (RLS) at time of study. Validated questionnaires assessed daytime sleepiness, insomnia, and risk of sleep apnea. The cortical standardized uptake value ratio (SUVr) was computed across six cortical regions. The relationship between sleep parameters and SUVr (cut-off ratio>1.17 and tertiles) was analyzed using logistic regression models.Results: Amyloid-PET was positive in 40.6% of participants. Almost 40% were at risk for apnea, 13.5% had RLS, 35.5% insomnia symptoms, 22.1% daytime sleepiness, and 18.8% took sleep drugs. No significant relationship was found between positive amyloid PET and nighttime sleep duration (as a continuous variable, or categorized into <6; 6–7; ≥7 h per night). Logistic regression models did not show any association between SUVr and daytime sleep duration, 24-h sleep duration, naps, RLS, daytime sleepiness, insomnia symptoms, and sleep apnea risk (before and after adjustment for APOEε4 and depressive symptoms).Conclusion: Our study did not confirm the association between amyloid-PET burden, poor sleep quantity/quality in elderly population, suggesting that the interplay between sleep, and amyloid is more complex than described.

Objective: To identify self-reported sleep-wake disturbances that increase the risk of cognitive decline over 1-year follow-up in frail participants.Background: Risk factors for cognitive impairment need to be better identified especially at earliest stages of the pathogenesis. Sleep-wake disturbances may be critical factors to consider and were thus being assessed in this at-risk population for cognitive decline.Methods: Frail elderly participants aged ≥70 years were selected from a subsample of the Multi-domain Alzheimer Preventive Trial (MAPT) for a sleep assessment (MAPT-sleep study) at 18-month follow-up (M18). Sleep-wake disturbances were evaluated using a clinical interview (duration of daytime and nighttime sleep, time in bed, number of naps, and presence of clinically-defined sleep disorders) and numerous validated questionnaires [Epworth Sleepiness Scale for excessive daytime sleepiness (EDS), Insomnia Severity Scale and Berlin Questionnaire]. Cognitive decline was defined as a difference between the MMSE and cognitive composite scores at M24 and M36 that was ranked in the lowest decile. Multivariate logistic regression models adjusted for several potential confounding factors were performed.Results: Among the 479 frail participants, 63 developed MMSE-cognitive decline and 50 cognitive composite score decrease between M24 and M36. Subjects with EDS had an increased risk of MMSE decline (OR = 2.46; 95% CI [1.28; 4.71], p = 0.007). A longer time spent in bed during night was associated with cognitive composite score decline (OR = 1.32 [1.03; 1.71], p = 0.03). These associations persisted when controlling for potential confounders. Patients with MMSE score decline and EDS had more naps, clinically-defined REM-sleep Behavior Disorder, fatigue and insomnia symptoms, while patients with cognitive composite score decline with longer time in bed had increased 24-h total sleep time duration but with higher wake time after onset.Conclusions: The risk of cognitive decline is higher in frailty subjects with EDS and longer nighttime in bed. Early detection of sleep-wake disturbances might help identifying frail subjects at risk of cognitive decline to further propose sleep health strategies to prevent cognitive impairment.http://www.clinicaltrials.gov NCT00672685; Date of registration May, 2nd 2008.

Background: Memory troubles and hippocampal atrophy are considered more frequent and focal atrophy less severe in late-onset (>65 years) than in presenile behavioral variant frontotemporal dementia (bvFTD).

Primary Sjögren’s syndrome (pSS) is an autoimmune disease with frequent neurological involvement. Memory complaints are common, but their precise patterns remain unclear. We wanted to characterize patterns of neurocognitive profiles in pSS patients with cognitive complaints. Only pSS patients with memory complaints were included, prospectively. Cognitive profiles were compiled through a comprehensive cognitive evaluation by neuropsychologists. Evaluations of anxiety, depression, fatigue, sleep disorders and quality of life were performed for testing their interactions with cognitive profiles. All 32 pSS patients showed at least borderline cognitive impairment, and 17 (53%) exhibited a pathological cognitive profile: a hippocampal profile (37%), a dysexecutive profile (22%), and an instrumental profile (16%) (possible overlap). Regarding the secondary objectives: 37% of patients were depressed, and 48% exhibited a mild-to-severe anxiety trait. Sleep disorders were frequent (excessive daytime sleepiness (55%), high risk for sleep apnea (45%), and insomnia (77%)). Cognitive impairments could not be explained alone by anxiety, depression or sleep disorders. Fatigue level was strongly associated with sleep disorders. Our study highlights that cognitive complaints in pSS patients are supported by measurable cognitive impairments, apart from frequently associated disorders such as depression, anxiety or sleep troubles. Sleep disorders should be screened.

Background Alzheimer’s disease (AD) is a complex neurodegenerative disorder with β-amyloid pathology as a key underlying process. The relevance of cerebrospinal fluid (CSF) and brain imaging biomarkers is validated in clinical practice for early diagnosis. Yet, their cost and perceived invasiveness are a limitation for large-scale implementation. Based on positive amyloid profiles, blood-based biomarkers should allow to detect people at risk for AD and to monitor patients under therapeutics strategies. Thanks to the recent development of innovative proteomic tools, the sensibility and specificity of blood biomarkers have been considerably improved. However, their diagnosis and prognosis relevance for daily clinical practice is still incomplete. Methods The Plasmaboost study included 184 participants from the Montpellier’s hospital NeuroCognition Biobank with AD (n = 73), mild cognitive impairments (MCI) (n = 32), subjective cognitive impairments (SCI) (n = 12), other neurodegenerative diseases (NDD) (n = 31), and other neurological disorders (OND) (n = 36). Dosage of β-amyloid biomarkers was performed on plasma samples using immunoprecipitation-mass spectrometry (IPMS) developed by Shimadzu (IPMS-Shim Aβ42, Aβ40, APP669–711) and Simoa Human Neurology 3-PLEX A assay (Aβ42, Aβ40, t-tau). Links between those biomarkers and demographical and clinical data and CSF AD biomarkers were investigated. Performances of the two technologies to discriminate clinically or biologically based (using the AT(N) framework) diagnosis of AD were compared using receiver operating characteristic (ROC) analyses. Results The amyloid IPMS-Shim composite biomarker (combining APP669–711/Aβ42 and Aβ40/Aβ42 ratios) discriminated AD from SCI (AUC: 0.91), OND (0.89), and NDD (0.81). The IPMS-Shim Aβ42/40 ratio also discriminated AD from MCI (0.78). IPMS-Shim biomarkers have similar relevance to discriminate between amyloid-positive and amyloid-negative individuals (0.73 and 0.76 respectively) and A−T−N−/A+T+N+ profiles (0.83 and 0.85). Performances of the Simoa 3-PLEX Aβ42/40 ratio were more modest. Pilot longitudinal analysis on the progression of plasma biomarkers indicates that IPMS-Shim can detect the decrease in plasma Aβ42 that is specific to AD patients. Conclusions Our study confirms the potential usefulness of amyloid plasma biomarkers, especially the IPMS-Shim technology, as a screening tool for early AD patients.