Susanna Schraen-Maschke

INTRODUCTION: We investigated the link between habitual caffeine intake with memory impairments and cerebrospinal fluid (CSF) biomarkers in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients.METHODS: MCI (N = 147) and AD (N = 116) patients of the Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk (BALTAZAR) cohort reported their caffeine intake at inclusion using a dedicated survey. Associations of caffeine consumption with memory impairments and CSF biomarkers (tau, p‐tau181, amyloid beta 1‐42 [Aβ_1‐42], Aβ_1‐40) were analyzed using logistic and analysis of covariance models.RESULTS: Adjusted on Apolipoprotein E (APOE ε4), age, sex, education level, and tobacco, lower caffeine consumption was associated with higher risk to be amnestic (OR: 2.49 [95% CI: 1.13 to 5.46]; p = 0.023) and lower CSF Aβ_1‐42 (p = 0.047), Aβ_1‐42/Aβ_1‐40 (p = 0.040), and Aβ_1‐42/p‐tau181 (p = 0.020) in the whole cohort.DISCUSSION: Data support the beneficial effect of caffeine consumption to memory impairments and CSF amyloid markers in MCI and AD patients.Highlights: We studied the impact of caffeine consumption in the BALTAZAR cohort. Low caffeine intake is associated with higher risk of being amnestic in MCI/AD patients. Caffeine intake is associated with CSF biomarkers in AD patients.

STRUCTURED INTRODUCTION: We investigated the link between habitual caffeine intake with memory deficits and CSF AD biomarkers in Mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) patients. METHODS: MCI (N=147) and AD (N=116) patients of the BALTAZAR longitudinal cohort reported their caffeine intake using a dedicated survey and were followed-up for 3 years. Associations of caffeine consumption with cognition, MMSE decline and CSF biomarkers (Tau, pTau181, Aβ _1-42 , Aβ _1-40 ) were analyzed using logistic and ANCOVA models. RESULTS: Adjusted on APOEε4, age, sex, education level and tobacco, lower caffeine consumption was associated with higher risk to be amnestic (OR: 2.49 [95%CI: 1.13 to 5.46]; p=0.023) and lower CSF Aβ _1-42 (p=0.047), Aβ _1-42 / Aβ _1-40 (p=0.040) and Aβ _1-42 /pTau (p=0.020) in the whole cohort and a faster MMSE decline in amnestic MCI (p=0.024). DISCUSSION: Data supports the beneficial effect of caffeine consumption to memory decline and CSF amyloid markers in MCI and AD patients.

Neurofilament light chain (NfL) is a potential diagnostic and prognostic plasma biomarker for numerous neurological diseases including Alzheimer’s disease (AD). In this study, we investigated the relationship between baseline plasma concentration of Nfl and Mild Cognitive Impairment in participants who did and did not have a clinically determined diagnosis of dementia by the end of the three-year study. Additionally, we explored the connection between baseline plasma concentration of NfL and AD dementia patients, considering their demographics, clinical features, and cognitive profiles. A total of 350 participants from the Biomarker of AmyLoid pepTide and AlZheimer’s diseAse Risk (BALTAZAR) multicenter prospective study were investigated: 161 AD dementia participants and 189 MCI participants (of which 141 had amnestic MCI and 48 non-amnestic MCI). Plasma biomarkers were measured at baseline and the progression of clinical and cognitive profiles was followed over the three years of follow-up. Baseline plasma NfL concentration increased across the Alzheimer’s disease continuum with a mean NfL value of 17.1 ng/mL [SD = 6.1] in non-amnestic MCI, 20.7 ng/mL [SD = 12.0] in amnestic MCI, and 23.1 ng/mL [SD = 22.7] in AD dementia patients. Plasma NfL concentration correlated with age, body mass index (BMI), and global cognitive performance and decline, as measured by the Mini-Mental State Examination (MMSE). MMSE scores decreased in parallel with increasing plasma NfL concentration, independently of age and BMI. However, NfL concentration did not predict MCI participants’ conversion to dementia within three years. Discussion: Baseline plasma NfL concentration is associated with cognitive status along the AD continuum, suggesting its usefulness as a potential informative biomarker for cognitive decline follow-up in patients.

Background and Objectives To elaborate a new algorithm to establish a standardized method to define cutoffs for CSF biomarkers of Alzheimer disease (AD) by validating the algorithm against CSF classification derived from PET imaging. Methods Low and high levels of CSF phosphorylated tau were first identified to establish optimal cutoffs for CSF β-amyloid (Aβ) peptide biomarkers. These Aβ cutoffs were then used to determine cutoffs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients. Results A total of 6,922 patients with CSF biomarker data were included (mean [SD] age: 70.6 [8.5] years, 51.0% women). In the ADNI study population (n = 497), the agreement between classification based on our algorithm and the one based on amyloid/tau PET imaging was high, with Cohen9s kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n = 6,425), the proportion of persons with AD ranged from 25.9% to 43.5%. Discussion The proposed novel, pragmatic method to determine CSF biomarker cutoffs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.

One can reasonably suppose that cerebrospinal spinal fluid (CSF) biomarkers can identify distinct subgroups of Alzheimer’s disease (AD) patients. In order to better understand differences in CSF biomarker patterns, we used FDG PET to assess cerebral metabolism in CSF-based subgroups of AD patients.

Background: Few patients with a normal cerebrospinal fluid (CSF) biomarker profile fulfill the clinical criteria for Alzheimer disease (AD). Objective: The aim of this study was to test the hypothesis of misdiagnoses for these patients. Method: Patients from the e-PLM centers fulfilling the core clinical criteria for probable AD dementia or mild cognitive impairment due to AD (AD-MCI), with normal CSF Aβ1-42, T-tau and P-tau biomarkers and clinical follow-up, were included. Clinical and imaging data were reviewed by an independent board, from baseline (visit with clinical evaluation and CSF analysis) to the end of the follow-up, for a final diagnosis. Results: In the e-PLM cohort of 1098 AD patients with CSF analysis, 37 (3.3%) patients (20 with AD dementia core clinical criteria and 17 with AD-MCI core clinical criteria) had normal CSF biomarker profile and a clinical follow-up. All patients presented with episodic memory impairment and 27 (73%) had medial temporal lobe atrophy on MRI-scan. After a median follow-up of 36 months (range 7-74), the final diagnosis was AD MCI or dementia for 9 (24%) patients, and unlikely due to AD for 28 (76%) patients. A misdiagnosis was corrected in 18 (49%) patients (mood disorders, non-AD degenerative dementia, vascular cognitive impairment, alcohol cognitive disorders, temporal epilepsy and hippocampal sclerosis), and 10 (27%) patients had cognitive disorders of undetermined etiology. Conclusion: AD diagnosis (MCI or dementia) with normal CSF biomarkers is a rare condition. A clinical follow- up is particularly recommended to consider an alternative diagnosis.

The diagnostic accuracy of hexamethylpropyleneamine oxime (HMPAo) single-photon emission computed tomography (SPECT) in Alzheimer disease (AD) remains undetermined in a real-life clinical population. The objective was to determine the HMPAo SPECT hypoperfusion pattern in cognitively impaired patients with positive CSF AD biomarker and to evaluate its diagnostic accuracy. This study included 120 patients referred to a university memory clinic assessed using HMPAo SPECT, MRI, and CSF biomarkers. Three biomarker signatures suggestive of AD were analyzed (1, A ss 1-42; 2, A ss 1-42+t-tau and/or p-tau; 3, A ss 1-42/p-tau). The clinical diagnoses were possible AD (n=29) or other causes of cognitive impairment (n=91). All CSF AD signatures were significantly (1, P=0.004; 2, P=0.017; 3, P=0.024) associated with the difference between inferior parietal perfusion and lateral dorsal frontal cortex perfusion. The hypoperfusion pattern discriminated between patients with positive CSF AD biomarkers and those with other cognitive impairments with a sensitivity of 67% to 71% and a specificity of 63% to 65% and a greatest negative predictive value (NPV) of 90%. Inferior parietal cortex hypoperfusion was the most sensitive and specific feature in AD patients diagnosed using clinical and CSF biomarker criteria. This hypoperfusion pattern was associated with an NPV of 90% and therefore discriminated sharply between AD and other cognitive disorders.

Background: Differential diagnosis between dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) is not straightforward, especially in the early stages of disease. We compared AD biomarkers (phospho-Tau₁₈₁, total-Tau, Aβ42 and Aβ40) in cerebrospinal fluid (CSF) of patients with DLB and AD, focusing especially on the prodromal stage.Methods: A total of 1221 CSF were collected in different memory centres (ePLM network) in France and analysed retrospectively. Samples were obtained from patients with prodromal DLB (pro-DLB; n=57), DLB dementia (DLB-d; n=154), prodromal AD (pro-AD; n=132) and AD dementia (n=783), and control subjects (CS; n=95). These centres use the same diagnostic procedure and criteria to evaluate the patients.Results: In patients with pro-DLB, CSF Aβ42 levels appeared much less disrupted than in patients at the demented stage (DLB-d) (Ppro-DLB; PDLB-d). On average, Aβ40 levels in patients with DLB (pro-DLB and DLB-d) were much below those in patients with pro-AD (P181 levels were unaltered in patients with DLB (pro-DLB and DLB-d).Conclusions: Reduced levels of CSF Aβ42 were found in patients with DLB but rather at a later stage, reaching those of patients with AD, in whom Aβ42 levels were decreased even at the prodromal stage. At the prodromal stage of DLB, the majority of patients presented a normal CSF profile. CSF t-Tau and phospho-Tau₁₈₁ were the best biomarkers to discriminate between AD and DLB, whatever the stage of disease.