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Background: Metagenomic data support an association between certain bacterial strains and Alzheimer’s disease (AD), but their functional dynamics remain elusive. Objective: To investigate the association between amyloid pathology, bacterial products such as lipopolysaccharide (LPS) and short chain fatty acids (SCFAs: acetate, valerate, butyrate), inflammatory mediators, and markers of endothelial dysfunction in AD. Methods: Eighty-nine older persons with cognitive performance from normal to dementia underwent florbetapir amyloid PET and blood collection. Brain amyloidosis was measured with standardized uptake value ratio versus cerebellum. Blood levels of LPS were measured by ELISA, SCFAs by mass spectrometry, cytokines by using real-time PCR, and biomarkers of endothelial dysfunction by flow cytometry. We investigated the association between the variables listed above with Spearman’s rank test. Results: Amyloid SUVR uptake was positively associated with blood LPS (rho ≥ 0.32, p ≤ 0.006), acetate and valerate (rho ≥ 0.45, p < 0.001), pro-inflammatory cytokines (rho ≥ 0.25, p ≤ 0.012), and biomarkers of endothelial dysfunction (rho ≥ 0.25, p ≤ 0.042). In contrast, it was negatively correlated with butyrate (rho ≤ –0.42, p ≤ 0.020) and the anti-inflammatory cytokine IL10 (rho ≤ −0.26, p ≤ 0.009). Endothelial dysfunction was positively associated with pro-inflammatory cytokines, acetate and valerate(rho ≥ 0.25, p ≤ 0.045)and negatively with butyrate and IL10 levels (rho ≤ −0.25, p ≤ 0.038). Conclusion: We report a novel association between gut microbiota-related products and systemic inflammation with brain amyloidosis via endothelial dysfunction, suggesting that SCFAs and LPS represent candidate pathophysiologic links between the gut microbiota and AD pathology.

Introduction: Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts.Methods: To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives.Results: With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes.Discussion: This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond.

Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test–retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal (“long_T1s” and “long_T1s_FLAIR”) and one cross-sectional (“long_T1s_FLAIR_crossT2”). Volume reproducibility was quantified in magnitude (reproducibility error—RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4–3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1–7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm3 had better RE (1–2%) and DICE (0.7–0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements. Electronic supplementary material The online version of this article (10.1007/s00429-020-02172-w) contains supplementary material, which is available to authorized users.

Background and purpose: Biomarkers support the aetiological diagnosis of neurocognitive disorders in vivo. Incomplete evidence is available to drive clinical decisions; available diagnostic algorithms are generic and not very helpful in clinical practice. The aim was to develop a biomarker-based diagnostic algorithm for mild cognitive impairment patients, leveraging on knowledge from recognized national experts. Methods: With a Delphi procedure, experienced clinicians making variable use of biomarkers in clinical practice and representing five Italian scientific societies (neurology – Società Italiana di Neurologia per le Demenze; neuroradiology – Associazione Italiana di Neuroradiologia; biochemistry – Società Italiana di Biochimica Clinica; psychogeriatrics – Associazione Italiana di Psicogeriatria; nuclear medicine – Associazione Italiana di Medicina Nucleare) defined the theoretical framework, relevant literature, the diagnostic issues to be addressed and the diagnostic algorithm. An N–1 majority defined consensus achievement. Results: The panellists chose the 2011 National Institute on Aging and Alzheimer's Association diagnostic criteria as the reference theoretical framework and defined the algorithm in seven Delphi rounds. The algorithm includes baseline clinical and cognitive assessment, blood examination, and magnetic resonance imaging with exclusionary and inclusionary roles; dopamine transporter single-photon emission computed tomography (if no/unclear parkinsonism) or metaiodobenzylguanidine cardiac scintigraphy for suspected dementia with Lewy bodies with clear parkinsonism (round VII, votes(yes-no-abstained): 3-1-1); 18F-fluorodeoxyglucose positron emission tomography for suspected frontotemporal lobar degeneration and low diagnostic confidence of Alzheimer’s disease (round VII, 4-0-1); cerebrospinal fluid for suspected Alzheimer’s disease (round IV, 4-1-0); and amyloid positron emission tomography if cerebrospinal fluid was not possible/accepted (round V, 4-1-0) or inconclusive (round VI, 5-0-0). Conclusions: These consensus recommendations can guide clinicians in the biomarker-based aetiological diagnosis of mild cognitive impairment, whilst guidelines cannot be defined with evidence-to-decision procedures due to incomplete evidence.