DEVELOPMENT OF IMAGING MARKERS TO TRACK ALZHEIMER¿S DISEASE PROGRESSION IN HUMANS AND MOUSE MODELS

La Malattia di Alzheimer (AD) \ue8 la forma pi\uf9 comune di demenza nella popolazione anziana e affligge pi\uf9 35 milioni di persone nel mondo. Ad oggi, le uniche terapie approvate per la sua cura sono dirette a ridurre i sintomi. Lo sviluppo di nuovi farmaci \ue8 lungo e costoso. Il processo di scoperta \ue8 arduo in quanto i trial clinici coinvolgono un ampio campione di pazienti e implicano dei follow-up troppo lunghi. Inoltre il valore predittivo dei modelli sperimentali \ue8 limitato a causa della mancanza di marcatori omologhi nell\u2019uomo e nei modelli animali. Questo lavoro si inserisce in Pharmacog, un progetto europeo che vede la collaborazione di universit\ue0 ed industrie allo scopo di identificare biomarcatori affidabili e sensibili alla progressione di malattia in pazienti affetti da decadimento cognitivo lieve (MCI) e modelli animali di AD allo scopo di colmare il vuoto tra risultati clinici e preclinici. Nell\u2019uomo, i marcatori di neuroimmagine sono tra i pi\uf9 promettenti candidati nel tracciare la progressione di malattia. Innovazioni nelle tecniche di risonanza magnetica (MRI) rendono possibile l\u2019identificazione di marcatori omologhi nell\u2019uomo e nel topo. Prima dello studio di neuroimmagine nei pazienti MCI, \ue8 necessario verificare che eventuali cambiamenti individuati siano dovuti all\u2019effettiva progressione di malattia e non causati dalla variabilit\ue0 intra e tra i diversi scanner utilizzati nel progetto. Il primo scopo di questo lavoro \ue8 lo studio dei cambiamenti morfometrici e di diffusione in tre diversi modelli murini di Malattia Alzheimer (TASTPM, TauPS2APP e PDAPP da 3 a 22 mesi) tramite l\u2019utilizzo di tecniche MRI. A nove mesi abbiamo trovato una significativa riduzione rispetto ai controlli del volume del caudato-putamen e della corteccia frontale nei TASTPM e nei TauPS2APP (p< 0.001). L\u2019assottigliamento della corteccia entorinale era significativo alla stessa et\ue0 in tutte e tre i modelli (p< 0.001). Abbiamo inoltre individuato delle anormalit\ue0 dipendenti dall\u2019et\ue0 anche in diverse regione di sostanza bianca. Quelle pi\uf9 precoci erano nella commissura anteriore e nel corpo calloso dei TASTPM di 13 mesi (p< 0.001). I danni dei TASTPM sono associabili al pesante carico di amiloide ed alla marcata attivazione della glia e degli astrociti. Il secondo scopo dello studio \ue8 la valutazione e la comparazione della riproducibilit\ue0 di misure volumetriche e di spessore tra test e retest ottenute utilizzando due diversi metodi di processazione esistenti (Freesurfer sulla singola acquisizione o Freesurfer longitudinale). Inoltre abbiamo saggiato la riproducibilit\ue0 di un\u2019analisi per le immagini di diffusione messa a punto nel nostro laboratorio. A questo scopo ognuno degli otto centri europei coinvolti nel progetto e con diversi scanner a 3T ha arruolato un gruppo di 5 volontari sani e anziani sottoponendoli a 2 acquisizioni di risonanza ad almeno una settimana di distanza l\u2019una dall\u2019altra. Abbiamo trovato che la variabilit\ue0 intra e tra i diversi centri nei volumi estratti da queste acquisizioni era inferiore al 3% per le strutture pi\uf9 grandi (come il talamo) e minore del 6% per quelle pi\uf9 piccole (es. amigdala). La variabilit\ue0 degli spessori era meno del 6% e le variazioni dei parametri di diffusione erano prevalentemente nell\u2019intervallo del 2-3%. In conclusione, abbiamo identificato nei modelli analizzati dei marcatori di immagine sensibili alla progressione dell\u2019AD simili a quelli visti nell\u2019uomo e questo apre la strada al possibile utilizzo di una \u201cdistintiva collezione\u201d di marcatori murini di immagine nei trial clinici. I dati collezionati nella parte umana mostrano un pi\uf9 altra riproducibilit\ue0 dei risultati morfometrici ottenuti con l\u2019analisi longitudinale rispetto a quella sulla singola acquisizione (p< 0.01). Infine, abbiamo dimostrato che l\u2019analisi delle immagini di diffusione messa a punto nel nostro laboratorio d\ue0 risultati ugualmente riproducibili a quelli riportati in letteratura.Alzheimer\u2019s disease (AD) is the most common form of dementia in elderly population, affecting more than 35 million people worldwide. To date, the only approved therapies for AD focus on symptomatic relief. The development of new therapeutic agents is time consuming and costly. Drug discovery process is arduous because clinical trials are currently involving too wide sample of patients and long follow-up. Moreover, the predicting value of experimental models used nowadays is limited due to the lack of homologous markers in humans and animals. This work is a branch of Pharmacog, an industry-academic European project aimed at identifying reliable biomarkers that are sensitive to disease progression in patients with Mild Cognitive Impairment (MCI) and in AD animal models in order to bridge the gap between preclinical and clinical outcomes. Human neuroimaging markers are among the most promising candidates to track disease progression. In addition, advanced magnetic resonance imaging (MRI) allow the identification of homologous biomarkers in humans and mice. Prior to investigate neuroimaging biomarkers on MCI patients, we have to test that there is no significant effect of within and across MRI sites variability on brain AD-related longitudinal changes. The first aim of this work is the study of the morphometric and diffusion changes in three different AD mouse model (TASTPM, TauPS2APP and PDAPP from 3 to 22 months of age) through MRI. We found significant volume reduction starting at 9 months in the caudate-putamen and frontal cortex of TASTPM and TauPS2APP (p< 0.001) compared to non transgenic mice. The decrease in the enthorinal cortex thickness was significantly lower in all the strains (p< 0.001). We also found age-related diffusion abnormalities in different white matter regions of TASTPM. The earlier changes were found in the corpus callosum and anterior commissure of 13 months old mice (p< 0.001). In TASTPM, deficits detected with MRI are related to heavy amyloid pathology, marked gliosis and astrocitosys. The second aim of this study is the evaluation and comparison of test-retest reproducibility of brain volumes and thicknesses by two existing Freesurfer pipelines (longitudinal and cross-sectional). Moreover, we assessed the reliability of a diffusion pipeline developed in our lab. Eight different 3T MRI sites in Europe enrolled a group of 5 healthy elderly subjects scanned twice at least a week apart. We found that the within and across sites variability of volumes was less than 3% for larger brain structures (such as thalamus) and less than 6% for smaller regions (i.e., hippocampus). The thickness variability was less than 6% and diffusion indices variations were mostly within the range 2-3%. In conclusion, the present data identify imaging biomarkers of disease progression in mice similar to that seen in humans and pave the way of a murine \u201cimaging signature\u201d usefulness in clinical trials. Human data show significantly higher reproducibility of brain morphometry using the longitudinal pipeline than using the cross-sectional one (p< 0.01). Finally, we demonstrated that the reliability of the analysis of brain diffusion we implemented in our lab is comparable to data reported in the literature

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies

A conformation variant of p53 combined with machine learning identifies alzheimer disease in preclinical and prodromal stages

Early diagnosis of Alzheimer’s disease (AD) is a crucial starting point in disease man-agement. Blood-based biomarkers could represent a considerable advantage in providing AD-risk information in primary care settings. Here, we report new data for a relatively unknown blood-based biomarker that holds promise for AD diagnosis. We evaluate a p53-misfolding conformation rec-ognized by the antibody 2D3A8, also named Unfolded p53 (U-p532D3A8+), in 375 plasma samples derived from InveCe.Ab and PharmaCog/E-ADNI longitudinal studies. A machine learning approach is used to combine U-p532D3A8+ plasma levels with Mini-Mental State Examination (MMSE) and apolipoprotein E epsilon-4 (APOEε4) and is able to predict AD likelihood risk in InveCe.Ab with an overall 86.67% agreement with clinical diagnosis. These algorithms also accurately classify (AUC = 0.92) Aβ+—amnestic Mild Cognitive Impairment (aMCI) patients who will develop AD in PharmaCog/E-ADNI, where subjects were stratified according to Cerebrospinal fluid (CSF) AD markers (Aβ42 and p-Tau). Results support U-p532D3A8+ plasma level as a promising additional candidate blood-based biomarker for AD

Brain atrophy in Alzheimer's Disease and aging

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression

Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples

Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples. We applied the SILVA 132 reference database for all the pipelines. We compared phyla and genera identification and relative abundances across the four pipelines using the Friedman rank sum test. QIIME2 and Bioconductor provided identical outputs on Linux and Mac OS, while UPARSE and mothur reported only minimal differences between OS. Taxa assignments were consistent at both phylum and genus level across all the pipelines. However, a difference in terms of relative abundance was identified for all phyla (p &lt; 0.013) and for the majority of the most abundant genera (p &lt; 0.028), such as Bacteroides (QIIME2: 24.5%, Bioconductor: 24.6%, UPARSE-linux: 23.6%, UPARSE-mac: 20.6%, mothur-linux: 22.2%, mothur-mac: 21.6%, p &lt; 0.001). The use of different bioinformatic pipelines affects the estimation of the relative abundance of gut microbial community, indicating that studies using different pipelines cannot be directly compared. A harmonization procedure is needed to move the field forward

Convergent and discriminant validity of default mode network and limbic network perfusion in amnestic mild cognitive impairment patients

International audienceBackground: Previous studies reported default mode network (DMN) and limbic network (LIN) brain perfusion deficits in patients with amnestic mild cognitive impairment (aMCI), frequently a prodromal stage of Alzheimer’s disease (AD). However, the validity of these measures as AD markers has not yet been tested using MRI arterial spin labeling (ASL). Objective: To investigate the convergent and discriminant validity of DMN and LIN perfusion in aMCI. Methods: We collected core AD markers (amyloid-β 42 [Aβ42], phosphorylated tau 181 levels in cerebrospinal fluid [CSF]), neurodegenerative (hippocampal volumes and CSF total tau), vascular (white matter hyperintensities), genetic (apolipoprotein E [APOE] status), and cognitive features (memory functioning on Paired Associate Learning test [PAL]) in 14 aMCI patients. Cerebral blood flow (CBF) was extracted from DMN and LIN using ASL and correlated with AD features to assess convergent validity. Discriminant validity was assessed carrying out the same analysis with AD-unrelated features, i.e., somatomotor and visual networks’ perfusion, cerebellar volume, and processing speed. Results: Perfusion was reduced in the DMN (F = 5.486, p = 0.039) and LIN (F = 12.678, p = 0.004) in APOE ɛ4 carriers compared to non-carriers. LIN perfusion correlated with CSF Aβ42 levels (r = 0.678, p = 0.022) and memory impairment (PAL, number of errors, r = –0.779, p = 0.002). No significant correlation was detected with tau, neurodegeneration, and vascular features, nor with AD-unrelated features. Conclusion: Our results support the validity of DMN and LIN ASL perfusion as AD markers in aMCI, indicating a significant correlation between CBF and amyloidosis, APOE ɛ4, and memory impairment