Directed Network Motifs in Alzheimer’s Disease and Mild Cognitive Impairment

Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains. We show that frequencies of specific directed network motifs can be used to distinguish between patients with Alzheimer’s disease (AD) and normal control (NC) subjects. Especially interesting from a clinical standpoint, these motif frequencies can also distinguish between subjects with mild cognitive impairment who remained stable over three years (MCI) and those who converted to AD (CONV). Furthermore, we find that the entropy of the distribution of directed network motifs increased from MCI to CONV to AD, implying that the distribution of pathology is more structured in MCI but becomes less so as it progresses to CONV and further to AD. Thus, directed network motifs frequencies and distributional properties provide new insights into the progression of Alzheimer’s disease as well as new imaging markers for distinguishing between normal controls, stable mild cognitive impairment, MCI converters and Alzheimer’s disease.     

Metalloproteinase’s Activity and Oxidative Stress in Mild Cognitive Impairment and Alzheimer’s Disease

Matrix metalloproteinases (MMPs) and oxidative stress have been implicated in neurological diseases such as Alzheimer’s disease (AD). Plasma MMP-2 and MMP-9 activities were assessed in Mild Cognitive Impairment (MCI) and AD subjects compared with aged-matched controls, and subsequently analysed in relation to oxidative stress markers. Both MMP-2 and MMP-9 showed no significant changes versus control subjects. Plasma glutathione peroxidase Se-dependent (GPx-Se) activity and malondialdehyde (MDA) levels were higher in AD than in controls (P < 0.05), suggesting a role for GPx-Se in controlling oxidative stress in AD. Negative correlations were observed between MMPs and MDA in AD and MCI patients (P < 0.05). In conclusion, oxidative stress events did not include activation of MMPs and this similar pattern in AD and MCI suggests that both are biochemically equivalent.     

A Depressive Endophenotype of Mild Cognitive Impairment and Alzheimer’s Disease

Background

Alzheimer’s disease (AD) is a devastating public health problem that affects over 5.4 million Americans. Depression increases the risk of Mild Cognitive Impairment (MCI) and AD. By understanding the influence of depression on cognition, the potential exists to identify subgroups of depressed elders at greater risk for cognitive decline and AD. The current study sought to: 1) clinically identify a sub group of geriatric patients who suffer from depression related cognitive impairment; 2) cross validate this depressive endophenotype of MCI/AD in an independent cohort.

Methods and Findings

Data was analyzed from 519 participants of Project FRONTIER. Depression was assessed with the GDS30 and cognition was assessed using the EXIT 25 and RBANS. Five GDS items were used to create the Depressive endophenotype of MCI and AD (DepE). DepE was significantly negatively related to RBANS index scores of Immediate Memory (B=-2.22, SE=.37, p<0.001), visuospatial skills (B=-1.11, SE=0.26, p<0.001), Language (B=-1.03, SE=0.21, p<0.001), Attention (B=-2.56, SE=0.49, p<0.001), and Delayed Memory (B=-1.54, SE = 037, p<0.001), and higher DepE scores were related to poorer executive functioning (EXIT25; B=0.65, SE=0.19, p=0.001). DepE scores significantly increased risk for MCI diagnosis (odds ratio [OR] = 2.04; 95% CI=1.54-2.69). Data from 235 participants in the TARCC (Texas Alzheimer’s Research & Care Consortium) were analyzed for cross-validation of findings in an independent cohort. The DepE was significantly related to poorer scores on all measures, and a significantly predicted of cognitive change over 12- and 24-months.

Conclusion

The current findings suggest that a depressive endophenotype of MCI and AD exists and can be clinically identified using the GDS-30. Higher scores increased risk for MCI and was cross-validated by predicting AD in the TARCC. A key purpose for the search for distinct subgroups of individuals at risk for AD and MCI is to identify novel treatment and preventative opportunities.     

Weight Loss Predicts Progression of Mild Cognitive Impairment to Alzheimer’s Disease

Background

Weight loss is common in people with Alzheimer’s disease (AD) and it could be a marker of impending AD in Mild Cognitive Impairment (MCI) and improve prognostic accuracy, if accelerated progression to AD would be shown.

Aims

To assess weight loss as a predictor of dementia and AD in MCI.

Methods

One hundred twenty-five subjects with MCI (age 73.8 ± 7.1 years) were followed for an average of 4 years. Two weight measurements were carried out at a minimum time interval of one year. Dementia was defined according to DSM-IV criteria and AD according to NINCDS-ADRDA criteria. Weight loss was defined as a ≥4% decrease in baseline weight.

Results

Fifty-three (42.4%) MCI progressed to dementia, which was of the AD-type in half of the cases. Weight loss was associated with a 3.4-fold increased risk of dementia (95% CI = 1.5–6.9) and a 3.2-fold increased risk of AD (95% CI = 1.4–8.3). In terms of years lived without disease, weight loss was associated to a 2.3 and 2.5 years earlier onset of dementia and AD.

Conclusions

Accelerated progression towards dementia and AD is expected when weight loss is observed in MCI patients. Weight should be closely monitored in elderly with mild cognitive impairment.     

Atrophic Patterns of the Frontal-Subcortical Circuits in Patients with Mild Cognitive Impairment and Alzheimer’s Disease

Atrophy of the cortical thickness and gray matter volume are regarded as sensitive markers for the early clinical diagnosis of Alzheimer’s disease (AD). This study aimed to investigate differences in atrophy patterns in the frontal-subcortical circuits between MCI and AD, assess whether these differences were essential for the pathologic basis of cognitive impairment. A total of 131 individuals were recruited, including 45 with cognitively normal controls (CN), 46 with MCI, and 40 with AD. FreeSurfer software was used to perform volumetric measurements of the frontal-subcortical circuits from 3.0T magnetic resonance (MR) scans. Data revealed that both MCI and AD subjects had a thinner cortex in the left caudal middle frontal gyrus and the left lateral orbitofrontal gyrus compared with CN individuals. The left lateral orbitofrontal gyrus was also thinner in AD compared with MCI patients. There were no statistically significant differences in the cortical mean curvature among the three groups. Both MCI and AD subjects exhibited smaller bilateral hippocampus volumes compared with CN individuals. The volumes of the bilateral hippocampus and the right putamen were also smaller in AD compared with MCI patients. Logistic regression analyses revealed that the left lateral orbitofrontal gyrus and bilateral hippocampus were risk factors for cognitive impairment. These current results suggest that atrophy was heterogeneous in subregions of the frontal-subcortical circuits in MCI and AD patients. Among these subregions, the reduced thickness of the left lateral orbitofrontal and the smaller volume of the bilateral hippocampus seemed to be markers for predicting cognitive impairment.     

Changes in White Matter Integrity before Conversion from Mild Cognitive Impairment to Alzheimer’s Disease

Background

Mild cognitive impairment (MCI) may represent an early stage of dementia conferring a particularly high annual risk of 15–20% of conversion to Alzheimer’s disease (AD). Recent findings suggest that not only gray matter (GM) loss but also a decline in white matter (WM) integrity may be associated with imminent conversion from MCI to AD.

Objective

In this study we used Voxel-based morphometry (VBM) to examine if gray matter loss and/or an increase of the apparent diffusion coefficient (ADC) reflecting mean diffusivity (MD) are an early marker of conversion from MCI to AD in a high risk population.

Method

Retrospective neuropsychological and clinical data were collected for fifty-five subjects (MCI converters n = 13, MCI non-converters n = 14, healthy controls n = 28) at baseline and one follow-up visit. All participants underwent diffusion weighted imaging (DWI) and T1-weighted structural magnetic resonance imaging scans at baseline to analyse changes in GM density and WM integrity using VBM.

Results

At baseline MCI converters showed impaired performance in verbal memory and naming compared to MCI non-converters. Further, MCI converters showed decreased WM integrity in the frontal, parietal, occipital, as well as the temporal lobe prior to conversion to AD. Multiple regression analysis showed a positive correlation of gray matter atrophy with specific neuropsychological test results.

Conclusion

Our results suggest that additionally to morphological changes of GM a reduced integrity of WM indicates an imminent progression from MCI stage to AD. Therefore, we suggest that DWI is useful in the early diagnosis of AD.     

Default-Mode Network Changes in Huntington’s Disease: An Integrated MRI Study of Functional Connectivity and Morphometry

Previous MRI studies of functional connectivity in pre-symptomatic mutation carriers of Huntington’s disease (HD) have shown dysfunction of the Default-Mode Network (DMN). No data however are currently available on the DMN alterations in the symptomatic stages of the disease, which are characterized by cortical atrophy involving several DMN nodes. We assessed DMN integrity and its possible correlations with motor and cognitive symptoms in 26 symptomatic HD patients as compared to 22 normal volunteers, by analyzing resting state functional MRI data, using the Precuneal Cortex/Posterior Cingulate Cortices (PC/PCC) as seed, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Direct correlation with PC/PCC was decreased, without correlation with atrophy, in the ventral medial prefrontal cortex (including anterior cingulate and subgenual cortex), right dorso-medial prefrontal cortex, and in the right inferior parietal cortex (mainly involving the angular gyrus). Negative correlations with PC/PCC were decreased bilaterally in the inferior parietal cortices, while a cluster in the right middle occipital gyrus presented increased correlation with PC/PCC. DMN changes in the ventral medial prefrontal cortex significantly correlated with the performance at the Stroop test (p = .0002). Widespread DMN changes, not correlating with the atrophy of the involved nodes, are present in symptomatic HD patients, and correlate with cognitive disturbances.     

Whole-brain Functional Networks in Cognitively Normal,Mild Cognitive Impairment,and Alzheimer’s Disease

The conceptual significance of understanding functional brain alterations and cognitive deficits associated with Alzheimer’s disease (AD) process has been widely established. However, the whole-brain functional networks of AD and its prodromal stage, mild cognitive impairment (MCI), are not well clarified yet. In this study, we compared the characteristics of the whole-brain functional networks among cognitively normal (CN), MCI, and AD individuals by applying graph theoretical analyses to [¹⁸F] fluorodeoxyglucose positron emission tomography (FDG-PET) data. Ninety-four CN elderly, 183 with MCI, and 216 with AD underwent clinical evaluation and FDG-PET scan. The overall small-world property as seen in the CN whole-brain network was preserved in MCI and AD. In contrast, individual parameters of the network were altered with the following patterns of changes: local clustering of networks was lower in both MCI and AD compared to CN, while path length was not different among the three groups. Then, MCI had a lower level of local clustering than AD. Subgroup analyses for AD also revealed that very mild AD had lower local clustering and shorter path length compared to mild AD. Regarding the local properties of the whole-brain networks, MCI and AD had significantly decreased normalized betweenness centrality in several hubs regionally associated with the default mode network compared to CN. Our results suggest that the functional integration in whole-brain network progressively declines due to the AD process. On the other hand, functional relatedness between neighboring brain regions may not gradually decrease, but be the most severely altered in MCI stage and gradually re-increase in clinical AD stages.     

Diagnosed Mild Cognitive Impairment Due to Alzheimer’s Disease with PET Biomarkers of Beta Amyloid and Neuronal Dysfunction

The aim of this study is to identify mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) using amyloid imaging of beta amyloid (Aβ) deposition and FDG imaging of reflecting neuronal dysfunction as PET biomarkers. Sixty-eight MCI patients underwent cognitive testing, [11C]-PIB PET and [18F]-FDG PET at baseline and follow-up. Regions of interest were defined on co-registered MRI. PIB distribution volume ratio (DVR) was calculated using Logan graphical analysis, and the standardized uptake value ratio (SUVR) on the same regions was used as quantitative analysis for [18F]-FDG. Thirty (44.1%) of all 68 MCI patients converted to AD over 19.2±7.1 months. The annual rate of MCI conversion was 23.4%. A positive Aβ PET biomarker significantly identified MCI due to AD in individual MCI subjects with a sensitivity (SS) of 96.6% and specificity (SP) of 42.1%. The positive predictive value (PPV) was 56.8%. A positive Aβ biomarker in APOE ε4/4 carriers distinguished with a SS of 100%. In individual MCI subjects who had a prominent impairment in episodic memory and aged older than 75 years, an Aβ biomarker identified MCI due to AD with a greater SS of 100%, SP of 66.6% and PPV of 80%, compared to FDG biomarker alone or both PET biomarkers combined. In contrast, when assessed in precuneus, both Aβ and FDG biomarkers had the greatest level of certainty for MCI due to AD with a PPV of 87.8%. The Aβ PET biomarker primarily defines MCI due to AD in individual MCI subjects. Furthermore, combined FDG biomarker in a cortical region of precuneus provides an added diagnostic value in predicting AD over a short period.     

A fuzzy-based system reveals Alzheimer’s Disease onset in subjects with Mild Cognitive Impairment

Alzheimer’s Disease (AD) is the most frequent neurodegenerative form of dementia. Although dementia cannot be cured, it is very important to detect preclinical AD as early as possible. Several studies demonstrated the effectiveness of the joint use of structural Magnetic Resonance Imaging (MRI) and cognitive measures to detect and track the progression of the disease. Since hippocampal atrophy is a well known biomarker for AD progression state, we propose here a novel methodology, exploiting it as a searchlight to detect the best discriminating features for the classification of subjects with Mild Cognitive Impairment (MCI) converting (MCI-c) or not converting (MCI-nc) to AD. In particular, we define a significant subdivision of the hippocampal volume in fuzzy classes, and we train for each class Support Vector Machine SVM classifiers on cognitive and morphometric measurements of normal controls (NC) and AD patients. From the ADNI database, we used MRI scans and cognitive measurements at baseline of 372 subjects, including 98 subjects with AD, and 117 NC as a training set, 86 with MCI-c and 71 with MCI-nc as an independent test set. The accuracy of early diagnosis was evaluated by means of a longitudinal analysis. The proposed methodology was able to accurately predict the disease onset also after one year (median AUC = 88.2%, interquartile range 87.2%–89.0%). Besides its robustness, the proposed fuzzy methodology naturally incorporates the uncertainty degree intrinsically affecting neuroimaging features. Thus, it might be applicable in several other pathological conditions affecting morphometric changes of the brain.     

Intra-Individual Reaction Time Variability in Mild Cognitive Impairment and Alzheimer’s Disease: Gender,Processing Load and Speed Factors

Compared to cognitively healthy ageing (CH), intra-individual variability in reaction time (IIV_RT), a behavioural marker of neurological integrity, is commonly reported to increase in both Alzheimer’s disease (AD) and mild cognitive impairment (MCI). It varies in MCI with respect to whether it represents the pro-dromal stages of dementia or not; being greatest in those most likely to convert. Abnormal IIV_RT in MCI therefore represents a potential measure of underlying functional integrity that may serve to differentiate MCI from CH and to help identify those patients for whom MCI is the result of a progressive pathological process. As the clinical approach to MCI is increasingly stratified with respect to gender, we investigated whether this factor could influence study outcome. The influence of RT_SPEED and processing load upon IIV_RT was also examined. Under low processing load conditions, IIV_RT was significantly increased in both MCI and AD compared to CH. However, correcting for an individual’s processing speed abolished this effect in MCI but not in AD, indicating that the increased IIV_RT in MCI and AD may result from different factors. In MCI but not in CH, IIV_RT was significantly greater for females. Increasing task processing load by adding distracting information, although increasing overall IIV_RT, failed to improve the differentiation between CH and both MCI and AD, and in MCI resulted in a reduction in the influence of gender upon study outcome. The outcome of studies investigating IIV_RT in MCI and AD compared to CH therefore appear influenced by the gender of the participants, by task-related processing load and processing speed.     

Biomarkers of Alzheimer′s Disease in the Cerebrospinal Fluid of Spanish Patients With Mild Cognitive Impairment

The study of biomarkers in the cerebrospinal fluid (CSF) of patients with mild cognitive impairment (MCI) is a technique used with increasing frequency in the early diagnosis of Alzheimers disease (AD). Our objectiv was to gain an own experience while evaluating the reliability, sensitivity, and reproducibility of this technique in Spanish patients. Thirty-seven patients with MCI and twenty-four control subjects were studied by means of AD biomarker analysis in CSF. xMAP Luminex and INNO-BIA Alzbio3 reagents of Innogenetics were used. The study variables assessed were levels of Aβ_1–42, T-tau and P-tau_181p proteins as well as the ratios of T-tau/Aβ_1–42 and P-tau_181p/Aβ_1–42. Samples from nineteen patients were examined twice. Intra-class correlation coefficients for the three biomarkers used showed values higher than 0.95. We observed significant differences between the control group and the MCI groups. In the 6 months following lumbar puncture (LP), eleven (29%) patients with MCI developed AD. These patients showed significant lower levels in Aβ_1–42 protein (276.35 ± 78 vs. 367.13 ± 123.49, P < 0.03) and higher ratios (T-tau/Aβ_1–42 [0.38 ± 0.2 vs. 0.22 ± 0.14, P < 0.01] and P-tau_181p/Aβ_1–42 [0.27 ± 0.13 vs. 0.16 ± 0.1, P < 0.008]) to those in the same group who remained stable. We obtained similar results to those in the most recent reliable literature with our ROC curves, especially with our P-tau_181p values and T-tau/Aβ_1–42 ratio in order to differentiate between control and AD groups. Our experience showed that the analysis of CSF-AD biomarkers in patients with MCI is reliable, sensitive and reproducible. In our knowledge, this is the first experience in Spanish patients.     

Periodontitis and Cognitive Decline in Alzheimer’s Disease

Periodontitis is common in the elderly and may become more common in Alzheimer’s disease because of a reduced ability to take care of oral hygiene as the disease progresses. Elevated antibodies to periodontal bacteria are associated with an increased systemic pro-inflammatory state. Elsewhere raised serum pro-inflammatory cytokines have been associated with an increased rate of cognitive decline in Alzheimer’s disease. We hypothesized that periodontitis would be associated with increased dementia severity and a more rapid cognitive decline in Alzheimer’s disease. We aimed to determine if periodontitis in Alzheimer’s disease is associated with both increased dementia severity and cognitive decline, and an increased systemic pro inflammatory state. In a six month observational cohort study 60 community dwelling participants with mild to moderate Alzheimer’s Disease were cognitively assessed and a blood sample taken for systemic inflammatory markers. Dental health was assessed by a dental hygienist, blind to cognitive outcomes. All assessments were repeated at six months. The presence of periodontitis at baseline was not related to baseline cognitive state but was associated with a six fold increase in the rate of cognitive decline as assessed by the ADAS-cog over a six month follow up period. Periodontitis at baseline was associated with a relative increase in the pro-inflammatory state over the six month follow up period. Our data showed that periodontitis is associated with an increase in cognitive decline in Alzheimer’s Disease, independent to baseline cognitive state, which may be mediated through effects on systemic inflammation.     

Untargeted Metabolomic Analysis of Human Plasma Indicates Differentially Affected Polyamine and L-Arginine Metabolism in Mild Cognitive Impairment Subjects Converting to Alzheimer’s Disease

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer’s disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients ‘at risk’ from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.     

Intra-Individual Variability of Physical Activity in Older Adults With and Without Mild Alzheimer’s Disease

Physical activity shows promise for protection against cognitive decline in older adults with and without Alzheimer’s disease (AD). To better understand barriers to adoption of physical activity in this population, a clear understanding of daily and weekly activity patterns is needed. Most accelerometry studies report average physical activity over an entire wear period without considering the potential importance of the variability of physical activity. This study evaluated individual differences in the amount and intra-individual variability of physical activity and determined whether these differences could be predicted by AD status, day of wear, age, gender, education, and cardiorespiratory capacity. Physical activity was measured via accelerometry (Actigraph GT3X+) over one week in 86 older adults with and without AD (n = 33 and n = 53, respectively). Mixed-effects location-scale models were estimated to evaluate and predict individual differences in the amount and intra-individual variability of physical activity. Results indicated that compared to controls, participants with AD averaged 21% less activity, but averaged non-significantly greater intra-individual variability. Women and men averaged similar amounts of physical activity, but women were significantly less variable. The amount of physical activity differed significantly across days of wear. Increased cardiorespiratory capacity was associated with greater average amounts of physical activity. Investigation of individual differences in the amount and intra-individual variability of physical activity provided insight into differences by AD status, days of monitor wear, gender, and cardiovascular capacity. All individuals regardless of AD status were equally consistent in their physical activity, which may have been due to a highly sedentary sample and/or the early disease stage of those participants with AD. These results highlight the value of considering individual differences in both the amount and intra-individual variability of physical activity.     

Fibrinogen Induces Microglia-Mediated Spine Elimination and Cognitive Impairment in an Alzheimer’s Disease Model

1. Download high-res image (279KB)
2. Download full-size image

     

Plasma protein profiling of Mild Cognitive Impairment and Alzheimer’s disease using iTRAQ quantitative proteomics

Background

With the promise of disease modifying treatments, there is a need for more specific diagnosis and prognosis of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Plasma biomarkers are likely to be utilised to increase diagnostic accuracy and specificity of AD and cognitive decline.

Methods

Isobaric tags (iTRAQ) and proteomic methods were used to identify potential plasma biomarkers of MCI and AD. Relative protein expression level changes were quantified in plasma of 411 cognitively normal subjects, 19 AD patients and 261 MCI patients. Plasma was pooled into 4 groups including normal control, AD, amnestic single and multiple domain MCI (aMCI), and nonamnestic single and multiple domain MCI (nMCI). Western-blotting was used to validate iTRAQ data. Integrated function and protein interactions were explored using WEB based bioinformatics tools (DAVID v6.7 and STRING v9.0).

Results

In at least two iTRAQ replicate experiments, 30 proteins were significantly dysregulated in MCI and AD plasma, relative to controls. These proteins included ApoA1, ApoB100, complement C3, C4b-binding protein, afamin, vitamin D-binding protein precursor, isoform 1 of Gelsolin actin regulator, Ig mμ chain C region (IGHM), histidine-rich glycoprotein and fibrinogen β and γ chains. Western-blotting confirmed that afamin was decreased and IGHM was increased in MCI and AD groups. Bioinformatics results indicated that these dysregulated proteins represented a diversity of biological processes, including acute inflammatory response, cholesterol transport and blood coagulation.

Conclusion

These findings demonstrate that expression level changes in multiple proteins are observed in MCI and AD plasma. Some of these, such as afamin and IGHM, may be candidate biomarkers for AD and the predementia condition of MCI.     

Effects of Baseline CSF α-Synuclein on Regional Brain Atrophy Rates in Healthy Elders,Mild Cognitive Impairment and Alzheimer’s Disease

Background

Cerebrospinal fluid (CSF) α-synuclein is reduced in synucleinopathies, including dementia with Lewy bodies, and some studies have found increased CSF α-synuclein in Alzheimer’s disease (AD). No study has explored effects of CSF α-synuclein on brain atrophy. Here we tested if baseline CSF α-synuclein affects brain atrophy rates and if these effects vary across brain regions, and across the cognitive spectrum from healthy elders (NL), to patients with mild cognitive impairment (MCI) and AD.

Methods

Baseline CSF α-synuclein measurements and longitudinal structural brain magnetic resonance imaging was performed in 74 NL, 118 MCI patients and 55 AD patients. Effects of baseline CSF α-synuclein on regional atrophy rates were tested in 1) four pre-hoc defined regions possibly associated with Lewy body and/or AD pathology (amygdala, caudate, hippocampus, brainstem), and 2) all available regions of interest. Differences across diagnoses were tested by assessing the interaction of CSF α-synuclein and diagnosis (testing NL versus MCI, and NL versus AD).

Results

The effects of CSF α-synuclein on longitudinal atrophy rates were not significant after correction for multiple comparisons. There were tendencies for effects in AD in caudate (higher atrophy rates in subjects with higher CSF α-synuclein, P=0.046) and brainstem (higher atrophy rates in subjects with lower CSF α-synuclein, P=0.063). CSF α-synuclein had significantly different effects on atrophy rates in NL and AD in brainstem (P=0.037) and caudate (P=0.006). Discussion: With the possible exception of caudate and brainstem, the overall weak effects of CSF α-synuclein on atrophy rates in NL, MCI and AD argues against CSF α-synuclein as a biomarker related to longitudinal brain atrophy in these diagnostic groups. Any effects of CSF α-synuclein may be attenuated by possible simultaneous occurrence of AD-related neuronal injury and concomitant Lewy body pathology, which may elevate and reduce CSF α-synuclein levels, respectively.