Langerhans cells participate in the immune response in leprosy by their ability to activate T cells that recognize the pathogen, Mycobacterium leprae, in a langerin-dependent manner. We hypothesized that langerin, the distinguishing C-type lectin of Langerhans cells, would recognize the highly mannosylated structures in pathogenic Mycobacterium spp. The coding region for the extracellular and neck domain of human langerin was cloned and expressed to produce a recombinant active trimeric form of human langerin (r-langerin). Binding assays performed in microtiter plates, by two-dimensional (2D) Western blotting, and by surface plasmon resonance demonstrated that r-langerin possessed carbohydrate-dependent affinity to glycoproteins in the cell wall of M. leprae. This lectin, however, yielded less binding to mannose-capped lipoarabinomannan (ManLAM) and even lower levels of binding to phosphatidylinositol mannosides. However, the superoxide dismutase C (SodC) protein of the M. leprae cell wall was identified as a langerin-reactive ligand. Tandem mass spectrometry verified the glycosylation of a recombinant form of M. leprae SodC (rSodC) produced in Mycobacterium smegmatis. Analysis of r-langerin affinity by surface plasmon resonance revealed a carbohydrate-dependent affinity of rSodC (equilibrium dissociation constant [KD] = 0.862 μM) that was 20-fold greater than for M. leprae ManLAM (KD = 18.69 μM). These data strongly suggest that a subset of the presumptively mannosylated M. leprae glycoproteins act as ligands for langerin and may facilitate the interaction of M. leprae with Langerhans cells.

Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.

Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%); the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

The innate immune system recognizes microbial pathogens via pattern recognition receptors. One such receptor, NOD2, via recognition of muramyl dipeptide (MDP), triggers a distinct network of innate immune responses, including the production of interleukin-32 (IL-32), which leads to the differentiation of monocytes into dendritic cells (DC). NOD2 has been implicated in the pathogenesis of human leprosy, yet it is not clear whether Mycobacterium leprae, which has a distinct MDP structure, can activate this pathway. We investigated the effect of MDP structure on the innate immune response, finding that infection of monocytes with M. leprae induces IL-32 and DC differentiation in a NOD2-dependent manner. The presence of the proximal l-Ala instead of Gly in the common configuration of the peptide side chain of M. leprae did not affect recognition by NOD2 or cytokine production. Furthermore, amidation of the d-Glu residue did not alter NOD2 activation. These data provide experimental evidence that NOD2 recognizes naturally occurring structural variants of MDP.

Objective

To determine the independent and synergistic effects of amyloid and small vessel disease (SVD) burden on longitudinal cognitive decline in patients with subcortical vascular dementia (SVaD).

Methods

A longitudinal cohort study was conducted involving patients from outpatient clinics of 2 tertiary referral centers. Sixty-one patients with SVaD were prospectively recruited and underwent MRI, 11C-Pittsburgh compound B (PiB) PET at baseline, and a 3-year annual neuropsychological follow-up. Effects of PiB positivity and SVD markers (white matter hyperintensities [WMH], lacunes, and microbleeds) on longitudinal cognitive decline were evaluated using generalized estimation equation after controlling for age, sex, education, APOE4 allele, and follow-up interval.

Results

When individual neuropsychological tests were used as outcome measures, PiB positivity was associated with faster cognitive decline in attention, visuospatial, visual memory, and global cognition function. Higher WMH burden was associated with faster cognitive decline in attention, visuospatial, visual recognition memory, and semantic/phonemic fluency function, whereas lacunes and microbleeds had no significant effects. When global dementia rating (Clinical Dementia Rating sum of boxes) was considered as an outcome measure, however, only PiB positivity was associated with faster cognitive decline. Significant interactions between PiB positivity and higher SVD burden were found to affect cognitive decline in semantic word fluency (from WMH burden) and global dementia rating (from microbleed burden).

Conclusions

In SVaD patients, amyloid burden, independently or interactively with SVD, contributed to longitudinal cognitive decline. Amyloid deposition was the strongest poor prognostic factor.

Background

We investigated the independent effects of Alzheimer's disease (AD) and cerebrovascular disease (CVD) pathologies on brain structural changes and cognition.

Methods

Amyloid burden (Pittsburgh compound B [PiB] retention ratio), CVD markers (volume of white matter hyperintensities [WMH] and number of lacunae), and structural changes (cortical thickness and hippocampal shape) were measured in 251 cognitively impaired patients. Path analyses were utilized to assess the effects of these markers on cognition.

Results

PiB retention ratio was associated with hippocampal atrophy, which was associated with memory impairment. WMH were associated with frontal thinning, which was associated with executive and memory dysfunctions. PiB retention ratio and lacunae were also associated with memory and executive dysfunction without the mediation of hippocampal or frontal atrophy.

Conclusions

Our results suggest that the impacts of AD and CVD pathologies on cognition are mediated by specific brain regions.

Background

We tested our hypothesis that the white matter network might mediate the effect of amyloid and small vessel disease (SVD) on cortical thickness and/or cognition.

Methods

We prospectively recruited 232 patients with cognitive impairment. Amyloid was assessed using Pittsburgh compound B-PET. SVD was quantified as white matter hyperintensity volume and lacune number. The regional white matter network connectivity was measured as regional nodal efficiency by applying graph theoretical analysis to diffusion tensor imaging data. We measured cortical thickness and performed neuropsychological tests.

Results

SVD burden was associated with decreased nodal efficiency in the bilateral frontal, lateral temporal, lateral parietal, and occipital regions. Path analyses showed that the frontal nodal efficiency mediated the effect of SVD on the frontal atrophy and frontal-executive dysfunction. The temporoparietal nodal efficiency mediated the effect of SVD on the temporoparietal atrophy and memory dysfunction. However, Pittsburgh compound B retention ratio affected cortical atrophy and cognitive impairment without being mediated by nodal efficiency.

Conclusions

We suggest that a disrupted white matter network mediates the effect of SVD, but not amyloid, on specific patterns of cortical atrophy and/or cognitive impairment. Therefore, our findings provide insight to better understand how amyloid and SVD burden can give rise to brain atrophy or cognitive impairment in specific patterns.

To characterize the course of Alzheimer's disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.

Purpose

We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement.

Methods

Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2.

Results

Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (β [SE] = -0.02 [0.004], p < 0.001), ADAS-cog 13 (0.05 [0.01], p < 0.001), FDG PET SUVR (-0.0008 [0.0003], p = 0.004), and hippocampal volumes (-4.46 [0.65], p < 0.001) compared to stage 1.

Conclusions

We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.

Objective

To investigate the association between APOE genotype and β-amyloid (Aβ) burden, as measured by PET in patients with subcortical vascular cognitive impairment (SVCI) and those with Alzheimer disease-related cognitive impairment (ADCI).

Methods

This was a cross-sectional study of 310 patients with SVCI and 999 with ADCI. To evaluate the effects of APOE genotype or diagnostic group on Aβ positivity, we performed multivariate logistic regression analyses. Further distinctive underlying features of latent subgroups were examined by employing a latent class cluster analysis approach.

Results

In comparison with ε3 homozygotes, in the ADCI group, ε2 carriers showed a lower frequency of Aβ positivity (odds ratio [OR] 0.43, 95% confidence interval [CI] 0.23-0.79), while in the SVCI group, ε2 carriers showed a higher frequency of Aβ positivity (OR 2.26, 95% CI 1.02-5.01). In particular, we observed an interaction effect of ε2 carrier status and diagnostic group on Aβ positivity (OR 5.12, 95% CI 1.93-13.56), in that relative to ε3 homozygotes, there were more Aβ-positive ε2 carriers in the SVCI group than in the ADCI group. We also identified latent subgroups of Aβ-positive APOE ε2 carriers with SVCI and Aβ-positive APOE ε4 carriers with ADCI.

Conclusions

Our findings suggest that APOE ε2 is distinctly associated with Aβ deposition in patients with SVCI and those with ADCI. Our findings further suggest that there is a distinctive subgroup of Aβ-positive APOE ε2 carriers with SVCI among patients with cognitive impairment.