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Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.

Microglia are the main immune cells in the brain and have roles in brain homeostasis and neurological diseases. Mechanisms underlying microglia–neuron communication remain elusive. Here, we identified an interaction site between neuronal cell bodies and microglial processes in mouse and human brain. Somatic microglia–neuron junctions have a specialized nanoarchitecture optimized for purinergic signaling. Activity of neuronal mitochondria was linked with microglial junction formation, which was induced rapidly in response to neuronal activation and blocked by inhibition of P2Y12 receptors. Brain injury–induced changes at somatic junctions triggered P2Y12 receptor–dependent microglial neuroprotection, regulating neuronal calcium load and functional connectivity. Thus, microglial processes at these junctions could potentially monitor and protect neuronal functions.

Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99–74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = -0.213 – 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.

Traumatic brain injury (TBI) causes acute and subacute tissue damage, but is also associated with chronic inflammation and progressive loss of brain tissue months and years after the initial event. The trigger and the subsequent molecular mechanisms causing chronic brain injury after TBI are not well understood. The aim of the current study was therefore to investigate the hypothesis that necroptosis, a form a programmed cell death mediated by the interaction of Receptor Interacting Protein Kinases (RIPK) 1 and 3, is involved in this process. Neuron-specific RIPK1- or RIPK3-deficient mice and their wild-type littermates were subjected to experimental TBI by controlled cortical impact. Posttraumatic brain damage and functional outcome were assessed longitudinally by repetitive magnetic resonance imaging (MRI) and behavioral tests (beam walk, Barnes maze, and tail suspension), respectively, for up to three months after injury. Thereafter, brains were investigated by immunohistochemistry for the necroptotic marker phosphorylated mixed lineage kinase like protein(pMLKL) and activation of astrocytes and microglia. WT mice showed progressive chronic brain damage in cortex and hippocampus and increased levels of pMLKL after TBI. Chronic brain damage occurred almost exclusively in areas with iron deposits and was significantly reduced in RIPK1- or RIPK3-deficient mice by up to 80%. Neuroprotection was accompanied by a reduction of astrocyte and microglia activation and improved memory function. The data of the current study suggest that progressive chronic brain damage and cognitive decline after TBI depend on the expression of RIPK1/3 in neurons. Hence, inhibition of necroptosis signaling may represent a novel therapeutic target for the prevention of chronic post-traumatic brain damage.

Introduction To describe the protocol and findings of the instrumental validation of three imaging‐based biomarker kits selected by the MarkVCID consortium: free water (FW) and peak width of skeletonized mean diffusivity (PSMD), both derived from diffusion tensor imaging (DTI), and white matter hyperintensity (WMH) volume derived from fluid attenuation inversion recovery and T1‐weighted imaging. Methods The instrumental validation of imaging‐based biomarker kits included inter‐rater reliability among participating sites, test–retest repeatability, and inter‐scanner reproducibility across three types of magnetic resonance imaging (MRI) scanners using intra‐class correlation coefficients (ICC). Results The three biomarkers demonstrated excellent inter‐rater reliability (ICC >0.94, P‐values < .001), very high agreement between test and retest sessions (ICC >0.98, P‐values < .001), and were extremely consistent across the three scanners (ICC >0.98, P‐values < .001). Discussion The three biomarker kits demonstrated very high inter‐rater reliability, test–retest repeatability, and inter‐scanner reproducibility, offering robust biomarkers suitable for future multi‐site observational studies and clinical trials in the context of vascular cognitive impairment and dementia (VCID).

Small subclinical hyperintense lesions are frequently encountered on brain diffusion-weighted imaging (DWI) scans of patients with cerebral amyloid angiopathy (CAA). Interpretation of these DWI+ lesions, however, has been limited by absence of histopathological examination. We aimed to determine whether DWI+ lesions represent acute microinfarcts on histopathology in brains with advanced CAA, using a combined in vivo MRI—ex vivo MRI—histopathology approach. We first investigated the histopathology of a punctate cortical DWI+ lesion observed on clinical in vivo MRI 7 days prior to death in a CAA case. Subsequently, we assessed the use of ex vivo DWI to identify similar punctate cortical lesions post-mortem. Intact formalin-fixed hemispheres of 12 consecutive cases with CAA and three non-CAA controls were subjected to high-resolution 3 T ex vivo DWI and T2 imaging. Small cortical lesions were classified as either DWI+/T2+ or DWI−/T2+. A representative subset of lesions from three CAA cases was selected for detailed histopathological examination. The DWI+ lesion observed on in vivo MRI could be matched to an area with evidence of recent ischemia on histopathology. Ex vivo MRI of the intact hemispheres revealed a total of 130 DWI+/T2+ lesions in 10/12 CAA cases, but none in controls ( p  = 0.022). DWI+/T2+ lesions examined histopathologically proved to be acute microinfarcts (classification accuracy 100%), characterized by presence of eosinophilic neurons on hematoxylin and eosin and absence of reactive astrocytes on glial fibrillary acidic protein-stained sections. In conclusion, we suggest that small DWI+ lesions in CAA represent acute microinfarcts. Furthermore, our findings support the use of ex vivo DWI as a method to detect acute microinfarcts post-mortem, which may benefit future histopathological investigations on the etiology of microinfarcts.

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer's disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.

Cerebral Amyloid Angiopathy (CAA) is a cerebral small vessel disease that can lead to microstructural disruption of white matter (WM), which can be measured by the Peak Width of Skeletonized Mean Diffusivity (PSMD). We hypothesized that PSMD measures would be increased in patients with CAA compared to healthy controls (HC), and increased PSMD is associated with lower cognitive scores in patients with CAA. Eighty-one probable CAA patients without cognitive impairment who were diagnosed with Boston criteria and 23 HCs were included. All subjects underwent an advanced brain MRI with high-resolution diffusion-weighted imaging (DWI). PSMD scores were quantified from a probabilistic skeleton of the WM tracts in the mean diffusivity (MD) image using a combination of fractional anisotropy (FA) and the FSL Tract-Based Spatial Statistics (TBSS) algorithm (www.psmd-marker.com). Within CAA cohort, standardized z-scores of processing speed, executive functioning and memory were obtained. The mean of age and sex were similar between CAA patients (69.6 ± 7.3, 59.3% male) and HCs (70.6 ± 8.5, 56.5% male) ( = 0.581 and = 0.814). PSMD was higher in the CAA group [(4.13 ± 0.94) × 10 mm /s] compared to HCs [(3.28 ± 0.51) × 10 mm /s] ( < 0.001). In a linear regression model corrected for relevant variables, diagnosis of CAA was independently associated with increased PSMD compared to HCs ( = 0.45, 95% CI 0.13-0.76, = 0.006). Within CAA cohort, higher PSMD was associated with lower scores in processing speed ( < 0.001), executive functioning ( = 0.004), and memory (0.047). Finally, PSMD outperformed all other MRI markers of CAA by explaining most of the variance in models predicting lower scores in each cognitive domain. Peak Width of Skeletonized Mean Diffusivity is increased in CAA, and it is associated with worse cognitive scores supporting the view that disruption of white matter has a significant role in cognitive impairment in CAA. As a robust marker, PSMD can be used in clinical trials or practice.

Background: Peak width of skeletonized mean diffusivity (PSMD) is a promising diffusion tensor imaging (DTI) marker that shows consistent and strong cognitive associations in the context of different cerebral small vessel diseases (cSVD). Purpose: Investigate whether PSMD 1) is higher in patients with Cerebral Amyloid Angiopathy (CAA) than those with arteriolosclerosis; 2) can capture the anteroposterior distribution of CAA-related abnormalities; 3) shows similar neuroimaging and cognitive associations in comparison to other classical DTI markers, such as average mean diffusivity (MD) and fractional anisotropy (FA). Methods: We analyzed cross-sectional neuroimaging and neuropsychological data from 90 non-demented memory-clinic subjects from a single center. Based on MRI findings, we classified them into probable-CAA (those that fulfilled the modified Boston criteria), subjects with MRI markers of cSVD not attributable to CAA (presumed arteriolosclerosis; cSVD), and subjects without evidence of cSVD on MRI (non-cSVD). We compared total and lobe-specific (frontal and occipital) DTI metrics values across the groups. We used linear regression models to investigate how PSMD, MD, and FA correlate with conventional neuroimaging markers of cSVD and cognitive scores in CAA. Results: PSMD was comparable in probable-CAA (median 4.06 x 10-4 mm2/s) and cSVD (4.07 x 10-4 mm2/s) patients, but higher than in non-cSVD (3.30 x 10-4 mm2/s; p<0.001) subjects. Occipital-frontal PSMD gradients were higher in probable-CAA patients, and we observed a significant interaction between diagnosis and region on PSMD values (F(2, 87) = 3.887, p = .024). PSMD was mainly associated with white matter hyperintensity volume, whereas MD and FA were also associated with other markers, especially with the burden of perivascular spaces. PSMD correlated with worse executive function (=-0.581, p<0.001) and processing speed (=-0.463, p=0.003), explaining more variance than other MRI markers. MD and FA were not associated with performance in any cognitive domain. Conclusions: PSMD is a promising biomarker of cognitive impairment in CAA that outperforms other conventional and DTI-based neuroimaging markers. Although global PSMD is similarly increased in different forms of cSVD, PSMD’s spatial variations could potentially provide insights into the predominant type of underlying microvascular pathology.

Background Recent evidence derived from functional magnetic resonance imaging (fMRI) studies suggests that functional hubs (i.e., highly connected brain regions) are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer’s disease. These results suggest that LFC connectivity supports reserve capacity, alleviating memory decline. An open question, however, is why LFC connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFC connectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities. Methods We assessed fMRI during a face-name association learning task performed by 26 healthy, cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC connectivity to key memory networks, including the default mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses to test the association between LFC connectivity with the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN small-worldness. Last, we tested network small-worldness as a predictor of memory performance. Results We found that higher LFC connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task. Conclusions The present results suggest that higher education-related LFC connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging.