Functional connectome and neuropsychiatric symptom clusters of Alzheimer's disease

Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease

Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Cingulate white matter mediates the effects of fecal Ruminococcus on neuropsychiatric symptoms in patients with amyloid-positive amnestic mild cognitive impairment

BACKGROUND

Microbiota-gut-brain axis interacts with one another to regulate brain functions. However, whether the impacts of gut dysbiosis on limbic white matter (WM) tracts contribute to the neuropsychiatric symptoms (NPS) in patients with amyloid-positive amnestic mild cognitive impairment (aMCI+), have not been explored yet. This study aimed to investigate the mediation effects of limbic WM integrity on the association between gut microbiota and NPS in patients with aMCI+.

METHODS

Twenty patients with aMCI + and 20 healthy controls (HCs) were enrolled. All subjects underwent neuropsychological assessments and their microbial compositions were characterized using 16S rRNA Miseq sequencing technique. Amyloid deposition inspected by positron emission tomography imaging and limbic WM tracts (i.e., fornix, cingulum, and uncinate fasciculus) detected by diffusion tensor imaging were additionally measured in patients with aMCI+. We employed a regression-based mediation analysis using Hayes's PROCESS macro in this study.

RESULTS

The relative abundance of genera Ruminococcus and Lactococcus was significantly decreased in patients with aMCI + versus HCs. The relative abundance of Ruminococcus was negatively correlated with affective symptom cluster in the aMCI + group. Notably, this association was mediated by WM integrity of the left cingulate gyrus.

CONCLUSIONS

Our findings suggest Ruminococcus as a potential target for the management of affective impairments in patients with aMCI+.

Application of orthogonal sparse joint non-negative matrix factorization based on connectivity in Alzheimer's disease research

Based on the mining of micro- and macro-relationships of genetic variation and brain imaging data, imaging genetics has been widely applied in the early diagnosis of Alzheimer's disease (AD). However, effective integration of prior knowledge remains a barrier to determining the biological mechanism of AD. This paper proposes a new connectivity-based orthogonal sparse joint non-negative matrix factorization (OSJNMF-C) method based on integrating the structural magnetic resonance image, single nucleotide polymorphism and gene expression data of AD patients; the correlation information, sparseness, orthogonal constraint and brain connectivity information between the brain image data and genetic data are designed as constraints in the proposed algorithm, which efficiently improved the accuracy and convergence through multiple iterative experiments. Compared with the competitive algorithm, OSJNMF-C has significantly smaller related errors and objective function values than the competitive algorithm, showing its good anti-noise performance. From the biological point of view, we have identified some biomarkers and statistically significant relationship pairs of AD/mild cognitive impairment (MCI), such as rs75277622 and BCL7A, which may affect the function and structure of multiple brain regions. These findings will promote the prediction of AD/MCI.

Associating brain imaging phenotypes and genetic risk factors via a hypergraph based netNMF method

Abstract

Alzheimer's disease (AD) is a severe neurodegenerative disease for which there is currently no effective treatment. Mild cognitive impairment (MCI) is an early disease that may progress to AD. The effective diagnosis of AD and MCI in the early stage has important clinical significance.

Methods

To this end, this paper proposed a hypergraph-based netNMF (HG-netNMF) algorithm for integrating structural magnetic resonance imaging (sMRI) of AD and MCI with corresponding gene expression profiles.

Results

Hypergraph regularization assumes that regions of interest (ROIs) and genes were located on a non-linear low-dimensional manifold and can capture the inherent prevalence of two modalities of data and mined high-order correlation features of the two data. Further, this paper used the HG-netNMF algorithm to construct a brain structure connection network and a protein interaction network (PPI) with potential role relationships, mine the risk (ROI) and key genes of both, and conduct a series of bioinformatics analyses.

Conclusion

Finally, this paper used the risk ROI and key genes of the AD and MCI groups to construct diagnostic models. The AUC of the AD group and MCI group were 0.8 and 0.797, respectively.

Relations of neuropsychiatric symptoms with disease stage, sex, and daily function in mild cognitive impairment and dementia due to Alzheimer's disease: A cross-sectional study

OBJECTIVE

To reveal the relations between neuropsychiatric symptoms (NPS), stages of cognitive impairment, sex, and daily function in patients with mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD).

METHODS

A cross-sectional study was conducted from 2014 to 2021 on 1154 patients. Cognitive function, disease severity, NPS, and daily function were evaluated by Mini-mental State Examination, Clinical Dementia Rating Scale, Neuropsychiatric Inventory, and Activities of Daily Living (ADL) respectively. Multivariate logistic regression and linear regression were used to explore the correlations between NPS, disease stage, sex and ADL.

RESULTS

Affective disturbance displayed the highest prevalence from MCI (52.7%) to severe dementia due to AD (98.2%). Multivariate logistic regression revealed that aberrant motor behavior displayed higher prevalence between groups from MCI to severe dementia due to AD (OR = 4.710, P < 0.001; OR = 3.141, P < 0.001; OR = 2.722, P = 0.002, respectively). In patients with dementia due to AD, hallucination and depression were more prevalent in female (OR = 1.730, P = 0.001; OR = 2.376, P < 0.001, respectively) while male presented higher prevalence in apathy (OR = 0.608, P = 0.002). Linear regression analysis showed that delusion and sleep disturbance were significantly associated with basic ADL across all dementia due to AD stages (delusion: mild: β = 0.113, P = 0.015; moderate: β = 0.159, P = 0.019; severe: β = 0.317, P = 0.018; sleep disturbance: mild: β = 0.164, P < 0.001; moderate: β = 0.167, P = 0.013; severe: β = 0.308, P = 0.025) while anxiety was correlated with instrumental ADL from MCI to moderate dementia due to AD (MCI: β = 0.119, P = 0.006; mild: β = 0.149, P < 0.001; moderate: β = 0.130, P = 0.042).

CONCLUSION

Different subitems of NPS are strongly correlated with sex, stage of cognitive impairment, and ADL.

Regional Cerebral Blood Flow Correlates of Neuropsychiatric Symptom Domains in Early Alzheimer’s Disease

Although various neuropsychiatric symptoms are frequently accompanied with Alzheimer’s disease (AD) and pose a substantial burden to both patients and caregivers, their neurobiological underpinnings remain unclear. This study investigated associations between regional cerebral blood flow (rCBF) and neuropsychiatric symptom domains in early AD. A total of 59 patients with early AD underwent brain technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) single-photon emission computed tomography (SPECT) scans. Neuropsychiatric symptoms were assessed by the Neuropsychiatric Inventory and clustered into the affective, apathy, hyperactivity, and psychotic domains. A voxel-wise multiple regression analysis was performed with four domain scores as independent variables and age, sex, and Mini-Mental State Examination scores as covariates. The affective domain score was negatively correlated with rCBF in the prefrontal cortex, thalamus, and caudate. The apathy domain score showed inverse correlations with rCBF in the prefrontal and pre/postcentral gyri and midbrain. Patients with higher hyperactivity domain scores had increased rCBF in the prefrontal and temporal lobes. The psychotic symptom domain was positively correlated with rCBF in the cuneus and negatively associated with rCBF in the prefrontal, cingulate, and occipital regions and putamen. The score of each neuropsychiatric symptom domain showed the differential correlates of brain perfusion, while altered rCBF in the prefrontal cortex was found in all domains. Although preliminary, our results may suggest common and distinct patterns of rCBF underlying neuropsychiatric symptoms in early AD. Further studies with larger samples and control participants are warranted to confirm these findings.

Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome

Down's syndrome results from trisomy of chromosome 21, a genetic change which also confers a probable 100% risk for the development of Alzheimer's disease neuropathology (amyloid plaque and neurofibrillary tangle formation) in later life. We aimed to assess the effectiveness of diffusion-weighted imaging and connectomic modelling for predicting brain amyloid plaque burden, baseline cognition and longitudinal cognitive change using support vector regression. Ninety-five participants with Down's syndrome successfully completed a full Pittsburgh Compound B (PiB) PET-MR protocol and memory assessment at two timepoints. Our findings indicate that graph theory metrics of node degree and strength based on the structural connectome are effective predictors of global amyloid deposition. We also show that connection density of the structural network at baseline is a promising predictor of current cognitive performance. Directionality of effects were mainly significant reductions in the white matter connectivity in relation to both PiB⁺ status and greater rate of cognitive decline. Taken together, these results demonstrate the integral role of the white matter during neuropathological progression and the utility of machine learning methodology for non-invasively evaluating Alzheimer's disease prognosis.

Sex Modifies the Associations of APOEɛ4 with Neuropsychiatric Symptom Burden in Both At-Risk and Clinical Cohorts of Alzheimer's Disease

BACKGROUND

Recent work suggests that APOEɛ4/4 females with Alzheimer's disease (AD) are more susceptible to developing neuropsychiatric symptoms (NPS).

OBJECTIVE

To examine the interaction of sex and APOEɛ4 status on NPS burden using two independent cohorts: 1) patients at risk for AD with mild cognitive impairment and/or major depressive disorder (n = 252) and 2) patients with probable AD (n = 7,261).

METHODS

Regression models examined the interactive effects of sex and APOEɛ4 on the number of NPS experienced and NPS Severity. APOEɛ3/4 and APOEɛ4/4 were pooled in the at-risk cohort due to the sample size.

RESULTS

In the at-risk cohort, there was a significant sex*APOEɛ4 interaction (p = 0.007) such that the association of APOEɛ4 with NPS was greater in females than in males (incident rate ratio (IRR) = 2.0). APOEɛ4/4 females had the most NPS (mean = 1.9) and the highest severity scores (mean = 3.5) of any subgroup. In the clinical cohort, APOEɛ4/4 females had significantly more NPS (IRR = 1.1, p = 0.001, mean = 3.1) and higher severity scores (b = 0.31, p = 0.015, mean = 3.7) than APOEɛ3/3 females (meanNPS = 2.9, meanSeverity = 3.3). No association was found in males.

CONCLUSION

Our study suggests that sex modifies the association of APOEɛ4 on NPS burden. APOEɛ4/4 females may be particularly susceptible to increased NPS burden among individuals with AD and among individuals at risk for AD. Further investigation into the mechanisms behind these associations are needed.

Bridging the Gap Between Morphometric Similarity Mapping and Gene Transcription in Alzheimer's Disease

Disruptions in brain connectivity have been widely reported in Alzheimer’s disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD.

Aberrant Topological Patterns of Structural Covariance Networks in Cognitively Normal Elderly Adults With Mild Behavioral Impairment

Mild behavioral impairment (MBI), characterized by the late-life onset of sustained and meaningful neuropsychiatric symptoms, is increasingly recognized as a prodromal stage of dementia. However, the underlying neural mechanisms of MBI remain unclear. Here, we examined alterations in the topological organization of the structural covariance networks of patients with MBI (N = 32) compared with normal controls (N = 38). We found that the gray matter structural covariance networks of both the patients with MBI and controls exhibited a small-world topology evidenced by sigma value larger than one. The patients with MBI had significantly decreased clustering coefficients at several network densities and local efficiency at densities ranging from 0.05 to 0.26, indicating decreased local segregation. No significant differences in the characteristic path length, gamma value, sigma value, or global efficiency were detected. Locally, the patients with MBI showed significantly decreased nodal betweenness centrality in the left middle frontal gyrus, right inferior frontal gyrus (opercular part), and left Heschl gyrus and increased betweenness centrality in the left gyrus rectus, right insula, bilateral precuneus, and left thalamus. Moreover, the difference in the bilateral precuneus survived after correcting for multiple comparisons. In addition, a different number and distribution of hubs was identified in patients with MBI, showing more paralimbic hubs than observed in the normal controls. In conclusion, we revealed abnormal topological patterns of the structural covariance networks in patients with MBI and offer new insights into the network dysfunctional mechanisms of MBI.