Abnormal Functional Connectivity of Thalamic Subdivisions in Alzheimer's Disease: A Functional Magnetic Resonance Imaging Study

Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Association between Sleep and Alzheimer's Disease: A Bibliometric Analysis from 2003 to 2022

INTRODUCTION

Alzheimer's disease (AD) often presents with sleep disorders, which are also an important risk factor for AD, affecting cognitive function to a certain extent. This study aimed to reveal the current global status, present hotspots, and discuss emerging trends of sleep and AD using a bibliometric approach.

METHODS

Research and review articles related to sleep and AD from 2003 to 2022 were extracted from the Web of Science Core Collection. VOSviewer 1.6.18.0, Scimago Graphica, and CiteSpace 6.2.R2 were used to map the productive and highly cited countries, institutions, journals, authors, references, and keywords in the field.

RESULTS

Overall, 4,008 publications were included in this bibliometric analysis. The number of publications and citations showed an increasing trend over the past two decades. The USA and China had the largest and second largest, respectively, number of publications and citations and cooperated with other countries more closely. Ancoli-Israel Sonia published the most papers, and Holtzman David M was co-cited most frequently. The most productive journal was Journal of Alzheimer's Disease, and Neurology was the most frequently cited journal. The risk factors, β-amyloid (Aβ), tau, neuroinflammation, astrocytes, glymphatic system, orexin, functional connectivity, and management have been the main research directions of researchers over the past few years and may be the future trend of valuable research.

CONCLUSION

We identified hotspots and emerging trends including risk factors, Aβ, tau, neuroinflammation, the glymphatic system, orexin, and management, which may help identify new therapeutic targets and improve clinical efficacy of sleep and AD.

White Matter Changes as an Independent Predictor of Alzheimer's Disease

BACKGROUND

Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer's disease (AD). However, neuroimaging's ability to visualize the underlying functional degradation of the WM region in AD is unclear.

OBJECTIVE

This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD.

METHODS

Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM.

RESULTS

Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%).

CONCLUSION

Our results suggest that WM activity is reduced in AD and can be used for disease classification.