Diffusion Tensor MRI Structural Connectivity and PET Amyloid Burden in Preclinical Autosomal Dominant Alzheimer Disease: The DIAN Cohort.

Background Pathologic evidence of Alzheimer disease (AD) is detectable years before onset of clinical symptoms. Imaging-based identification of structural changes of the brain in people at genetic risk for early-onset AD may provide insights into how genes influence the pathologic cascade that leads to dementia. Purpose To assess structural connectivity differences in cortical networks between cognitively normal autosomal dominant Alzheimer disease (ADAD) mutation carriers versus noncarriers and to determine the cross-sectional relationship of structural connectivity and cortical amyloid burden with estimated years to symptom onset (EYO) of dementia in carriers.

Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer's disease.

The heterogeneity of Alzheimer's disease contributes to the high failure rate of prior clinical trials. We analyzed 5-year longitudinal outcomes and biomarker data from 562 subjects with mild cognitive impairment (MCI) from two national studies (ADNI) using a novel multilayer clustering algorithm. The algorithm identified homogenous clusters of MCI subjects with markedly different prognostic cognitive trajectories.

The Influence of Corticosteroids on Heart Rate Variablity in Acute Cervical Spinal Cord Injury.

Heart rate variability (HRV) gives information on the sympathetic-parasympathetic autonomic balance. The aim of the study was to analyze sympathovagal balance after acute spinal cord injury (SCI), demonstrated by linear measures in time and frequency domain of HRV and to analyze the effect of corticosteroids on HRV parameters in SCI. The study included 40 tetraplegic patients with acute SCI and 40 healthy subjects as control group.

Clusters of male and female Alzheimer's disease patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

This paper presents homogeneous clusters of patients, identified in the Alzheimer's Disease Neuroimaging Initiative (ADNI) data population of 317 females and 342 males, described by a total of 243 biological and clinical descriptors. Clustering was performed with a novel methodology, which supports identification of patient subpopulations that are homogeneous regarding both clinical and biological descriptors. Properties of the constructed clusters clearly demonstrate the differences between female and male Alzheimer's disease patient groups.

Homogeneous clusters of Alzheimer's disease patient population.

Background: Identification of biomarkers for the Alzheimer's disease (AD) is a challenge and a very difficult task both for medical research and data analysis.

Methods: We applied a novel clustering tool with the goal to identify subpopulations of the AD patients that are homogeneous in respect of available clinical as well as in respect of biological descriptors.

Results: The main result is identification of three clusters of patients with significant problems with dementia.