Serum osteopontin negatively impacts on intima-media thickness in patients with systemic lupus erythematosus

BACKGROUND Ultrasound evaluation of carotid intima-media thickness (cIMT) has been extensively used for potentially improving cardiovascular (CV) risk stratification in several patients' categories. Subjects with systemic lupus erythematosus (SLE) have been investigated by both imaging and molecular biomarker approaches with contrasting results. Here, we focused on the role of osteopontin (OPN) as biomarker of subclinical atherosclerosis associated with SLE. MATERIALS AND METHODS Eighty females (age 18-65 years) affected by SLE and eighty age-matched healthy female controls without a clinical history of CV disease underwent ultrasound evaluation of cIMT and blood sample assay of high-sensitivity C-reactive protein (hs-CRP) and OPN. RESULTS Healthy controls and SLE patients significantly differed for CV risk factors (ie, waist circumference, hypertension and dyslipidaemia) and the inflammatory status. Noteworthy, an opposite association between cIMT and OPN was observed in the two study groups. Whereas OPN was positively associated with mean cIMT (r = 0.364; P = 0.001) in SLE patients, a negative correlation was found in healthy controls. Furthermore, in SLE patients increased circulating levels of OPN were associated with the use of hydroxychloroquine and the positivity for the anti-dsDNA autoantibodies. At linear regression analysis, only OPN remained independently associated with cIMT also after adjustment for age, smoking pack-year, Heart SCORE, disease length and steroid therapy length. CONCLUSIONS These results indicate that serum OPN levels were strongly associated with subclinical atherosclerosis in patients with LES and it might be a useful CV biomarker that requires additional validation in larger trials

The metabolic signature of C9ORF72-related ALS: FDG PET comparison with nonmutated patients

Purpose Recently, a GGGGCC hexanucleotide repeat expansion in the C9ORF72 gene, located on chromosome 9p21 has been demonstrated to be the commonest cause of familial amyotrophic lateral sclerosis (ALS) and to account for 5 to 10 % of apparently sporadic ALS. Relatively little is known about the brain metabolism profile of patients carrying the expansion. Our aim was to identify the [18F]FDG PET profile in ALS patients with the C9ORF72 expansion (C9ORF72-ALS). Methods Fifteen C9ORF72-ALS patients were compared with 12 patients with ALS and comorbid frontotemporal dementia (FTD) without the C9ORF72 expansion (ALSFTD) and 30 cognitively normal patients with ALS without mutations of ALS-related genes (sALS). The three groups were then cross-matched to 40 neurologically normal controls. All patients underwent FDG PET within 4 months of diagnosis. Results The C9ORF72-ALS patients compared with the sALS patients showed significant hypometabolism in the anterior and posterior cingulate cortex, insula, caudate and thalamus, the left frontal and superior temporal cortex, and hypermetabolism in the midbrain, bilateral occipital cortex, globus pallidus and left inferior temporal cortex. The ALS FTD patients compared with the sALS patients showed more limited hypometabolic areas, including the orbitofrontal, prefrontal, anterior cingulate and insular cortex, and hypermetabolic areas, including the bilateral occipital cortex, the left precentral and postcentral cortex and superior temporal gyrus. The C9ORF72-ALS patients compared with the ALS-FTD patients showed hypometabolism in the left temporal cortex. Conclusion ALS patients with the C9ORF72 hexanucleotide repeat expansion had a more widespread central nervous system involvement than ALS patients without genetic mutations, with or without comorbid FTD, consistent with their more severe clinical picture

Brain hypermetabolism in amyotrophic lateral sclerosis: A FDG PET study in ALS of spinal and bulbar onset.

Abstract Purpose To identify the neurobiological traits of amyotrophic lateral sclerosis (ALS) and to elucidate functional differences between ALS of spinal and bulbar onset. We hypothesized that glucose metabolism distribution might vary between groups. Methods The study groups comprised 32 patients with ALS of either bulbar (n=13) or spinal (n=19) onset and 22 subjects as controls. They were investigated by [ 18 F]fluorodeoxyglucose (FDG) positron emission tomography (FDG PET), comparing the patient groups with each other and with the controls by statistical parametric mapping. Results Highly significant relative increases in glucose metabolism distribution were found in the group comprising all 32 ALS patients as compared with the controls in the bilateral amygdalae, midbrain, pons and cerebellum. Relative hypermetabolism was also found in patients with spinal onset as compared with the controls in the right midbrain. In patients with bulbar onset compared with the controls and with patients with spinal onset, large relatively hypometabolic areas were found in the bilateral frontal cortex, right insula, anterior cingulate, precuneus and inferior parietal lobe. Patients with spinal onset had significantly higher scores in a neuropsychological test assessing verbal fluency compared with patients with bulbar onset. Conclusion This large FDG PET investigation provided unprecedented evidence of relatively increased metabolism in the amygdalae, midbrain and pons in ALS patients as compared with control subjects, possibly due to local activation of astrocytes and microglia. Highly significant relative decreases in metabolism were found in large frontal and parietal regions in the bulbar onset patients as compared with the spinal onset patients and the controls, suggesting a differential metabolic and neuropsychological state between the two conditions

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones

Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage

Vos et al. compare the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage based on the IWG-1, IWG-2 and NIA-AA criteria. All three aid identification of early Alzheimer's disease, but combining amyloid and neuronal injury markers according to the NIA-AA criteria offers the most accurate prognosi

Biomarker counseling, disclosure of diagnosis and follow-up in patients with mild cognitive impairment:A European Alzheimer's Disease Consortium survey

Objectives: Mild cognitive impairment (MCI) is associated with an increased risk of further cognitive decline, partly depending on demographics and biomarker status. The aim of the present study was to survey the clinical practices of physicians in terms of biomarker counseling, management, and follow-up in European expert centers diagnosing patients with MCI. Methods: An online email survey was distributed to physicians affiliated with European Alzheimer's disease Consortium centers (Northern Europe: 10 centers; Eastern and Central Europe: 9 centers; and Southern Europe: 15 centers) with questions on attitudes toward biomarkers and biomarker counseling in MCI and dementia. This included postbiomarker counseling and the process of diagnostic disclosure of MCI, as well as treatment and follow-up in MCI. Results: The response rate for the survey was 80.9% (34 of 42 centers) across 20 countries. A large majority of physicians had access to biomarkers and found them useful. Pre- and postbiomarker counseling varied across centers, as did practices for referral to support groups and advice on preventive strategies. Less than half reported discussing driving and advance care planning with patients with MCI. Conclusions: The variability in clinical practices across centers calls for better biomarker counseling and better training to improve communication skills. Future initiatives should address the importance of communicating preventive strategies and advance planning

What Electrophysiology Tells Us About Alzheimer’s Disease::A Window into the Synchronization and Connectivity of Brain Neurons

Electrophysiology provides a real-time readout of neural functions and network capability in different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and macro) scales unmet by other methodologies. However, current international guidelines do not endorse the use of electroencephalographic (EEG)/magnetoencephalographic (MEG) biomarkers in clinical trials performed in patients with Alzheimer’s disease (AD), despite a surge in recent validated evidence. This Position Paper of the ISTAART Electrophysiology Professional Interest Area endorses consolidated and translational electrophysiological techniques applied to both experimental animal models of AD and patients, to probe the effects of AD neuropathology (i.e., brain amyloidosis, tauopathy, and neurodegeneration) on neurophysiological mechanisms underpinning neural excitation/inhibition and neurotransmission as well as brain network dynamics, synchronization, and functional connectivity reflecting thalamocortical and cortico-cortical residual capacity. Converging evidence shows relationships between abnormalities in EEG/MEG markers and cognitive deficits in groups of AD patients at different disease stages. The supporting evidence for the application of electrophysiology in AD clinical research as well as drug discovery pathways warrants an international initiative to include the use of EEG/MEG biomarkers in the main multicentric projects planned in AD patients, to produce conclusive findings challenging the present regulatory requirements and guidelines for AD studies