BACE1 and SCD1 are associated with neurodegeneration.

Introduction: Proteolytic processing of amyloid protein precursor by ß-site secretase enzyme (BACE1) is dependent on the cellular lipid composition and is affected by endomembrane trafficking in dementia and Alzheimer's disease (AD). Stearoyl-CoA desaturase 1 (SCD1) is responsible for the synthesis of fatty acid monounsaturation (MUFAs), whose accumulation is strongly associated with cognitive dysfunction. Methods: In this study, we analyzed the relationship between BACE1 and SCD1 in vivo and in vitro neurodegenerative models and their association in familial AD (FAD), sporadic AD (SAD), and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) using microscopy, biochemical, and mass SPECT approach. Results: Our findings showed that BACE1 and SCD1 immunoreactivities were increased and colocalized in astrocytes of the hippocampus in a rat model of global cerebral ischemia (2-VO). A synergistic effect of double BACE1/SCD1 silencing on the recovery of motor and cognitive functions was obtained. This neuroprotective regulation involved the segregation of phospholipids (PLs) associated with polyunsaturated fatty acids in the hippocampus, cerebrospinal fluid, and serum. The double silencing in the sham and ischemic groups was stronger in the serum, inducing an inverse ratio between total phosphatydilcholine (PC) and lysophosphatidylcholine (LPC), represented mainly by the reduction of PC 38:4 and PC 36:4 and an increase in LPC 16:0 and LPC 18:0. Furthermore, PC 38:4 and PC:36:4 levels augmented in pathological conditions in in vitro AD models. BACE1 and SCD1 increases were confirmed in the hippocampus of FAD, SAD, and CADASIL. Conclusion: Therefore, the findings suggest a novel convergence of BACE-1 and SCD1 in neurodegeneration, related to pro-inflammatory phospholipids.

Common disbalance in the brain parenchyma of dementias: Phospholipid profile analysis between CADASIL and sporadic Alzheimer's disease.

Sporadic Alzheimer's disease (SAD) is the most common form of dementia, and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most frequent hereditary ischemic small vessel disease of the brain. Relevant biomarkers or specific metabolic signatures could provide powerful tools to manage these diseases. Therefore, the main goal of this study was to compare the postmortem frontal cortex gray matter, white matter and cerebrospinal fluid (CSF) between a cognitively healthy group and CADASIL and SAD groups. We evaluated 352 individual lipids, belonging to 13 lipid classes/subclasses, using mass spectrometry, and the lipid profiles were subjected to multivariate analysis to discriminate between the dementia groups (CADASIL and SAD) and healthy controls. The main lipid molecular species showing greater discrimination by partial least squares-discriminant analysis (PLS-DA) and a higher significance multivariate correlation (sMC) index were as follows: phosphatidylserine (PS) PS(44:7) and lysophosphatidylethanolamine (LPE) LPE(18:2) in gray matter (GM); phosphatidylethanolamine (PE) PE(32:2) and phosphatidylcholine PC PC(44:6) in white matter (WM), and ether PE (ePE) ePE(38:2) and ether PC (ePC) ePC(34:3) in CSF. Common phospholipid molecular species were obtained in both dementias, such as PS(44:7) and lyso PC (LPC) LPC(22:5) in GM, PE(32:2) in WM and phosphatidic acid (PA) PA(38:5) and PC(42:7) in CFS. Our exploratory study suggests that phospholipids (PLs) involved in neurotransmission alteration, connectivity impairment and inflammation response in GM, WM and CSF are a transversal phenomenon affecting dementias such as CADASIL and SAD independent of the etiopathogenesis, thus providing a possible common prodromal phospholipidic biomarker of dementia.

Inverse Phosphatidylcholine/Phosphatidylinositol Levels as Peripheral Biomarkers and Phosphatidylcholine/Lysophosphatidylethanolamine-Phosphatidylserine as Hippocampal Indicator of Postischemic Cognitive Impairment in Rats.

Vascular dementia is a transversal phenomenon in different kinds of neurodegenerative diseases involving acute and chronic brain alterations. Specifically, the role of phospholipids in the pathogenesis of dementia remains unknown. In the present study, we explored phospholipid profiles a month postischemia in cognitively impaired rats. The two-vessel occlusion (2-VO) model was used to generate brain parenchyma ischemia in adult male rats confirmed by alterations in myelin, endothelium, astrocytes and inflammation mediator. A lipidomic analysis was performed via mass spectrometry in the hippocampus and serum a month postischemia. We found decreases in phospholipids (PLs) associated with neurotransmission, such as phosphatidylcholine (PC 32:0, PC 34:2, PC 36:3, PC 36:4, and PC 42:1), and increases in PLs implied in membrane structure and signaling, such as lysophosphatidylethanolamine (LPE 18:1, 20:3, and 22:6) and phosphatidylserine (PS 38:4, 36:2, and 40:4), in the hippocampus. Complementarily, PC (PC 34:2, PC 34:3, PC 38:5, and PC 36:5) and ether-PC (ePC 34:1, 34:2, 36:2, 38:2, and 38:3) decreased, while Lyso-PC (LPC 18:0, 18:1, 20:4, 20:5, and LPC 22:6) and phosphatidylinositol (PI 36:2, 38:4, 38:5, and 40:5), as neurovascular state sensors, increased in the serum. Taken together, these data suggest inverse PC/LPC-PI levels as peripheral biomarkers and inverse PC/LPE-PS as a central indicator of postischemic cognitive impairment in rats.

Differential Pattern of Phospholipid Profile in the Temporal Cortex from E280A-Familiar and Sporadic Alzheimer's Disease Brains.

Lipids are considered important factors in the pathogenesis of Alzheimer's disease (AD). In this study, we realized a comparative analysis of the phospholipid profile and phospholipid composition of the temporal cortex from E280A-familiar AD (FAD), sporadic AD (SAD), and healthy human brains. Findings showed a significant decrease of lysophosphatidylcholine and phosphatidylethanolamine formed by low levels of polyunsaturated fatty acids (20 : 4, 22 : 6) in AD brains. However, phosphatidylethanolamine-ceramide and phosphoglycerol were significantly increased in SAD, conformed by high levels of (18 : 0/18 : 1) and (30/32/36 : 0/1/2), respectively. Together, the findings suggest a deficiency in lysophosphacholine and phosphatidylethanolamine, and alteration in the balance between poly- and unsaturated fatty acids in both types of AD, and a differential pattern of phospholipid profile and fatty acid composition between E280A FAD and SAD human brains.

Characterization Methods for the Detection of Multiple Voice Disorders: Neurological, Functional, and Laryngeal Diseases.

This paper evaluates the accuracy of different characterization methods for the automatic detection of multiple speech disorders. The speech impairments considered include dysphonia in people with Parkinson's disease (PD), dysphonia diagnosed in patients with different laryngeal pathologies (LP), and hypernasality in children with cleft lip and palate (CLP). Four different methods are applied to analyze the voice signals including noise content measures, spectral-cepstral modeling, nonlinear features, and measurements to quantify the stability of the fundamental frequency. These measures are tested in six databases: three with recordings of PD patients, two with patients with LP, and one with children with CLP. The abnormal vibration of the vocal folds observed in PD patients and in people with LP is modeled using the stability measures with accuracies ranging from 81% to 99% depending on the pathology. The spectral-cepstral features are used in this paper to model the voice spectrum with special emphasis around the first two formants. These measures exhibit accuracies ranging from 95% to 99% in the automatic detection of hypernasal voices, which confirms the presence of changes in the speech spectrum due to hypernasality. Noise measures suitably discriminate between dysphonic and healthy voices in both databases with speakers suffering from LP. The results obtained in this study suggest that it is not suitable to use every kind of features to model all of the voice pathologies; conversely, it is necessary to study the physiology of each impairment to choose the most appropriate set of features.

On combining information from modulation spectra and mel-frequency cepstral coefficients for automatic detection of pathological voices.

This work presents a novel approach for the automatic detection of pathological voices based on fusing the information extracted by means of mel-frequency cepstral coefficients (MFCC) and features derived from the modulation spectra (MS). The system proposed uses a two-stepped classification scheme. First, the MFCC and MS features were used to feed two different and independent classifiers; and then the outputs of each classifier were used in a second classification stage. In order to establish the best configuration which provides the highest accuracy in the detection, the fusion of information was carried out employing different classifier combination strategies. The experiments were carried out using two different databases: the one developed by The Massachusetts Eye and Ear Infirmary Voice Laboratory, and a database recorded by the Universidad Politécnica de Madrid. The results show that the combination of MFCC and MS features employing the proposed approach yields an improvement in the detection accuracy, demonstrating that both methods of parameterization are complementary.