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An abundant presynaptic protein, [alpha]-synuclein, is centrally involved in the pathogenesis of Parkinson's disease. However, conflicting data exist about the normal function of [alpha]-synuclein, possibly because [alpha]-synuclein is redundant with the very similar [beta]-synuclein. To investigate the functions of synucleins systematically, we have now generated single- and double-knockout (KO) mice that lack [alpha]- and/or [beta]-synuclein. We find that deletion of synucleins in mice does not impair basic brain functions or survival. We detected no significant changes in the ultrastructure of synuclein-deficient synapses, in short- or long-term synaptic plasticity, or in the pool size or replenishment of recycling synaptic vesicles. However, protein quantitations revealed that KO of synucleins caused selective changes in two small synaptic signaling proteins, complexins and 14-3-3 proteins. Moreover, we found that dopamine levels in the brains of double-KO but not single-KO mice were decreased by [approximately equal to] 20%. In contrast, serotonin levels were unchanged, and dopamine uptake and release from isolated nerve terminals were normal. These results show that synudeins are not essential components of the basic machinery for neurotransmitter release but may contribute to the long-term regulation and/or maintenance of presynaptic function.

Background: Metabolites are biological compounds reflecting the functional activity of organs and tissues. Understanding metabolic changes in Alzheimer's disease (AD) can provide insight into potential risk factors in this multifactorial disease and suggest new intervention strategies or improve non-invasive diagnosis.Objective: In this study, we searched for changes in AD metabolism in plasma and frontal brain cortex tissue samples and evaluated the performance of plasma measurements as biomarkers.Methods: This is a case-control study with two tissue cohorts: 158 plasma samples (94 AD, 64 controls; Texas Alzheimer's Research and Care Consortium - TARCC) and 71 postmortem cortex samples (35 AD, 36 controls; Banner Sun Health Research Institute brain bank). We performed targeted mass spectrometry analysis of 630 compounds (106 small molecules: UHPLC-MS/MS, 524 lipids: FIA-MS/MS) and 232 calculated metabolic indicators with a metabolomic kit (Biocrates MxP® Quant 500).Results: We discovered disturbances (FDR≤0.05) in multiple metabolic pathways in AD in both cohorts including microbiome-related metabolites with pro-toxic changes, methylhistidine metabolism, polyamines, corticosteroids, omega-3 fatty acids, acylcarnitines, ceramides, and diglycerides. In AD, plasma reveals elevated triglycerides, and cortex shows altered amino acid metabolism. A cross-validated diagnostic prediction model from plasma achieves AUC = 82% (CI95 = 75-88%); for females specifically, AUC = 88% (CI95 = 80-95%). A reduced model using 20 features achieves AUC = 79% (CI95 = 71-85%); for females AUC = 84% (CI95 = 74-92%).Conclusion: Our findings support the involvement of gut environment in AD and encourage targeting multiple metabolic areas in the design of intervention strategies, including microbiome composition, hormonal balance, nutrients, and muscle homeostasis. [ABSTRACT FROM AUTHOR]

The objective of the study was to identify brain structures that mediate reward as evidenced by positive reinforcing effects of stimuli on behavior. Testing by intracerebral self‐stimulation enabled monkeys to inform whether activation of ~2900 sites in 74 structures of 4 sensorimotor pathways and 4 modulatory loop pathways was positive, negative or neutral. Stimulation was rewarding at 30% of sites, negative at 17%, neutral at 52%. Virtually all (99%) structures yielded some positive or negative sites, suggesting a ubiquitous distribution of pathways transmitting valence information. Mapping of sites to structures with dense versus sparse dopaminergic (DA) or noradrenergic (NA) innervation showed that stimulation of DA‐pathways was rewarding or neutral. Stimulation of NA‐pathways was not rewarding. Stimulation of association areas was generally rewarding; stimulation of purely sensory or motor structures was generally negative. Reward related more to structures' sensorimotor function than to density of DA‐innervation. Stimulation of basal ganglia loop pathways was rewarding except in lateral globus pallidus, an inhibitory structure in the negative feedback loop; stimulation of the cerebellar loop was rewarding in anterior vermis and the spinocerebellar pathway; and stimulation of the hippocampal CA1 loop was rewarding. While most positive sites were in the DA reward system, numerous sites in sparsely DA‐innervated posterior cingulate and parietal cortices may represent a separate reward system. DA‐density represents concentrations of plastic synapses that mediate acquisition of new synaptic connections. DA‐sparse areas may represent innate, genetically programmed reward‐associated pathways. Implications of findings in regard to response habituation and addiction are discussed. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. A wide range of putative biological markers for ASD is currently being investigated. Proteomic analyses indicate that the levels of many proteins in plasma/serum are altered in ASD, suggesting that a panel of proteins may provide a blood biomarker for ASD. Serum samples from 76 boys with ASD and 78 typically developing (TD) boys, 18 months-8 years of age, were analyzed to identify possible early biological markers for ASD. Proteomic analysis of serum was performed using SomaLogic's SOMAScanTM assay 1.3K platform. A total of 1,125 proteins were analyzed. There were 86 downregulated proteins and 52 upregulated proteins in ASD (FDR < 0.05). Combining three different algorithms, we found a panel of 9 proteins that identified ASD with an area under the curve (AUC) = 0.8599±0.0640, with specificity and sensitivity of 0.8217±0.1178 and 0.835±0.1176, respectively. All 9 proteins were significantly different in ASD compared with TD boys, and were significantly correlated with ASD severity as measured by ADOS total scores. Using machine learning methods, a panel of serum proteins was identified that may be useful as a blood biomarker for ASD in boys. Further verification of the protein biomarker panel with independent test sets is warranted. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) affects approximately 1 in 68 children in the USA. An ASD blood biomarker may enable early diagnosis and/or identification of new therapeutic targets. Serum samples from ASD and typically developing (TD) boys (n = 30/group) were screened for differences in 110 proteins using a multiplex immunoassay.Results: Eleven proteins were found that together could confirm ASD with modest accuracy using multiple training and test sets. Two of the 11 proteins identified here were further tested using a different detection platform and with a larger sample of ASD and TD boys. The two proteins, thyroid-stimulating hormone (TSH) and interleukin-8 (IL-8), have been previously identified as putative biomarkers for ASD. TSH levels were significantly lower in ASD boys, whereas IL-8 levels were significantly elevated. The diagnostic accuracy for ASD based upon TSH or IL-8 levels alone varied from 74 to 76%, but using both proteins together, the diagnostic accuracy increased to 82%. In addition, TSH levels were negatively correlated with the Autism Diagnostic Observation Schedule subdomain scores.Conclusions: These data suggest that a panel of proteins may be useful as a putative blood biomarker for ASD. [ABSTRACT FROM AUTHOR]

Background: There is a significant need for rapid and cost-effective biomarkers of Alzheimer's disease (AD) for advancement of clinical practice and therapeutic trials. Objective: The aim of the current study was to cross-validate our previously published serum-based algorithm on an independent assay platform as well as validate across tissues and species. Preliminary analyses were conducted to examine the utility in distinguishing AD from non-AD neurological disease (Parkinson's disease, PD). Methods: Serum proteins from our previously published algorithm were quantified from 150 AD cases and 150 controls on the Meso Scale Discovery (MSD) platform. Serum samples were analyzed from 49 PD cases and compared to a random sample of 51 AD cases and 62 controls. Support vector machines (SVM) were used to discriminate PD versus AD versus controls. Human and AD mouse model microvessel images were quantified with HAMAMATSU imaging software. Mouse serum biomarkers were assayed via MSD. Results: Analysis of 21 serum proteins from 150 AD cases and 150 controls yielded an algorithm with sensitivity and specificity of 0.90 for correctly classifying AD. This multi-marker approach was then validated across species and tissue. Assay of the top proteins in human and AD mouse model brain microvessels correctly classified 90-100% of the samples. SVM analyses were highly accurate at distinguishing PD versus AD versus controls. Conclusions: This serum-based biomarker panel should be tested in a community-based setting to determine its utility as a first-line screen for AD and non-AD neurological diseases for primary care providers. [ABSTRACT FROM AUTHOR]

Apoptosis signal-regulating kinase 1 (ASK1), a member of the mitogen-activated protein kinase 3 family, is activated by oxidative stress. The death-signaling pathway mediated by ASK1 is inhibited by DJ-1, which is linked to recessively inherited Parkinson's disease (PD). Considering that DJ-1 deficiency exacerbates the toxicity of the mitochondrial complex I inhibitor 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), we sought to investigate the direct role and mechanism of ASK1 in MPTP-induced dopamine neuron toxicity. In the present study, we found that MPTP administration to wild-type mice activates ASK1 in the midbrain. In ASK1 null mice, MPTP-induced motor impairment was less profound, and striatal dopamine content and nigral dopamine neuron counts were relatively preserved compared to wild-type littermates. Further, microglia and astrocyte activation seen in wild-type mice challenged with MPTP was markedly attenuated in ASK12/2 mice. These data suggest that ASK1 is a key player in MPTP-induced glial activation linking oxidative stress with neuroinflammation, two well recognized pathogenetic factors in PD. These findings demonstrate that ASK1 is an important effector of MPTP-induced toxicity and suggest that inhibiting this kinase is a plausible therapeutic strategy for protecting dopamine neurons in PD. [ABSTRACT FROM AUTHOR]

A high-throughput software pipeline for analyzing high-performance mass spectral data sets has been developed to facilitate rapid and accurate biomarker determination. The software exploits the mass precision and resolution of high-performance instrumentation, bypasses peak-finding steps, and instead uses discrete m/z data points to identify putative biomarkers. The technique is insensitive to peak shape, and works on overlapping and non-Gaussian peaks which can confound peak-finding algorithms. Methods are presented to assess data set quality and the suitability of groups of m/z values that map to peaks as potential biomarkers. The algorithm is demonstrated with serum mass spectra from patients with and without ovarian cancer. Biomarker candidates are identified and ranked by their ability to discriminate between cancer and noncancer conditions. Their discriminating power is tested by classifying unknowns using a simple distance calculation, and a sensitivity of 95.6% and a specificity of 97.1% are obtained. In contrast, the sensitivity of the ovarian cancer blood marker CA125 is ~50% for stage I/II and ~80% for stage III/IV cancers. While the generalizability of these markers is currently unknown, we have demonstrated the ability of our analytical package to extract biomarker candidates from high-performance mass spectral data. [ABSTRACT FROM AUTHOR]