Proteomic investigations of adult polyglucosan body disease: insights into the pathobiology of a neurodegenerative disorder

Inadequate glycogen branching enzyme 1 (GBE1) activity results in different forms of glycogen storage disease type IV, including adult polyglucosan body disorder (APBD). APBD is clinically characterized by adult-onset development of progressive spasticity, neuropathy, and neurogenic bladder and is histologically characterized by the accumulation of structurally abnormal glycogen (polyglucosan bodies) in multiple cell types. How insufficient GBE1 activity causes the disease phenotype of APBD is poorly understood. We hypothesized that proteomic analysis of tissue from GBE1-deficient individuals would provide insights into GBE1-mediated pathobiology. In this discovery study, we utilized label-free LC–MS/MS to quantify the proteomes of lymphoblasts from 3 persons with APBD and 15 age- and gender-matched controls, with validation of the findings by targeted MS. There were 531 differentially expressed proteins out of 3,427 detected between APBD subjects vs. controls, including pronounced deficiency of GBE1. Bioinformatic analyses indicated multiple canonical pathways and protein–protein interaction networks to be statistically markedly enriched in APBD subjects, including: RNA processing/transport/translation, cell cycle control/replication, mTOR signaling, protein ubiquitination, unfolded protein and endoplasmic reticulum stress responses, glycolysis and cell death/apoptosis. Dysregulation of these processes, therefore, are primary or secondary factors in APBD pathobiology in this model system. Our findings further suggest that proteomic analysis of GBE1 mutant lymphoblasts can be leveraged as part of the screening for pharmaceutical agents for the treatment of APBD

Metabolomic analysis of obesity, metabolic syndrome, and type 2 diabetes: amino acid and acylcarnitine levels change along a spectrum of metabolic wellness

Background Metabolic syndrome (MS) is a construct used to separate “healthy” from “unhealthy” obese patients, and is a major risk factor for type 2 diabetes (T2D) and cardiovascular disease. There is controversy over whether obese “metabolically well” persons have a higher morbidity and mortality than lean counterparts, suggesting that MS criteria do not completely describe physiologic risk factors or consequences of obesity. We hypothesized that metabolomic analysis of plasma would distinguish obese individuals with and without MS and T2D along a spectrum of obesity-associated metabolic derangements, supporting metabolomic analysis as a tool for a more detailed assessment of metabolic wellness than currently used MS criteria. Methods Fasting plasma samples from 90 adults were assigned to groups based on BMI and ATP III criteria for MS: (1) lean metabolically well (LMW; n = 24); (2) obese metabolically well (OBMW; n = 26); (3) obese metabolically unwell (OBMUW; n = 20); and (4) obese metabolically unwell with T2D (OBDM; n = 20). Forty-one amino acids/dipeptides, 33 acylcarnitines and 21 ratios were measured. Obesity and T2D effects were analyzed by Wilcoxon rank-sum tests comparing obese nondiabetics vs LMW, and OBDM vs nondiabetics, respectively. Metabolic unwellness was analyzed by Jonckheere-Terpstra trend tests, assuming worsening health from LMW → OBMW → OBMUW. To adjust for multiple comparisons, statistical significance was set at p < 0.005. K-means cluster analysis of aggregated amino acid and acylcarnitine data was also performed. Results Analytes and ratios significantly increasing in obesity, T2D, and with worsening health include: branched-chain amino acids (BCAAs), cystine, alpha-aminoadipic acid, phenylalanine, leucine + lysine, and short-chain acylcarnitines/total carnitines. Tyrosine, alanine and propionylcarnitine increase with obesity and metabolic unwellness. Asparagine and the tryptophan/large neutral amino acid ratio decrease with T2D and metabolic unwellness. Malonylcarnitine decreases in obesity and 3-OHbutyrylcarnitine increases in T2D; neither correlates with unwellness. Cluster analysis did not separate subjects into discreet groups based on metabolic wellness. Discussion Levels of 15 species and metabolite ratios trend significantly with worsening metabolic health; some are newly recognized. BCAAs, aromatic amino acids, lysine, and its metabolite, alpha-aminoadipate, increase with worsening health. The lysine pathway is distinct from BCAA metabolism, indicating that biochemical derangements associated with MS involve pathways besides those affected by BCAAs. Even those considered “obese, metabolically well” had metabolite levels which significantly trended towards those found in obese diabetics. Overall, this analysis yields a more granular view of metabolic wellness than the sole use of cardiometabolic MS parameters. This, in turn, suggests the possible utility of plasma metabolomic analysis for research and public health applications

Dravet syndrome patient‐derived neurons suggest a novel epilepsy mechanism

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99647/1/ana23897.pd

Mitochondrial Disease in Autism Spectrum Disorder Patients: A Cohort Analysis

Previous reports indicate an association between autism spectrum disorders (ASD) and disorders of mitochondrial oxidative phosphorylation. One study suggested that children with both diagnoses are clinically indistinguishable from children with idiopathic autism. There are, however, no detailed analyses of the clinical and laboratory findings in a large cohort of these children. Therefore, we undertook a comprehensive review of patients with ASD and a mitochondrial disorder.We reviewed medical records of 25 patients with a primary diagnosis of ASD by DSM-IV-TR criteria, later determined to have enzyme- or mutation-defined mitochondrial electron transport chain (ETC) dysfunction. Twenty-four of 25 patients had one or more major clinical abnormalities uncommon in idiopathic autism. Twenty-one patients had histories of significant non-neurological medical problems. Nineteen patients exhibited constitutional symptoms, especially excessive fatigability. Fifteen patients had abnormal neurological findings. Unusual developmental phenotypes included marked delay in early gross motor milestones (32%) and unusual patterns of regression (40%). Levels of blood lactate, plasma alanine, and serum ALT and/or AST were increased at least once in 76%, 36%, and 52% of patients, respectively. The most common ETC disorders were deficiencies of complex I (64%) and complex III (20%). Two patients had rare mtDNA mutations of likely pathogenicity.Although all patients' initial diagnosis was idiopathic autism, careful clinical and biochemical assessment identified clinical findings that differentiated them from children with idiopathic autism. These and prior data suggest a disturbance of mitochondrial energy production as an underlying pathophysiological mechanism in a subset of individuals with autism

Brain Transcriptional and Epigenetic Associations with Autism

<div><h3>Background</h3><p>Autism is a common neurodevelopmental syndrome. Numerous rare genetic etiologies are reported; most cases are idiopathic.</p> <h3>Methodology/Principal Findings</h3><p>To uncover important gene dysregulation in autism we analyzed carefully selected idiopathic autistic and control cerebellar and BA19 (occipital) brain tissues using high resolution whole genome gene expression and whole genome DNA methylation microarrays. No changes in DNA methylation were identified in autistic brain but gene expression abnormalities in two areas of metabolism were apparent: down-regulation of genes of mitochondrial oxidative phosphorylation and of protein translation. We also found associations between specific behavioral domains of autism and specific brain gene expression modules related to myelin/myelination, inflammation/immune response and purinergic signaling.</p> <h3>Conclusions/Significance</h3><p>This work highlights two largely unrecognized molecular pathophysiological themes in autism and suggests differing molecular bases for autism behavioral endophenotypes.</p> </div

No differential methylation of genomic DNA was identified between control and autism cerebellar cortex or BA19 cortex.

<p>(<b>A</b>) Unsupervised correspondence analysis of genome-wide CpG methylation in control and autism cerebellar cortex and BA19 cerebral cortex demonstrates that brain region and age are associated with the largest two sources of variability, respectively, in the data. The first two principal components are listed on the x- and y-axis respectively, with percent of variance explained in parentheses. Bubbles correspond to individual samples with area proportional to age of subject, bubble outline to region, and color to phenotype. (<b>B</b>) Percent of genome-wide methylated probes in cerebellar cortex or BA19 cortex in control and autism samples. Error bars represent standard deviations. There was no significant difference in global methylation between autism vs control cerebellum or BA19 cortex. There was a significant difference between brain regions, as expected (alpha = 0.05; Wilcoxon rank-sum test). (<b>C</b>) Pyrosequencing of bisulfite-treated DNA. Percent methylation at individual CpG dinucleotides is reported in cerebellar cortex samples (n ≥7 per group) for <i>a priori</i> candidate genes suspected to exhibit differential methylation. X-axis represents locus relative to transcription start site. Error bars represent standard deviations.</p

Autistic brain shows transcriptional heterogeneity and differential expression of genes of mitochondrial oxidative phosphorylation and protein translation.

<p>(<b>A</b>) Unsupervised correspondence analysis of whole-genome transcriptome expression data demonstrates that brain region is associated with the greatest source of variability in the data. The second principal component is associated with variability mostly among autistic samples. The first two principal components are listed on the x- and y-axis respectively, with percent of variance explained in parentheses. Bubbles represent individual samples, with area proportional to age, outline to brain region, and color to phenotype. (<b>B</b>) Heatmap of the top 50 differentially expressed probes between autistic and control brain, accounting for brain region, separates most autistic brains from controls (FDR ≤5%). Rows correspond to probes and columns to samples. The dendrogram represents sample similarity on the basis of the top 50 differentially expressed probes. Probes with log₂-fold change >0.7 are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044736#pone.0044736.s007" target="_blank">table S3</a>. (<b>C</b>) The top 300 differentially expressed probes are enriched for gene ontology annotation clusters corresponding to mitochondrial oxidative phosphorylation and protein translation. ADI-R, Autism Diagnostic Interview-Revised; BA19, Brodmann area 19; CER, cerebellum; PMI, postmortem interval.</p