Towards a Pharmacophore for Amyloid

Diagnosing and treating Alzheimer's and other diseases associated with amyloid fibers remains a great challenge despite intensive research. To aid in this effort, we present atomic structures of fiber-forming segments of proteins involved in Alzheimer's disease in complex with small molecule binders, determined by X-ray microcrystallography. The fiber-like complexes consist of pairs of β-sheets, with small molecules binding between the sheets, roughly parallel to the fiber axis. The structures suggest that apolar molecules drift along the fiber, consistent with the observation of nonspecific binding to a variety of amyloid proteins. In contrast, negatively charged orange-G binds specifically to lysine side chains of adjacent sheets. These structures provide molecular frameworks for the design of diagnostics and drugs for protein aggregation diseases

A chronic fatigue syndrome – related proteome in human cerebrospinal fluid

BACKGROUND: Chronic Fatigue Syndrome (CFS), Persian Gulf War Illness (PGI), and fibromyalgia are overlapping symptom complexes without objective markers or known pathophysiology. Neurological dysfunction is common. We assessed cerebrospinal fluid to find proteins that were differentially expressed in this CFS-spectrum of illnesses compared to control subjects. METHODS: Cerebrospinal fluid specimens from 10 CFS, 10 PGI, and 10 control subjects (50 μl/subject) were pooled into one sample per group (cohort 1). Cohort 2 of 12 control and 9 CFS subjects had their fluids (200 μl/subject) assessed individually. After trypsin digestion, peptides were analyzed by capillary chromatography, quadrupole-time-of-flight mass spectrometry, peptide sequencing, bioinformatic protein identification, and statistical analysis. RESULTS: Pooled CFS and PGI samples shared 20 proteins that were not detectable in the pooled control sample (cohort 1 CFS-related proteome). Multilogistic regression analysis (GLM) of cohort 2 detected 10 proteins that were shared by CFS individuals and the cohort 1 CFS-related proteome, but were not detected in control samples. Detection of ≥1 of a select set of 5 CFS-related proteins predicted CFS status with 80% concordance (logistic model). The proteins were α-1-macroglobulin, amyloid precursor-like protein 1, keratin 16, orosomucoid 2 and pigment epithelium-derived factor. Overall, 62 of 115 proteins were newly described. CONCLUSION: This pilot study detected an identical set of central nervous system, innate immune and amyloidogenic proteins in cerebrospinal fluids from two independent cohorts of subjects with overlapping CFS, PGI and fibromyalgia. Although syndrome names and definitions were different, the proteome and presumed pathological mechanism(s) may be shared

The clinical application of proteomics

Proteins are key regulators of the biochemistry of cells and, therefore, in the maintenance of good health. It is important to both identify and quantify the proteins that are causative of a particular pathology since this information can inform the clinician as to both the selection of the correct treatment and monitor the success of its use. In the previous chapter, we described the methods used to analyse proteins. Here we turn our attention to the application of proteomics in the clinical context, outline the markers currently in use and describe in more depth several examples of proteins of clinical importance.</p

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein–coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology

Best practice in healthcare environment decontamination

There is now strong evidence that surface contamination is linked to healthcare-associated infections (HCAIs). Cleaning and disinfection should be sufficient to decrease the microbial bioburden from surfaces in healthcare settings, and, overall, help in decreasing infections. It is, however, not necessarily the case. Evidence suggests that there is a link between educational interventions and a reduction in infections. To improve the overall efficacy and appropriate usage of disinfectants, manufacturers need to engage with the end users in providing clear claim information and product usage instructions. This review provides a clear analysis of the scientific evidence supporting the role of surfaces in HCAIs and the role of education in decreasing such infections. It also examines the debate opposing the use of cleaning versus disinfection in healthcare settings