Evidence for bystander signalling between human trophoblast cells and human embryonic stem cells

Maternal exposure during pregnancy to toxins can occasionally lead to miscarriage and malformation. It is currently thought that toxins pass through the placental barrier, albeit bilayered in the first trimester, and damage the fetus directly, albeit at low concentration. Here we examined the responses of human embryonic stem (hES) cells in tissue culture to two metals at low concentration. We compared direct exposures with indirect exposures across a bi-layered model of the placenta cell barrier. Direct exposure caused increased DNA damage without apoptosis or a loss of cell number but with some evidence of altered differentiation. Indirect exposure caused increased DNA damage and apoptosis but without loss of pluripotency. This was not caused by metal ions passing through the barrier. Instead the hES cells responded to signalling molecules (including TNF-α) secreted by the barrier cells. This mechanism was dependent on connexin 43 mediated intercellular ‘bystander signalling’ both within and between the trophoblast barrier and the hES colonies. These results highlight key differences between direct and indirect exposure of hES cells across a trophoblast barrier to metal toxins. It offers a theoretical possibility that an indirectly mediated toxicity of hES cells might have biological relevance to fetal development

Test-retest reliability and longitudinal analysis of automated hippocampal subregion volumes in healthy ageing and Alzheimer’s disease populations

The hippocampal formation is a complex brain structure that is important in cognitive processes such as memory, mood, reward processing and other executive functions. Histological and neuroimaging studies have implicated the hippocampal region in neuropsychiatric disorders as well as in neurodegenerative diseases. This highly plastic limbic region is made up of several subregions that are believed to have different functional roles. Therefore, there is a growing interest in imaging the subregions of the hippocampal formation rather than modelling the hippocampus as a homogenous structure, driving the development of new automated analysis tools. Consequently, there is a pressing need to understand the stability of the measures derived from these new techniques. In this study, an automated hippocampal subregion segmentation pipeline, released as a developmental version of Freesurfer (v6.0), was applied to T1-weighted magnetic resonance imaging (MRI) scans of 22 healthy older participants, scanned on 3 separate occasions and a separate longitudinal dataset of 40 Alzheimer’s disease (AD) patients. Test-retest reliability of hippocampal subregion volumes was assessed using the intra-class correlation coefficient (ICC), percentage volume difference and percentage volume overlap (Dice). Sensitivity of the regional estimates to longitudinal change was estimated using linear mixed effects (LME) modelling. The results show that out of the twenty four hippocampal subregions, twenty had ICC scores of 0.9 or higher in both samples; these regions include the molecular layer, granule cell layer of the dentate gyrus, CA1, CA3 and the subiculum (ICC > 0.9), whilst the hippocampal fissure and fimbria had lower ICC scores (0.73-0.88). Furthermore, LME analysis of the independent AD dataset demonstrated sensitivity to group and individual differences in the rate of volume change over time in several hippocampal subregions (CA1, molecular layer, CA3, hippocampal tail, fissure and presubiculum). These results indicate that this automated segmentation method provides a robust method with which to measure hippocampal subregions, and may be useful in tracking disease progression and measuring the effects of pharmacological intervention

Time Trends of Cerebrospinal Fluid Biomarkers of Neurodegeneration in Idiopathic Normal Pressure Hydrocephalus

Background: Longitudinal changes in cerebrospinal fluid (CSF) biomarkers are seldom studied. Furthermore, data on biomarker gradient between lumbar (L-) and ventricular (V-) compartments seems to be discordant. Objective: To examine alteration of CSF biomarkers reflecting Alzheimer's disease (AD)-related amyloid-beta (A beta) aggregation, tau pathology, neurodegeneration, and early synaptic degeneration by CSF shunt surgery in idiopathic normal pressure hydrocephalus (iNPH) in relation to AD-related changes in brain biopsy. In addition, biomarker levels in L- and V-CSF were compared. Methods: L-CSF was collected prior to shunt placement and, together with V-CSF, 3-73 months after surgery. Thereafter, additional CSF sampling took place at 3, 6, and 18 months after the baseline sample from 26 iNPH patients with confirmed A beta plaques in frontal cortical brain biopsy and 13 iNPH patients without A beta pathology. CSF Amyloid-beta(42) (A beta(42)), total tau (T-tau), phosphorylated tau (P-tau(181)), neurofilament light (NFL), and neurogranin (NRGN) were analyzed with customized ELISAs. Results: All biomarkers but A beta(42) increased notably by 140-810% in L-CSF after CSF diversion and then stabilized. A beta(42) instead showed divergent longitudinal decrease between A beta-positive and -negative patients in L-CSF, and thereafter increase in A beta-negative iNPH patients in both L- and V-CSF. All five biomarkers correlated highly between V-CSF and L-CSF (A beta(42) R = 0.87, T-tau R = 0.83, P-tau R = 0.92, NFL R = 0.94, NRGN R = 0.9; all p < 0.0001) but were systematically lower in V-CSF (A beta(42) 14 %, T-tau 22%, P-tau 20%, NFL 32%, NRGN 19%). With APOE genotype-grouping, only A beta(42) showed higher concentration in non-carriers of allele epsilon 4. Conclusion: Longitudinal follow up shows that after an initial post-surgery increase, T-tau, P-tau, and NRGN are stable in iNPH patients regardless of brain biopsy A beta pathology, while NFL normalized toward its pre-shunt levels. A beta(42) as biomarker seems to be the least affected by the surgical procedure or shunt and may be the best predictor of AD risk in iNPH patients. All biomarker concentrations were lower in V-than L-CSF yet showing strong correlations.Peer reviewe

Involvement of the choroid plexus in Alzheimer’s disease pathophysiology: findings from mouse and human proteomic studies

Background: Structural and functional changes of the choroid plexus (ChP) have been reported in Alzheimer’s disease (AD). Nonetheless, the role of the ChP in the pathogenesis of AD remains largely unknown. We aim to unravel the relation between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans. Methods: We used an APP knock-in mouse model, APPNL-G-F, exhibiting amyloid pathology, to study the association between AD brain pathology and protein changes in mouse ChP tissue and CSF using liquid chromatography mass spectrometry. Mouse proteomes were investigated at the age of 7 weeks (n = 5) and 40 weeks (n = 5). Results were compared with previously published human AD CSF proteomic data (n = 496) to identify key proteins and pathways associated with ChP changes in AD. Results: ChP tissue proteome was dysregulated in APPNL-G-F mice relative to wild-type mice at both 7 and 40 weeks. At both ages, ChP tissue proteomic changes were associated with epithelial cells, mitochondria, protein modification, extracellular matrix and lipids. Nonetheless, some ChP tissue proteomic changes were different across the disease trajectory; pathways related to lysosomal function, endocytosis, protein formation, actin and complement were uniquely dysregulated at 7 weeks, while pathways associated with nervous system, immune system, protein degradation and vascular system were uniquely dysregulated at 40 weeks. CSF proteomics in both mice and humans showed similar ChP-related dysregulated pathways. Conclusions: Together, our findings support the hypothesis of ChP dysfunction in AD. These ChP changes were related to amyloid pathology. Therefore, the ChP could become a novel promising therapeutic target for AD

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways