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Abstract Introduction Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer’s disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches. Methods We employed heparin-affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to enrich HBPs from plasma obtained from AD (n = 62) and control (n = 47) samples. These profiles were then correlated to Aβ, tau and phosphorylated tau (pTau) CSF biomarkers and plasma pTau181 from the same individuals, as well as a consensus brain proteome network to assess the overlap with AD brain pathophysiology. Results Heparin enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundant proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude in abundance, were measured across 109 samples. Compared to the consensus AD brain protein co-expression network, we observed that specific plasma proteins exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes, highlighting the complex interplay between the two compartments. Elevated proteins in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate with Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and the APOE4 proteoform. Additionally, heparin-enriched proteins in plasma demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau181. A panel of five plasma proteins classified AD from control individuals with an area under the curve (AUC) of 0.85. When combined with plasma pTau181, the panel significantly improved the classification performance of pTau181 alone, increasing the AUC from 0.93 to 0.98. This suggests that the heparin-enriched plasma proteome captures additional variance in cognitive dementia beyond what is explained by pTau181. Conclusion These findings support the utility of a heparin-affinity approach coupled with TMT-MS for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Abstract Preventative treatment for Alzheimer’s Disease (AD) is dire, yet mechanisms underlying early regional vulnerability remain unknown. In AD, one of the earliest pathophysiological correlates to cognitive decline is hyperexcitability, which is observed first in the entorhinal cortex. Why hyperexcitability preferentially emerges in specific regions in AD is unclear. Using regional, cell-type-specific proteomics and electrophysiology in wild-type mice, we uncovered a unique susceptibility of the entorhinal cortex to human amyloid precursor protein (hAPP). Entorhinal hyperexcitability resulted from selective vulnerability of parvalbumin (PV) interneurons, with respect to surrounding excitatory neurons. This effect was partially replicated with an APP chimera containing a humanized amyloid-beta sequence. EC hyperexcitability could be ameliorated by co-expression of human Tau with hAPP at the expense of increased pathological tau species, or by enhancing PV interneuron excitability in vivo. This study suggests early interventions targeting inhibitory neurons may protect vulnerable regions from the effects of APP/amyloid and tau pathology.

Abstract Objective To define tauopathy‐associated changes in the human gray and white matter proteome. Method We applied tandem mass tagged labeling and mass spectrometry, consensus, and ratio weighted gene correlation network analysis (WGCNA) to gray and white matter sampled from postmortem human dorsolateral prefrontal cortex. The sampled tissues included control as well as Alzheimer's disease, corticobasal degeneration, progressive supranuclear palsy, frontotemporal degeneration with tau pathology, and chronic traumatic encephalopathy. Results Only eight proteins were unique to gray matter while six were unique to white matter. Comparison of the gray and white matter proteome revealed an enrichment of microglial proteins in the white matter. Consensus WGCNA sorted over 6700 protein isoforms into 46 consensus modules across the gray and white matter proteomic networks. Consensus network modules demonstrated unique and shared disease‐associated microglial and endothelial protein changes. Ratio WGCNA sorted over 6500 protein ratios (white:gray) into 33 modules. Modules associated with mitochondrial proteins and processes demonstrated higher white:gray ratios in diseased tissues relative to control, driven by mitochondrial protein downregulation in gray and upregulation in white. Interpretation The dataset is a valuable resource for understanding proteomic changes in human tauopathy gray and white matter. The identification of unique and shared disease‐associated changes across gray and white matter emphasizes the utility of examining both tissue types. Future studies of microglial, endothelial, and mitochondrial changes in white matter may provide novel insights into tauopathy‐associated changes in human brain.

Abstract Lewy body dementia (LBD), a class of disorders comprising Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer’s disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson’s disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or “modules” of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

The French Flooding Prevention Action Program of Saint-Malo, France, requires the assessment of coastal flooding risks and the development of a local flood warning system. The first prerequisite is knowledge of the topography and bathymetry of the bay of Saint-Malo; the acquisition of new multibeam bathymetric data was performed in 2018 and 2019 to increase the resolution of the existing topo-bathymetric datasets and to produce two high-resolution (20 and 5 m) topo-bathymetric digital terrain models. Second, the hydrodynamics associated with coastal flooding were investigated through a dense and extensive oceanographic field experiment conducted during winter 2018–2019 using a network of 22 moorings with 37 sensors: the network included 2 directional buoys, 2 pressure tide gauges, 18 wave pressure gauges, 4 single-point current meters, 7 current profilers, and 4 acoustic wave current profilers from mid-depth (25 m) up to the upper beach and the dike system. The oceanographic dataset thus provides an extended overview of the hydrodynamics and wave processes in the bay of Saint-Malo from the coast up to over-flooding and over-topping areas. This dataset helps to identify the physical drivers of the coastal flooding and provides a quantification of their respective contributions. In particular, the wave processes at the foot of the protection structures can be observed: in this macro-tidal environment, during high spring tides, short and infragravity waves propagate up to the protection structures, while the wave set-up remains negligible, and over-topping by sea packs can occur. The combination of high-resolution topo-bathymetric and oceanographic datasets allows the construction, calibration and validation of a wave and hydrodynamic coupled model that is used to investigate flooding processes more deeply and might be integrated into a future local warning system by means of Saint-Malo inter-communality. The topo-bathymetric and oceanographic datasets are available freely at https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84, https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 and https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO (Shom, 2020a, b, 2021).

Abstract Deregulated apoptosis signaling is characteristic for many cancers and contributes to leukemogenesis and treatment failure in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Apoptosis is controlled by different pro- and anti-apoptotic molecules. Inhibition of anti-apoptotic molecules like B-cell lymphoma 2 (BCL-2) has been developed as therapeutic strategy. Venetoclax (VEN), a selective BCL-2 inhibitor has shown clinical activity in different lymphoid malignancies and is currently evaluated in first clinical trials in BCP-ALL. However, insensitivity to VEN has been described constituting a major clinical concern. Here, we addressed and modeled VEN-resistance in BCP-ALL, investigated the underlying mechanisms in cell lines and patient-derived xenograft (PDX) samples and identified potential strategies to overcome VEN-insensitivity. Leukemia lines with VEN-specific resistance were generated in vitro and further characterized using RNA-seq analysis. Interestingly, gene sets annotated to the citric/tricarboxylic acid cycle and the respiratory electron transport chain were significantly enriched and upregulated, indicating increased mitochondrial metabolism in VEN-resistant ALL. Metabolic profiling showed sustained high mitochondrial metabolism in VEN-resistant lines as compared to control lines. Accordingly, primary PDX-ALL samples with intrinsic VEN-insensitivity showed higher oxygen consumption and ATP production rates, further highlighting that increased mitochondrial activity is a characteristic feature of VEN-resistant ALL. VEN-resistant PDX-ALL showed significant higher mitochondrial DNA content and differed in mitochondria morphology with significantly larger and elongated structures, further corroborating our finding of augmented mitochondrial metabolism upon VEN-resistance. Using Oligomycin, an inhibitor of the complex V/ATPase subunit, we found synergistic activity and apoptosis induction in VEN-resistant BCP-ALL cell lines and PDX samples, demonstrating that acquired and intrinsic VEN-insensitivity can be overcome by co-targeting BCL-2 and the OxPhos pathway. These findings of reprogrammed, high mitochondrial metabolism in VEN-resistance and synergistic activity upon co-targeting BCL-2 and oxidative phosphorylation strongly suggest further preclinical and potential clinical evaluation in VEN-resistant BCP-ALL.

Introduction: Weight bias internalization (WBI) is associated with reduced psychological well-being in individuals with obesity. The aim of this study was to investigate the application of Cohen’s stress-buffering model of social support for WBI on well-being in patients presenting for bariatric surgery. Methods: In N = 804 adult prebariatric patients, WBI, social support, depression severity, health-related quality of life (HRQOL), and self-esteem were assessed by self-report questionnaires. Structural Equation Modeling was applied to test for direct associations between social support and well-being and for a buffering effect of social support on the relationship between WBI and well-being. Results: After controlling for age, sex, and body mass index, greater social support was directly associated with reduced depression severity and increased self-esteem, but not with increased HRQOL. Contrary to Cohen’s stress-buffering model, social support showed no moderating effects on the association between WBI and depression severity, HRQOL, and self-esteem. Conclusion: These cross-sectional results may indicate that greater social support is associated with improved well-being, supporting it as a potential coping resource in bariatric surgery. Given the absence of supporting evidence for the buffering effect in the present study, future prospective research may reevaluate the existence of a moderating effect of social support and investigate whether support-focused interventions improve psychological well-being.

Abstract Due to their exceptional solubility and stability, nanobodies have emerged as powerful building blocks for research tools and therapeutics. However, their generation in llamas is cumbersome and costly. Here, by inserting an engineered llama immunoglobulin heavy chain (IgH) locus into IgH-deficient mice, we generate a transgenic mouse line, which we refer to as ‘LamaMouse’. We demonstrate that LamaMice solely express llama IgH molecules without association to Igκ or λ light chains. Immunization of LamaMice with AAV8, the receptor-binding domain of the SARS-CoV-2 spike protein, IgE, IgG2c, and CLEC9A enabled us to readily select respective target-specific nanobodies using classical hybridoma and phage display technologies, single B cell screening, and direct cloning of the nanobody-repertoire into a mammalian expression vector. Our work shows that the LamaMouse represents a flexible and broadly applicable platform for a facilitated selection of target-specific nanobodies.

Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimers disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimers disease, linking both central and peripheral metabolism, and illustrates the necessity for the omics data integration to uncover associations beyond gene co-expression.