Fast and robust recombinant protein production utilizing episomal stable pools in WAVE bioreactors

Protein reagents are essential resources for several stages of drug discovery projects from structural biology and assay development through lead optimization. Depending on the aim of the project different amounts of pure protein are required. Small-scale expressions are initially used to determine the reachable levels of production and quality before scaling up protein reagent supply. Commonly, amounts of several hundreds of milligrams to grams are needed for different experiments, including structural investigations and activity evaluations, which require rather large cultivation volumes. This implies that cultivation of large volumes of either transiently transfected cells or stable pools/stable cell lines is needed. Hence, a production process that is scalable, speeds up the development projects, and increases the robustness of protein reagent quality throughout scales. Here we present a protein production pipeline with high scalability. We show that our protocols for protein production in Chinese hamster ovary cells allow for a seamless and efficient scale-up with robust product quality and high performance. The flexible scale of the production process, as shown here, allows for shorter lead times in drug discovery projects where there is a reagent demand for a specific protein or a set of target proteins.

Plasma proteomics for prediction of subclinical coronary artery calcifications in primary prevention

BACKGROUND AND AIMS

Recent developments in high-throughput proteomic technologies enable the discovery of novel biomarkers of coronary atherosclerosis. The aims of this study were to test if plasma protein subsets could detect coronary artery calcifications (CAC) in asymptomatic individuals and if they add predictive value beyond traditional risk factors.

METHODS

Using proximity extension assays, 1,342 plasma proteins were measured in 1,827 individuals from the Impaired Glucose Tolerance and Microbiota (IGTM) study and 883 individuals from the Swedish Cardiopulmonary BioImage Study (SCAPIS) aged 50-64 years without history of ischaemic heart disease and with CAC assessed by computed tomography. After data-driven feature selection, extreme gradient boosting machine learning models were trained on the IGTM cohort to predict the presence of CAC using combinations of proteins and traditional risk factors. The trained models were validated in SCAPIS.

RESULTS

The best plasma protein subset (44 proteins) predicted CAC with an area under the curve (AUC) of 0.691 in the validation cohort. However, this was not better than prediction by traditional risk factors alone (AUC = 0.710, P = .17). Adding proteins to traditional risk factors did not improve the predictions (AUC = 0.705, P = .6). Most of these 44 proteins were highly correlated with traditional risk factors.

CONCLUSIONS

A plasma protein subset that could predict the presence of subclinical CAC was identified but it did not outperform nor improve a model based on traditional risk factors. Thus, support for this targeted proteomics platform to predict subclinical CAC beyond traditional risk factors was not found.

Arachidonic acid and docosahexaenoic acid levels correlate with the inflammation proteome in extremely preterm infants

BACKGROUND & AIM

Clinical trials supplementing the long-chain polyunsaturated fatty acids (LCPUFAs) docosahexaenoic acid (DHA) and arachidonic acid (AA) to preterm infants have shown positive effects on inflammation-related morbidities, but the molecular mechanisms underlying these effects are not fully elucidated. This study aimed to determine associations between DHA, AA, and inflammation-related proteins during the neonatal period in extremely preterm infants.

METHODS

A retrospective exploratory study of infants (n = 183) born below 28 weeks gestation from the Mega Donna Mega trial, a randomized multicenter trial designed to study the effect of DHA and AA on retinopathy of prematurity. Serial serum samples were collected after birth until postnatal day 100 (median 7 samples per infant) and analyzed for phospholipid fatty acids and proteins using targeted proteomics covering 538 proteins. Associations over time between LCPUFAs and proteins were explored using mixed effect modeling with splines, including an interaction term for time, and adjusted for gestational age, sex, and center.

RESULTS

On postnatal day one, 55 proteins correlated with DHA levels and 10 proteins with AA levels. Five proteins were related to both fatty acids, all with a positive correlation. Over the first 100 days after birth, we identified 57 proteins to be associated with DHA and/or AA. Of these proteins, 41 (72%) related to inflammation. Thirty-eight proteins were associated with both fatty acids and the overall direction of association did not differ between DHA and AA, indicating that both LCPUFAs similarly contribute to up- and down-regulation of the preterm neonate inflammatory proteome. Primary examples of this were the inflammation-modulating cytokines IL-6 and CCL7, both being negatively related to levels of DHA and AA in the postnatal period.

CONCLUSIONS

This study supports postnatal non-antagonistic and potentially synergistic effects of DHA and AA on the inflammation proteome in preterm infants, indicating that supplementation with both fatty acids may contribute to limiting the disease burden in this vulnerable population.

CLINICAL REGISTRATION NUMBER

ClinicalTrials.gov (NCT03201588).

Combined Metabolic Activators with Different NAD+ Precursors Improve Metabolic Functions in the Animal Models of Neurodegenerative Diseases

BACKGROUND

Mitochondrial dysfunction and metabolic abnormalities are acknowledged as significant factors in the onset of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Our research has demonstrated that the use of combined metabolic activators (CMA) may alleviate metabolic dysfunctions and stimulate mitochondrial metabolism. Therefore, the use of CMA could potentially be an effective therapeutic strategy to slow down or halt the progression of PD and AD. CMAs include substances such as the glutathione precursors (L-serine and N-acetyl cysteine), the NAD+ precursor (nicotinamide riboside), and L-carnitine tartrate.

METHODS

Here, we tested the effect of two different formulations, including CMA1 (nicotinamide riboside, L-serine, N-acetyl cysteine, L-carnitine tartrate), and CMA2 (nicotinamide, L-serine, N-acetyl cysteine, L-carnitine tartrate), as well as their individual components, on the animal models of AD and PD. We assessed the brain and liver tissues for pathological changes and immunohistochemical markers. Additionally, in the case of PD, we performed behavioral tests and measured responses to apomorphine-induced rotations.

FINDINGS

Histological analysis showed that the administration of both CMA1 and CMA2 formulations led to improvements in hyperemia, degeneration, and necrosis in neurons for both AD and PD models. Moreover, the administration of CMA2 showed a superior effect compared to CMA1. This was further corroborated by immunohistochemical data, which indicated a reduction in immunoreactivity in the neurons. Additionally, notable metabolic enhancements in liver tissues were observed using both formulations. In PD rat models, the administration of both formulations positively influenced the behavioral functions of the animals.

INTERPRETATION

Our findings suggest that the administration of both CMA1 and CMA2 markedly enhanced metabolic and behavioral outcomes, aligning with neuro-histological observations. These findings underscore the promise of CMA2 administration as an effective therapeutic strategy for enhancing metabolic parameters and cognitive function in AD and PD patients.

A human stomach cell type transcriptome atlas

BACKGROUND

The identification of cell type-specific genes and their modification under different conditions is central to our understanding of human health and disease. The stomach, a hollow organ in the upper gastrointestinal tract, provides an acidic environment that contributes to microbial defence and facilitates the activity of secreted digestive enzymes to process food and nutrients into chyme. In contrast to other sections of the gastrointestinal tract, detailed descriptions of cell type gene enrichment profiles in the stomach are absent from the major single-cell sequencing-based atlases.

RESULTS

Here, we use an integrative correlation analysis method to predict human stomach cell type transcriptome signatures using unfractionated stomach RNAseq data from 359 individuals. We profile parietal, chief, gastric mucous, gastric enteroendocrine, mitotic, endothelial, fibroblast, macrophage, neutrophil, T-cell, and plasma cells, identifying over 1600 cell type-enriched genes.

CONCLUSIONS

We uncover the cell type expression profile of several non-coding genes strongly associated with the progression of gastric cancer and, using a sex-based subset analysis, uncover a panel of male-only chief cell-enriched genes. This study provides a roadmap to further understand human stomach biology.

Substance P, NPY, CCK and their receptors in five brain regions in major depressive disorder with transcriptomic analysis of locus coeruleus neurons

Major depressive disorder (MDD) is a serious disease and a burden to patients, families and society. Rodent experiments and human studies suggest that several neuropeptide systems are involved in mood regulation. The aim of this study is two-fold: (i) to monitor, with qPCR, transcript levels of the substance P/tachykinin (TAC), NPY and CCK systems in bulk samples from control and suicide subjects, targeting five postmortem brain regions including locus coeruleus (LC); and (ii) to analyse expression of neuropeptide family transcripts in LC neurons of 'normal' postmortem brains by using laser capture microdissection with Smart-Seq2 RNA sequencing. qPCR revealed distinct regional expression patterns in male and female controls with higher levels for the TAC system in the dorsal raphe nucleus and LC, versus higher transcripts levels of the NPY and CCK systems in prefrontal cortex. In suicide patients, TAC, TAC receptors and a few NPY family transcript levels were increased mainly in prefrontal cortex and LC. The second study on 'normal' noradrenergic LC neurons revealed expression of transcripts for GAL, NPY, TAC1, CCK, and TACR1 and many other peptides (e.g. Cerebellin4 and CARTPT) and receptors (e.g. Adcyap1R1 and GPR173). These data and our previous results on suicide brains indicates that the tachykinin and galanin systems may be valid targets for developing antidepressant medicines. Moreover, the perturbation of neuropeptide systems in MDD patients, and the detection of further neuropeptide and receptor transcripts in LC, shed new light on signalling in noradrenergic LC neurons and on mechanisms possibly associated with mood disorders.

Expanding the GPCR-RAMP interactome

Receptor activity-modifying proteins (RAMPs) can form complexes with G protein-coupled receptors (GPCRs) and regulate their cellular trafficking and pharmacology. RAMP interactions have been identified for about 50 GPCRs, but only a few GPCR-RAMP complexes have been studied in detail. To elucidate a complete interactome between GPCRs and the three RAMPs, we developed a customized library of 215 Dual Epitope-Tagged (DuET) GPCRs representing all GPCR subfamilies. Using a multiplexed suspension bead array (SBA) assay, we identified 122 GPCRs that showed strong evidence for interaction with at least one RAMP. We screened for native interactions in three cell lines and found 23 GPCRs that formed complexes with RAMPs. Mapping the GPCR-RAMP interactome expands the current system-wide functional characterization of RAMP-interacting GPCRs to inform the design of selective GPCR-targeted therapeutics.

One-Sentence Summary

Novel complexes between G protein-coupled receptors and interacting proteins point to a system-wide regulation of GPCR function.

Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy

MOTIVATION

Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA).

RESULTS

We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/XinmengLiao/Open_MoA.

Characterization of an in vitro steatosis model simulating activated de novo lipogenesis in MAFLD patients

Activated de novo lipogenesis (DNL) is the critical pathway involved in the progression of metabolic-associated fatty liver disease (MAFLD). We present an in vitro steatosis model for MAFLD that induces steatosis through activated DNL. This model utilizes insulin and LXR receptor ligand T0901317, eliminating the need for fatty acid treatment. Significant increases in triglycerides (TAGs) and expression of DNL-related transcription factors were observed. Transcriptomic analysis revealed distinct gene expression profiles between the DNL and conventional oleic acid (OA)-induced steatosis model. DNL steatosis model exhibited elevated pathways related to glycolysis, cholesterol homeostasis, and bile acid metabolism, reflecting its clinical relevance to MAFLD. Moreover, C75 and JNK-IN-5A compounds effectively reduced TAG accumulation and steatosis-related protein expression in the DNL model, whereas they had no significant impact on TAG accumulation in the OA model. In conclusion, we introduce an ideal model for steatosis study, which could help in understanding the MAFLD mechanisms.

Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma

Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation

Cell lines are valuable resources as model for human biology and translational medicine. It is thus important to explore the concordance between the expression in various cell lines vis-à-vis human native and disease tissues. In this study, we investigate the expression of all human protein-coding genes in more than 1,000 human cell lines representing 27 cancer types by a genome-wide transcriptomics analysis. The cell line gene expression is compared with the corresponding profiles in various tissues, organs, single-cell types and cancers. Here, we present the expression for each cell line and give guidance for the most appropriate cell line for a given experimental study. In addition, we explore the cancer-related pathway and cytokine activity of the cell lines to aid human biology studies and drug development projects. All data are presented in an open access cell line section of the Human Protein Atlas to facilitate the exploration of all human protein-coding genes across these cell lines.

The acute effect of different NAD+ precursors included in the combined metabolic activators

NAD+ and glutathione precursors are currently used as metabolic modulators for improving the metabolic conditions associated with various human diseases, including non-alcoholic fatty liver disease, neurodegenerative diseases, mitochondrial myopathy, and age-induced diabetes. Here, we performed a one-day double blinded, placebo-controlled human clinical study to assess the safety and acute effects of six different Combined Metabolic Activators (CMAs) with 1 g of different NAD+ precursors based on global metabolomics analysis. Our integrative analysis showed that the NAD+ salvage pathway is the main source for boosting the NAD+ levels with the administration of CMAs without NAD+ precursors. We observed that incorporation of nicotinamide (Nam) in the CMAs can boost the NAD+ products, followed by niacin (NA), nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN), but not flush free niacin (FFN). In addition, the NA administration led to a flushing reaction, accompanied by decreased phospholipids and increased bilirubin and bilirubin derivatives, which could be potentially risky. In conclusion, this study provided a plasma metabolomic landscape of different CMA formulations, and proposed that CMAs with Nam, NMN as well as NR can be administered for boosting NAD+ levels to improve altered metabolic conditions.

The development of blood protein profiles in extremely preterm infants follows a stereotypic evolution pattern

BACKGROUND

Preterm birth is the leading cause of neonatal mortality and morbidity. Early diagnosis and interventions are critical to improving the clinical outcomes of extremely premature infants. Blood protein profiling during the first months of life in preterm infants can shed light on the role of early extrauterine development and provide an increased understanding of maturation after extremely preterm birth and the underlying mechanisms of prematurity-related disorders.

METHODS

We have investigated the blood protein profiles during the first months of life in preterm infants on the role of early extrauterine development. The blood protein levels were analyzed using next generation blood profiling on 1335 serum samples, collected longitudinally at nine time points from birth to full-term from 182 extremely preterm infants.

RESULTS

The protein analysis reveals evident predestined serum evolution patterns common for all included infants. The majority of the variations in blood protein expression are associated with the postnatal age of the preterm infants rather than any other factors. There is a uniform protein pattern on postnatal day 1 and after 30 weeks postmenstrual age (PMA), independent of gestational age (GA). However, during the first month of life, GA had a significant impact on protein variability.

CONCLUSIONS

The unified pattern of protein development for all included infants suggests an age-dependent stereotypic development of blood proteins after birth. This knowledge should be considered in neonatal settings and might alter the clinical approach within neonatology, where PMA is today the most dominant age variable.

Next generation pan-cancer blood proteome profiling using proximity extension assay

A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers

BACKGROUND

Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.

METHODS

Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).

RESULTS

Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.

CONCLUSIONS

These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism

Venous thromboembolism (VTE) is a common, multi-causal disease with potentially serious short- and long-term complications. In clinical practice, there is a need for improved plasma biomarker-based tools for VTE diagnosis and risk prediction. Here we show, using proteomics profiling to screen plasma from patients with suspected acute VTE, and several case-control studies for VTE, how Complement Factor H Related 5 protein (CFHR5), a regulator of the alternative pathway of complement activation, is a VTE-associated plasma biomarker. In plasma, higher CFHR5 levels are associated with increased thrombin generation potential and recombinant CFHR5 enhanced platelet activation in vitro. GWAS analysis of ~52,000 participants identifies six loci associated with CFHR5 plasma levels, but Mendelian randomization do not demonstrate causality between CFHR5 and VTE. Our results indicate an important role for the regulation of the alternative pathway of complement activation in VTE and that CFHR5 represents a potential diagnostic and/or risk predictive plasma biomarker.

Longitudinal metabolomics analysis reveals the acute effect of cysteine and NAC included in the combined metabolic activators

Growing evidence suggests that the depletion of plasma NAD⁺ and glutathione (GSH) may play an important role in the development of metabolic disorders. The administration of Combined Metabolic Activators (CMA), consisting of GSH and NAD⁺ precursors, has been explored as a promising therapeutic strategy to target multiple altered pathways associated with the pathogenesis of the diseases. Although studies have examined the therapeutic effect of CMA that contains N-acetyl-l-cysteine (NAC) as a metabolic activator, a system-wide comparison of the metabolic response to the administration of CMA with NAC and cysteine remains lacking. In this placebo-controlled study, we studied the acute effect of the CMA administration with different metabolic activators, including NAC or cysteine with/without nicotinamide or flush free niacin, and performed longitudinal untargeted-metabolomics profiling of plasma obtained from 70 well-characterized healthy volunteers. The time-series metabolomics data revealed the metabolic pathways affected after the administration of CMAs showed high similarity between CMA containing nicotinamide and NAC or cysteine as metabolic activators. Our analysis also showed that CMA with cysteine is well-tolerated and safe in healthy individuals throughout the study. Last, our study systematically provided insights into a complex and dynamics landscape involved in amino acid, lipid and nicotinamide metabolism, reflecting the metabolic responses to CMA administration containing different metabolic activators.

Multiplexed selectivity screening of anti-GPCR antibodies

G protein-coupled receptors (GPCRs) control critical cellular signaling pathways. Therapeutic agents including anti-GPCR antibodies (Abs) are being developed to modulate GPCR function. However, validating the selectivity of anti-GPCR Abs is challenging because of sequence similarities among individual receptors within GPCR subfamilies. To address this challenge, we developed a multiplexed immunoassay to test >400 anti-GPCR Abs from the Human Protein Atlas targeting a customized library of 215 expressed and solubilized GPCRs representing all GPCR subfamilies. We found that ~61% of Abs tested were selective for their intended target, ~11% bound off-target, and ~28% did not bind to any GPCR. Antigens of on-target Abs were, on average, significantly longer, more disordered, and less likely to be buried in the interior of the GPCR protein than the other Abs. These results provide important insights into the immunogenicity of GPCR epitopes and form a basis for designing therapeutic Abs and for detecting pathological auto-Abs against GPCRs.

Display of a naïve affibody library on staphylococci for selection of binders by means of flow cytometry sorting

Within the field of combinatorial protein engineering there is a great demand for robust high-throughput selection platforms that allow for unbiased protein library display, affinity-based screening, and amplification of selected clones. We have previously described the development of a staphylococcal display system used for displaying both alternative-scaffolds and antibody-derived proteins. In this study, the objective was to generate an improved expression vector for displaying and screening a high-complexity naïve affibody library, and to facilitate downstream validation of isolated clones. A high-affinity normalization tag, consisting of two ABD-moieties, was introduced to simplify off-rate screening procedures. In addition, the vector was furnished with a TEV protease substrate recognition sequence upstream of the protein library which enables proteolytic processing of the displayed construct for improved binding signal. In the library design, 13 of the 58 surface-exposed amino acid positions were selected for full randomization (except proline and cysteine) using trinucleotide technology. The genetic library was successfully transformed to Staphylococcus carnosus cells, generating a protein library exceeding 10⁹ members. De novo selections against three target proteins (CD14, MAPK9 and the affibody Z_EGFR:2377) were successfully performed using magnetic bead-based capture followed by flow-cytometric sorting, yielding affibody molecules binding their respective target with nanomolar affinity. Taken together, the results demonstrate the feasibility of the staphylococcal display system and the proposed selection procedure to generate new affibody molecules with high affinity.

Targeted proteomics using stable isotope labeled protein fragments enables precise and robust determination of total apolipoprotein(a) in human plasma

Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.

Combined metabolic activators improve metabolic functions in the animal models of neurodegenerative diseases

BACKGROUND

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are associated with metabolic abnormalities. Integrative analysis of human clinical data and animal studies have contributed to a better understanding of the molecular and cellular pathways involved in the progression of NDDs. Previously, we have reported that the combined metabolic activators (CMA), which include the precursors of nicotinamide adenine dinucleotide and glutathione can be utilized to alleviate metabolic disorders by activating mitochondrial metabolism.

METHODS

We first analysed the brain transcriptomics data from AD patients and controls using a brain-specific genome-scale metabolic model (GEM). Then, we investigated the effect of CMA administration in animal models of AD and PD. We evaluated pathological and immunohistochemical findings of brain and liver tissues. Moreover, PD rats were tested for locomotor activity and apomorphine-induced rotation.

FINDINGS

Analysis of transcriptomics data with GEM revealed that mitochondrial dysfunction is involved in the underlying molecular pathways of AD. In animal models of AD and PD, we showed significant damage in the high-fat diet groups' brain and liver tissues compared to the chow diet. The histological analyses revealed that hyperemia, degeneration and necrosis in neurons were improved by CMA administration in both AD and PD animal models. These findings were supported by immunohistochemical evidence of decreased immunoreactivity in neurons. In parallel to the improvement in the brain, we also observed dramatic metabolic improvement in the liver tissue. CMA administration also showed a beneficial effect on behavioural functions in PD rats.

INTERPRETATION

Overall, we showed that CMA administration significantly improved behavioural scores in parallel with the neurohistological outcomes in the AD and PD animal models and is a promising treatment for improving the metabolic parameters and brain functions in NDDs.

Combined metabolic activators improve cognitive functions in Alzheimer's disease patients: a randomised, double-blinded, placebo-controlled phase-II trial

BACKGROUND

Alzheimer's disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administered combined metabolic activators (CMA) to the AD rat model and observed that CMA improves the AD-associated histological parameters in the animals. CMA promotes mitochondrial fatty acid uptake from the cytosol, facilitates fatty acid oxidation in the mitochondria, and alleviates oxidative stress.

METHODS

Here, we designed a randomised, double-blinded, placebo-controlled phase-II clinical trial and studied the effect of CMA administration on the global metabolism of AD patients. One-dose CMA included 12.35 g L-serine (61.75%), 1 g nicotinamide riboside (5%), 2.55 g N-acetyl-L-cysteine (12.75%), and 3.73 g L-carnitine tartrate (18.65%). AD patients received one dose of CMA or placebo daily during the first 28 days and twice daily between day 28 and day 84. The primary endpoint was the difference in the cognitive function and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. A comprehensive plasma metabolome and proteome analysis was also performed to evaluate the efficacy of the CMA in AD patients.

RESULTS

We showed a significant decrease of AD Assessment Scale-cognitive subscale (ADAS-Cog) score on day 84 vs day 0 (P = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant decline (P = 0.0073) in ADAS-Cog scores (improvement of cognitive functions) in the CMA compared to the placebo group in patients with higher ADAS-Cog scores. Improved cognitive functions in AD patients were supported by the relevant alterations in the hippocampal volumes and cortical thickness based on imaging analysis. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism were significantly improved after CMA treatment.

CONCLUSION

Our results indicate that treatment of AD patients with CMA can lead to enhanced cognitive functions and improved clinical parameters associated with phenomics, metabolomics, proteomics and imaging analysis. Trial registration ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131.

An easy-to-use high-throughput selection system for the discovery of recombinant protein binders from alternative scaffold libraries

Selection by phage display is a popular and widely used technique for the discovery of recombinant protein binders from large protein libraries for therapeutic use. The protein library is displayed on the surface of bacteriophages which are amplified using bacteria, preferably Escherichia coli, to enrich binders in several selection rounds. Traditionally, the so-called panning procedure during which the phages are incubated with the target protein, washed and eluted is done manually, limiting the throughput. High-throughput systems with automated panning already in use often require high-priced equipment. Moreover, the bottleneck of the selection process is usually the screening and characterization. Therefore, having a high-throughput panning procedure without a scaled screening platform does not necessarily increase the discovery rate. Here, we present an easy-to-use high-throughput selection system with automated panning using cost-efficient equipment integrated into a workflow with high-throughput sequencing and a tailored screening step using biolayer-interferometry. The workflow has been developed for selections using two recombinant libraries, ADAPT (Albumin-binding domain-derived affinity proteins) and CaRA (Calcium-regulated affinity) and has been evaluated for three new targets. The newly established semi-automated system drastically reduced the hands-on time and increased robustness while the selection outcome, when compared to manual handling, was very similar in deep sequencing analysis and generated binders in the nanomolar affinity range. The developed selection system has shown to be highly versatile and has the potential to be applied to other binding domains for the discovery of new protein binders.

CaRA - A multi-purpose phage display library for selection of calcium-regulated affinity proteins

Protein activity regulated by interactions with metal ions can be utilized for many different purposes, including biological therapies and bioprocessing, among others. Calcium ions are known to interact with the frequently occurring EF-hand motif, which can alter protein activity upon binding through an induced conformational change. The calcium-binding loop of the EF-hand motif has previously been introduced into a small protein domain derived from staphylococcal Protein A in a successful effort to render antibody binding dependent on calcium. Presented here, is a combinatorial library for calcium-regulated affinity, CaRA, based on this domain. CaRA is the first alternative scaffold library designed to achieve novel target specificities with metal-dependent binding. From this library, several calcium-dependent binders could be isolated through phage display campaigns towards a set of unrelated target proteins (IgE Cε3-Cε4, TNFα, IL23, scFv, tPA, PCSK9 and HER3) useful for distinct applications. Overall, these monomeric CaRA variants showed high stability and target affinities within the nanomolar range. They displayed considerably higher melting temperatures in the presence of 1 mM calcium compared to without calcium. Further, all discovered binders proved to be calcium-dependent, with the great majority showing complete lack of target binding in the absence of calcium. As demonstrated, the CaRA library is highly capable of providing protein-binding domains with calcium-dependent behavior, independent of the type of target protein. These binding domains could subsequently be of great use in gentle protein purification or as novel therapeutic modalities.

Addressing the Protease Bias in Quantitative Proteomics

Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02–70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow.

Machine Learning Analysis Reveals Biomarkers for the Detection of Neurological Diseases

It is critical to identify biomarkers for neurological diseases (NLDs) to accelerate drug discovery for effective treatment of patients of diseases that currently lack such treatments. In this work, we retrieved genotyping and clinical data from 1,223 UK Biobank participants to identify genetic and clinical biomarkers for NLDs, including Alzheimer's disease (AD), Parkinson's disease (PD), motor neuron disease (MND), and myasthenia gravis (MG). Using a machine learning modeling approach with Monte Carlo randomization, we identified a panel of informative diagnostic biomarkers for predicting AD, PD, MND, and MG, including classical liver disease markers such as alanine aminotransferase, alkaline phosphatase, and bilirubin. A multinomial model trained on accessible clinical markers could correctly predict an NLD diagnosis with an accuracy of 88.3%. We also explored genetic biomarkers. In a genome-wide association study of AD, PD, MND, and MG patients, we identified single nucleotide polymorphisms (SNPs) implicated in several craniofacial disorders such as apnoea and branchiootic syndrome. We found evidence for shared genetic risk loci among NLDs, including SNPs in cancer-related genes and SNPs known to be associated with non-brain cancers such as Wilms tumor, leukemia, and colon cancer. This indicates overlapping genetic characterizations among NLDs which challenges current clinical definitions of the neurological disorders. Taken together, this work demonstrates the value of data-driven approaches to identify novel biomarkers in the absence of any known or promising biomarkers.

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

Dynamics of the normal gut microbiota: A longitudinal one-year population study in Sweden

Temporal dynamics of the gut microbiota potentially limit the identification of microbial features associated with health status. Here, we used whole-genome metagenomic and 16S rRNA gene sequencing to characterize the intra- and inter-individual variations of gut microbiota composition and functional potential of a disease-free Swedish population (n = 75) over one year. We found that 23% of the total compositional variance was explained by intra-individual variation. The degree of intra-individual compositional variability was negatively associated with the abundance of Faecalibacterium prausnitzii (a butyrate producer) and two Bifidobacterium species. By contrast, the abundance of facultative anaerobes and aerotolerant bacteria such as Escherichia coli and Lactobacillus acidophilus varied extensively, independent of compositional stability. The contribution of intra-individual variance to the total variance was greater for functional pathways than for microbial species. Thus, reliable quantification of microbial features requires repeated samples to address the issue of intra-individual variations of the gut microbiota.

Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disease involving alterations in multiple biological processes regulated by the interactions between obesity, genetic background, and environmental factors including the microbiome. To decipher hepatic steatosis (HS) pathogenesis by excluding critical confounding factors including genetic variants and diabetes, 56 heterogenous MAFLD patients are characterized by generating multiomics data including oral and gut metagenomics as well as plasma metabolomics and inflammatory proteomics data. The dysbiosis in the oral and gut microbiome is explored and the host-microbiome interactions based on global metabolic and inflammatory processes are revealed. These multiomics data are integrated using the biological network and HS's key features are identified using multiomics data. HS is finally predicted using these key features and findings are validated in a follow-up cohort, where 22 subjects with varying degree of HS are characterized.

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer

Simple Summary

Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4–7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort.

Abstract

Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Polymorphisms in alpha 7 nicotinic acetylcholine receptor gene, CHRNA7, and its partially duplicated gene, CHRFAM7A, associate with increased inflammatory response in human peripheral mononuclear cells

The vagus nerve can, via the alpha 7 nicotinic acetylcholine receptor (α7nAChR), regulate inflammation. The gene coding for the α7nAChR, CHRNA7, can be partially duplicated, that is, CHRFAM7A, which is reported to impair the anti-inflammatory effect mediated via the α7nAChR. Several single nucleotide polymorphisms (SNPs) have been described in both CHRNA7 and CHRFAM7A, however, the functional role of these SNPs for immune responses remains to be investigated. In the current study, we set out to investigate whether genetic variants of CHRNA7 and CHRFAM7A can influence immune responses. By investigating data available from the Swedish SciLifeLab SCAPIS Wellness Profiling (S3WP) study, in combination with droplet digital PCR and freshly isolated PBMCs from the S3WP participants, challenged with lipopolysaccharide (LPS), we show that CHRNA7 and CHRFAM7A are expressed in human PBMCs, with approximately four times higher expression of CHRFAM7A compared with CHRNA7. One SNP in CHRFAM7A, rs34007223, is positively associated with hsCRP in healthy individuals. Furthermore, gene ontology (GO)-terms analysis of plasma proteins associated with gene expression of CHRNA7 and CHRFAM7A demonstrated an involvement for these genes in immune responses. This was further supported by in vitro data showing that several SNPs in both CHRNA7 and CHRFAM7A are significantly associated with cytokine response. In conclusion, genetic variants of CHRNA7 and CHRFAM7A alters cytokine responses. Furthermore, given that CHRFAM7A SNP rs34007223 is associated with inflammatory marker hsCRP in healthy individuals suggests that CHRFAM7A may have a more pronounced role in regulating inflammatory processes in humans than previously been recognized.

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

Longitudinal Serum Metabolomics in Extremely Premature Infants: Relationships With Gestational Age, Nutrition, and Morbidities

An increasing number of extremely premature infants survive the neonatal period and beyond. Little is known about the maturation of the preterm infant’s metabolome and its relation to the development of morbidities. Using 1H-NMR, we investigated the serum metabolic profile of 87 infants born at a gestational age (GA) <28 weeks [mean GA (SD) 25.4 (1.4) weeks] in samples longitudinally collected from birth to term equivalent age. The infant metabolome was analyzed in relation to GA, postnatal age, nutrition, and preterm morbidities. At postnatal day 1, low GA correlated with high levels of 3-hydroxyisobutyrate, acetate, acetoacetate, acetone, formate, glucose, and valine. Nearly all quantified metabolites displayed postnatal concentration changes. For example, the two phospholipid-related metabolites myo-inositol and ethanolamine displayed a similar decline from birth over the first weeks of life, irrespectively of GA. The proportion of enteral/parenteral energy intake in the first 28 days significantly correlated with mean levels of 52% of the analyzed metabolites. Low enteral energy intake was associated with high serum levels of 3-hydroxyisobutyrate, creatinine, glucose, glycerol, histidine, lactate, leucine, lysine, methionine, ornithine, phenylalanine, proline, threonine, and uridine. There were also significant correlations between high enteral intake and high serum levels of isoleucine and tyrosine. Retinopathy of prematurity (ROP) and bronchopulmonary dysplasia (BPD) outcomes were not significantly associated with metabolite levels in the neonatal period after correcting for multiple testing. In conclusion, the serum metabolome of extremely premature infants changes substantially in the neonatal period, largely driven by the gradual transfer from total parenteral nutrition to full enteral feeding. Further studies are needed to disentangle the intricate relationships between the metabolome, nutritional management, GA, and the development of preterm morbidities.

Blood protein profiles related to preterm birth and retinopathy of prematurity

BACKGROUND

Nearly one in ten children is born preterm. The degree of immaturity is a determinant of the infant's health. Extremely preterm infants have higher morbidity and mortality than term infants. One disease affecting extremely preterm infants is retinopathy of prematurity (ROP), a multifactorial neurovascular disease that can lead to retinal detachment and blindness. The advances in omics technology have opened up possibilities to study protein expressions thoroughly with clinical accuracy, here used to increase the understanding of protein expression in relation to immaturity and ROP.

METHODS

Longitudinal serum protein profiles the first months after birth in 14 extremely preterm infants were integrated with perinatal and ROP data. In total, 448 unique protein targets were analyzed using Proximity Extension Assays.

RESULTS

We found 20 serum proteins associated with gestational age and/or ROP functioning within mainly angiogenesis, hematopoiesis, bone regulation, immune function, and lipid metabolism. Infants with severe ROP had persistent lower levels of several identified proteins during the first postnatal months.

CONCLUSIONS

The study contributes to the understanding of the relationship between longitudinal serum protein levels and immaturity and abnormal retinal neurovascular development. This is essential for understanding pathophysiological mechanisms and to optimize diagnosis, treatment and prevention for ROP.

IMPACT

Longitudinal protein profiles of 14 extremely preterm infants were analyzed using a novel multiplex protein analysis platform combined with perinatal data. Proteins associated with gestational age at birth and the neurovascular disease ROP were identified. Among infants with ROP, longitudinal levels of the identified proteins remained largely unchanged during the first postnatal months. The main functions of the proteins identified were angiogenesis, hematopoiesis, immune function, bone regulation, lipid metabolism, and central nervous system development. The study contributes to the understanding of longitudinal serum protein patterns related to gestational age and their association with abnormal retinal neuro-vascular development.

A network-based approach reveals the dysregulated transcriptional regulation in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogeneous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1, and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitates the understanding of the regulatory mechanism of these perturbed TFs and their associated biological processes.

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Disease-associated gene modules are conserved across multiple NAFLD cohorts

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The central genes in disease-associated modules are key enzymes in cholesterol synthesis

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YY1 and KLF13 are potential key transcriptional regulators of NAFLD development

Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis

Reliable, robust, large-scale molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for monitoring the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a scalable analytical approach to detect viral proteins based on peptide immuno-affinity enrichment combined with liquid chromatography-mass spectrometry (LC-MS). This is a multiplexed strategy, based on targeted proteomics analysis and read-out by LC-MS, capable of precisely quantifying and confirming the presence of SARS-CoV-2 in phosphate-buffered saline (PBS) swab media from combined throat/nasopharynx/saliva samples. The results reveal that the levels of SARS-CoV-2 measured by LC-MS correlate well with their correspondingreal-time polymerase chain reaction (RT-PCR) read-out (r = 0.79). The analytical workflow shows similar turnaround times as regular RT-PCR instrumentation with a quantitative read-out of viral proteins corresponding to cycle thresholds (Ct) equivalents ranging from 21 to 34. Using RT-PCR as a reference, we demonstrate that the LC-MS-based method has 100% negative percent agreement (estimated specificity) and 95% positive percent agreement (estimated sensitivity) when analyzing clinical samples collected from asymptomatic individuals with a Ct within the limit of detection of the mass spectrometer (Ct ≤ 30). These results suggest that a scalable analytical method based on LC-MS has a place in future pandemic preparedness centers to complement current virus detection technologies.

Identification of Endothelial Proteins in Plasma Associated With Cardiovascular Risk Factors

Supplemental Digital Content is available in the text.

Objective:

Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response.

Approach and Results:

We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (N=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles.

Conclusions:

EC proteins in plasma could reflect vascular health status.

Revealing the Molecular Mechanisms of Alzheimer's Disease Based on Network Analysis

The complex pathology of Alzheimer's disease (AD) emphasises the need for comprehensive modelling of the disease, which may lead to the development of efficient treatment strategies. To address this challenge, we analysed transcriptome data of post-mortem human brain samples of healthy elders and individuals with late-onset AD from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MayoRNAseq) studies in the AMP-AD consortium. In this context, we conducted several bioinformatics and systems medicine analyses including the construction of AD-specific co-expression networks and genome-scale metabolic modelling of the brain in AD patients to identify key genes, metabolites and pathways involved in the progression of AD. We identified AMIGO1 and GRPRASP2 as examples of commonly altered marker genes in AD patients. Moreover, we found alterations in energy metabolism, represented by reduced oxidative phosphorylation and ATPase activity, as well as the depletion of hexanoyl-CoA, pentanoyl-CoA, (2E)-hexenoyl-CoA and numerous other unsaturated fatty acids in the brain. We also observed that neuroprotective metabolites (e.g., vitamins, retinoids and unsaturated fatty acids) tend to be depleted in the AD brain, while neurotoxic metabolites (e.g., β-alanine, bilirubin) were more abundant. In summary, we systematically revealed the key genes and pathways related to the progression of AD, gained insight into the crucial mechanisms of AD and identified some possible targets that could be used in the treatment of AD.

Combined Metabolic Activators Decrease Liver Steatosis by Activating Mitochondrial Metabolism in Hamsters Fed with a High-Fat Diet

Although the prevalence of non-alcoholic fatty liver disease (NAFLD) continues to increase, there is no effective treatment approved for this condition. We previously showed, in high-fat diet (HFD)-fed mice, that the supplementation of combined metabolic activators (CMA), including nicotinamide riboside (NAD+ precursor) and the potent glutathione precursors serine and N-acetyl-l-cysteine (NAC), significantly decreased fatty liver by promoting fat oxidation in mitochondria. Afterwards, in a one-day proof-of-concept human supplementation study, we observed that this CMA, including also L-carnitine tartrate (LCT), resulted in increased fatty acid oxidation and de novo glutathione synthesis. However, the underlying molecular mechanisms associated with supplementation of CMA have not been fully elucidated. Here, we demonstrated in hamsters that the chronic supplementation of this CMA (changing serine for betaine) at two doses significantly decreased hepatic steatosis. We further generated liver transcriptomics data and integrated these data using a liver-specific genome-scale metabolic model of liver tissue. We systemically determined the molecular changes after the supplementation of CMA and found that it activates mitochondria in the liver tissue by modulating global lipid, amino acid, antioxidant and folate metabolism. Our findings provide extra evidence about the beneficial effects of a treatment based on this CMA against NAFLD.

Combined metabolic activators therapy ameliorates liver fat in nonalcoholic fatty liver disease patients

Nonalcoholic fatty liver disease (NAFLD) refers to excess fat accumulation in the liver. In animal experiments and human kinetic study, we found that administration of combined metabolic activators (CMAs) promotes the oxidation of fat, attenuates the resulting oxidative stress, activates mitochondria, and eventually removes excess fat from the liver. Here, we tested the safety and efficacy of CMA in NAFLD patients in a placebo-controlled 10-week study. We found that CMA significantly decreased hepatic steatosis and levels of aspartate aminotransferase, alanine aminotransferase, uric acid, and creatinine, whereas found no differences on these variables in the placebo group after adjustment for weight loss. By integrating clinical data with plasma metabolomics and inflammatory proteomics as well as oral and gut metagenomic data, we revealed the underlying molecular mechanisms associated with the reduced hepatic fat and inflammation in NAFLD patients and identified the key players involved in the host-microbiome interactions. In conclusion, we showed that CMA can be used to develop a pharmacological treatment strategy in NAFLD patients.

Systems Analysis Reveals Ageing-Related Perturbations in Retinoids and Sex Hormones in Alzheimer's and Parkinson's Diseases

Neurodegenerative diseases, including Alzheimer's (AD) and Parkinson's diseases (PD), are complex heterogeneous diseases with highly variable patient responses to treatment. Due to the growing evidence for ageing-related clinical and pathological commonalities between AD and PD, these diseases have recently been studied in tandem. In this study, we analysed transcriptomic data from AD and PD patients, and stratified these patients into three subclasses with distinct gene expression and metabolic profiles. Through integrating transcriptomic data with a genome-scale metabolic model and validating our findings by network exploration and co-analysis using a zebrafish ageing model, we identified retinoids as a key ageing-related feature in all subclasses of AD and PD. We also demonstrated that the dysregulation of androgen metabolism by three different independent mechanisms is a source of heterogeneity in AD and PD. Taken together, our work highlights the need for stratification of AD/PD patients and development of personalised and precision medicine approaches based on the detailed characterisation of these subclasses.

Combined Metabolic Activators Accelerates Recovery in Mild-to-Moderate COVID-19

COVID-19 is associated with mitochondrial dysfunction and metabolic abnormalities, including the deficiencies in nicotinamide adenine dinucleotide (NAD+ ) and glutathione metabolism. Here it is investigated if administration of a mixture of combined metabolic activators (CMAs) consisting of glutathione and NAD+ precursors can restore metabolic function and thus aid the recovery of COVID-19 patients. CMAs include l-serine, N-acetyl-l-cysteine, nicotinamide riboside, and l-carnitine tartrate, salt form of l-carnitine. Placebo-controlled, open-label phase 2 study and double-blinded phase 3 clinical trials are conducted to investigate the time of symptom-free recovery on ambulatory patients using CMAs. The results of both studies show that the time to complete recovery is significantly shorter in the CMA group (6.6 vs 9.3 d) in phase 2 and (5.7 vs 9.2 d) in phase 3 trials compared to placebo group. A comprehensive analysis of the plasma metabolome and proteome reveals major metabolic changes. Plasma levels of proteins and metabolites associated with inflammation and antioxidant metabolism are significantly improved in patients treated with CMAs as compared to placebo. The results show that treating patients infected with COVID-19 with CMAs lead to a more rapid symptom-free recovery, suggesting a role for such a therapeutic regime in the treatment of infections leading to respiratory problems.

Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows

Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed.

Secretome screening reveals immunomodulating functions of IFNα-7, PAP and GDF-7 on regulatory T-cells

Regulatory T cells (Tregs) are the key cells regulating peripheral autoreactive T lymphocytes. Tregs exert their function by suppressing effector T cells. Tregs have been shown to play essential roles in the control of a variety of physiological and pathological immune responses. However, Tregs are unstable and can lose the expression of FOXP3 and suppressive functions as a consequence of outer stimuli. Available literature suggests that secreted proteins regulate Treg functional states, such as differentiation, proliferation and suppressive function. Identification of secreted proteins that affect Treg cell function are highly interesting for both therapeutic and diagnostic purposes in either hyperactive or immunosuppressed populations. Here, we report a phenotypic screening of a human secretome library in human Treg cells utilising a high throughput flow cytometry technology. Screening a library of 575 secreted proteins allowed us to identify proteins stabilising or destabilising the Treg phenotype as suggested by changes in expression of Treg marker proteins FOXP3 and/or CTLA4. Four proteins including GDF-7, IL-10, PAP and IFNα-7 were identified as positive regulators that increased FOXP3 and/or CTLA4 expression. PAP is a phosphatase. A catalytic-dead version of the protein did not induce an increase in FOXP3 expression. Ten interferon proteins were identified as negative regulators that reduced the expression of both CTLA4 and FOXP3, without affecting cell viability. A transcriptomics analysis supported the differential effect on Tregs of IFNα-7 versus other IFNα proteins, indicating differences in JAK/STAT signaling. A conformational model experiment confirmed a tenfold reduction in IFNAR-mediated ISG transcription for IFNα-7 compared to IFNα-10. This further strengthened the theory of a shift in downstream messaging upon external stimulation. As a summary, we have identified four positive regulators of FOXP3 and/or CTLA4 expression. Further exploration of these Treg modulators and their method of action has the potential to aid the discovery of novel therapies for both autoimmune and infectious diseases as well as for cancer.

High Amounts of SARS-CoV-2 Precede Sickness Among Asymptomatic Health Care Workers

Background

Whether SARS-CoV-2 positivity among symptomatic subjects reflects past or future disease may be difficult to ascertain.

Methods

We tested a cohort of 9449 employees at work at the Karolinska University Hospital, Stockholm, Sweden for SARS-CoV-2 RNA and antibodies, linked the testing results to sick leave records and determined associations with past or future sick leave using multinomial logistic regression. ClinicalTrials.gov NCT04411576.

Results

Subjects with high amounts of SARS-CoV-2 virus, as indicated by the Cycle threshold (Ct) value in the PCR, had the highest risk for sick leave in the two weeks after testing (OR 11.97 (CI 95% 6.29-22.80)) whereas subjects with low amounts of virus had the highest risk for sick leave in the past three weeks before testing (OR 6.31 (4.38-9.08)). Only 2.5% of employees were SARS-CoV-2 positive while 10.5% were positive by serology and 1.2% were positive in both tests. Serology-positive subjects were not at excess risk for future sick leave (OR 1.06 (95% CI, 0.71-1.57)).

Conclusions

High amounts of SARS-CoV-2 virus, as determined using PCR Ct values, associates with development of sickness in the next few weeks. The results support the concept that PCR Ct may be informative when testing for SARS-CoV-2 is performed.

Disorganization and degeneration of liver sympathetic innervations in nonalcoholic fatty liver disease revealed by 3D imaging

Hepatic nerves have a complex role in synchronizing liver metabolism. Here, we used three-dimensional (3D) immunoimaging to explore the integrity of the hepatic nervous system in experimental and human nonalcoholic fatty liver disease (NAFLD). We demonstrate parallel signs of mild degeneration and axonal sprouting of sympathetic innervations in early stages of experimental NAFLD and a collapse of sympathetic arborization in steatohepatitis. Human fatty livers display a similar pattern of sympathetic nerve degeneration, correlating with the severity of NAFLD pathology. We show that chronic sympathetic hyperexcitation is a key factor in the axonal degeneration, here genetically phenocopied in mice deficient of the Rac-1 activator Vav3. In experimental steatohepatitis, 3D imaging reveals a severe portal vein contraction, spatially correlated with the extension of the remaining nerves around the portal vein, enlightening a potential intrahepatic neuronal mechanism of portal hypertension. These fundamental alterations in liver innervation and vasculature uncover previously unidentified neuronal components in NAFLD pathomechanisms.