Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant Women.

Metabolism during pregnancy is a dynamic and precisely programmed process, the failure of which can bring devastating consequences to the mother and fetus. To define a high-resolution temporal profile of metabolites during healthy pregnancy, we analyzed the untargeted metabolome of 784 weekly blood samples from 30 pregnant women. Broad changes and a highly choreographed profile were revealed: 4,995 metabolic features (of 9,651 total), 460 annotated compounds (of 687 total), and 34 human metabolic pathways (of 48 total) were significantly changed during pregnancy. Using linear models, we built a metabolic clock with five metabolites that time gestational age in high accordance with ultrasound (R = 0.92). Furthermore, two to three metabolites can identify when labor occurs (time to delivery within two, four, and eight weeks, AUROC ≥ 0.85). Our study represents a weekly characterization of the human pregnancy metabolome, providing a high-resolution landscape for understanding pregnancy with potential clinical utilities.

Longitudinal and simultaneous profiling of 11 modes of cell death in mouse retina post-optic nerve injury.

Retinal ganglion cell (RGC) death is a critical pathological trigger leading to irreversible visual impairment and blindness after optic nerve (ON) injury. Yet, there is still no effective clinical treatment to rescue RGC death after ON injury. Understanding the involvement of different modes of cell death post-ON injury could facilitate the development of targeting treatments against RGC death. Herein we aimed to characterize the regulation of 11 modes of cell death simultaneously and longitudinally in mouse retina post-ON injury. The number of RGCs gradually decreased from Day 3-14 in mice post-ON injury. Increase in the apoptosis (cleaved caspase-3), autolysis (cleaved cathespin B) and pyroptosis (cleaved caspase-1) marker expression in the retina began at Day 3 post-ON injury. Meanwhile, the markers for autophagy (Atg7 and Becn1) and phagocytosis (Mfge8 and Mertk) were downregulated from Day 1 to Day 5. Additionally, the expression of ferroptosis marker (4-hydroxynonenal) was upregulated from Day 7 to Day 14 post-ON injury following the early reduction of Gpx4. Yet, the reduction of parthanatos, sarmoptosis, and mitochondrial permeable transition could be related to autophagy and apoptosis. The markers for necroptosis did not show significant changes post-ON injury. In summary, this study revealed that the activation of apoptosis, autolysis, pyroptosis and ferroptosis, together with the early downregulation of autophagy and phagocytosis, are the major modes of cell death involved in the RGC death post-ON injury. Simultaneously targeting multiple modes of cell death at different time courses could be a potential treatment approach against RGC death for traumatic optic neuropathy.

Deep Characterization of the Human Antibody Response to Natural Infection Using Longitudinal Immune Repertoire Sequencing.

Human antibody response studies are largely restricted to periods of high immune activity (e.g. vaccination). To comprehensively understand the healthy B cell immune repertoire and how this changes over time and through natural infection, we conducted immune repertoire RNA sequencing on flow cytometry-sorted B cell subsets to profile a single individual's antibodies over 11 months through two periods of natural viral infection. We found that 1) a baseline of healthy variable (V) gene usage in antibodies exists and is stable over time, but antibodies in memory cells consistently have a different usage profile relative to earlier B cell stages; 2) a single complementarity-determining region 3 (CDR3) is potentially generated from more than one VJ gene combination; and 3) IgG and IgA antibody transcripts are found at low levels in early human B cell development, suggesting that class switching may occur earlier than previously realized. These findings provide insight into immune repertoire stability, response to natural infections, and human B cell development.

Circulating proteins associated with allergy development in infants-an exploratory analysis.

BACKGROUND: Protein profiles that can predict allergy development in children are lacking and the ideal sampling age is unknown. By applying an exploratory proteomics approach in the prospective FARMFLORA birth cohort, we sought to identify previously unknown circulating proteins in early life that associate to protection or risk for development of allergy up to 8 years of age. METHODS: We analyzed plasma prepared from umbilical cord blood (n = 38) and blood collected at 1 month (n = 42), 4 months (n = 39), 18 months (n = 42), 36 months (n = 42) and 8 years (n = 44) of age. We profiled 230 proteins with a multiplexed assay and evaluated the global structure of the data with principal component analysis (PCA). Protein profiles informative to allergic disease at 18 months, 36 months and/or 8 years were evaluated using Lasso logistic regression and random forest. RESULTS: Two clusters emerged in the PCA analysis that separated samples obtained at birth and at 1 month of age from samples obtained later. Differences between the clusters were mostly driven by abundant plasma proteins. For the prediction of allergy, both Lasso logistic regression and random forest were most informative with samples collected at 1 month of age. A Lasso model with 27 proteins together with farm environment differentiated children who remained healthy from those developing allergy. This protein panel was primarily composed of antigen-presenting MHC class I molecules, interleukins and chemokines. CONCLUSION: Sampled at one month of age, circulating proteins that reflect processes of the immune system may predict the development of allergic disease later in childhood.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fueled the COVID-19 pandemic with its enduring medical and socioeconomic challenges because of subsequent waves and long-term consequences of great concern. Here, we chart the molecular basis of COVID-19 pathogenesis by analyzing patients' immune responses at single-cell resolution across disease course and severity. This approach confirms cell subpopulation-specific dysregulation in COVID-19 across disease course and severity and identifies a severity-associated activation of the receptor for advanced glycation endproducts (RAGE) pathway in monocytes. In vitro THP1-based experiments indicate that monocytes bind the SARS-CoV-2 S1-receptor binding domain (RBD) via RAGE, pointing to RAGE-Spike interaction enabling monocyte infection. Thus, our results demonstrate that RAGE is a functional receptor of SARS-CoV-2 contributing to COVID-19 severity.

Measurements of hydrocortisone and cortisone for longitudinal profiling of equine plasma by liquid chromatography-tandem mass spectrometry.

The conventional detection of exogenous drugs in equine doping samples has been used for confirmation and subsequent prosecution of participants responsible. In recent years, alternative methods using indirect detection have been investigated due to the expanding number of pharmaceutical agents available with the potential of misuse. The monitoring of endogenous biomarkers such as hydrocortisone (HC) has been studied in equine urine with an international threshold of 1 µg/ml established; however, there is no current threshold for equine plasma. The aim of this research was to investigate plasma concentrations of HC and cortisone (C) in race day samples compared to an administration of Triamcinolone Acetonide (TACA). The reference population (n = 1150) provided HC (6 to 145 ng/ml) and C (0.7 to 13 ng/ml) levels to derive the HC to C ratio (HC/C). Population reference limits (PRLs) were proposed for HC/C values at 0.2 (lower) and 61 (upper). Administration of TACA resulted in down-regulation of HC/C values below the estimated PRLs for up to 96 h post-administration. This indirect detection period was longer than the detection of TACA for 72 h. The use of individual reference limits (IRLs) for HC/C values was investigated to support the Equine Biological Passport (EBP), an intelligence model developed by Racing NSW for longitudinal monitoring of biomarkers.

Longitudinal plasma protein profiling of newly diagnosed type 2 diabetes.

BACKGROUND: Comprehensive proteomics profiling may offer new insights into the dysregulated metabolic milieu of type 2 diabetes, and in the future, serve as a useful tool for personalized medicine. This calls for a better understanding of circulating protein patterns at the early stage of type 2 diabetes as well as the dynamics of protein patterns during changes in metabolic status. METHODS: To elucidate the systemic alterations in early-stage diabetes and to investigate the effects on the proteome during metabolic improvement, we measured 974 circulating proteins in 52 newly diagnosed, treatment-naïve type 2 diabetes subjects at baseline and after 1 and 3 months of guideline-based diabetes treatment, while comparing their protein profiles to that of 94 subjects without diabetes. FINDINGS: Early stage type 2 diabetes was associated with distinct protein patterns, reflecting key metabolic syndrome features including insulin resistance, adiposity, hyperglycemia and liver steatosis. The protein profiles at baseline were attenuated during guideline-based diabetes treatment and several plasma proteins associated with metformin medication independently of metabolic variables, such as circulating EPCAM. INTERPRETATION: The results advance our knowledge about the biochemical manifestations of type 2 diabetes and suggest that comprehensive protein profiling may serve as a useful tool for metabolic phenotyping and for elucidating the biological effects of diabetes treatments. FUNDING: This work was supported by the Swedish Heart and Lung Foundation, the Swedish Research Council, the Erling Persson Foundation, the Knut and Alice Wallenberg Foundation, and the Swedish state under the agreement between the Swedish government and the county councils (ALF-agreement).

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling.

BACKGROUND: Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate. METHODS: To provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals' short-term health trajectories. FINDINGS: We found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed that 49% of the protein profiles were stable over one year. We also identified eight networks of proteins in which 11-242 proteins covaried over time. For each participant, there were unique protein profiles of which some could be explained by associations to genetic variants. INTERPRETATION: This observational and non-interventional study identifyed noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. To enable more personal hence precise assessments of health states, longitudinal profiling of circulating proteomes can provide a valuable component for precision medicine approaches. FUNDING: This work was supported by the Erling Persson Foundation, the Swedish Heart and Lung Foundation, the Knut and Alice Wallenberg Foundation, Science for Life Laboratory, and the Swedish Research Council.

Persistent Antibody Clonotypes Dominate the Serum Response to Influenza over Multiple Years and Repeated Vaccinations.

Humans are repeatedly exposed to influenza virus via infections and vaccinations. Understanding how multiple exposures and pre-existing immunity impact antibody responses is essential for vaccine development. Given the recent prevalence of influenza H1N1 A/California/7/2009 (CA09), we examined the clonal composition and dynamics of CA09 hemagglutinin (HA)-reactive IgG repertoire over 5 years in a donor with multiple influenza exposures. The anti-CA09 HA polyclonal response in this donor comprised 24 persistent antibody clonotypes, accounting for 72.6% ± 10.0% of the anti-CA09 HA repertoire over 5 years. These persistent antibodies displayed higher somatic hypermutation relative to transient serum antibodies detected at one time point. Additionally, persistent antibodies predominantly demonstrated cross-reactivity and potent neutralization toward a phylogenetically distant H5N1 A/Vietnam/1203/2004 (VT04) strain, a feature correlated with HA stem recognition. This analysis reveals how "serological imprinting" impacts responses to influenza and suggests that once elicited, cross-reactive antibodies targeting the HA stem can persist for years.

Individualized Transcriptional Resolution of Complicated Malaria in a Colombian Study.

To evaluate whether recovery from complicated malaria follows a common trajectory in terms of immunological mechanism or, rather, is highly individualized for each patient, we performed longitudinal gene expression profiling of whole blood. RNA sequencing (RNAseq) was performed on blood samples obtained from eight patients on four consecutive days between hospital admission and discharge. Six patients were infected with Plasmodium falciparum, and two with Plasmodium vivax; one patient was a pregnant woman infected with P. falciparum, who was hospitalized for several weeks. The characterization of blood transcript modules (BTM) and blood informative transcripts (BIT) revealed that patients' responses showed little commonality, being dominated by the balance of gene activity relating to lymphocyte function, inflammation, and interferon responses specific to each patient. Only weak correlations with specific complicated malaria symptoms such as jaundice, thrombocytopenia, or anemia were observed. The differential expression of individual genes, including transcripts derived from the human leukocyte antigen (HLA) complex, generally reflected differences in the underlying immune processes. Although the results of this pilot study do not point to any single process that might provide a target for complicated malaria treatment or prevention or personalized medical strategies, larger patient series and more extensive blood sampling may allow the classification of patients according to their type of response in order to develop novel therapeutic approaches.

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression.

Blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n=11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n=10). To our knowledge, the current study represents the largest (>2000 proteins measured) longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA. BIOLOGICAL SIGNIFICANCE: The temporal changes of >2000 plasma proteins (at least quantified in two subjects), spanning the entire period of T1D natural progression were provided to the research community. Oxidative stress related proteins have consistently different dysregulated patterns in T1D group than in age-sex matched healthy controls, even prior to appearance of islet autoantibodies - the earliest sign of islet autoimmunity and pancreatic beta cell stress.