Monocyte Differentiation and Heterogeneity: Inter-Subset and Interindividual Differences.

The three subsets of human monocytes, classical, intermediate, and nonclassical, show phenotypic heterogeneity, particularly in their expression of CD14 and CD16. This has enabled researchers to delve into the functions of each subset in the steady state as well as in disease. Studies have revealed that monocyte heterogeneity is multi-dimensional. In addition, that their phenotype and function differ between subsets is well established. However, it is becoming evident that heterogeneity also exists within each subset, between health and disease (current or past) states, and even between individuals. This realisation casts long shadows, impacting how we identify and classify the subsets, the functions we assign to them, and how they are examined for alterations in disease. Perhaps the most fascinating is evidence that, even in relative health, interindividual differences in monocyte subsets exist. It is proposed that the individual's microenvironment could cause long-lasting or irreversible changes to monocyte precursors that echo to monocytes and through to their derived macrophages. Here, we will discuss the types of heterogeneity recognised in monocytes, the implications of these for monocyte research, and most importantly, the relevance of this heterogeneity for health and disease.

Clustering of clinical and echocardiographic phenotypes of covid-19 patients.

We sought to divide COVID-19 patients into distinct phenotypical subgroups using echocardiography and clinical markers to elucidate the pathogenesis of the disease and its heterogeneous cardiac involvement. A total of 506 consecutive patients hospitalized with COVID-19 infection underwent complete evaluation, including echocardiography, at admission. A k-prototypes algorithm applied to patients' clinical and imaging data at admission partitioned the patients into four phenotypical clusters: Clusters 0 and 1 were younger and healthier, 2 and 3 were older with worse cardiac indexes, and clusters 1 and 3 had a stronger inflammatory response. The clusters manifested very distinct survival patterns (C-index for the Cox proportional hazard model 0.77), with survival best for cluster 0, intermediate for 1-2 and worst for 3. Interestingly, cluster 1 showed a harsher disease course than cluster 2 but with similar survival. Clusters obtained with echocardiography were more predictive of mortality than clusters obtained without echocardiography. Additionally, several echocardiography variables (E' lat, E' sept, E/e average) showed high discriminative power among the clusters. The results suggested that older infected males have a higher chance to deteriorate than older infected females. In conclusion, COVID-19 manifests differently for distinctive clusters of patients. These clusters reflect different disease manifestations and prognoses. Although including echocardiography improved the predictive power, its marginal contribution over clustering using clinical parameters only does not justify the burden of echocardiography data collection.

Definition and clinical variability of SHANK3-related Phelan-McDermid syndrome.

Phelan-McDermid syndrome (PMS) is an infrequently described syndrome that presents with a disturbed development, neurological and psychiatric characteristics, and sometimes other comorbidities. As part of the development of European medical guidelines we studied the definition, phenotype, genotype-phenotype characteristics, and natural history of the syndrome. The number of confirmed diagnoses of PMS in different European countries was also assessed and it could be concluded that PMS is underdiagnosed. The incidence of PMS in European countries is estimated to be at least 1 in 30,000. Next generation sequencing, including analysis of copy number variations, as first tier in diagnostics of individuals with intellectual disability will likely yield a larger number of individuals with PMS than presently known. A definition of PMS by its phenotype is at the present not possible, and therefore PMS-SHANK3 related is defined by the presence of SHANK3 haploinsufficiency, either by a deletion involving region 22q13.2-33 or a pathogenic/likely pathogenic variant in SHANK3. In summarizing the phenotype, we subdivided it into that of individuals with a 22q13 deletion and that of those with a pathogenic/likely pathogenic SHANK3 variant. The phenotype of individuals with PMS is variable, depending in part on the deletion size or whether only a variant of SHANK3 is present. The core phenotype in the domains development, neurology, and senses are similar in those with deletions and SHANK3 variants, but individuals with a SHANK3 variant more often are reported to have behavioural disorders and less often urogenital malformations and lymphedema. The behavioural disorders may, however, be a less outstanding feature in individuals with deletions accompanied by more severe intellectual disability. Data available on the natural history are limited. Results of clinical trials using IGF-1, intranasal insulin, and oxytocin are available, other trials are in progress. The present guidelines for PMS aim at offering tools to caregivers and families to provide optimal care to individuals with PMS.

Functional CVIDs phenotype clusters identified by the integration of immune parameters after BNT162b2 boosters.

Introduction: Assessing the response to vaccinations is one of the diagnostic criteria for Common Variable Immune Deficiencies (CVIDs). Vaccination against SARS-CoV-2 offered the unique opportunity to analyze the immune response to a novel antigen. We identify four CVIDs phenotype clusters by the integration of immune parameters after BTN162b2 boosters. Methods: We performed a longitudinal study on 47 CVIDs patients who received the 3rd and 4th vaccine dose of the BNT162b2 vaccine measuring the generation of immunological memory. We analyzed specific and neutralizing antibodies, spike-specific memory B cells, and functional T cells. Results: We found that, depending on the readout of vaccine efficacy, the frequency of responders changes. Although 63.8% of the patients have specific antibodies in the serum, only 30% have high-affinity specific memory B cells and generate recall responses. Discussion: Thanks to the integration of our data, we identified four functional groups of CVIDs patients with different B cell phenotypes, T cell functions, and clinical diseases. The presence of antibodies alone is not sufficient to demonstrate the establishment of immune memory and the measurement of the in-vivo response to vaccination distinguishes patients with different immunological defects and clinical diseases.

SARS-CoV-2 omicron variants harbor spike protein mutations responsible for their attenuated fusogenic phenotype.

Since the emergence of the Omicron variants at the end of 2021, they quickly became the dominant variants globally. The Omicron variants may be more easily transmitted compared to the earlier Wuhan and the other variants. In this study, we aimed to elucidate mechanisms of the altered infectivity associated with the Omicron variants. We systemically evaluated mutations located in the S2 sequence of spike and identified mutations that are responsible for altered viral fusion. We demonstrated that mutations near the S1/S2 cleavage site decrease S1/S2 cleavage, resulting in reduced fusogenicity. Mutations in the HR1 and other S2 sequences also affect cell-cell fusion. Based on nuclear magnetic resonance (NMR) studies and in silico modeling, these mutations affect fusogenicity possibly at multiple steps of the viral fusion. Our findings reveal that the Omicron variants have accumulated mutations that contribute to reduced syncytial formation and hence an attenuated pathogenicity.

Genetic correlation, causal relationship, and shared loci between vitamin D and COVID-19: A genome-wide cross-trait analysis.

Observational studies have shown that vitamin D supplementation reduces the risk of COVID-19 infection, yet little is known about the shared genomic architectures between them. Leveraging large-scale genome-wide association study (GWAS) summary statistics, we investigated the genetic correlation and causal relationship between genetically determined vitamin D and COVID-19 using linkage disequilibrium score regression and Mendelian randomization (MR) analyses, and conducted a cross-trait GWAS meta-analysis to identify the overlapping susceptibility loci of them. We observed a significant genetic correlation between genetically predicted vitamin D and COVID-19 (rg = -0.143, p = 0.011), and the risk of COVID-19 infection would decrease by 6% for every 0.76 nmol L-1 increase of serum 25 hydroxyvitamin D (25OHD) concentrations in generalized MR (OR = 0.94, 95% CI: 0.89-0.99, p = 0.019). We identified rs4971066 (EFNA1) as a risk locus for the joint phenotype of vitamin D and COVID-19. In conclusion, genetically determined vitamin D is associated with COVID-19. Increased levels of serum 25OHD concentration may benefit the prevention and treatment of COVID-19.

De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository.

Machine learning (ML)-driven computable phenotypes are among the most challenging to share and reproduce. Despite this difficulty, the urgent public health considerations around Long COVID make it especially important to ensure the rigor and reproducibility of Long COVID phenotyping algorithms such that they can be made available to a broad audience of researchers. As part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, researchers with the National COVID Cohort Collaborative (N3C) devised and trained an ML-based phenotype to identify patients highly probable to have Long COVID. Supported by RECOVER, N3C and NIH's All of Us study partnered to reproduce the output of N3C's trained model in the All of Us data enclave, demonstrating model extensibility in multiple environments. This case study in ML-based phenotype reuse illustrates how open-source software best practices and cross-site collaboration can de-black-box phenotyping algorithms, prevent unnecessary rework, and promote open science in informatics.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis.

AIMS/HYPOTHESIS: To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death. METHODS: This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach. RESULTS: A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out. CONCLUSIONS/INTERPRETATION: Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease. REGISTRATION: PROSPERO registration no. CRD42020193692. PREVIOUS VERSION: This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD).

Case Report: Molecular autopsy underlie COVID-19-associated sudden, unexplained child mortality.

Herein, we report a child with COVID-19 and seemingly no underlying disease, who died suddenly. The autopsy revealed severe anemia and thrombocytopenia, splenomegaly, hypercytokinemia, and a rare ectopic congenital coronary origin. Immunohistochemical analysis demonstrated that the patient had acute lymphoblastic leukemia of the B-cell precursor phenotype (BCP-ALL). The complex cardiac and hematological abnormalities suggested the presence of an underlying disease; therefore, we performed whole-exome sequencing (WES). WES revealed a leucine-zipper-like transcription regulator 1 (LZTR1) variant, indicating Noonan syndrome (NS). Therefore, we concluded that the patient had underlying NS along with coronary artery malformation and that COVID-19 infection may have triggered the sudden cardiac death due to increased cardiac load caused by high fever and dehydration. In addition, multiple organ failure due to hypercytokinemia probably contributed to the patient's death. This case would be of interest to pathologists and pediatricians because of the limited number of NS patients with LZTR1 variants; the complex combination of an LZTR1 variant, BCP-ALL, and COVID-19; and a rare pattern of the anomalous origin of the coronary artery. Thus, we highlight the significance of molecular autopsy and the application of WES with conventional diagnostic methods.

Biologic Mechanisms of Macrophage Phenotypes Responding to Infection and the Novel Therapies to Moderate Inflammation.

Pro-inflammatory and anti-inflammatory types are the main phenotypes of the macrophage, which are commonly notified as M1 and M2, respectively. The alteration of macrophage phenotypes and the progression of inflammation are intimately associated; both phenotypes usually coexist throughout the whole inflammation stage, involving the transduction of intracellular signals and the secretion of extracellular cytokines. This paper aims to address the interaction of macrophages and surrounding cells and tissues with inflammation-related diseases and clarify the crosstalk of signal pathways relevant to the phenotypic metamorphosis of macrophages. On these bases, some novel therapeutic methods are proposed for regulating inflammation through monitoring the transition of macrophage phenotypes so as to prevent the negative effects of antibiotic drugs utilized in the long term in the clinic. This information will be quite beneficial for the diagnosis and treatment of inflammation-related diseases like pneumonia and other disorders involving macrophages.

Mendelian randomization of genetically independent aging phenotypes identifies LPA and VCAM1 as biological targets for human aging.

Length and quality of life are important to us all, yet identification of promising drug targets for human aging using genetics has had limited success. In the present study, we combine six European-ancestry genome-wide association studies of human aging traits-healthspan, father and mother lifespan, exceptional longevity, frailty index and self-rated health-in a principal component framework that maximizes their shared genetic architecture. The first principal component (aging-GIP1) captures both length of life and indices of mental and physical wellbeing. We identify 27 genomic regions associated with aging-GIP1, and provide additional, independent evidence for an effect on human aging for loci near HTT and MAML3 using a study of Finnish and Japanese survival. Using proteome-wide, two-sample, Mendelian randomization and colocalization, we provide robust evidence for a detrimental effect of blood levels of apolipoprotein(a) and vascular cell adhesion molecule 1 on aging-GIP1. Together, our results demonstrate that combining multiple aging traits using genetic principal components enhances the power to detect biological targets for human aging.

Acute coronavirus infection triggers a TNF-dependent osteoporotic phenotype in mice.

AIMS: Millions of people died during the COVID-19 pandemic, but the vast majority of infected individuals survived. Now, some consequences of the disease, known as long COVID, are been revealed. Although the respiratory system is the target of Sars-CoV-2, COVID-19 can influence other parts of the body, including bone. The aim of this work was to investigate the impact of acute coronavirus infection in bone metabolism. MAIN METHODS: We evaluated RANKL/OPG levels in serum samples of patients with and without acute COVID-19. In vitro, the effects of coronavirus in osteoclasts and osteoblasts were investigated. In vivo, we evaluated the bone phenotype in a BSL2 mouse model of SARS-like disease induced by murine coronavirus (MHV-3). KEY FINDINGS: Patients with acute COVID-19 presented decreased OPG and increased RANKL/OPG ratio in the serum versus healthy individuals. In vitro, MHV-3 infected macrophages and osteoclasts, increasing their differentiation and TNF release. Oppositely, osteoblasts were not infected. In vivo, MHV-3 lung infection triggered bone resorption in the femur of mice, increasing the number of osteoclasts at 3dpi and decreasing at 5dpi. Indeed, apoptotic-caspase-3+ cells have been detected in the femur after infection as well as viral RNA. RANKL/OPG ratio and TNF levels also increased in the femur after infection. Accordingly, the bone phenotype of TNFRp55-/- mice infected with MHV-3 showed no signs of bone resorption or increase in the number of osteoclasts. SIGNIFICANCE: Coronavirus induces an osteoporotic phenotype in mice dependent on TNF and on macrophage/osteoclast infection.

Prevalence and clinical implications of abnormal body composition phenotypes in patients with COVID-19: a systematic review.

BACKGROUND: The impact of body composition (BC) abnormalities on COVID-19 outcomes remains to be determined. OBJECTIVES: We summarized the evidence on BC abnormalities and their relationship with adverse clinical outcomes in patients with COVID-19. METHODS: A systematic search was conducted up until 26 September, 2022 for observational studies using BC techniques to quantify skeletal muscle mass (or related compartments), muscle radiodensity or echo intensity, adipose tissue (AT; or related compartments), and phase angle (PhA) in adults with COVID-19. Methodological quality of studies was assessed using the Newcastle-Ottawa Scale. A synthesis without meta-analysis was conducted to summarize the prevalence of BC abnormalities and their significant associations with clinical outcomes. RESULTS: We included 62 studies (69.4% low risk of bias) with 12-1138 participants, except 3 studies with ≤490,301 participants. Using CT and different cutoff values, prevalence ranged approximately from 22% to 90% for low muscle mass, 12% to 85% for low muscle radiodensity, and 16% to 70% for high visceral AT. Using BIA, prevalence of high FM was 51%, and low PhA was 22% to 88%. Mortality was inversely related to PhA (3/4 studies) and positively related to intra- and intermuscular AT (4/5 studies), muscle echo intensity (2/2 studies), and BIA-estimated FM (2/2 studies). Intensive care unit (ICU) admission was positively related to visceral AT (6/7 studies) and total AT (2/3 studies). Disease severity and hospitalization outcomes were positively related to intra- and intermuscular AT (2/2 studies). Inconsistent associations were found for the rest of the BC measures and hospitalization outcomes. CONCLUSIONS: Abnormalities in BC were prevalent in patients with COVID-19. Although conflicting associations were observed among certain BC abnormalities and clinical outcomes, higher muscle echo intensity (reflective of myosteatosis) and lower PhA were more consistently associated with greater mortality risk. Likewise, high intra- and intermuscular AT and visceral AT were associated with mortality and ICU admission, respectively. This trial was registered at PROSPERO as CRD42021283031.

Single cell sequencing of neutrophils demonstrates phenotypic heterogeneity and functional plasticity in health, disease, and cancer.

A vital constituent of innate immunity, neutrophils had previously been considered functionally rigid with a fixed, defined role in host pathogen response, in part due to their fleeting lifespan. However, that consensus opinion has changed with evidence of functional neutrophil plasticity in a range of diseases including cancer. Typically difficult to sequence due to their low level of transcriptomic activity, advances in single cell RNA sequencing has allowed for closer examination of the neutrophil transcriptome in humans and mouse models and their interaction with other immune system constituents, both in health and disease, allowing for description of neutrophil phenotypes beyond previous descriptions reliant upon microscopic appearance, surface marker expression, and function. Transcriptomic analysis shows that neutrophils develop and mature along a fixed trajectory, but their transcriptome varies based on maturity, the insult that has provoked release from the bone marrow, and the tissue to which they are recruited. Thus neutrophil heterogeneity increases with maturity, with immature neutrophils being more transcriptomically rigid. Here, we review work done in neutrophil single cell RNA sequencing in mice and humans in health and a range of disease states including coronavirus disease 2019 (COVID-19) infection, and solid cancers to provide a template for understanding neutrophil biology in context.

Self-control and performance while working from home.

This study explores the role of trait self-control in individuals' changes in performance and well-being when working from home (WFH). In a three-wave longitudinal study with UK workers in the midst of the COVID-19 pandemic, we find that low self-control workers experienced a significant positive adjustment to WFH over time: The number of reported work distractions decreased, and self-assessed performance increased over the period of four months. In contrast, high self-control individuals did not show a similar upward trajectory. Despite the positive adjustment of low self-control individuals over time, on average, self-control was still positively associated with performance and negatively associated with work distractions. However, trait self-control was not consistently associated with changes in well-being. These findings provide a more nuanced view on trait self-control, suggesting that low self-control individuals can improve initial performance over time when working from home.

A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses.

Surface antigens of pathogens are commonly targeted by vaccine-elicited antibodies but antigenic variability, notably in RNA viruses such as influenza, HIV and SARS-CoV-2, pose challenges for control by vaccination. For example, influenza A(H3N2) entered the human population in 1968 causing a pandemic and has since been monitored, along with other seasonal influenza viruses, for the emergence of antigenic drift variants through intensive global surveillance and laboratory characterisation. Statistical models of the relationship between genetic differences among viruses and their antigenic similarity provide useful information to inform vaccine development, though accurate identification of causative mutations is complicated by highly correlated genetic signals that arise due to the evolutionary process. Here, using a sparse hierarchical Bayesian analogue of an experimentally validated model for integrating genetic and antigenic data, we identify the genetic changes in influenza A(H3N2) virus that underpin antigenic drift. We show that incorporating protein structural data into variable selection helps resolve ambiguities arising due to correlated signals, with the proportion of variables representing haemagglutinin positions decisively included, or excluded, increased from 59.8% to 72.4%. The accuracy of variable selection judged by proximity to experimentally determined antigenic sites was improved simultaneously. Structure-guided variable selection thus improves confidence in the identification of genetic explanations of antigenic variation and we also show that prioritising the identification of causative mutations is not detrimental to the predictive capability of the analysis. Indeed, incorporating structural information into variable selection resulted in a model that could more accurately predict antigenic assay titres for phenotypically-uncharacterised virus from genetic sequence. Combined, these analyses have the potential to inform choices of reference viruses, the targeting of laboratory assays, and predictions of the evolutionary success of different genotypes, and can therefore be used to inform vaccine selection processes.