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The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during human acute viral infection. The analysis of IgM N-glycosylation from healthy controls and hospitalized coronavirus disease 2019 (COVID-19) patients reveals increased high-mannose and sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific immunoglobulin N-glycan profiles. Moreover, the degree of total IgM mannosylation and sialylation correlate significantly with markers of disease severity. We link the changes of IgM N-glycosylation with the expression of Golgi glycosyltransferases. Lastly, we observe antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients and modulated by exoglycosidase digestion. Taken together, this work links the IgM N-glycosylation with COVID-19 severity and highlights the need to understand IgM glycosylation and downstream immune function during human disease.

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

ObjectiveLimited information is available regarding youth-onset diabetes in Mali. We investigated demographic, clinical, biochemical, and genetic features in new diabetes cases in children and adolescents.Research design and methodsThe study was conducted at Hôpital du Mali in Bamako. A total of 132 recently-diagnosed cases

BackgroundBetter understanding of the association between characteristics of patients hospitalized with coronavirus disease 2019 (COVID-19) and outcome is needed to further improve upon patient management.MethodsImmunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective, observational study of 1164 patients from 20 hospitals across the United States. Disease severity was assessed using a 7-point ordinal scale based on degree of respiratory illness. Patients were prospectively surveyed for 1 year after discharge for post-acute sequalae of COVID-19 (PASC) through quarterly surveys. Demographics, comorbidities, radiographic findings, clinical laboratory values, SARS-CoV-2 PCR and serology were captured over a 28-day period. Multivariable logistic regression was performed.FindingsThe median age was 59 years (interquartile range [IQR] 20); 711 (61%) were men; overall mortality was 14%, and 228 (20%) required invasive mechanical ventilation. Unsupervised clustering of ordinal score over time revealed distinct disease course trajectories. Risk factors associated with prolonged hospitalization or death by day 28 included age ≥ 65 years (odds ratio [OR], 2.01; 95% CI 1.28-3.17), Hispanic ethnicity (OR, 1.71; 95% CI 1.13-2.57), elevated baseline creatinine (OR 2.80; 95% CI 1.63- 4.80) or troponin (OR 1.89; 95% 1.03-3.47), baseline lymphopenia (OR 2.19; 95% CI 1.61-2.97), presence of infiltrate by chest imaging (OR 3.16; 95% CI 1.96-5.10), and high SARS-CoV2 viral load (OR 1.53; 95% CI 1.17-2.00). Fatal cases had the lowest ratio of SARS-CoV-2 antibody to viral load levels compared to other trajectories over time (p=0.001). 589 survivors (51%) completed at least one survey at follow-up with 305 (52%) having at least one symptom consistent with PASC, most commonly dyspnea (56% among symptomatic patients). Female sex was the only associated risk factor for PASC.InterpretationIntegration of PCR cycle threshold, and antibody values with demographics, comorbidities, and laboratory/radiographic findings identified risk factors for 28-day outcome severity, though only female sex was associated with PASC. Longitudinal clinical phenotyping offers important insights, and provides a framework for immunophenotyping for acute and long COVID-19.FundingNIH.

The IMmunoPhenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective longitudinal study designed to enroll 1000 hospitalized patients with COVID-19 (NCT04378777). IMPACC collects detailed clinical, laboratory and radiographic data along with longitudinal biologic sampling of blood and respiratory secretions for in depth testing. Clinical and lab data are integrated to identify immunologic, virologic, proteomic, metabolomic and genomic features of COVID-19-related susceptibility, severity and disease progression. The goals of IMPACC are to better understand the contributions of pathogen dynamics and host immune responses to the severity and course of COVID-19 and to generate hypotheses for identification of biomarkers and effective therapeutics, including optimal timing of such interventions. In this report we summarize the IMPACC study design and protocols including clinical criteria and recruitment, multi-site standardized sample collection and processing, virologic and immunologic assays, harmonization of assay protocols, high-level analyses and the data sharing plans.

ObjectiveTo further understand clinical and biochemical features, and HLA-DRB1 genotypes, in new cases of diabetes in Sudanese children and adolescents.Research design and methodsDemographic characteristics, clinical information, and biochemical parameters (blood glucose, HbA1c, C-peptide, autoantibodies against glutamic acid decarboxylase 65 [GADA] and insulinoma-associated protein-2 [IA-2A], and HLA-DRB1) were assessed in 99 individuals

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P

Previously, we demonstrated low-dose antithymocyte globulin (ATG) and granulocyte colony-stimulating factor (GCSF) immunotherapy preserved C-peptide for 2 years in a pilot study of patients with established type 1 diabetes (n = 25). Here, we evaluated the long-term outcomes of ATG/GCSF in study participants with 5 years of available follow-up data (n = 15). The primary end point was area under the curve (AUC) C-peptide during a 2-h mixed-meal tolerance test. After 5 years, there were no statistically significant differences in AUC C-peptide when comparing those who received ATG/GCSF versus placebo (P = 0.41). A modeling framework based on mean trajectories in C-peptide AUC over 5 years, accounting for differing trends between groups, was applied to recategorize responders (n = 9) and nonresponders (n = 7). ATG/GCSF reponders demonstrated nearly unchanged HbA1c over 5 years (mean [95% CI] adjusted change 0.29% [-0.69%, 1.27%]), but the study was not powered for comparisons against nonresponders 1.75% (-0.57%, 4.06%) or placebo recipients 1.44% (0.21%, 2.66%). These data underscore the importance of long-term follow-up in previous and ongoing phase 2 trials of low-dose ATG in recent-onset type 1 diabetes.

Some theories propose that human cumulative culture is dependent on System 2 cognitive processes. We aimed to restrictaccess to adults executive functions via a dual-task paradigm, to assess whether this reduced their ability to improveupon information provided by a computer model. 206 participants completed a grid-search task in conjunction with aworking-memory task and a matched control, with the aim of outperforming an example attempt observed vicariously,presented on the computer. Participants behaviour was then used to simulate the outcome if the task was iterated overmultiple generations. Simulations run using the data showed that, across all conditions, participant behaviour would leadto cumulatively increasing scores over successive generations. However, scores plateaued without reaching the maximum.Overall, the task did not provide clear evidence that working-memory directly facilitates cumulative cultural evolution.However, differences between conditions may have been masked by offloading task demands to the concurrent working-memory task.

Human cognition is routinely challenged by today’smultitasking demands which require continuous attentionaldeployment to multiple task components in parallel. Whilepractice-based multitasking training has been shown toimprove multitasking performance, little is known about howattention should be best deployed for optimal training. To thisend, we leveraged a large-scale dataset from an onlinecognitive-training platform to investigate individualdifferences in task learning across long-term training. Wedeveloped an index of attentional deployment that specifies thetemporal dynamics of learning for each component of themultitask and calculate distance maps between clusters of usersto specify distinct learning styles. While long-term practiceimproved the multitasking performance of all participantgroups, participants who focused on learning one taskcomponent earlier and more emphatically, benefited fromsuperior learning gains throughout the entirety of training.

Population size has been proposed to promote cumulative culture in humans. Experimental evidence from adult humanssuggests that this may be due to the potential for combining beneficial information from multiple models. However, it ispossible that such combinatory social learning requires cognitive capacities restricted to adult humans. In our task, childrenaged 5-10 years watched two models consecutively search a 3x3 grid for rewards. Models revealed different correct andincorrect reward locations. This information could be used by the child to maximise their own score on the same task. Wewere interested in childrens ability to select rewarded locations, and avoid unrewarded ones, revealed by both models. Wealso manipulated the spatial and temporal displacement of the information available. Childrens performance on the taskimproved with age. Most children could outperform the mean score of the two models, but outperforming the combinedscore occurred in only limited circumstances.

We investigated whether capuchin monkeys could use information about rewarded and unrewarded stimuli such that chain-ing of their response patterns would in principle generate increasingly successful performances, indicative of potential forcumulative culture. Two populations of tufted capuchin monkeys were tested using a touchscreen stimulus-selection taskrequiring subjects to learn the strategy of repeating rewarded, and avoiding unrewarded selections following demonstra-tions of varying success. Although capuchins outperformed demonstrations of chance-level performance (simulating per-formance of a nave individual), they did not consistently outperform demonstrations of above-chance-level success. Thissuggests that, in a social transmission scenario, the accumulation of beneficial information over successive transmissionevents would be relatively limited. Despite mastering the task contingencies, the capuchins did not use the informationoptimally, limiting the potential for cumulative culture. Our data may provide insights into factors constraining cumulativeculture in the natural behaviour of non-humans.

Using an experimental transmission design, we investigated the extent to which intentional information-sending creates anaccumulation of beneficial information, relative to transmission via inadvertent information.A small subset of an information providers search was transmitted to an information receiver, either selected by theinformation provider themselves (Intentional), or randomly sampled from their full search history (Inadvertent). A thirdcondition where information receivers were shown all of the information providers search attempts was included as acontrol.Intentional information-sending led to cumulative improvements that were comparable to receiving full information froma previous participants search, demonstrating that intentional information-sending had promoted cumulative cultural evo-lution. A follow-up study manipulated whether the sender also received feedback from the receiver which provided infor-mation about locations which had not been searched. No difference was found between these conditions, indicating thatfor this task, bidirectional communication did not further boost the effects of unidirectional intentional communication.

The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

AimsLittle information is published on diabetes in young people in Bangladesh. We aimed to investigate the demographic, clinical, and biochemical features, and HLA-DRB1 alleles in new cases of diabetes affecting Bangladeshi children and adolescents

Transformative technologies are enabling the construction of threedimensional (3D) maps of tissues with unprecedented spatial and molecularresolution. Over the next seven years, the NIH Common Fund Human BiomolecularAtlas Program (HuBMAP) intends to develop a widely accessible framework forcomprehensively mapping the human body at single-cell resolution by supportingtechnology development, data acquisition, and detailed spatial mapping. HuBMAPwill integrate its efforts with other funding agencies, programs, consortia,and the biomedical research community at large towards the shared vision of acomprehensive, accessible 3D molecular and cellular atlas of the human body, inhealth and various disease settings.

A three-arm, randomized, double-masked, placebo-controlled phase 2b trial performed by the Type 1 Diabetes TrialNet Study Group previously demonstrated that low-dose anti-thymocyte globulin (ATG) (2.5 mg/kg) preserved β-cell function and reduced HbA1c for 1 year in new-onset type 1 diabetes. Subjects (N = 89) were randomized to 1) ATG and pegylated granulocyte colony-stimulating factor (GCSF), 2) ATG alone, or 3) placebo. Herein, we report 2-year area under the curve (AUC) C-peptide and HbA1c, prespecified secondary end points, and potential immunologic correlates. The 2-year mean mixed-meal tolerance test-stimulated AUC C-peptide, analyzed by ANCOVA adjusting for baseline C-peptide, age, and sex (n = 82) with significance defined as one-sided P < 0.025, was significantly higher in subjects treated with ATG versus placebo (P = 0.00005) but not ATG/GCSF versus placebo (P = 0.032). HbA1c was significantly reduced at 2 years in subjects treated with ATG (P = 0.011) and ATG/GCSF (P = 0.022) versus placebo. Flow cytometry analyses demonstrated reduced circulating CD4:CD8 ratio, increased regulatory T-cell:conventional CD4 T-cell ratios, and increased PD-1+CD4+ T cells following low-dose ATG and ATG/GCSF. Low-dose ATG partially preserved β-cell function and reduced HbA1c 2 years after therapy in new-onset type 1 diabetes. Future studies should determine whether low-dose ATG might prevent or delay the onset of type 1 diabetes.

Antigen specificity is a primary goal in developing curative therapies for autoimmune disease. Dendritic cells (DCs), as the most effective antigen presenting cells in the body, represent a key target to mediate restoration of antigen-specific immune regulation. Here, we describe an injectable, dual-sized microparticle (MP) approach that employs phagocytosable ∼1 μm and nonphagocytosable ∼30 μm MPs to deliver tolerance-promoting factors both intracellularly and extracellularly, as well as the type 1 diabetes autoantigen, insulin, to DCs for reprogramming of immune responses and remediation of autoimmunity. This poly(lactic-co-glycolic acid) (PLGA) MP system prevented diabetes onset in 60% of nonobese diabetic (NOD) mice when administered subcutaneously in 8 week old mice. Prevention of disease was dependent upon antigen inclusion and required encapsulation of factors in MPs. Moreover, administration of this "suppressive-vaccine" boosted pancreatic lymph node and splenic regulatory T cells (Tregs), upregulated PD-1 on CD4+ and CD8+ T cells, and reversed hyperglycemia for up to 100 days in recent-onset NOD mice. Our results demonstrate that a MP-based platform can reeducate the immune system in an antigen-specific manner, augment immunomodulation compared to soluble administration of drugs, and provide a promising alternative to systemic immunosuppression for autoimmunity.

There has been considerable debate as to whether obesity can act as an accelerator of type 1 diabetes (T1D). We assessed this possibility using transgenic mice (MIP-TF mice) whose ß-cells express enhanced green fluorescent protein (EGFP). Infecting these mice with EGFP-expressing murine herpes virus-68 (MHV68-EGFP) caused occasional transient elevation in their blood glucose, peri-insulitis, and Th1 responses to EGFP which did not spread to other ß-cell antigens. We hypothesized that obesity-related systemic inflammation and ß-cell stress could exacerbate the MHV68-EGFP-induced ß-cell autoreactivity. We crossed MIP-TF mice with Avy mice which develop obesity and provide models of metabolic disease alongside early stage T2D. Unlike their MIP-TF littermates, MHV68-EGFP-infected Avy/MIP-TF mice developed moderate intra-insulitis and transient hyperglycemia. MHV68-EGFP infection induced a more pronounced intra-insulitis in older, more obese, Avy/MIP-TF mice. Moreover, in MHV68-EGFP-infected Avy/MIP-TF mice, Th1 reactivity spread from EGFP to other ß-cell antigens. Thus, the spreading of autoreactivity among ß-cell antigens corresponded with the transition from peri-insulitis to intra-insulitis and occurred in obese Avy/MIP-TF mice but not lean MIP-TF mice. These observations are consistent with the notion that obesity-associated systemic inflammation and ß-cell stress lowers the threshold necessary for T cell autoreactivity to spread from EGFP to other ß-cell autoantigens.

Published information on diabetes in Pakistani youth is limited. We aimed to investigate the demographic, clinical, and biochemical features, and HLA-DRB1 alleles in new cases of diabetes affecting children and adolescents

ObjectiveGenetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS.Research design and methodsWe generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10-8) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10-5).ResultsAfrican-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts.ConclusionsGenetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

ObjectiveThe type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes.Research design and methodsWe evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used.ResultsDuring follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age.ConclusionsThe type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight.

AimsDetermine the incidence and typology of diabetes in children in Azerbaijan.MethodsClinical features, C-peptide, autoantibodies (glutamic acid decarboxylase 65 (GAD65) and islet antigen 2 (IA-2)), and HLA-DRB1 status were studied in 106 subjects

Clinical trials seeking to delay or prevent the onset of type 1 diabetes (T1D) face a series of pragmatic challenges. Despite more than 100 years since the discovery of insulin, teplizumab remains the only FDA‐approved therapy to delay progression from Stage 2 to Stage 3 T1D. To increase the efficiency of clinical trials seeking this goal, our project sought to inform T1D clinical trial designs by developing a disease progression model‐based clinical trial simulation tool. Using individual‐level data collected from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies, we previously developed a quantitative joint model to predict the time to T1D onset. We then applied trial‐specific inclusion/exclusion criteria, sample sizes in treatment and placebo arms, trial duration, assessment interval, and dropout rate. We implemented a function for presumed drug effects. To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. Using this tool, power curves can also be generated through iterations. The web‐based tool is publicly available: https://app.cop.ufl.edu/t1d/. Herein, we briefly describe the tool and provide instructions for simulating a planned clinical trial with two case studies. This tool will allow for improved clinical trial designs and accelerate efforts seeking to prevent or delay the onset of T1D. [ABSTRACT FROM AUTHOR]