Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19.

COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56dimCD16hi NK cells linked positively to circulating interleukin (IL)-15. CD8+ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17-23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19.

Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19.

Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genes including Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.

Expanding the Immunology Toolbox: Embracing Public-Data Reuse and Crowdsourcing.

New technologies have been propelling dramatic increases in the volume and diversity of large-scale public data, which can potentially be reused to answer questions beyond those originally envisioned. However, this often requires computational and statistical skills beyond the reach of most bench scientists. The development of educational and accessible computational tools is thus critical, as are crowdsourcing efforts that utilize the community's expertise to curate public data for hypothesis generation and testing. Here we review the history of public-data reuse and argue for greater incorporation of computational and statistical sciences into the biomedical education curriculum and the development of biologist-friendly crowdsourcing tools. Finally, we provide a resource list for the reuse of public data and highlight an illustrative crowdsourcing exercise to explore public gene-expression data of human autoimmune diseases and corresponding mouse models. Through education, tool development, and community engagement, immunologists will be poised to transform public data into biological insights.

Diffusion MRI of the facial-vestibulocochlear nerve complex: a prospective clinical validation study.

OBJECTIVES: Surgical planning of vestibular schwannoma surgery would benefit greatly from a robust method of delineating the facial-vestibulocochlear nerve complex with respect to the tumour. This study aimed to optimise a multi-shell readout-segmented diffusion-weighted imaging (rs-DWI) protocol and develop a novel post-processing pipeline to delineate the facial-vestibulocochlear complex within the skull base region, evaluating its accuracy intraoperatively using neuronavigation and tracked electrophysiological recordings. METHODS: In a prospective study of five healthy volunteers and five patients who underwent vestibular schwannoma surgery, rs-DWI was performed and colour tissue maps (CTM) and probabilistic tractography of the cranial nerves were generated. In patients, the average symmetric surface distance (ASSD) and 95% Hausdorff distance (HD-95) were calculated with reference to the neuroradiologist-approved facial nerve segmentation. The accuracy of patient results was assessed intraoperatively using neuronavigation and tracked electrophysiological recordings. RESULTS: Using CTM alone, the facial-vestibulocochlear complex of healthy volunteer subjects was visualised on 9/10 sides. CTM were generated in all 5 patients with vestibular schwannoma enabling the facial nerve to be accurately identified preoperatively. The mean ASSD between the annotators' two segmentations was 1.11 mm (SD 0.40) and the mean HD-95 was 4.62 mm (SD 1.78). The median distance from the nerve segmentation to a positive stimulation point was 1.21 mm (IQR 0.81-3.27 mm) and 2.03 mm (IQR 0.99-3.84 mm) for the two annotators, respectively. CONCLUSIONS: rs-DWI may be used to acquire dMRI data of the cranial nerves within the posterior fossa. CLINICAL RELEVANCE STATEMENT: Readout-segmented diffusion-weighted imaging and colour tissue mapping provide 1-2 mm spatially accurate imaging of the facial-vestibulocochlear nerve complex, enabling accurate preoperative localisation of the facial nerve. This study evaluated the technique in 5 healthy volunteers and 5 patients with vestibular schwannoma. KEY POINTS: • Readout-segmented diffusion-weighted imaging (rs-DWI) with colour tissue mapping (CTM) visualised the facial-vestibulocochlear nerve complex on 9/10 sides in 5 healthy volunteer subjects. • Using rs-DWI and CTM, the facial nerve was visualised in all 5 patients with vestibular schwannoma and within 1.21-2.03 mm of the nerve's true intraoperative location. • Reproducible results were obtained on different scanners.

Occipitocervical instrumented fixation utilising patient-specific C2 3D-printed spinal screw trajectory guides in complex paediatric skeletal dysplasia.

PURPOSE: Instability of the craniocervical junction in paediatric patients with skeletal dysplasia poses a unique set of challenges including anatomical abnormalities, poor bone quality, skeletal immaturity and associated general anaesthetic risks. Instrumented fixation provides optimal stabilisation and fusion rates. The small vertebrae make the placement of C2 pedicle screws technically demanding with low margins of error between the spinal canal and the vertebral artery. METHODS: We describe a novel clinical strategy utilising 3D-printed spinal screw trajectory guides (3D-SSTG) for individually planned C2 pedicle and laminar screws. The technique is based on a pre-operative CT scan and does not require intraoperative CT imaging. This reduces the radiation burden to the patient and forgoes the associated time and cost. The time for model generation and sterilisation was < 24 h. RESULTS: We describe two patients (3 and 6 years old) requiring occipitocervical instrumented fixation for cervical myelopathy secondary to Morquio syndrome with 3D-SSTGs. In the second case, bilateral laminar screw trajectories were also incorporated into the same guide due to the presence of high-riding vertebral arteries. Registration of the postoperative CT to the pre-operative imaging revealed that screws were optimally placed and accurately followed the predefined trajectory. CONCLUSION: To our knowledge, we present the first clinical report of 3D-printed spinal screw trajectory guides at the craniocervical junction in paediatric patients with skeletal dysplasia. The novel combination of multiple trajectories within the same guide provides the intraoperative flexibility of potential bailout options. Future studies will better define the potential of this technology to optimise personalised non-standard screw trajectories.

Resection of the piriform cortex for temporal lobe epilepsy: a Novel approach on imaging segmentation and surgical application.

BACKGROUND: The piriform cortex (PC) occupies both banks of the endorhinal sulcus and has an important role in the pathophysiology of temporal lobe epilepsy (TLE). A recent study showed that resection of more than 50% of PC increased the odds of becoming seizure free by a factor of 16. OBJECTIVE: We report the feasibility of manual segmentation of PC and application of the Geodesic Information Flows (GIF) algorithm to automated segmentation, to guide resection. METHODS: Manual segmentation of PC was performed by two blinded independent examiners in 60 patients with TLE (55% Left TLE, 52% female) with a median age of 35 years (IQR, 29-47 years) and 20 controls (60% Women) with a median age of 39.5 years (IQR, 31-49). The GIF algorithm was used to create an automated pipeline for parcellating PC which was used to guide excision as part of temporal lobe resection for TLE. RESULTS: Right PC was larger in patients and controls. Parcellation of PC was used to guide anterior temporal lobe resection, with subsequent seizure freedom and no visual field or language deficit. CONCLUSION: Reliable segmentation of PC is feasible and can be applied prospectively to guide neurosurgical resection that increases the chances of a good outcome from temporal lobe resection for TLE.

Stereoelectroencephalography electrode placement: Detection of blood vessel conflicts.

OBJECTIVE: Various forms of vascular imaging are performed to identify vessels that should be avoided during stereoelectroencephalography (SEEG) planning. Digital subtraction angiography (DSA) is the gold standard for intracranial vascular imaging. DSA is an invasive investigation, and a balance is necessary to identify all clinically relevant vessels and not to visualize irrelevant vessels that may unnecessarily restrict electrode placement. We sought to estimate the size of vessels that are clinically significant for SEEG planning. METHODS: Thirty-three consecutive patients who underwent 354 SEEG electrode implantations planned with computer-assisted planning and DSA segmentation between 2016 and 2018 were identified from a prospectively maintained database. Intracranial positions of electrodes were segmented from postimplantation computed tomography scans. Each electrode was manually reviewed using "probe-eye view" with the raw preoperative DSA images for vascular conflicts. The diameter of vessels and the location of conflicts were noted. Vessel conflicts identified on raw DSA images were cross-referenced against other modalities to determine whether the conflict could have been detected. RESULTS: One hundred sixty-six vessel conflicts were identified between electrodes and DSA-identified vessels, with 0-3 conflicts per electrode and a median of four conflicts per patient. The median diameter of conflicting vessels was 1.3 mm (interquartile range [IQR] = 1.0-1.5 mm). The median depth of conflict was 31.0 mm (IQR = 14.3-45.0 mm) from the cortical surface. The addition of sulcal models to DSA, magnetic resonance venography (MRV), and T1 + gadolinium images, as an exclusion zone during computer-assisted planning, would have prevented the majority of vessel conflicts. We were unable to determine whether vessels were displaced or transected by the electrodes. SIGNIFICANCE: Vascular segmentation from DSA images was significantly more sensitive than T1 + gadolinium or MRV images. Electrode conflicts with vessels 1-1.5 mm in size did not result in a radiologically detectable or clinically significant hemorrhage and could potentially be excluded from consideration during SEEG planning.

Multicenter validation of automated trajectories for selective laser amygdalohippocampectomy.

OBJECTIVE: Laser interstitial thermal therapy (LITT) is a novel minimally invasive alternative to open mesial temporal resection in drug-resistant mesial temporal lobe epilepsy (MTLE). The safety and efficacy of the procedure are dependent on the preplanned trajectory and the extent of the planned ablation achieved. Ablation of the mesial hippocampal head has been suggested to be an independent predictor of seizure freedom, whereas sparing of collateral structures is thought to result in improved neuropsychological outcomes. We aim to validate an automated trajectory planning platform against manually planned trajectories to objectively standardize the process. METHODS: Using the EpiNav platform, we compare automated trajectory planning parameters derived from expert opinion and machine learning to undertake a multicenter validation against manually planned and implemented trajectories in 95 patients with MTLE. We estimate ablation volumes of regions of interest and quantify the size of the avascular corridor through the use of a risk score as a marker of safety. We also undertake blinded external expert feasibility and preference ratings. RESULTS: Automated trajectory planning employs complex algorithms to maximize ablation of the mesial hippocampal head and amygdala, while sparing the parahippocampal gyrus. Automated trajectories resulted in significantly lower calculated risk scores and greater amygdala ablation percentage, whereas overall hippocampal ablation percentage did not differ significantly. In addition, estimated damage to collateral structures was reduced. Blinded external expert raters were significantly more likely to prefer automated to manually planned trajectories. SIGNIFICANCE: Retrospective studies of automated trajectory planning show much promise in improving safety parameters and ablation volumes during LITT for MTLE. Multicenter validation provides evidence that the algorithm is robust, and blinded external expert ratings indicate that the trajectories are clinically feasible. Prospective validation studies are now required to determine if automated trajectories translate into improved seizure freedom rates and reduced neuropsychological deficits.

Automated trajectory planning for laser interstitial thermal therapy in mesial temporal lobe epilepsy.

OBJECTIVE: Surgical resection of the mesial temporal structures brings seizure remission in 65% of individuals with drug-resistant mesial temporal lobe epilepsy (MTLE). Laser interstitial thermal therapy (LiTT) is a novel therapy that may provide a minimally invasive means of ablating the mesial temporal structures with similar outcomes, while minimizing damage to the neocortex. Systematic trajectory planning helps ensure safety and optimal seizure freedom through adequate ablation of the amygdalohippocampal complex (AHC). Previous studies have highlighted the relationship between the residual unablated mesial hippocampal head and failure to achieve seizure freedom. We aim to implement computer-assisted planning (CAP) to improve the ablation volume and safety of LiTT trajectories. METHODS: Twenty-five patients who had previously undergone LiTT for MTLE were studied retrospectively. The EpiNav platform was used to automatically generate an optimal ablation trajectory, which was compared with the previous manually planned and implemented trajectory. Expected ablation volumes and safety profiles of each trajectory were modeled. The implemented laser trajectory and achieved ablation of mesial temporal lobe structures were quantified and correlated with seizure outcome. RESULTS: CAP automatically generated feasible trajectories with reduced overall risk metrics (P < .001) and intracerebral length (P = .007). There was a significant correlation between the actual and retrospective CAP-anticipated ablation volumes, supporting a 15 mm diameter ablation zone model (P < .001). CAP trajectories would have provided significantly greater ablation of the amygdala (P = .0004) and AHC (P = .008), resulting in less residual unablated mesial hippocampal head (P = .001), and reduced ablation of the parahippocampal gyrus (P = .02). SIGNIFICANCE: Compared to manually planned trajectories CAP provides a better safety profile, with potentially improved seizure-free outcome and reduced neuropsychological deficits, following LiTT for MTLE.

Accuracy of intracranial electrode placement for stereoencephalography: A systematic review and meta-analysis.

OBJECTIVE: Stereoencephalography (SEEG) is a procedure in which electrodes are inserted into the brain to help define the epileptogenic zone. This is performed prior to definitive epilepsy surgery in patients with drug-resistant focal epilepsy when noninvasive data are inconclusive. The main risk of the procedure is hemorrhage, which occurs in 1-2% of patients. This may result from inaccurate electrode placement or a planned electrode damaging a blood vessel that was not detected on the preoperative vascular imaging. Proposed techniques include the use of a stereotactic frame, frameless image guidance systems, robotic guidance systems, and customized patient-specific fixtures. METHODS: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a structured search of the PubMed, Embase, and Cochrane databases identified studies that involve the following: (1) SEEG placement as part of the presurgical workup in patients with (2) drug-resistant focal epilepsy for which (3) accuracy data have been provided. RESULTS: Three hundred twenty-six publications were retrieved, of which 293 were screened following removal of duplicate and non-English-language studies. Following application of the inclusion and exclusion criteria, 15 studies were included in the qualitative and quantitative synthesis of the meta-analysis. Accuracies for SEEG electrode implantations have been combined using a random-effects analysis and stratified by technique. SIGNIFICANCE: The published literature regarding accuracy of SEEG implantation techniques is limited. There are no prospective controlled clinical trials comparing different SEEG implantation techniques. Significant systematic heterogeneity exists between the identified studies, preventing any meaningful comparison between techniques. The recent introduction of robotic trajectory guidance systems has been suggested to provide a more accurate method of implantation, but supporting evidence is limited to class 3 only. It is important that new techniques are compared to the previous "gold-standard" through well-designed and methodologically sound studies before they are introduced into widespread clinical practice.

Resection planning in extratemporal epilepsy surgery using 3D multimodality imaging and intraoperative MRI.

Surgical resection in non-lesional, extratemporal epilepsy, informed by stereoEEG recordings, is challenging. There are no clear borders of resection, and the surgeon is often operating in deep areas of the brain that are difficult to access. We present a technical note where 3D multimodality image integration in EpiNavTM is used to build a planned resection model, based on a previous intracranial EEG evaluation. Intraoperative MRI is then used to ensure a complete resection of the planned model. As stereoEEG becomes more common in the presurgical evaluation of epilepsy, these tools will become increasingly important to facilitate targeted cortical resections.

Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer.

BACKGROUND: To identify computer extracted in vivo dynamic contrast enhanced (DCE) MRI markers associated with quantitative histomorphometric (QH) characteristics of microvessels and Gleason scores (GS) in prostate cancer. METHODS: This study considered retrospective data from 23 biopsy confirmed prostate cancer patients who underwent 3 Tesla multiparametric MRI before radical prostatectomy (RP). Representative slices from RP specimens were stained with vascular marker CD31. Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. Seventy-seven microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to distinguish low from intermediate and high GS. The effect of temporal sampling on kinetic features was assessed and correlations between those robust to temporal resolution and microvessel features discriminative of GS were examined. RESULTS: A total of 12 microvessel architectural features were discriminative of low and intermediate/high grade tumors with area under the receiver operating characteristic curve (AUC) > 0.7. These features were most highly correlated with mean washout gradient (WG) (max rho = -0.62). Independent analysis revealed WG to be moderately robust to temporal resolution (intraclass correlation coefficient [ICC] = 0.63) and WG variance, which was poorly correlated with microvessel features, to be predictive of low grade tumors (AUC = 0.77). Enhancement ratio was the most robust (ICC = 0.96) and discriminative (AUC = 0.78) kinetic feature but was moderately correlated with microvessel features (max rho = -0.52). CONCLUSION: Computer extracted features of prostate DCE MRI appear to be correlated with microvessel architecture and may be discriminative of low versus intermediate and high GS.

Utility of 3D multimodality imaging in the implantation of intracranial electrodes in epilepsy.

OBJECTIVE: We present a single-center prospective study, validating the use of 3D multimodality imaging (3 DMMI) in patients undergoing intracranial electroencephalography (IC-EEG). METHODS: IC-EEG implantation preparation entails first designing of the overall strategy of implantation (strategy) and second the precise details of implantation (planning). For each case, the multidisciplinary team made decisions on strategy and planning before the disclosure of multimodal brain imaging models. Any changes to decisions, following disclosure of the multimodal models, were recorded. RESULTS: Disclosure of 3 DMMI led to a change in strategy in 15 (34%) of 44 individuals. The changes included addition and subtraction of electrodes, addition of grids, and going directly to resection. For the detailed surgical planning, 3 DMMI led to a change in 35 (81%) of 43 individuals. Twenty-five (100%) of 25 patients undergoing stereo-EEG (SEEG) underwent a change in electrode placement, with 158 (75%) of 212 electrode trajectories being altered. SIGNIFICANCE: The use of 3 DMMI makes substantial changes in clinical decision making.

A unified metric of human immune health.

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.

Limited clinical validity of univariate resting-state EEG markers for classifying seizure disorders.

Differentiating between epilepsy and psychogenic non-epileptic seizures presents a considerable challenge in clinical practice, resulting in frequent misdiagnosis, unnecessary treatment and long diagnostic delays. Quantitative markers extracted from resting-state EEG may reveal subtle neurophysiological differences that are diagnostically relevant. Two observational, retrospective diagnostic accuracy studies were performed to test the clinical validity of univariate resting-state EEG markers for the differential diagnosis of epilepsy and psychogenic non-epileptic seizures. Clinical EEG data were collected for 179 quasi-consecutive patients (age > 18) with a suspected diagnosis of epilepsy or psychogenic non-epileptic seizures who were medication-naïve at the time of EEG; 148 age- and gender-matched patients subsequently received a diagnosis from specialist clinicians and were included in the analyses. Study 1 is a hypothesis-driven study testing the ability of theta power and peak alpha frequency to classify people with epilepsy and people with psychogenic non-epileptic seizures, with an advanced machine learning pipeline. The next study (Study 2) is data-driven; a high number of quantitative EEG features are extracted and a similar machine learning approach as Study 1 assesses whether previously unexplored univariate EEG measures show promise as diagnostic markers. The results of Study 1 suggest that EEG markers that were previously identified as promising diagnostic indicators (i.e. theta power and peak alpha frequency) have limited clinical validity for the classification of epilepsy and psychogenic non-epileptic seizures (mean accuracy: 48%). The results of Study 2 indicate that identifying univariate markers that show good correlation with a categorical diagnostic label is challenging (mean accuracy: 45-60%). This is due to a considerable overlap in neurophysiological features between the diagnostic classes considered in this study, and to the presence of more dominant EEG dynamics such as alterations due to temporal proximity to epileptiform discharges. Markers that were identified in the context of previous epilepsy research using visually normal resting-state EEG were found to have limited clinical validity for the classification task of distinguishing between people with epilepsy and people with psychogenic non-epileptic seizures. A search for alternative diagnostic markers uncovered the challenges involved and generated recommendations for further research.

Assessing informative tract segmentation and nTMS for pre-operative planning.

BACKGROUND: Deep learning-based (DL) methods are the best-performing methods for white matter tract segmentation in anatomically healthy subjects. However, tract annotations are variable or absent in clinical data and manual annotations are especially difficult in patients with tumors where normal anatomy may be distorted. Direct cortical and subcortical stimulation is the gold standard ground truth to determine the cortical and sub-cortical lo- cation of motor-eloquent areas intra-operatively. Nonetheless, this technique is invasive, prolongs the surgical procedure, and may cause patient fatigue. Navigated Transcranial Magnetic Stimulation (nTMS) has a well-established correlation to direct cortical stimulation for motor mapping and the added advantage of being able to be acquired pre-operatively. NEW METHOD: In this work, we evaluate the feasibility of using nTMS motor responses as a method to assess corticospinal tract (CST) binary masks and estimated uncertainty generated by a DL-based tract segmentation in patients with diffuse gliomas. RESULTS: Our results show CST binary masks have a high overlap coefficient (OC) with nTMS response masks. A strong negative correlation is found between estimated uncertainty and nTMS response mask distance to the CST binary mask. COMPARISON WITH EXISTING METHODS: We compare our approach (UncSeg) with the state-of-the-art TractSeg in terms of OC between the CST binary masks and nTMS response masks. CONCLUSIONS: In this study, we demonstrate that estimated uncertainty from UncSeg is a good measure of the agreement between the CST binary masks and nTMS response masks distance to the CST binary mask boundary.

Evaluation and Management of Deficiency of Adenosine Deaminase 2: An International Consensus Statement.

Importance: Deficiency of adenosine deaminase 2 (DADA2) is a recessively inherited disease characterized by systemic vasculitis, early-onset stroke, bone marrow failure, and/or immunodeficiency affecting both children and adults. DADA2 is among the more common monogenic autoinflammatory diseases, with an estimate of more than 35 000 cases worldwide, but currently, there are no guidelines for diagnostic evaluation or management. Objective: To review the available evidence and develop multidisciplinary consensus statements for the evaluation and management of DADA2. Evidence Review: The DADA2 Consensus Committee developed research questions based on data collected from the International Meetings on DADA2 organized by the DADA2 Foundation in 2016, 2018, and 2020. A comprehensive literature review was performed for articles published prior to 2022. Thirty-two consensus statements were generated using a modified Delphi process, and evidence was graded using the Oxford Center for Evidence-Based Medicine Levels of Evidence. Findings: The DADA2 Consensus Committee, comprising 3 patient representatives and 35 international experts from 18 countries, developed consensus statements for (1) diagnostic testing, (2) screening, (3) clinical and laboratory evaluation, and (4) management of DADA2 based on disease phenotype. Additional consensus statements related to the evaluation and treatment of individuals with DADA2 who are presymptomatic and carriers were generated. Areas with insufficient evidence were identified, and questions for future research were outlined. Conclusions and Relevance: DADA2 is a potentially fatal disease that requires early diagnosis and treatment. By summarizing key evidence and expert opinions, these consensus statements provide a framework to facilitate diagnostic evaluation and management of DADA2.

Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health.

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.

Characterization of the antispike IgG immune response to COVID-19 vaccines in people with a wide variety of immunodeficiencies.

Research on coronavirus disease 2019 vaccination in immune-deficient/disordered people (IDP) has focused on cancer and organ transplantation populations. In a prospective cohort of 195 IDP and 35 healthy volunteers (HV), antispike immunoglobulin G (IgG) was detected in 88% of IDP after dose 2, increasing to 93% by 6 months after dose 3. Despite high seroconversion, median IgG levels for IDP never surpassed one-third that of HV. IgG binding to Omicron BA.1 was lowest among variants. Angiotensin-converting enzyme 2 pseudo-neutralization only modestly correlated with antispike IgG concentration. IgG levels were not significantly altered by receipt of different messenger RNA-based vaccines, immunomodulating treatments, and prior severe acute respiratory syndrome coronavirus 2 infections. While our data show that three doses of coronavirus disease 2019 vaccinations induce antispike IgG in most IDP, additional doses are needed to increase protection. Because of the notably reduced IgG response to Omicron BA.1, the efficacy of additional vaccinations, including bivalent vaccines, should be studied in this population.

OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data.

OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-seq datasets, compendia sharing, RESTful API support, and an additional meta-analysis method based on random effects. Here, we provide a step-by-step guide for using OMiCC. For complete details on the use and execution of this protocol, please refer to Shah et al. (2016).