Sex differences in symptomatology and immune profiles of Long COVID.

Strong sex differences in the frequencies and manifestations of Long COVID (LC) have been reported with females significantly more likely than males to present with LC after acute SARS-CoV-2 infection 1-7 . However, whether immunological traits underlying LC differ between sexes, and whether such differences explain the differential manifestations of LC symptomology is currently unknown. Here, we performed sex-based multi-dimensional immune-endocrine profiling of 165 individuals 8 with and without LC in an exploratory, cross-sectional study to identify key immunological traits underlying biological sex differences in LC. We found that female and male participants with LC experienced different sets of symptoms, and distinct patterns of organ system involvement, with female participants suffering from a higher symptom burden. Machine learning approaches identified differential sets of immune features that characterized LC in females and males. Males with LC had decreased frequencies of monocyte and DC populations, elevated NK cells, and plasma cytokines including IL-8 and TGF-ß-family members. Females with LC had increased frequencies of exhausted T cells, cytokine-secreting T cells, higher antibody reactivity to latent herpes viruses including EBV, HSV-2, and CMV, and lower testosterone levels than their control female counterparts. Testosterone levels were significantly associated with lower symptom burden in LC participants over sex designation. These findings suggest distinct immunological processes of LC in females and males and illuminate the crucial role of immune-endocrine dysregulation in sex-specific pathology.

Causal identification of single-cell experimental perturbation effects with CINEMA-OT.

Recent advancements in single-cell technologies allow characterization of experimental perturbations at single-cell resolution. While methods have been developed to analyze such experiments, the application of a strict causal framework has not yet been explored for the inference of treatment effects at the single-cell level. Here we present a causal-inference-based approach to single-cell perturbation analysis, termed CINEMA-OT (causal independent effect module attribution + optimal transport). CINEMA-OT separates confounding sources of variation from perturbation effects to obtain an optimal transport matching that reflects counterfactual cell pairs. These cell pairs represent causal perturbation responses permitting a number of novel analyses, such as individual treatment-effect analysis, response clustering, attribution analysis, and synergy analysis. We benchmark CINEMA-OT on an array of treatment-effect estimation tasks for several simulated and real datasets and show that it outperforms other single-cell perturbation analysis methods. Finally, we perform CINEMA-OT analysis of two newly generated datasets: (1) rhinovirus and cigarette-smoke-exposed airway organoids, and (2) combinatorial cytokine stimulation of immune cells. In these experiments, CINEMA-OT reveals potential mechanisms by which cigarette-smoke exposure dulls the airway antiviral response, as well as the logic that governs chemokine secretion and peripheral immune cell recruitment.

Distinguishing features of long COVID identified through immune profiling.

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2-4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Single-cell analysis reveals inflammatory interactions driving macular degeneration.

Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate therapies for neurodegenerative diseases, leading us to examine whether pathways of disease progression are shared across neurodegenerative conditions. Here we use single-nucleus RNA sequencing to profile lesions from 11 postmortem human retinas with age-related macular degeneration and 6 control retinas with no history of retinal disease. We create a machine-learning pipeline based on recent advances in data geometry and topology and identify activated glial populations enriched in the early phase of disease. Examining single-cell data from Alzheimer's disease and progressive multiple sclerosis with our pipeline, we find a similar glial activation profile enriched in the early phase of these neurodegenerative diseases. In late-stage age-related macular degeneration, we identify a microglia-to-astrocyte signaling axis mediated by interleukin-1ß which drives angiogenesis characteristic of disease pathogenesis. We validated this mechanism using in vitro and in vivo assays in mouse, identifying a possible new therapeutic target for AMD and possibly other neurodegenerative conditions. Thus, due to shared glial states, the retina provides a potential system for investigating therapeutic approaches in neurodegenerative diseases.

Innate immune biology in age-related macular degeneration.

Age-related macular degeneration (AMD) is a neurodegenerative disease and a leading cause of irreversible vision loss in the developed world. While not classically described as an inflammatory disease, a growing body of evidence has implicated several components of the innate immune system in the pathophysiology of age-related macular degeneration. In particular, complement activation, microglial involvement, and blood-retinal-barrier disruption have been shown to play key roles in disease progression, and subsequent vision loss. This review discusses the role of the innate immune system in age-related macular degeneration as well as recent developments in single-cell transcriptomics that help advance the understanding and treatment of age-related macular degeneration. We also explore the several potential therapeutic targets for age-related macular degeneration in the context of innate immune activation.

NK/T-cell Lymphoma With Orbital Involvement: A Case Report and Systematic Review of the Literature.

PURPOSE: To present the clinical course of a patient with recurrent NK/T-cell lymphoma (NKTL) involving the orbit and to review the literature on patients with NKTL involving the orbit. METHODS: The PubMed database was searched for all cases of NKTL involving orbital, intraocular, or adnexal ocular structures. RESULTS: Ninety-six patients were included in the final analysis. The mean age of diagnosis was 48.1 ± 16.8 years. The patients were 53/96 (55.2%) male and 43/96 (44.8%) female. Tumor location varied and included the orbit in 80/96 (83.3%), nasosinus in 56/96 (58.3%), uvea in 11/96 (11.5%), lacrimal gland in 9/96 (9.4%), lacrimal drainage system in 11/96 (11.5%), and conjunctiva in 7/96 (7.3%) cases. Management included surgical debulking in 29/96 (30.2%) cases, radiotherapy in 52/96 (54.2%) cases, and chemotherapy in 82/96 (85.4%) cases. Median survival was 6 months (95% CI: 5-9). Chemotherapy (hazard ratio = 0.80, 95% CI: 0.67-0.95, p = 0.013), radiotherapy (hazard ratio = 0.75, 95% CI: 0.64-0.87, p < 0.001), and orbital involvement being a recurrence of disease (hazard ratio = 0.79, 95% CI: 0.67-0.95, p = 0.009) were associated with improved survival. Advanced Ann Arbor stage (III-IV) at diagnosis (hazard ratio = 1.22, 95% CI: 1.08-1.38, p = 0.001), vision loss (hazard ratio = 1.18, 95% CI: 1.04-1.34, p = 0.009), proptosis (hazard ratio = 1.15, 95% CI: 1.01-1.30, p = 0.035) and periorbital swelling (hazard ratio = 1.15, 95% CI: 1.00-1.33, p = 0.048) were associated with poor survival. CONCLUSIONS: NK/T-cell lymphoma involving the orbit, globe, or ocular adnexa heralds a poor prognosis where early diagnosis and therapy are critical. The use of radiotherapy and chemotherapy is associated with improved survival.

A case of extrafoveal focal choroidal excavation.

Purpose: To describe an extrafoveal presentation of focal choroidal excavation and corresponding imaging findings. Methods: Retrospective case report. Patients: Single patient with diagnosis of extrafoveal focal choroidal excavation. Results: A 28-year-old man was referred for evaluation of a suspicious lesion in his right posterior fundus. Functional examination demonstrated best-corrected visual acuity of 20/40 in the right eye and 20/20 in the left eye. Ophthalmoscopy exam and fundus photography revealed a yellowish lesion superior to the fovea of the right eye. The lesion was hyperfluorescent on fundus autofluorescence imaging and late phase fluorescein angiography demonstrated staining of the lesion without leakage. Optical coherence tomography (OCT) of the lesion was consistent with focal choroidal excavation. Five months after presentation, the patient's vision, exam, and imaging remained stable. Discussion: Focal choroidal excavation is a recently recognized clinical entity that is often incidentally found, and presents asymptomatic or with mildly decreased visual acuity in the affected eye. It has characteristic findings on optical coherence tomography (OCT) that can be used to distinguish it from other retinal lesions that may appear similar on ophthalmoscopy. We present the case of an uncommon extrafoveal presentation of FCE at a relatively young age, which may represent either a congenital abnormality or the sequelae of an unidentified chronic process. While most FCE remain stable, patients are often followed for lesion progression and the possibility of choroidal vascular pathology which might necessitate intervention.

Deep learning for quality assessment of optical coherence tomography angiography images.

Optical coherence tomography angiography (OCTA) is an emerging non-invasive technique for imaging the retinal vasculature. While there are many promising clinical applications for OCTA, determination of image quality remains a challenge. We developed a deep learning-based system using a ResNet152 neural network classifier, pretrained using ImageNet, to classify images of the superficial capillary plexus in 347 scans from 134 patients. Images were also manually graded by two independent graders as a ground truth for the supervised learning models. Because requirements for image quality may vary depending on the clinical or research setting, two models were trained-one to identify high-quality images and one to identify low-quality images. Our neural network models demonstrated outstanding area under the curve (AUC) metrics for both low quality image identification (AUC = 0.99, 95%CI 0.98-1.00, [Formula: see text] = 0.90) and high quality image identification (AUC = 0.97, 95%CI 0.96-0.99, [Formula: see text] = 0.81), significantly outperforming machine-reported signal strength (AUC = 0.82, 95%CI 0.77-0.86, [Formula: see text]= 0.52 and AUC = 0.78, 95%CI 0.73-0.83, [Formula: see text] = 0.27 respectively). Our study demonstrates that techniques from machine learning may be used to develop flexible and robust methods for quality control of OCTA images.

Distinguishing features of Long COVID identified through immune profiling.

SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID 1-3 . Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions 1-3 ; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.

Glial-mediated neuroinflammatory mechanisms in age-related macular degeneration.

Age-related macular degeneration (AMD) is a neurodegenerative disorder characterized by photoreceptor and retinal pigment epithelium loss often complicated by neovascularization and is one of the leading causes of irreversible vision loss worldwide. However, the precise pathophysiology of AMD remains to date unclear, and there is a dearth of effective therapies for the early stages of the disease. A growing body of evidence has identified microglia-mediated neuroinflammation as a key driver of neuronal damage in AMD, presenting a novel avenue for the development of pharmacological agents targeting this cell population. The local microglial response interacts with other glia as well as engages in crosstalk with peripheral immunological niches. This article presents a review of the current evidence regarding the involvement of glia in the pathophysiology of AMD, an overview of the key immune circuits and effector mechanisms shown to be active in AMD, and potential therapeutic avenues targeting glial involvement.

Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism.

We have undertaken a genome-wide analysis of rare copy-number variation (CNV) in 1124 autism spectrum disorder (ASD) families, each comprised of a single proband, unaffected parents, and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, characterized by a highly social personality. We identify rare recurrent de novo CNVs at five additional regions, including 16p13.2 (encompassing genes USP7 and C16orf72) and Cadherin 13, and implement a rigorous approach to evaluating the statistical significance of these observations. Overall, large de novo CNVs, particularly those encompassing multiple genes, confer substantial risks (OR = 5.6; CI = 2.6-12.0, p = 2.4 × 10(-7)). We estimate there are 130-234 ASD-related CNV regions in the human genome and present compelling evidence, based on cumulative data, for association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin 1.