Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy

Change in absolute neutrophil count after COVID-19 infection in patients using clozapine versus other antipsychotics

It was reported that patients who contracted COVID-19 while taking clozapine exhibited a distinct hematological response. However, the absence of control groups made it difficult to attribute it to clozapine. The changes in absolute neutrophil counts (ANCs) during the 4 weeks after COVID-19 infection were compared between the two groups of patients with severe mental illnesses (SMIs) (49 patients using clozapine and 54 using other antipsychotics) using generalized additive modeling. Although the pattern of a transient drop in ANC followed by gradual recovery could be demonstrated in both groups, it was more pronounced in the clozapine group ( P  = 0.00025). Nevertheless, overall ANC remained at a higher level in the clozapine group. The results suggested potential interaction between clozapine and COVID-19 at the level of hematological dynamics. However, it did not necessarily indicate that such interaction is inevitably harmful or dangerous. It was more of a concern that some patients using other antipsychotics exhibited decreased ANC, which did not easily recover. Traditionally, clinicians have been concerned about the worsening of hematological side effects in clozapine patients after COVID-19 infection. However, the obtained result highlighted the necessity of hematological monitoring in patients using any type of antipsychotics for SMIs.

Nervous system-related tropism of SARS-CoV-2 and autoimmunity in COVID-19 infection

The effects of SARS-CoV-2 in COVID-19 on the nervous system are incompletely understood. SARS-CoV-2 can infect endothelial cells, neurons, astrocytes, and oligodendrocytes with consequences for the host. There are indications that infection of these CNS-resident cells may result in long-term effects, including emergence of neurodegenerative diseases. Indirect effects of infection with SARS-CoV-2 relate to the induction of autoimmune disease involving molecular mimicry or/and bystander activation of T- and B cells and emergence of autoantibodies against various self-antigens. Data obtained in preclinical models of coronavirus-induced disease gives important clues for the understanding of nervous system-related assault of SARS-CoV-2. The pathophysiology of long-COVID syndrome and post-COVID syndrome in which autoimmunity and immune dysregulation might be the driving forces are still incompletely understood. A better understanding of nervous-system-related immunity in COVID-19 might support the development of therapeutic approaches. In this review, the current understanding of SARS-CoV-2 tropism for the nervous system, the associated immune responses, and diseases are summarized. The data indicates that there is viral tropism of SARS-CoV-2 in the nervous system resulting in various disease conditions. Prevention of SARS-CoV-2 infection by means of vaccination is currently the best strategy for the prevention of subsequent tissue damage involving the nervous system.

Fast and accurate local ancestry inference with Recomb-Mix

The availability of large genotyped cohorts brings new opportunities for revealing high-resolution genetic structure of admixed populations, via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g., intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. Here, we present a new LAI method, Recomb-Mix. Adopting the commonly used site-based formulation based on the classic Li and Stephens' model, Recomb-Mix integrates the elements of existing methods and introduces a new graph collapsing to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations.