Genomic, transcriptomic, and protein landscape profile of CFTR and cystic fibrosis

Interleukin-1 Receptor Antagonist Gene (IL1RN) Variants Modulate the Cytokine Release Syndrome and Mortality of COVID-19

BACKGROUND

We examined effects of single-nucleotide variants (SNVs) of IL1RN, the gene encoding the anti-inflammatory interleukin 1 receptor antagonist (IL-1Ra), on the cytokine release syndrome (CRS) and mortality in patients with acute severe respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

IL1RN CTA haplotypes formed from 3 SNVs (rs419598, rs315952, rs9005) and the individual SNVs were assessed for association with laboratory markers of inflammation and mortality. We studied 2589 patients hospitalized with SARS-CoV-2 between March 2020 and March 2021.

RESULTS

Mortality was 15.3% and lower in women than men (13.1% vs 17.3%, P = .0003). Carriers of the CTA-1/2 IL1RN haplotypes exhibited decreased inflammatory markers and increased plasma IL-1Ra. Evaluation of the individual SNVs of the IL1RN, carriers of the rs419598 C/C SNV exhibited significantly reduced inflammatory biomarker levels and numerically lower mortality compared to the C/T-T/T genotype (10.0% vs 17.8%, P = .052) in men, with the most pronounced association observed in male patients ≤74 years old, whose mortality was reduced by 80% (3.1% vs 14.0%, P = .030).

CONCLUSIONS

The IL1RN haplotype CTA and C/C variant of rs419598 are associated with attenuation of the CRS and decreased mortality in men with acute SARS-CoV-2 infection. The data suggest that the IL1RN pathway modulates the severity of coronavirus disease 2019 (COVID-19) via endogenous anti-inflammatory mechanisms.

Gene Therapy for Genetic Syndromes: Understanding the Current State to Guide Future Care

Gene therapy holds promise as a life-changing option for individuals with genetic variants that give rise to disease. FDA-approved gene therapies for Spinal Muscular Atrophy (SMA), cerebral adrenoleukodystrophy, β-Thalassemia, hemophilia A/B, retinal dystrophy, and Duchenne Muscular Dystrophy have generated buzz around the ability to change the course of genetic syndromes. However, this excitement risks over-expansion into areas of genetic disease that may not fit the current state of gene therapy. While in situ (targeted to an area) and ex vivo (removal of cells, delivery, and administration of cells) approaches show promise, they have a limited target ability. Broader in vivo gene therapy trials have shown various continued challenges, including immune response, use of immune suppressants correlating to secondary infections, unknown outcomes of overexpression, and challenges in driving tissue-specific corrections. Viral delivery systems can be associated with adverse outcomes such as hepatotoxicity and lethality if uncontrolled. In some cases, these risks are far outweighed by the potentially lethal syndromes for which these systems are being developed. Therefore, it is critical to evaluate the field of genetic diseases to perform cost-benefit analyses for gene therapy. In this work, we present the current state while setting forth tools and resources to guide informed directions to avoid foreseeable issues in gene therapy that could prevent the field from continued success.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

N-methyl-d-aspartate (NMDA) receptor genetics: The power of paralog homology and protein dynamics in defining dominant genetic variants

Predicting genotype-to-phenotype correlations from genomic variants has been challenging, particularly for genes that have a complex balance of dominant and recessive inheritance for phenotypes. Variants in NMDA receptor components GRIN1, GRIN2A, and GRIN2B cause a myriad of dominant disease phenotypes, with the most common being epilepsy and autism spectrum disorder. Starting from the analysis of a variant of uncertain significance (VUS, GRIN2A G760S), we realized the need for tools to map dominant variants for the components of the NMDA receptor. Some variants within GRIN1, GRIN2A, and GRIN2B exert dominant epilepsy and developmental delay, yet other amino acid variants are conserved and predicted to alter protein function but do not have dominant phenotypes. Common variant annotation tools are not powered to determine pathogenic dominant outcomes. To address this gap, we integrated sequence and structural analyses for GRIN1, GRIN2A, and GRIN2B. Using this approach, we determined that paralog homology mapping and topology can segregate dominant variants, with an elevation of intermolecular contacts between the subunits. Furthermore, demonstrating the general utility of our methodology, we show that 25 VUS within ClinVar also reach a dominant variant annotation, including the GRIN2A G760S variant. Our work suggests paralog homology and protein topology as a powerful strategy within the receptor complex to resolve dominant genetic variants relative to variants that would fit a recessive inheritance, requiring two damaging variants. These strategies should be tested in additional dominant genetic disorders to determine the broader utility.