Expanding the mutational spectrum of ReNU syndrome: insights into 5’ Stem-loop variants
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Mechanisms of NLRP3 activation and inhibition elucidated by functional analysis of disease-associated variants
The NLRP3 inflammasome is a multiprotein complex that mediates caspase-1 activation and the release of proinflammatory cytokines, including interleukin (IL)-1β and IL-18. Gain-of-function variants in the gene encoding NLRP3 (also called cryopyrin) lead to constitutive inflammasome activation and excessive IL-1β production in cryopyrin-associated periodic syndromes (CAPS). Here we present functional screening and automated analysis of 534 NLRP3 variants from the international INFEVERS registry and the ClinVar database. This resource captures the effect of NLRP3 variants on ASC speck formation spontaneously, at low temperature, after inflammasome stimulation and with the specific NLRP3 inhibitor MCC950. Most notably, our analysis facilitated the updated classification of NLRP3 variants in INFEVERS. Structural analysis suggested multiple mechanisms by which CAPS variants activate NLRP3, including enhanced ATP binding, stabilizing the active NLRP3 conformation, destabilizing the inactive NLRP3 complex and promoting oligomerization of the pyrin domain. Furthermore, we identified pathogenic variants that can hypersensitize the activation of NLRP3 in response to nigericin and cold temperature exposure. We also found that most CAPS-related NLRP3 variants can be inhibited by MCC950; however, NLRP3 variants with changes to proline affecting helices near the inhibitor binding site are resistant to MCC950, as are variants in the pyrin domain, which likely trigger activation directly with the pyrin domain of ASC. Our findings could help stratify the CAPS population for NLRP3 inhibitor clinical trials and our automated methodologies can be implemented for molecules with a different mechanism of activation and in laboratories worldwide that are interested in adding new functionally validated NLRP3 variants to the resource. Overall, our study provides improved diagnosis for patients with CAPS, mechanistic insight into the activation of NLRP3 and stratification of patients for the future application of targeted therapeutics.
Selection for somatic escape variants in SERPINA1 in the liver of patients with alpha-1 antitrypsin deficiency
Somatic variants accumulate in non-malignant tissues with age. Functional variants, leading to clonal advantage of hepatocytes, accumulate in the liver of patients with acquired chronic liver disease (CLD). Whether somatic variants are common to CLD from differing etiologies is unknown. We analyzed liver somatic variants in patients with genetic CLD from alpha-1 antitrypsin (A1AT) deficiency or hemochromatosis. We show that somatic variants in SERPINA1, the gene encoding A1AT, are strongly selected for in A1AT deficiency, with evidence of convergent evolution. Acquired SERPINA1 variants are clustered at the carboxyl terminus of A1AT, leading to truncation. In vitro and in vivo, C-terminal truncation variants reduce disease-associated Z-A1AT polymer accumulation and disruption of the endoplasmic reticulum, supporting the C-terminal domain swap mechanism. Therefore, somatic escape variants from a deleterious germline variant are selected for in A1AT deficiency, suggesting that functional somatic variants are disease-specific in CLD and point to disease-associated mechanisms.
Deep mutational learning for the selection of therapeutic antibodies resistant to the evolution of Omicron variants of SARS-CoV-2
Most antibodies for treating COVID-19 rely on binding the receptor-binding domain (RBD) of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). However, Omicron and its sub-lineages, as well as other heavily mutated variants, have rendered many neutralizing antibodies ineffective. Here we show that antibodies with enhanced resistance to the evolution of SARS-CoV-2 can be identified via deep mutational learning. We constructed a library of full-length RBDs of Omicron BA.1 with high mutational distance and screened it for binding to the angiotensin-converting-enzyme-2 receptor and to neutralizing antibodies. After deep-sequencing the library, we used the data to train ensemble deep-learning models for the prediction of the binding and escape of a panel of eight therapeutic antibody candidates targeting a diverse range of RBD epitopes. By using in silico evolution to assess antibody breadth via the prediction of the binding and escape of the antibodies to millions of Omicron sequences, we found combinations of two antibodies with enhanced and complementary resistance to viral evolution. Deep learning may enable the development of therapeutic antibodies that remain effective against future SARS-CoV-2 variants.
Ion channel traffic jams: the significance of trafficking deficiency in long QT syndrome
A well-balanced ion channel trafficking machinery is paramount for the normal electromechanical function of the heart. Ion channel variants and many drugs can alter the cardiac action potential and lead to arrhythmias by interfering with mechanisms like ion channel synthesis, trafficking, gating, permeation, and recycling. A case in point is the Long QT syndrome (LQTS), a highly arrhythmogenic disease characterized by an abnormally prolonged QT interval on ECG produced by variants and drugs that interfere with the action potential. Disruption of ion channel trafficking is one of the main sources of LQTS. We review some molecular pathways and mechanisms involved in cardiac ion channel trafficking. We highlight the importance of channelosomes and other macromolecular complexes in helping to maintain normal cardiac electrical function, and the defects that prolong the QT interval as a consequence of variants or the effect of drugs. We examine the concept of “interactome mapping” and illustrate by example the multiple protein–protein interactions an ion channel may undergo throughout its lifetime. We also comment on how mapping the interactomes of the different cardiac ion channels may help advance research into LQTS and other cardiac diseases. Finally, we discuss how using human induced pluripotent stem cell technology to model ion channel trafficking and its defects may help accelerate drug discovery toward preventing life-threatening arrhythmias. Advancements in understanding ion channel trafficking and channelosome complexities are needed to find novel therapeutic targets, predict drug interactions, and enhance the overall management and treatment of LQTS patients.
Beyond CHD7 gene: unveiling genetic diversity in clinically suspected CHARGE syndrome
The Verloes or Hale diagnostic criteria have been applied for diagnosing CHARGE syndrome in suspected patients. This study was conducted to evaluate the diagnostic rate of CHD7 according to these diagnostic criteria in suspected patients and also to investigate other genetic defects in CHD7-negative patients. The clinical findings and the results of genetic testing of CHD7, chromosome microarray, exome sequencing, or genome sequencing of 59 subjects were reviewed. CHD7 pathogenic variants were identified in 78% of 46 subjects who met either the Verloes or Hale diagnostic criteria and in 87% of 38 subjects who met both criteria, whereas no CHD7 variant was detected in 13 subjects who met neither criterion. Among 23 patients without the CHD7 variant, six genetic diseases were identified in 7 patients, including Wolf–Hirschhorn syndrome, 1q21 deletion syndrome, 19q13 microdeletion, and pathogenic variants in PLCB4, TRRAP, and OTX2. Based on these comprehensive analyses, the overall diagnostic rate was 73% for seven different genetic diseases. This study emphasizes the importance of comprehensive clinical and genetic evaluation in patients with clinically suspected CHARGE syndrome, recognizing the overlapping phenotypes in other rare genetic disorders.
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