IL-17 signaling in primary sclerosing cholangitis patient-derived organoids.

BACKGROUND: The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study, we aimed to investigate and characterize the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation. METHODS: Cholangiocytes obtained from patients with PSC and without PSC by endoscopic retrograde cholangiography were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing. RESULTS: Unsupervised clustering of all integrated single-cell RNA sequencing data identified 8 cholangiocyte clusters that did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, as noted by an increased number of differentially expressed genes by transcriptomics and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, genome sequencing identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO. CONCLUSIONS: PSC and non-PSC patient-derived ECO respond differently to IL-17 stimulation, implicating this pathway in the pathogenesis of PSC.

A retrospective multicenter study on clinical and serological parameters in patients with MuSK myasthenia gravis with and without general immunosuppression.

Introduction: Muscle-specific kinase (MuSK)- myasthenia gravis (MG) is caused by pathogenic autoantibodies against MuSK that correlate with disease severity and are predominantly of the IgG4 subclass. The first-line treatment for MuSK-MG is general immunosuppression with corticosteroids, but the effect of treatment on IgG4 and MuSK IgG4 levels has not been studied. Methods: We analyzed the clinical data and sera from 52 MuSK-MG patients (45 female, 7 male, median age 49 (range 17-79) years) from Italy, the Netherlands, Greece and Belgium, and 43 AChR-MG patients (22 female, 21 male, median age 63 (range 2-82) years) from Italy, receiving different types of immunosuppression, and sera from 46 age- and sex-matched non-disease controls (with no diagnosed diseases, 38 female, 8 male, median age 51.5 (range 20-68) years) from the Netherlands. We analyzed the disease severity (assessed by MGFA or QMG score), and measured concentrations of MuSK IgG4, MuSK IgG, total IgG4 and total IgG in the sera by ELISA, RIA and nephelometry. Results: We observed that MuSK-MG patients showed a robust clinical improvement and reduction of MuSK IgG after therapy, and that MuSK IgG4 concentrations, but not total IgG4 concentrations, correlated with clinical severity. MuSK IgG and MuSK IgG4 concentrations were reduced after immunosuppression in 4/5 individuals with before-after data, but data from non-linked patient samples showed no difference. Total serum IgG4 levels were within the normal range, with IgG4 levels above threshold (1.35g/L) in 1/52 MuSK-MG, 2/43 AChR-MG patients and 1/45 non-disease controls. MuSK-MG patients improved within the first four years after disease onset, but no further clinical improvement or reduction of MuSK IgG4 were observed four years later, and only 14/52 (26.92%) patients in total, of which 13 (93.3%) received general immunosuppression, reached clinical remission. Discussion: We conclude that MuSK-MG patients improve clinically with general immunosuppression but may require further treatment to reach remission. Longitudinal testing of individual patients may be clinically more useful than single measurements of MuSK IgG4. No significant differences in the serum IgG4 concentrations and IgG4/IgG ratio between AChR- and MuSK-MG patients were found during follow-up. Further studies with larger patient and control cohorts are necessary to validate the findings.

Diagnostic yield of exome and genome sequencing after non-diagnostic multi-gene panels in patients with single-system diseases.

BACKGROUND: Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. RESULTS: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). CONCLUSION: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates.

Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data.

Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.

Clinical Trials for Special Populations: Children, Older Adults, and Rare Diseases.

Research cannot maximize population health unless it improves health for all members of the public, including special populations such as children, older adults, and people living with rare diseases. Each of these categories require special considerations when planning and performing clinical trials, and common threads of ethical conduct of research in vulnerable populations appear throughout. In this review, definitions of each of the three categories of special population (children, older adults, and rare diseases) are discussed in terms of US research regulations, the unique challenges to conducting clinical trials for these special populations, critical ethical issues, and opportunities for innovative ways to design and operationalize clinical trials in special populations. Additional critical attention is focused on factors that influence the generalizability of study results to reduce health disparities, as well as the importance of community engagement and advocacy groups that can help to educate potential trial participants of the benefits of clinical trial participation.

Most patients with disorders of gut-brain interaction receive pharmacotherapy with major or moderate drug-gene interactions.

BACKGROUND: How variations predicted by pharmacogenomic testing to alter drug metabolism and therapeutic response affect outcomes for patients with disorders of gut- brain interaction is unclear. AIMS: To assess the prevalence of pharmacogenomics-predicted drug-gene interactions and symptom outcomes for patients with disorders of gut-brain interaction. METHODS: Patients who were treated in our clinical practice for functional dyspepsia/bowel disorder underwent pharmacogenomic testing. The change in symptoms from baseline to 6 months was compared for patients with variations in CYP2D6 and CYP2C19, which metabolize neuromodulators, and SLC6A4, which encodes the sodium- dependent serotonin transporter. RESULTS: At baseline, 79 of 94 participants (84%) had at least one predicted major drug- gene interaction, and all 94 (100%) had at least one predicted moderate interaction. For the 44 participants who completed a survey of their symptoms at 6 months, the mean (SD) irritable bowel syndrome-symptom severity score decreased from 284 (71) at baseline to 231 (95) at 6 months (p < 0.001). Among patients taking selective serotonin reuptake inhibitors, the decrease in symptom severity (p = 0.03) and pain (p = 0.002) scores from baseline to 6 months was greater for patients with a homozygous SLC6A4 long/long genotype (n = 30) (ie, increased serotonin transporter activity) than for patients with homozygous short/short or heterozygous long/short genotypes (n = 64). Symptom outcomes were not affected by CYP2D6 or CYP2C19 variations. CONCLUSIONS: The homozygous SLC6A4 long/long genotype confers better symptom resolution for patients with disorders of gut-brain interaction who take selective serotonin reuptake inhibitors than do the homozygous short/short or heterozygous long/short genotypes.

IL-17 Signaling in Primary Sclerosing Cholangitis Patient-Derived Organoids.

The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study we aimed to investigate the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation. Cholangiocytes obtained from PSC and non-PSC patients by endoscopic retrograde cholangiography (ERC) were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing (GS). Unsupervised clustering of all integrated scRNA-seq data identified 8 cholangiocyte clusters which did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, noted by an increased number of differentially expressed genes (DEG) by transcriptomics, and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, GS identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO. In conclusion, PSC and non-PSC patient derived ECO respond differently to IL-17 stimulation implicating this pathway in the pathogenesis of PSC.

Silencing of FCRLB by shRNA ameliorates MuSK-induced EAMG in mice.

INTRODUCTION: Muscle specific kinase (MuSK) antibody positive myasthenia gravis (MG) often presents with a severe disease course and resistance to treatment. Treatment-refractory patients may respond to B cell depleting treatment methods. Our aim was to investigate whether inhibition of Fc receptor-like B (FCRLB) could effectively suppress autoimmunity without diminishing B cell counts in animal model of MG, a classical antibody-mediated autoimmune disease. METHODS: Experimental autoimmune MG was induced in Balb/C mice with two s.c. immunizations with recombinant human MuSK in complete Freund's adjuvant. FCRLB was silenced with a lentiviral particle transported shRNA in myasthenic mice with a single i.p. injection during second MuSK-immunization. Control immunized mice received scrambled shRNA or saline. Mice were observed for clinical parameters for 28 days and at termination, anti-MuSK IgG, neuromuscular junction (NMJ) deposits, muscle AChR expression and lymph node B and T cell ratios were assessed by ELISA, immunofluorescence, immunoblotting and flow cytometry, respectively. RESULTS: FCRLB shRNA-treated mice showed no muscle weakness or weight loss at termination. Also, they exhibited higher grip strength and muscle AChR levels, lower anti-MuSK IgG and NMJ IgG/C3 levels than control mice. Flow cytometry analysis showed that ratios of major effector lymph node B and T cell populations were not altered by FCRLB silencing. However, regulatory T and CD19 + CD5+ B cell ratios were decreased in FCRLB shRNA-group. CONCLUSION: Our results provide evidence regarding involvement and therapeutic value of FCRLB in MuSK-MG. Silencing of FCRLB appears to substantially inhibit antibody production without interfering with survival of major lymphocyte populations.

Predicting cholangiocarcinoma in primary sclerosing cholangitis: using artificial intelligence, clinical and laboratory data.

BACKGROUND: Primary sclerosing cholangitis (PSC) patients have a risk of developing cholangiocarcinoma (CCA). Establishing predictive models for CCA in PSC is important. METHODS: In a large cohort of 1,459 PSC patients seen at Mayo Clinic (1993-2020), we quantified the impact of clinical/laboratory variables on CCA development using univariate and multivariate Cox models and predicted CCA using statistical and artificial intelligence (AI) approaches. We explored plasma bile acid (BA) levels' predictive power of CCA (subset of 300 patients, BA cohort). RESULTS: Eight significant risk factors (false discovery rate: 20%) were identified with univariate analysis; prolonged inflammatory bowel disease (IBD) was the most important one. IBD duration, PSC duration, and total bilirubin remained significant (p < 0.05) with multivariate analysis. Clinical/laboratory variables predicted CCA with cross-validated C-indexes of 0.68-0.71 at different time points of disease, significantly better compared to commonly used PSC risk scores. Lower chenodeoxycholic acid, higher conjugated fraction of lithocholic acid and hyodeoxycholic acid, and higher ratio of cholic acid to chenodeoxycholic acid were predictive of CCA. BAs predicted CCA with a cross-validated C-index of 0.66 (std: 0.11, BA cohort), similar to clinical/laboratory variables (C-index = 0.64, std: 0.11, BA cohort). Combining BAs with clinical/laboratory variables leads to the best average C-index of 0.67 (std: 0.13, BA cohort). CONCLUSIONS: In a large PSC cohort, we identified clinical and laboratory risk factors for CCA development and demonstrated the first AI based predictive models that performed significantly better than commonly used PSC risk scores. More predictive data modalities are needed for clinical adoption of these models.

The exposome and liver disease - how environmental factors affect liver health.

Since the initial development of the exposome concept, much effort has been devoted to the characterisation of the exposome through analytical, epidemiological, and toxicological/mechanistic studies. There is now an urgent need to link the exposome to human diseases and to include exposomics in the characterisation of environment-linked pathologies together with genomics and other omics. Liver diseases are particularly well suited for such studies since major functions of the liver include the detection, detoxification, and elimination of xenobiotics, as well as inflammatory responses. It is well known that several liver diseases are associated with i) addictive behaviours such as alcohol consumption, smoking, and to a certain extent dietary imbalance and obesity, ii) viral and parasitic infections, and iii) exposure to toxins and occupational chemicals. Recent studies indicate that environmental exposures are also significantly associated with liver diseases, and these include air pollution (particulate matter and volatile chemicals), contaminants such as polyaromatic hydrocarbons, bisphenol A and per-and poly-fluorinated substances, and physical stressors such as radiation. Furthermore, microbial metabolites and the "gut-liver" axis play a major role in liver diseases. Exposomics is poised to play a major role in the field of liver pathology. Methodological advances such as the exposomics-metabolomics framework, the determination of risk factors' genomic and epigenomic signatures, and cross-species biological pathway analysis should further delineate the impact of the exposome on the liver, opening the way for improved prevention, as well as the identification of new biomarkers of exposure and effects, and additional therapeutic targets.

Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.

Environmental chemicals and endogenous metabolites in bile of USA and Norway patients with primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a complex bile duct disorder. Its etiology is incompletely understood, but environmental chemicals likely contribute to risk. Patients with PSC have an altered bile metabolome, which may be influenced by environmental chemicals. This novel study utilized state-of-the-art high-resolution mass spectrometry (HRMS) with bile samples to provide the first characterization of environmental chemicals and metabolomics (collectively, the exposome) in PSC patients located in the United States of America (USA) (n = 24) and Norway (n = 30). First, environmental chemical- and metabolome-wide association studies were conducted to assess geographic-based similarities and differences in the bile of PSC patients. Nine environmental chemicals (false discovery rate, FDR < 0.20) and 3143 metabolic features (FDR < 0.05) differed by site. Next, pathway analysis was performed to identify metabolomic pathways that were similarly and differentially enriched by the site. Fifteen pathways were differentially enriched (P < .05) in the categories of amino acid, glycan, carbohydrate, energy, and vitamin/cofactor metabolism. Finally, chemicals and pathways were integrated to derive exposure-effect correlation networks by site. These networks demonstrate the shared and differential chemical-metabolome associations by site and highlight important pathways that are likely relevant to PSC. The USA patients demonstrated higher environmental chemical bile content and increased associations between chemicals and metabolic pathways than those in Norway. Polychlorinated biphenyl (PCB)-118 and PCB-101 were identified as chemicals of interest for additional investigation in PSC given broad associations with metabolomic pathways in both the USA and Norway patients. Associated pathways include glycan degradation pathways, which play a key role in microbiome regulation and thus may be implicated in PSC pathophysiology.

Incorporation of Genetic Studies in the Kidney Transplant Evaluation Clinic: The Value of a Multidisciplinary Approach.

BACKGROUND: Recent studies identified underlying genetic causes in a proportion of patients with various forms of kidney disease. In particular, genetic testing reclassified some focal segmental glomerulosclerosis (FSGS) cases into collagen type 4 (COL4)-related nephropathy. This knowledge has major implications for counseling prospective transplant recipients about recurrence risk and screening biologically related donors. We describe our experience incorporating genetic testing in our kidney transplant multidisciplinary practice. METHODS: Patients' DNA was analyzed using whole exome sequencing for a comprehensive kidney gene panel encompassing 344 genes associated with kidney diseases and candidate genes highly expressed in the kidney. Results were correlated with phenotype by a multidisciplinary committee of nephrologists, renal pathologists, geneticists, and genetic counselors. Between October 2018 and July 2020, 30 recipient and 5 donor candidates completed testing. RESULTS: Among recipient candidates, 24 (80%) carried the diagnosis of FSGS, 2 (6.7%) tubulointerstitial nephritis, and 1 (3.3%) nephrolithiasis, and 3 (10%) had an unknown cause of kidney disease. The yield for pathogenic/likely pathogenic variants was 43.3%, with majority being COL4 variants (53.8%). Among those with FSGS diagnosis, the yield was 10 of 24 (41.6%), with 29% reclassified into a COL4-related nephropathy. Family history of kidney disease was the only clinical characteristic difference between recipients with positive and negative results (76.9 versus 29.4%; P = 0.025). One of 5 donors tested positive for a pathogenic/likely pathogenic variant and was excluded from donation. CONCLUSIONS: We conclude that thoughtful use of genetic testing can be valuable for kidney donor selection and transplant recipient management.

Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease that can lead to cirrhosis and hepatic decompensation. However, predicting future outcomes in patients with PSC is challenging. Our aim was to extract magnetic resonance imaging (MRI) features that predict the development of hepatic decompensation by applying algebraic topology-based machine learning (ML). METHODS: We conducted a retrospective multicenter study among adults with large duct PSC who underwent MRI. A topological data analysis-inspired nonlinear framework was used to predict the risk of hepatic decompensation, which was motivated by algebraic topology theory-based ML. The topological representations (persistence images) were employed as input for classification to predict who developed early hepatic decompensation within one year after their baseline MRI. RESULTS: We reviewed 590 patients; 298 were excluded due to poor image quality or inadequate liver coverage, leaving 292 potentially eligible subjects, of which 169 subjects were included in the study. We trained our model using contrast-enhanced delayed phase T1-weighted images on a single center derivation cohort consisting of 54 patients (hepatic decompensation, n = 21; no hepatic decompensation, n = 33) and a multicenter independent validation cohort of 115 individuals (hepatic decompensation, n = 31; no hepatic decompensation, n = 84). When our model was applied in the independent validation cohort, it remained predictive of early hepatic decompensation (area under the receiver operating characteristic curve = 0.84). CONCLUSIONS: Algebraic topology-based ML is a methodological approach that can predict outcomes in patients with PSC and has the potential for application in other chronic liver diseases.

Combined monitoring of IgG and IgA anti-Spike and anti-Receptor binding domain long term responses following BNT162b2 mRNA vaccination in Greek healthcare workers.

Studies on the humoral response to homologous BNT162b2 mRNA-vaccination focus mainly on IgG antibody dynamics, while long-term IgA kinetics are understudied. Herein, kinetics of IgG and IgA levels against trimeric-Spike (S) and Receptor-Binding-Domain (RBD) were evaluated by in-house ELISAs in 146 two-dose vaccinated Greek healthcare workers (HCWs) in a 9-month period at six time points (up to 270 days after the first dose). The effect of a homologous booster third dose was also studied and evaluated. The peak of immune response was observed 21 days after the second dose; 100% seroconversion rate for anti-S and anti-RBD IgG, and 99.7% and 96.3% respectively for IgA. IgG antibody levels displayed higher increase compared to IgA. Declining but persistent anti-SARS-CoV-2 antibody levels were detected 9 months after vaccination; IgG and IgA anti-S levels approached those after the first dose, while a more rapid reduction rate for anti-RBD antibodies led to significantly lower levels for both classes, supporting the need for a booster dose. Indeed, a homologous booster third dose resulted in enhanced levels of anti-S of both classes, whereas anti-RBD didn't exceed the peak levels after the second dose. Previous SARS-CoV-2 infection, flu vaccination, BMI<35 and the occurrence of an adverse event upon vaccination, were associated with higher IgG antibody levels over time, which however were negatively affected by age increase and the presence of chronic diseases. Overall, after concurrently using the S and RBD target-antigens in in-house ELISAs, we report in addition to IgG, long-term persistence of IgA antibodies. Regarding antibody levels, homologous mRNA vaccination gives rise to an effective anti-viral protection up to 9 months negatively correlated to age. Considering that COVID-19 is still a matter of public concern, booster vaccine doses remain critical to vulnerable individuals.

Network science approach elucidates integrative genomic-metabolomic signature of antidepressant response and lifetime history of attempted suicide in adults with major depressive disorder.

Background: Individuals with major depressive disorder (MDD) and a lifetime history of attempted suicide demonstrate lower antidepressant response rates than those without a prior suicide attempt. Identifying biomarkers of antidepressant response and lifetime history of attempted suicide may help augment pharmacotherapy selection and improve the objectivity of suicide risk assessments. Towards this goal, this study sought to use network science approaches to establish a multi-omics (genomic and metabolomic) signature of antidepressant response and lifetime history of attempted suicide in adults with MDD. Methods: Single nucleotide variants (SNVs) which associated with suicide attempt(s) in the literature were identified and then integrated with a) p180-assayed metabolites collected prior to antidepressant pharmacotherapy and b) a binary measure of antidepressant response at 8 weeks of treatment using penalized regression-based networks in 245 'Pharmacogenomics Research Network Antidepressant Medication Study (PGRN-AMPS)' and 103 'Combining Medications to Enhance Depression Outcomes (CO-MED)' patients with major depressive disorder. This approach enabled characterization and comparison of biological profiles and associated antidepressant treatment outcomes of those with (N = 46) and without (N = 302) a self-reported lifetime history of suicide attempt. Results: 351 SNVs were associated with suicide attempt(s) in the literature. Intronic SNVs in the circadian genes CLOCK and ARNTL (encoding the CLOCK:BMAL1 heterodimer) were amongst the top network analysis features to differentiate patients with and without a prior suicide attempt. CLOCK and ARNTL differed in their correlations with plasma phosphatidylcholines, kynurenine, amino acids, and carnitines between groups. CLOCK and ARNTL-associated phosphatidylcholines showed a positive correlation with antidepressant response in individuals without a prior suicide attempt which was not observed in the group with a prior suicide attempt. Conclusion: Results provide evidence for a disturbance between CLOCK:BMAL1 circadian processes and circulating phosphatidylcholines, kynurenine, amino acids, and carnitines in individuals with MDD who have attempted suicide. This disturbance may provide mechanistic insights for differential antidepressant pharmacotherapy outcomes between patients with MDD with versus without a lifetime history of attempted suicide. Future investigations of CLOCK:BMAL1 metabolic regulation in the context of suicide attempts may help move towards biologically-augmented pharmacotherapy selection and stratification of suicide risk for subgroups of patients with MDD and a lifetime history of attempted suicide.

ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants.

The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a 'landing pad' system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

A Recombinant Acetylcholine Receptor α1 Subunit Extracellular Domain Is a Promising New Drug Candidate for Treatment Of Myasthenia Gravis.

Background and Aims: Myasthenia gravis (MG) is a T-cell dependent antibody-mediated autoimmune disease in which the nicotinic acetylcholine receptor (AChR) is the major autoantigen, comprising several T and B cell auto-epitopes. We hypothesized that an efficacious drug candidate for antigen-specific therapy in MG should comprise a broad range of these auto-epitopes and be administered in a noninflammatory and tolerogenic context. Methods: We used a soluble mutated form of the extracellular domain of the α1 chain of the AChR (α1-ECDm), which represents the major portion of auto-epitopes involved in MG, and investigated, in a well-characterized rat model of experimental autoimmune myasthenia gravis (EAMG) whether its intravenous administration could safely and efficiently treat the autoimmune disease. Results: We demonstrated that intravenous administration of α1-ECDm abrogates established EAMG, in a dose and time dependent manner, as assessed by clinical symptoms, body weight, and compound muscle action potential (CMAP) decrement. Importantly, the effect was more pronounced compared to drugs representing current standard of care for MG. The protein had a short plasma half-life, most of what could be recovered was sequestered in the liver, kidneys and spleen. Further, we did not observe any signs of toxicity or intolerability in animals treated with α1-ECDm. Conclusion: We conclude that intravenous treatment with α1-ECDm is safe and effective in suppressing EAMG. α1-ECDm is in preclinical development as a promising new drug candidate for MG.