Genomic epidemiology of Streptococcus dysgalactiae subsp. equisimilis strains causing invasive disease in Norway during 2018

Background: Streptococcus dysgalactiae subspecies equisimilis (SDSE) is an emerging global pathogen, yet the epidemiology and population genetics of SDSE species have not been extensively characterized. Methods: We carried out whole genome sequencing to characterize 274 SDSE isolates causing bloodstream infections obtained through national surveillance program in 2018. We conducted multilocus sequence typing (MLST), emm-typing, core genome phylogeny, as well as investigated key features associated with virulence. Moreover, comparison to SDSE from other geographic regions were performed in order to gain more insight in the evolutionary dynamics in SDSE. Results: The phylogenetic analysis indicated a substantial diversity of emm-types and sequence types (STs). Briefly, 17 emm-types and 58 STs were identified that formed 10 clonal complexes (CCs). The predominant ST-types were ST20 (20%), ST17 (17%), and ST29 (11%). While CC17 and CC29 clades showed a substantial heterogeneity with well-separated emm-associated subclades, the CC20 clade harboring the stG62647 emm-type was more homogenous and the most prevalent in the present study. Moreover, we observed notable differences in the distribution of clades within Norway, as well as several disseminated CCs and also distinct geographic variations when compared to data from other countries. We also revealed extensive intra-species recombination events involving surface exposed virulence factors, including the emm gene important for phylogenetic profiling. Conclusion: Recombination events involving the emm as well as other virulence genes in SDSE, are important mechanisms in shaping the genetic variability in the SDSE population, potentially offering selective advantages to certain lineages. The enhanced phylogenetic resolution offered by whole genome sequencing is necessary to identify and delimitate outbreaks, monitor and properly characterize emerging strains, as well as elucidate bacterial population dynamics.publishedVersio

Characterisation of HNF1A variants in paediatric diabetes in Norway using functional and clinical investigations to unmask phenotype and monogenic diabetes

Aims/hypothesis Correctly diagnosing MODY is important, as individuals with this diagnosis can discontinue insulin injections; however, many people are misdiagnosed. We aimed to develop a robust approach for determining the pathogenicity of variants of uncertain significance in hepatocyte nuclear factor-1 alpha (HNF1A)-MODY and to obtain an accurate estimate of the prevalence of HNF1A-MODY in paediatric cases of diabetes. Methods We extended our previous screening of the Norwegian Childhood Diabetes Registry by 830 additional samples and comprehensively genotyped HNF1A variants in autoantibody-negative participants using next-generation sequencing. Carriers of pathogenic variants were treated by local healthcare providers, and participants with novel likely pathogenic variants and variants of uncertain significance were enrolled in an investigator-initiated, non-randomised, open-label pilot study (ClinicalTrials.gov registration no. NCT04239586). To identify variants associated with HNF1A-MODY, we functionally characterised their pathogenicity and assessed the carriers’ phenotype and treatment response to sulfonylurea. Results In total, 615 autoantibody-negative participants among 4712 cases of paediatric diabetes underwent genetic sequencing, revealing 19 with HNF1A variants. We identified nine carriers with novel variants classified as variants of uncertain significance or likely to be pathogenic, while the remaining ten participants carried five pathogenic variants previously reported. Of the nine carriers with novel variants, six responded favourably to sulfonylurea. Functional investigations revealed their variants to be dysfunctional and demonstrated a correlation with the resulting phenotype, providing evidence for reclassifying these variants as pathogenic. Conclusions/interpretation Based on this robust classification, we estimate that the prevalence of HNF1A-MODY is 0.3% in paediatric diabetes. Clinical phenotyping is challenging and functional investigations provide a strong complementary line of evidence. We demonstrate here that combining clinical phenotyping with functional protein studies provides a powerful tool to obtain a precise diagnosis of HNF1A-MODY.publishedVersio

A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland

Background: The genetic disease architecture of Inuit includes a large number of common high-impact variants. Identification of such variants contributes to our understanding of the genetic aetiology of diseases and improves global equity in genomic personalised medicine. We aimed to identify and characterise novel variants in genes associated with Maturity Onset Diabetes of the Young (MODY) in the Greenlandic population. Methods: Using combined data from Greenlandic population cohorts of 4497 individuals, including 448 whole genome sequenced individuals, we screened 14 known MODY genes for previously identified and novel variants. We functionally characterised an identified novel variant and assessed its association with diabetes prevalence and cardiometabolic traits and population impact. Findings: We identified a novel variant in the known MODY gene HNF1A with an allele frequency of 1.9% in the Greenlandic Inuit and absent elsewhere. Functional assays indicate that it prevents normal splicing of the gene. The variant caused lower 30-min insulin (β = −232 pmol/L, βSD = −0.695, P = 4.43 × 10−4) and higher 30-min glucose (β = 1.20 mmol/L, βSD = 0.441, P = 0.0271) during an oral glucose tolerance test. Furthermore, the variant was associated with type 2 diabetes (OR 4.35, P = 7.24 × 10−6) and HbA1c (β = 0.113 HbA1c%, βSD = 0.205, P = 7.84 × 10−3). The variant explained 2.5% of diabetes variance in Greenland. Interpretation: The reported variant has the largest population impact of any previously reported variant within a MODY gene. Together with the recessive TBC1D4 variant, we show that close to 1 in 5 cases of diabetes (18%) in Greenland are associated with high-impact genetic variants compared to 1–3% in large populations.publishedVersio

The E3 SUMO ligase PIASy is a novel interaction partner regulating the activity of diabetes associated hepatocyte nuclear factor-1a

The transcription factor hepatocyte nuclear factor-1α (HNF-1A) is involved in normal pancreas development and function. Rare variants in the HNF1A gene can cause monogenic diabetes, while common variants confer type 2 diabetes risk. The precise mechanisms for regulation of HNF-1A, including the role and function of post-translational modifications, are still largely unknown. Here, we present the first evidence for HNF-1A being a substrate of SUMOylation in cellulo and identify two lysine (K) residues (K205 and K273) as SUMOylation sites. Overexpression of protein inhibitor of activated STAT (PIASγ) represses the transcriptional activity of HNF-1A and is dependent on simultaneous HNF-1A SUMOylation at K205 and K273. Moreover, PIASγ is a novel HNF-1A interaction partner whose expression leads to translocation of HNF-1A to the nuclear periphery. Thus, our findings support that the E3 SUMO ligase PIASγ regulates HNF-1A SUMOylation with functional implications, representing new targets for drug development and precision medicine in diabetes

The E3 SUMO ligase PIASγ is a novel interaction partner regulating the activity of diabetes associated hepatocyte nuclear factor-1α

The transcription factor hepatocyte nuclear factor-1α (HNF-1A) is involved in normal pancreas development and function. Rare variants in the HNF1A gene can cause monogenic diabetes, while common variants confer type 2 diabetes risk. The precise mechanisms for regulation of HNF-1A, including the role and function of post-translational modifications, are still largely unknown. Here, we present the first evidence for HNF-1A being a substrate of SUMOylation in cellulo and identify two lysine (K) residues (K205 and K273) as SUMOylation sites. Overexpression of protein inhibitor of activated STAT (PIASγ) represses the transcriptional activity of HNF-1A and is dependent on simultaneous HNF-1A SUMOylation at K205 and K273. Moreover, PIASγ is a novel HNF-1A interaction partner whose expression leads to translocation of HNF-1A to the nuclear periphery. Thus, our findings support that the E3 SUMO ligase PIASγ regulates HNF-1A SUMOylation with functional implications, representing new targets for drug development and precision medicine in diabetes

The E3 SUMO ligase PIASy is a novel interaction partner regulating the activity of diabetes associated hepatocyte nuclear factor-1a

The transcription factor hepatocyte nuclear factor-1α (HNF-1A) is involved in normal pancreas development and function. Rare variants in the HNF1A gene can cause monogenic diabetes, while common variants confer type 2 diabetes risk. The precise mechanisms for regulation of HNF-1A, including the role and function of post-translational modifications, are still largely unknown. Here, we present the first evidence for HNF-1A being a substrate of SUMOylation in cellulo and identify two lysine (K) residues (K205 and K273) as SUMOylation sites. Overexpression of protein inhibitor of activated STAT (PIASγ) represses the transcriptional activity of HNF-1A and is dependent on simultaneous HNF-1A SUMOylation at K205 and K273. Moreover, PIASγ is a novel HNF-1A interaction partner whose expression leads to translocation of HNF-1A to the nuclear periphery. Thus, our findings support that the E3 SUMO ligase PIASγ regulates HNF-1A SUMOylation with functional implications, representing new targets for drug development and precision medicine in diabetes

Functional Analyses of HNF1A-MODY Variants Refine the Interpretation of Identified Sequence Variants

Context While rare variants of the hepatocyte nuclear factor-1 alpha (HNF1A) gene can cause maturity-onset diabetes of the young (HNF1A-MODY), other variants can be risk factors for the development of type 2 diabetes. As has been suggested by the American College of Medical Genetics (ACMG) guidelines for variant interpretation, functional studies provide strong evidence to classify a variant as pathogenic. Objective We hypothesized that a functional evaluation can improve the interpretation of the HNF1A variants in our Czech MODY Registry. Design, Settings, and Participants We studied 17 HNF1A variants that were identified in 48 individuals (33 female/15 male) from 20 Czech families with diabetes, using bioinformatics in silico tools and functional protein analyses (transactivation, protein expression, DNA binding, and nuclear localization). Results Of the 17 variants, 12 variants (p.Lys120Glu, p.Gln130Glu, p.Arg131Pro, p.Leu139Pro, p.Met154Ile, p.Gln170Ter, p.Glu187SerfsTer40, p.Phe215SerfsTer18, p.Gly253Arg, p.Leu383ArgfsTer3, p.Gly437Val, and p.Thr563HisfsTer85) exhibited significantly reduced transcriptional activity or DNA binding (< 40%) and were classified as (likely) pathogenic, 2/17 variants were (likely) benign and 3/17 remained of uncertain significance. Functional analyses allowed for the reclassification of 10/17 variants (59%). Diabetes treatment was improved in 20/29 (69%) carriers of (likely) pathogenic HNF1A variants. Conclusion Functional evaluation of the HNF1A variants is necessary to better predict the pathogenic effects and to improve the diagnostic interpretation and treatment, particularly in cases where the cosegregation or family history data are not available or where the phenotype is more diverse and overlaps with other types of diabetes

Unsupervised clustering of missense variants in HNF1A using multidimensional functional data aids clinical interpretation

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens

Unsupervised clustering of missense variants in HNF1A using multidimensional functional data aids clinical interpretation

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

BackgroundWe previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in similar to 80% of cases.MethodsWe report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded.ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P=1.1x10(-4)) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70[95%CI 1.3-8.2], P=2.1x10(-4)). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR=19.65[95%CI 2.1-2635.4], P=3.4x10(-3)), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR=4.40[9%CI 2.3-8.4], P=7.7x10(-8)). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10(-5)).ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old