Penetrance and expressivity of mitochondrial variants in a large clinically unselected population.

Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.

Galectin-4 Antimicrobial Activity Primarily Occurs Through its C-Terminal Domain.

Although immune tolerance evolved to reduce reactivity with self, it creates a gap in the adaptive immune response against microbes that decorate themselves in self-like antigens. This is particularly apparent with carbohydrate-based blood group antigens, wherein microbes can envelope themselves in blood group structures similar to human cells. In this study, we demonstrate that the innate immune lectin, galectin-4 (Gal-4), exhibits strain-specific binding and killing behavior towards microbes that display blood group-like antigens. Examination of binding preferences using a combination of microarrays populated with ABO(H) glycans and a variety of microbial strains, including those that express blood group-like antigens, demonstrated that Gal-4 binds mammalian and microbial antigens that have features of blood group and mammalian-like structures. Although Gal-4 was thought to exist as a monomer that achieves functional bivalency through its two linked carbohydrate recognition domains, our data demonstrate that Gal-4 forms dimers and that differences in the intrinsic ability of each domain to dimerize likely influences binding affinity. While each Gal-4 domain exhibited blood group-binding activity, the C-terminal domain (Gal-4C) exhibited dimeric properties, while the N-terminal domain (Gal-4N) failed to similarly display dimeric activity. Gal-4C not only exhibited the ability to dimerize but also possessed higher affinity toward ABO(H) blood group antigens and microbes expressing glycans with blood group-like features. Furthermore, when compared to Gal-4N, Gal-4C exhibited more potent antimicrobial activity. Even in the context of the full-length protein, where Gal-4N is functionally bivalent by virtue of Gal-4C dimerization, Gal-4C continued to display higher antimicrobial activity. These results demonstrate that Gal-4 exists as a dimer and exhibits its antimicrobial activity primarily through its C-terminal domain. In doing so, these data provide important insight into key features of Gal-4 responsible for its innate immune activity against molecular mimicry.

Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

Prior immunization against an intracellular antigen enhances subsequent red blood cell alloimmunization in mice.

Antibodies against red blood cell (RBC) alloantigens can increase morbidity and mortality among transfusion recipients. However, alloimmunization rates can vary dramatically, as some patients never generate alloantibodies after transfusion, whereas others not only become alloimmunized but may also be prone to generating additional alloantibodies after subsequent transfusion. Previous studies suggested that CD4 T-cell responses that drive alloantibody formation recognize the same alloantigen engaged by B cells. However, because RBCs express numerous antigens, both internally and externally, it is possible that CD4 T-cell responses directed against intracellular antigens may facilitate subsequent alloimmunization against a surface RBC antigen. Here, we show that B cells can acquire intracellular antigens from RBCs. Using a mouse model of donor RBCs expressing 2 distinct alloantigens, we demonstrate that immune priming to an intracellular antigen, which would not be detected by any currently used RBC compatibility assays, can directly influence alloantibody formation after exposure to a subsequent distinct surface RBC alloantigen. These findings suggest a previously underappreciated mechanism whereby transfusion recipient responders may exhibit an increased rate of alloimmunization because of prior immune priming toward intracellular antigens.

Blood group A enhances SARS-CoV-2 infection.

Among the risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ABO(H) blood group antigens are among the most recognized predictors of infection. However, the mechanisms by which ABO(H) antigens influence susceptibility to COVID-19 remain incompletely understood. The receptor-binding domain (RBD) of SARS-CoV-2, which facilitates host cell engagement, bears significant similarity to galectins, an ancient family of carbohydrate-binding proteins. Because ABO(H) blood group antigens are carbohydrates, we compared the glycan-binding specificity of SARS-CoV-2 RBD with that of galectins. Similar to the binding profile of several galectins, the RBDs of SARS-CoV-2, including Delta and Omicron variants, exhibited specificity for blood group A. Not only did each RBD recognize blood group A in a glycan array format, but each SARS-CoV-2 virus also displayed a preferential ability to infect blood group A-expressing cells. Preincubation of blood group A cells with a blood group-binding galectin specifically inhibited the blood group A enhancement of SARS-CoV-2 infection, whereas similar incubation with a galectin that does not recognize blood group antigens failed to impact SARS-CoV-2 infection. These results demonstrated that SARS-CoV-2 can engage blood group A, providing a direct link between ABO(H) blood group expression and SARS-CoV-2 infection.

Antibody-mediated antigen loss switches augmented immunity to antibody-mediated immunosuppression.

Antibodies against fetal red blood cell (RBC) antigens can cause hemolytic disease of the fetus and newborn (HDFN). Reductions in HDFN due to anti-RhD antibodies have been achieved through use of Rh immune globulin (RhIg), a polyclonal antibody preparation that causes antibody-mediated immunosuppression (AMIS), thereby preventing maternal immune responses against fetal RBCs. Despite the success of RhIg, it is only effective against 1 alloantigen. The lack of similar interventions that mitigate immune responses toward other RBC alloantigens reflects an incomplete understanding of AMIS mechanisms. AMIS has been previously attributed to rapid antibody-mediated RBC removal, resulting in B-cell ignorance of the RBC alloantigen. However, our data demonstrate that antibody-mediated RBC removal can enhance de novo alloimmunization. In contrast, inclusion of antibodies that possess the ability to rapidly remove the target antigen in the absence of detectable RBC clearance can convert an augmented antibody response to AMIS. These results suggest that the ability of antibodies to remove target antigens from the RBC surface can trigger AMIS in situations in which enhanced immunity may otherwise occur. In doing so, these results hold promise in identifying key antibody characteristics that can drive AMIS, thereby facilitating the design of AMIS approaches toward other RBC antigens to eliminate all forms of HDFN.

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.

BACKGROUND: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

Recurrent 17q12 microduplications contribute to renal disease but not diabetes.

BACKGROUND: 17q12 microdeletion and microduplication syndromes present as overlapping, multisystem disorders. We assessed the disease phenotypes of individuals with 17q12 CNV in a population-based cohort. METHODS: We investigated 17q12 CNV using microarray data from 450 993 individuals in the UK Biobank and calculated disease status associations for diabetes, liver and renal function, neurological and psychiatric traits. RESULTS: We identified 11 17q12 microdeletions and 106 microduplications. Microdeletions were strongly associated with diabetes (p=2×10-7) but microduplications were not. Estimated glomerular filtration rate (eGFR mL/min/1.73 m2) was consistently lower in individuals with microdeletions (p=3×10-12) and microduplications (p=6×10-25). Similarly, eGFR <60, including end-stage renal disease, was associated with microdeletions (p=2×10-9, p<0.003) and microduplications (p=1×10-9, p=0.009), respectively, highlighting sometimes substantially reduced renal function in each. Microduplications were associated with decreased fluid intelligence (p=3×10-4). SNP association analysis in the 17q12 region implicated changes to HNF1B as causing decreased eGFR (NC_000017.11:g.37741642T>G, rs12601991, p=4×10-21) and diabetes (NC_000017.11:g.37741165C>T, rs7501939, p=6×10-17). A second locus within the region was also associated with fluid intelligence (NC_000017.11:g.36593168T>C, rs1005552, p=6×10-9) and decreased eGFR (NC_000017.11:g.36558947T>C, rs12150665, p=4×10-15). CONCLUSION: We demonstrate 17q12 microdeletions but not microduplications are associated with diabetes in a population-based cohort, likely caused by HNF1B haploinsufficiency. We show that both 17q12 microdeletions and microduplications are associated with renal disease, and multiple genes within the region likely contribute to renal and neurocognitive phenotypes.

The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes.

AIMS/HYPOTHESIS: The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults. METHODS: We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants. RESULTS: The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4). CONCLUSIONS/INTERPRETATION: The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.

FOXP3 TSDR Measurement Could Assist Variant Classification and Diagnosis of IPEX Syndrome.

Pathogenic FOXP3 variants cause immune dysregulation polyendocrinopathy enteropathy X-linked (IPEX) syndrome, a progressive autoimmune disease resulting from disruption of the regulatory T cell (Treg) compartment. Assigning pathogenicity to novel variants in FOXP3 is challenging due to the heterogeneous phenotype and variable immunological abnormalities. The number of cells with demethylation at the Treg cell-specific demethylated region (TSDR) is an independent biomarker of IPEX. We aimed to investigate if diagnosing IPEX at presentation with isolated diabetes could allow for effective monitoring of disease progression and assess whether TSDR analysis can aid FOXP3 variant classification and predict disease course. We describe a large genetically diagnosed IPEX cohort (n = 65) and 13 individuals with other monogenic autoimmunity subtypes in whom we quantified the proportion of cells with FOXP3 TSDR demethylation, normalized to the number with CD4 demethylation (%TSDR/CD4) and compare them to 29 unaffected controls. IPEX patients presenting with isolated diabetes (50/65, 77%) often later developed enteropathy (20/50, 40%) with a median interval of 23.5 weeks. %TSDR/CD4 was a good discriminator of IPEX vs. unaffected controls (ROC-AUC 0.81, median 13.6% vs. 8.5%, p < 0.0001) with higher levels of demethylation associated with more severe disease. Patients with other monogenic autoimmunity had a similar %TSDR/CD4 to controls (median 8.7%, p = 1.0). Identifying increased %TSDR/CD4 in patients with novel FOXP3 mutations presenting with isolated diabetes facilitates diagnosis and could offer an opportunity to monitor patients and begin immune modulatory treatment before onset of severe enteropathy.

SavvyCNV: Genome-wide CNV calling from off-target reads.

Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this 'free data' to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.

Congenital beta cell defects are not associated with markers of islet autoimmunity, even in the context of high genetic risk for type 1 diabetes.

AIMS/HYPOTHESIS: A key unanswered question in type 1 diabetes is whether beta cells initiate their own destruction or are victims of an aberrant immune response (beta cell suicide or homicide?). To investigate this, we assessed islet autoantibodies in individuals with congenital beta cell defects causing neonatal diabetes mellitus (NDM). METHODS: We measured autoantibodies to GAD (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A) in 242 individuals with NDM (median age diagnosed 1.8 months [IQR 0.39-2.9 months]; median age collected 4.6 months [IQR 1.8-27.6 months]; median diabetes duration 2 months [IQR 0.6-23 months]), including 75 whose NDM resulted from severe beta cell endoplasmic reticulum (ER) stress. As a control cohort we also tested samples from 69 diabetes-free individuals (median age collected 9.9 months [IQR 9.0-48.6 months]) for autoantibodies. RESULTS: We found low prevalence of islet autoantibodies in individuals with monogenic NDM; 13/242 (5.4% [95% CI 2.9, 9.0%]) had detectable GADA, IA-2A and/or ZnT8A. This was similar to the proportion in the control participants who did not have diabetes (1/69 positive [1.4%, 95% CI 0.03, 7.8%], p=0.3). Importantly, monogenic individuals with beta cell ER stress had a similar rate of GADA/IA-2A/ZnT8A positivity to non-ER stress aetiologies (2.7% [95% CI 0.3, 9.3%] vs 6.6% [95% CI 3.3, 11.5%] p=0.4). We observed no association between islet autoimmunity and genetic risk, age at testing (including 30 individuals >10 years at testing) or diabetes duration (p>0.4 for all). CONCLUSIONS/INTERPRETATION: Our data support the hypothesis that beta cell stress/dysfunction alone does not lead to the production of islet autoantibodies, even in the context of high-risk HLA types. This suggests that additional factors are required to trigger an autoimmune response towards beta cells.

Systematic genetic testing for recessively inherited monogenic diabetes: a cross-sectional study in paediatric diabetes clinics.

AIMS/HYPOTHESIS: Current clinical guidelines for childhood-onset monogenic diabetes outside infancy are mainly focused on identifying and testing for dominantly inherited, predominantly MODY genes. There are no systematic studies of the recessively inherited causes of monogenic diabetes that are likely to be more common in populations with high rates of consanguinity. We aimed to determine the contribution of recessive causes of monogenic diabetes in paediatric diabetes clinics and to identify clinical criteria by which to select individuals for recessive monogenic diabetes testing. METHODS: We conducted a cross-sectional study of 1093 children from seven paediatric diabetes clinics across Turkey (a population with high rates of consanguinity). We undertook genetic testing of 50 known dominant and recessive causes of monogenic diabetes for 236 children at low risk of type 1 diabetes. As a comparison, we used monogenic diabetes cases from UK paediatric diabetes clinics (a population with low rates of consanguinity). RESULTS: Thirty-four children in the Turkish cohort had monogenic diabetes, equating to a minimal prevalence of 3.1%, similar to that in the UK cohort (p = 0.40). Forty-one per cent (14/34) had autosomal recessive causes in contrast to 1.6% (2/122) in the UK monogenic diabetes cohort (p < 0.0001). All conventional criteria for identifying monogenic diabetes (parental diabetes, not requiring insulin treatment, HbA1c ≤ 58 mmol/mol [≤7.5%] and a composite clinical probability of MODY >10%) assisted the identification of the dominant (all p ≤ 0.0003) but not recessive cases (all p ≥ 0.2) in Turkey. The presence of certain non-autoimmune extra-pancreatic features greatly assisted the identification of recessive (p < 0.0001, OR 66.9) but not dominant cases. CONCLUSIONS/INTERPRETATION: Recessively inherited mutations are a common cause of monogenic diabetes in populations with high rates of consanguinity. Present MODY-focused genetic testing strategies do not identify affected individuals. To detect all cases of monogenic paediatric diabetes, it is crucial that recessive genes are included in genetic panels and that children are selected for testing if they have certain non-autoimmune extra-pancreatic features in addition to current criteria.

Fc γ receptor IIIa/CD16a processing correlates with the expression of glycan-related genes in human natural killer cells.

Many therapeutic monoclonal antibodies require binding to Fc γ receptors (FcγRs) for full effect and increasing the binding affinity increases efficacy. Preeminent among the five activating human FcγRs is FcγRIIIa/CD16a expressed by natural killer (NK) cells. CD16a is heavily processed, and recent reports indicate that the composition of the five CD16a asparagine(N)-linked carbohydrates (glycans) impacts affinity. These observations indicate that specific manipulation of CD16a N-glycan composition in CD16a-expressing effector cells including NK cells may improve treatment efficacy. However, it is unclear if modifying the expression of select genes that encode processing enzymes in CD16a-expressing effector cells is sufficient to affect N-glycan composition. We identified substantial processing differences using a glycoproteomics approach by comparing CD16a isolated from two NK cell lines, NK92 and YTS, with CD16a expressed by HEK293F cells and previous reports of CD16a from primary NK cells. Gene expression profiling by RNA-Seq and qRT-PCR revealed expression levels for glycan-modifying genes that correlated with CD16a glycan composition. These results identified a high degree of variability between the processing of the same human protein by different human cell types. N-glycan processing correlated with the expression of glycan-modifying genes and thus explained the substantial differences in CD16a processing by NK cells of different origins.

Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting.

More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as "clinically relevant" variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM_175914.4) variant associated with diabetes is <10% penetrant by the time an individual is 40 years old. We also observed associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g., heterozygous carriers of the ERCC4 c.2395C>T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants.

How do I diagnose Maturity Onset Diabetes of the Young in my patients?

Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes diagnosed in young individuals that lack the typical features of type 1 and type 2 diabetes. The genetic subtype of MODY determines the most effective treatment and this is the driver for MODY genetic testing in diabetes populations. Despite the obvious clinical and health economic benefits, MODY is significantly underdiagnosed with the majority of patients being inappropriately managed as having type 1 or type 2 diabetes. Low detection rates result from the difficulty in identifying patients with a likely diagnosis of MODY from the high background population of young onset type 1 and type 2 diabetes, compounded by the lack of MODY awareness and education in diabetes care physicians. MODY diagnosis can be improved through (1) access to education and training, (2) the use of sensitive and specific selection criteria based on accurate prediction models and biomarkers to identify patients for testing, (3) the development and mainstream implementation of simple criteria-based selection pathways applicable across a range of healthcare settings and ethnicities to select the most appropriate patients for genetic testing and (4) the correct use of next generation sequencing technology to provide accurate and comprehensive testing of all known MODY and monogenic diabetes genes. The creation and public sharing of educational materials, clinical and scientific best practice guidelines and genetic variants will help identify the missing patients so they can benefit from the more effective clinical care that a genetic diagnosis brings.

Site-specific N-glycan Analysis of Antibody-binding Fc γ Receptors from Primary Human Monocytes.

FcγRIIIa (CD16a) and FcγRIIa (CD32a) on monocytes are essential for proper effector functions including antibody dependent cellular cytotoxicity (ADCC) and phagocytosis (ADCP). Indeed, therapeutic monoclonal antibodies (mAbs) that bind FcγRs with greater affinity exhibit greater efficacy. Furthermore, post-translational modification impacts antibody binding affinity, most notably the composition of the asparagine(N)-linked glycan at N162 of CD16a. CD16a is widely recognized as the key receptor for the monocyte response, however the post-translational modifications of CD16a from endogenous monocytes are not described. Here we isolated monocytes from individual donors and characterized the composition of CD16a and CD32a N-glycans from all modified sites. The composition of CD16a N-glycans varied by glycosylation site and donor. CD16a displayed primarily complex-type biantennary N-glycans at N162, however some individuals expressed CD16a V158 with ∼20% hybrid and oligomannose types which increased affinity for IgG1 Fc according to surface plasmon resonance binding analyses. The CD16a N45-glycans contain markedly less processing than other sites with >75% hybrid and oligomannose forms. N38 and N74 of CD16a both contain highly processed complex-type N-glycans with N-acetyllactosamine repeats and complex-type biantennary N-glycans dominate at N169. The composition of CD16a N-glycans isolated from monocytes included a higher proportion of oligomannose-type N-glycans at N45 and less sialylation plus greater branch fucosylation than we observed in a recent analysis of NK cell CD16a. The additional analysis of CD32a from monocytes revealed different features than observed for CD16a including the presence of a predominantly biantennary complex-type N-glycans with two sialic acids at both sites (N64 and N145).

DR15-DQ6 remains dominantly protective against type 1 diabetes throughout the first five decades of life.

AIMS/HYPOTHESIS: Among white European children developing type 1 diabetes, the otherwise common HLA haplotype DR15-DQ6 is rare, and highly protective. Adult-onset type 1 diabetes is now known to represent more overall cases than childhood onset, but it is not known whether DR15-DQ6 is protective in older-adult-onset type 1 diabetes. We sought to quantify DR15-DQ6 protection against type 1 diabetes as age of onset increased. METHODS: In two independent cohorts we assessed the proportion of type 1 diabetes cases presenting through the first 50 years of life with DR15-DQ6, compared with population controls. In the After Diabetes Diagnosis Research Support System-2 (ADDRESS-2) cohort (n = 1458) clinician-diagnosed type 1 diabetes was confirmed by positivity for one or more islet-specific autoantibodies. In UK Biobank (n = 2502), we estimated type 1 diabetes incidence rates relative to baseline HLA risk for each HLA group using Poisson regression. Analyses were restricted to white Europeans and were performed in three groups according to age at type 1 diabetes onset: 0-18 years, 19-30 years and 31-50 years. RESULTS: DR15-DQ6 was protective against type 1 diabetes through to age 50 years (OR < 1 for each age group, all p < 0.001). The following ORs for type 1 diabetes, relative to a neutral HLA genotype, were observed in ADDRESS-2: age 5-18 years OR 0.16 (95% CI 0.08, 0.31); age 19-30 years OR 0.10 (0.04, 0.23); and age 31-50 years OR 0.37 (0.21, 0.68). DR15-DQ6 also remained highly protective at all ages in UK Biobank. Without DR15-DQ6, the presence of major type 1 diabetes high-risk haplotype (either DR3-DQ2 or DR4-DQ8) was associated with increased risk of type 1 diabetes. CONCLUSIONS/INTERPRETATION: HLA DR15-DQ6 confers dominant protection from type 1 diabetes across the first five decades of life.

Comparison of Antibody Class-Specific SARS-CoV-2 Serologies for the Diagnosis of Acute COVID-19.

Accurate diagnosis of acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is critical for appropriate management of patients with this disease. We examined the possible complementary role of laboratory-developed class-specific clinical serology in assessing SARS-CoV-2 infection in hospitalized patients. Serological tests for immunoglobulin G (IgG), IgA, and IgM antibodies against the receptor binding domain (RBD) of SARS-CoV-2 were evaluated using samples from real-time reverse transcription-quantitative PCR (qRT-PCR)-confirmed inpatient coronavirus disease 2019 (COVID-19) cases. We analyzed the influence of timing and clinical severity on the diagnostic value of class-specific COVID-19 serology testing. Cross-sectional analysis revealed higher sensitivity and specificity at lower optical density cutoffs for IgA in hospitalized patients than for IgG and IgM serology (IgG area under the curve [AUC] of 0.91 [95% confidence interval {CI}, 0.89 to 0.93] versus IgA AUC of 0.97 [95% CI, 0.96 to 0.98] versus IgM AUC of 0.95 [95% CI, 0.92 to 0.97]). The enhanced performance of IgA serology was apparent in the first 2 weeks after symptom onset and the first week after PCR testing. In patients requiring intubation, all three tests exhibit enhanced sensitivity. Among PCR-negative patients under investigation for SARS-CoV-2 infection, 2 out of 61 showed clear evidence of seroconversion IgG, IgA, and IgM. Suspected false-positive results in the latter population were most frequently observed in IgG and IgM serology tests. Our findings suggest the potential utility of IgA serology in the acute setting and explore the benefits and limitations of class-specific serology as a complementary diagnostic tool to PCR for COVID-19 in the acute setting.