Abstract:Schizophrenia is a complex mental disorder with unknown aetiology. Both candidate gene and genome-wide association (GWA) studies suggest that the human leukocyte antigen (HLA) system may play a part in development of the illness, but the causal HLA variant(s) remain(s) unclear. Previous studies showed that the DRB1*0101 and DRB1*13 alleles might be associated with a high risk of schizophrenia. Therefore, the present study was undertaken to test their association with the disease by genotyping seven DRB1-taggin… Show more
“…It is noteworthy that similar variation in repertoire size was recently noted in the case of the class I molecules expressed by the rhesus macaque ( Macaca mulatta (55)). Therefore, it is reasonable to speculate that similar allele-related variation in repertoire size will be broadly observed.…”
Prediction of HLA binding affinity is widely utilized to identify candidate T cell epitopes, and an affinity of 500 nM is routinely used as a threshold for peptide selection. However, the fraction (%) of peptides predicted to bind with affinities of 500 nM varies by allele. For example, of a large collection of about 30,000 dengue virus derived peptides only 0.3% were predicted to bind HLA A*0101, while nearly 5% were predicted for A*0201. This striking difference could not be ascribed to variation in accuracy of the algorithms utilized, as predicted values closely correlated with affinity measured in vitro with purified HLA molecules. These data raised the question whether different alleles would also vary in terms of epitope repertoire size, defined as the number of associated epitopes or, alternatively, whether alleles vary drastically in terms of the affinity threshold associated with immunogenicity. To address this issue, strains of HLA transgenic mice with wide (A*0201), intermediate (B*0702) or narrow (A*0101) repertoires were immunized with peptides of varying binding affinity and relative percentile ranking. The results show that absolute binding capacity is a better predictor of immunogenicity, and analysis of epitopes from the Immune Epitope Database (IEDB) revealed that predictive efficacy is increased using allele-specific affinity thresholds. Finally, we investigate the genetic and structural basis of the phenomenon. While no stringent correlate was defined, on average HLA B alleles are associated with significantly narrower repertoires than HLA A alleles.
“…It is noteworthy that similar variation in repertoire size was recently noted in the case of the class I molecules expressed by the rhesus macaque ( Macaca mulatta (55)). Therefore, it is reasonable to speculate that similar allele-related variation in repertoire size will be broadly observed.…”
Prediction of HLA binding affinity is widely utilized to identify candidate T cell epitopes, and an affinity of 500 nM is routinely used as a threshold for peptide selection. However, the fraction (%) of peptides predicted to bind with affinities of 500 nM varies by allele. For example, of a large collection of about 30,000 dengue virus derived peptides only 0.3% were predicted to bind HLA A*0101, while nearly 5% were predicted for A*0201. This striking difference could not be ascribed to variation in accuracy of the algorithms utilized, as predicted values closely correlated with affinity measured in vitro with purified HLA molecules. These data raised the question whether different alleles would also vary in terms of epitope repertoire size, defined as the number of associated epitopes or, alternatively, whether alleles vary drastically in terms of the affinity threshold associated with immunogenicity. To address this issue, strains of HLA transgenic mice with wide (A*0201), intermediate (B*0702) or narrow (A*0101) repertoires were immunized with peptides of varying binding affinity and relative percentile ranking. The results show that absolute binding capacity is a better predictor of immunogenicity, and analysis of epitopes from the Immune Epitope Database (IEDB) revealed that predictive efficacy is increased using allele-specific affinity thresholds. Finally, we investigate the genetic and structural basis of the phenomenon. While no stringent correlate was defined, on average HLA B alleles are associated with significantly narrower repertoires than HLA A alleles.
“…The extensive polymorphism of HLA class II molecules in the general population does represent a formidable obstacle to epitope identification approaches. However, it has been recognized that the majority of molecules expressed in the general population can be reconciled to a manageable number by focusing on those most frequently expressed (McKinney et al, 2013). At the same time, extensive similarities exist within the peptides bound by different allelic variants, and even across different loci (Greenbaum et al, 2011).…”
Computational prediction of HLA class II restricted T cell epitopes has great significance in many immunological studies including vaccine discovery. In recent years, prediction of HLA class II binding has improved significantly but a strategy to globally predict the most dominant epitopes has not been rigorously defined. Using human immunogenicity data associated with sets of 15-mer peptides overlapping by 10 residues spanning over 30 different allergens and bacterial antigens, and HLA class II binding prediction tools from the Immune Epitope Database and Analysis Resource (IEDB), we optimized a strategy to predict the top epitopes recognized by human populations. The most effective strategy was to select peptides based on predicted median binding percentiles for a set of seven DRB1 and DRB3/4/5 alleles. These results were validated with predictions on a blind set of 15 new allergens and bacterial antigens. We found that the top 21% predicted peptides (based on the predicted binding to seven DRB1 and DRB3/4/5 alleles) were required to capture 50% of the immune response. This corresponded to an IEDB consensus percentile rank of 20.0, which could be used as a universal prediction threshold. Utilizing actual binding data (as opposed to predicted binding data) did not appreciably change the efficacy of global predictions, suggesting that the imperfect predictive capacity is not due to poor algorithm performance, but intrinsic limitations of HLA class II epitope prediction schema based on HLA binding in genetically diverse human populations.
“…Schizophrenia (SCZ) is a chronic, severe psychotic mental disorder characterized by both positive (e.g., delusions, hallucinations, and thought disorders) and negative symptoms (e.g., social withdrawal, apathy, and cognitive impairment) [ 1 ]. As a serious neurological disability, SCZ affects approximately 1% of the general population worldwide and is regarded as a major public health problem, ranking ninth in terms of global disease burden [ 2 ]. Based on evidence from family-based, twin and adoption studies, which have implicated numerous genes in the etiology of SCZ, the disorder is currently understood as a polygenic neurodevelopment disorder caused by the interplay between environmental factors and genetics [ 3 ].…”
NOTCH4 regulates signaling pathways associated with neuronal maturation, a process involved in the development and patterning of the central nervous system. The NOTCH4 gene has also been identified as a possible susceptibility gene for schizophrenia (SCZ). The objective of this study was to examine the relationship between NOTCH4 polymorphisms and SCZ in the Chinese Han population. The rs2071287 and rs204993 polymorphisms of the NOTCH4 gene were analyzed in 443 patients with SCZ and 628 controls of Han Chinese descent. Single SNP allele-, genotype-, and gender-specific associations were analyzed using different models (i.e., additive, dominant, and recessive models). This association study revealed that the rs204993 polymorphism is significantly associated with susceptibility for SCZ and that the AA genotype of rs204993 is associated with a higher risk for SCZ (P = 0.027; OR = 1.460; 95% CI, 1.043–2.054). Our data are consistent with those obtained in previous studies that suggested that rs204993 is associated with SCZ and that the AA genotype of rs204993 demonstrates a higher risk. Further large-scale association analyses in Han Chinese populations are warranted.
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