Identification of the novel HLA-A*30:221 allele by next-generation sequencing.

The novel HLA-A*30:221 allele differs from HLA-A*30:01:01:01 by one nucleotide substitution in Exon 7.

Identification of a robust DNA methylation signature for Fanconi anemia.

Fanconi anemia (FA) is a clinically variable and genetically heterogeneous cancer-predisposing disorder representing the most common bone marrow failure syndrome. It is caused by inactivating predominantly biallelic mutations involving >20 genes encoding proteins with roles in the FA/BRCA DNA repair pathway. Molecular diagnosis of FA is challenging due to the wide spectrum of the contributing gene mutations and structural rearrangements. The assessment of chromosomal fragility after exposure to DNA cross-linking agents is generally required to definitively confirm diagnosis. We assessed peripheral blood genome-wide DNA methylation (DNAm) profiles in 25 subjects with molecularly confirmed clinical diagnosis of FA (FANCA complementation group) using Illumina's Infinium EPIC array. We identified 82 differentially methylated CpG sites that allow to distinguish subjects with FA from healthy individuals and subjects with other genetic disorders, defining an FA-specific DNAm signature. The episignature was validated using a second cohort of subjects with FA involving different complementation groups, documenting broader genetic sensitivity and demonstrating its specificity using the EpiSign Knowledge Database. The episignature properly classified DNA samples obtained from bone marrow aspirates, demonstrating robustness. Using the selected probes, we trained a machine-learning model able to classify EPIC DNAm profiles in molecularly unsolved cases. Finally, we show that the generated episignature includes CpG sites that do not undergo functional selective pressure, allowing diagnosis of FA in individuals with reverted phenotype due to gene conversion. These findings provide a tool to accelerate diagnostic testing in FA and broaden the clinical utility of DNAm profiling in the diagnostic setting.

Identification of the novel HLA-DPA1*01:149 allele by next-generation sequencing.

The novel HLA-DPA1*01:149 allele differs from HLA-DPA1*01:03:01:05 by one nucleotide substitution in exon 2.

Identification of the novel HLA-DPA1*02:110:02 allele by next-generation sequencing.

The novel HLA-DPA1*02:110:02 allele differs from HLA-DPA1*02:01:01:06 by one nucleotide substitution in exon 4.

Characterization of the novel HLA-DPA1*01:159 allele by sequencing-based typing.

HLA-DPA1*01:159 differs from HLA-DPA1*01:03:01:03 by one nucleotide substitution in codon 120 in exon 3.

Genome-Wide DNA Methylation Profiling Solves Uncertainty in Classifying NSD1 Variants.

BACKGROUND: Inactivating NSD1 mutations causing Sotos syndrome have been previously associated with a specific genome-wide DNA methylation (DNAm) pattern. Sotos syndrome is characterized by phenotypic overlap with other overgrowth syndromes, and a definite diagnosis might not be easily reached due to the high prevalence of variants of unknown significance (VoUS) that are identified in patients with a suggestive phenotype. OBJECTIVE: we performed microarray DNAm profiling in a set of 11 individuals with a clinical suspicion of Sotos syndrome and carrying an NSD1 VoUS or previously unreported variants to solve uncertainty in defining pathogenicity of the observed variants. The impact of the training cohort size on sensitivity and prediction confidence of the classifier was assessed. RESULTS: The Sotos syndrome-specific DNAm signature was validated in six individuals with a clinical diagnosis of Sotos syndrome and carrying bona fide pathogenic NSD1 variants. Applying this approach to the remaining 11 individuals with NSD1 variants, we succeeded in confirming pathogenicity in eight subjects and excluding the diagnosis of Sotos syndrome in three. The sensitivity and prediction confidence of the classifier based on the different sizes of the training sets did not show substantial differences, though the overall performance was improved by using a data balancing strategy. CONCLUSIONS: The present approach solved uncertainty in cases with NDS1 VoUS, further demonstrating the clinical utility of DNAm profiling.

Characterization of the novel HLA-DRB3*02:179N allele by sequencing-based typing.

HLA-DRB3*02:179N differs from DRB3*02:02:01:02 by one nucleotide substitution in codon 98 in exon 3.

Identification of the novel HLA-B allele, HLA-B*44:532 by next-generation sequencing.

The novel HLA-B*44:532 allele differs from HLA-B*44:02:01:01 by one nucleotide substitution in Exon 3.

Identification of the novel HLA-DPA1 allele, DPA1*02:53 by next-generation sequencing.

The novel HLA-DPA1*02:53 allele differs from HLA-DPA1*02:01:01:02 by one nucleotide substitution in exon 3.

Characterization of the novel HLA-DQA1*05:49 allele by sequencing-based typing.

HLA-DQA1*05:49 differs from HLA-DQA1*05:01:01:02 by one nucleotide substitution in codon 78 in exon 2.

Identification of the novel HLA-DRB1*03:01:32 in an Italian patient.

The novel HLA-DRB1*03:01:32 allele differs from HLA-DRB1*03:01:01:01 by one nucleotide substitution in exon 4.

Identification of the novel HLA-DPB1*1149:01.

The new allele HLA-DPB1*1149:01 differs from HLA-DPB1*09:01:01 by one nucleotide substitution in Exon 4.

HLA-Cw6 and other HLA-C alleles, as well as MICB-DT, DDX58, and TYK2 genetic variants associate with optimal response to anti-IL-17A treatment in patients with psoriasis.

Objective: Our pharmacogenomic study evaluated the influence of the presence/absence of genetic variants of psoriasis-risk loci on the clinical response to secukinumab. Differences in the single-nucleotide polymorphism (SNP) pattern characterizing HLA-Cw6+ or HLA-Cw6- patient subpopulations, showing high or low responses to secukinumab, were also analyzed. Methods: 417 SNPs were analyzed by Next-Generation Sequencing technology, in a cohort of 62 psoriatic patients and undergone secukinumab treatment. Univariate regression analysis was employed to examine the association between SNP and clinical response to secukinumab. Multivariate analysis was also performed to assess multivariate differences in SNP pattern of HLA-Cw6+ or HLA-Cw6- patients showing high or low responses to secukinumab. Results: Eight SNPs in HLA-C and upstream region (rs13207315, rs6900444, rs12189871, rs12191877, rs4406273, and rs10484554), including HLA-Cw6 classical allele (rs1131118), and three in MICB-DT (rs9267325), DDX58 (rs34085293) and TYK2 (rs2304255) genes, associating with excellent response to secukinumab were identified. Importantly, rs34085293 or rs2304255 SNP status defined a subgroup of super-responder patients. We also found that HLA-Cw6+ and HLA-Cw6- patients carried out specific patterns of SNPs associating with different responses to secukinumab. Conclusion: Assessment of HLA-Cw6, together with other allelic variants of genes, could be helpful to define patients which better benefit from anti-IL-17 therapy. Abbreviations: PASI: Psoriasis Area and Severity Index; SNP: Single-Nucleotide Polymorphism Rs: Reference SNP; PASI75: 75% reduction in Psoriasis Area and Severity Index; PASI90: 90% reduction in Psoriasis Area and Severity Index; PASI100: 100% reduction in Psoriasis Area and Severity Index; NGS: Next-Generation Sequencing; OR: Odds Ratio; CAP: Canonical Analysis of Principal coordinates; BMI: Body Mass Index; LD: Linkage Disequilibrium.

Characterization of the novel HLA-DPA1*01:42 allele by sequencing-based typing.

HLA-DPA1*01:42 differs from DPA1*01:03:01:02 by one nucleotide substitution in Codon 76 in Exon 2.

Characterization of the novel HLA-DRB3*01:86 allele by sequencing-based typing.

HLA-DRB3*01:86 differs from HLA-DRB3*01:01:02:01 by one nucleotide substitution in codon 225 in exon 4.

Characterization of the novel HLA-DQA1*03:15 allele by sequencing-based typing.

HLA-DQA1*03:15 differs from HLA-DQA1*03:01:01:01 by one nucleotide substitution in codon 79 in exon 2.

Characterization of the novel HLA-DRB3*02:142 allele by sequencing-based typing.

HLA-DRB3*02:142 differs from HLA-DRB3*02:02:01:02 by one nucleotide substitution in codon 98 in exon 3.

Characterization of the novel HLA-DPA1*02:26 allele by sequencing-based typing.

HLA-DPA1*02:26 differs from HLA-DPA1*02:01:01:02 by one nucleotide substitution in codon 186 in exon 4.

Characterization of the novel HLA-DQA1*01:25 allele by sequencing-based typing.

HLA-DQA1*01:25 differs from HLA-DQA1*01:02:01:01 by one nucleotide substitution in codon 8 in exon 2.

Identification of the novel HLA-A*01:289 allele in an Italian patient.

The new allele HLA-A*01:289 differs from HLA-A*01:95 by one nucleotide substitution in exon 2.