Non-invasive prenatal testing of beta-hemoglobinopathies using next generation sequencing, in-silico sequence size selection, and haplotyping.

AIM: To develop a non-invasive prenatal test for beta-hemoglobinopathies based on analyzing maternal plasma by using next generation sequencing. METHODS: We applied next generation sequencing (NGS) of maternal plasma to the non-invasive prenatal testing (NIPT) of autosomal recessive diseases, sickle cell disease and beta-thalassemia. Using the Illumina MiSeq, we sequenced plasma libraries obtained via a Twist Bioscience probe capture panel covering 4 Kb of chromosome 11, including the beta-globin (HBB) gene and >450 genomic single-nucleotide polymorphisms (SNPs) used to estimate the fetal fraction (FF). The FF is estimated by counting paternally transmitted allelic sequence reads present in the plasma but absent in the mother. We inferred fetal beta-globin genotypes by comparing the observed mutation (Mut) and reference (Ref) read ratios to those expected for the three possible fetal genotypes (Mut/Mut; Mut/Ref; Ref/Ref), based on the FF. RESULTS: We bioinformatically enriched the FF by excluding reads over a specified length via in-silico size selection (ISS), favoring the shorter fetal reads, which increased fetal genotype prediction accuracy. Finally, we determined the parental HBB haplotypes, which allowed us to use the read ratios observed at linked SNPs to help predict the fetal genotype at the mutation site(s). We determined HBB haplotypes via Oxford Nanopore MinION sequencing of a 2.2 kb amplicon and aligned these sequences using Soft Genetics' NextGENe LR software. CONCLUSION: The combined use of ISS and HBB haplotypes enabled us to correctly predict fetal genotypes in cases where the prediction based on variant read ratios alone was incorrect.

HLA-C dysregulation as a possible mechanism of immune evasion in SARS-CoV-2 and other RNA-virus infections.

One of the mechanisms by which viruses can evade the host's immune system is to modify the host's DNA methylation pattern. This work aims to investigate the DNA methylation and gene expression profile of COVID-19 patients, divided into symptomatic and asymptomatic, and healthy controls, focusing on genes involved in the immune response. In this study, changes in the methylome of COVID-19 patients' upper airways cells, the first barrier against respiratory infections and the first cells presenting viral antigens, are shown for the first time. Our results showed alterations in the methylation pattern of genes encoding proteins implicated in the response against pathogens, in particular the HLA-C gene, also important for the T-cell mediated memory response. HLA-C expression significantly decreases in COVID-19 patients, especially in those with a more severe prognosis and without other possibly confounding co-morbidities. Moreover, our bionformatic analysis revealed that the identified methylation alteration overlaps with enhancers regulating HLA-C expression, suggesting an additional mechanism exploited by SARS-CoV-2 to inhibit this fundamental player in the host's immune response. HLA-C could therefore represent both a prognostic marker and an excellent therapeutic target, also suggesting a preventive intervention that conjugate a virus-specific antigenic stimulation with an adjuvant increasing the T-cell mediated memory response.

Noninvasive Prenatal Test for ß-Thalassemia and Sickle Cell Disease Using Probe Capture Enrichment and Next-Generation Sequencing of DNA in Maternal Plasma.

BACKGROUND: Noninvasive prenatal testing (NIPT) of chromosomal aneuploidies based on next-generation sequencing (NGS) analysis of fetal DNA in maternal plasma is well established, but testing for autosomal recessive disorders remains challenging. NGS libraries prepared by probe capture facilitate the analysis of the short DNA fragments plasma. This system has been applied to the ß-hemoglobinopathies to reduce the risk to the fetus. METHOD: Our probe panel captures >4 kb of the HBB region and 435 single-nucleotide polymorphisms (SNPs) used to estimate fetal fraction. Contrived mixtures of DNA samples, plasma, and whole blood samples from 7 pregnant women with ß-thalassemia or sickle cell anemia mutations and samples from the father, sibling, and baby or chorionic villus were analyzed. The fetal genotypes, including point mutations and deletions, were inferred by comparing the observed and expected plasma sequence read ratios, based on fetal fraction, at the mutation site and linked SNPs. Accuracy was increased by removing PCR duplicates and by in silico size selection of plasma sequence reads. A probability was assigned to each of the potential fetal genotypes using a statistical model for the experimental variation, and thresholds were established for assigning clinical status. RESULTS: Using in silico size selection of plasma sequence files, the predicted clinical fetal genotype assignments were correct in 9 of 10 plasma libraries with maternal point mutations, with 1 inconclusive result. For 2 additional plasmas with deletions, the most probable fetal genotype was correct. The ß-globin haplotype determined from linked SNPs, when available, was used to infer the fetal genotype at the mutation site. CONCLUSION: This probe capture NGS assay demonstrates the potential of NIPT for ß-hemoglobinopathies.

Type 1 Diabetes Risk in African-Ancestry Participants and Utility of an Ancestry-Specific Genetic Risk Score.

OBJECTIVE: Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS. RESEARCH DESIGN AND METHODS: We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10-8) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10-5). RESULTS: African-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts. CONCLUSIONS: Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis.

We investigated association between HLA class I and class II alleles and haplotypes, and KIR loci and their HLA class I ligands, with multiple sclerosis (MS) in 412 European American MS patients and 419 ethnically matched controls, using next-generation sequencing. The DRB1*15:01~DQB1*06:02 haplotype was highly predisposing (odds ratio (OR) = 3.98; 95% confidence interval (CI) = 3-5.31; p-value (p) = 2.22E-16), as was DRB1*03:01~DQB1*02:01 (OR = 1.63; CI = 1.19-2.24; p = 1.41E-03). Hardy-Weinberg (HW) analysis in MS patients revealed a significant DRB1*03:01~DQB1*02:01 homozyote excess (15 observed; 8.6 expected; p = 0.016). The OR for this genotype (5.27; CI = 1.47-28.52; p = 0.0036) suggests a recessive MS risk model. Controls displayed no HW deviations. The C*03:04~B*40:01 haplotype (OR = 0.27; CI = 0.14-0.51; p = 6.76E-06) was highly protective for MS, especially in haplotypes with A*02:01 (OR = 0.15; CI = 0.04-0.45; p = 6.51E-05). By itself, A*02:01 is moderately protective, (OR = 0.69; CI = 0.54-0.87; p = 1.46E-03), and haplotypes of A*02:01 with the HLA-B Thr80 Bw4 variant (Bw4T) more so (OR = 0.53; CI = 0.35-0.78; p = 7.55E-04). Protective associations with the Bw4 KIR ligand resulted from linkage disequilibrium (LD) with DRB1*15:01, but the Bw4T variant was protective (OR = 0.64; CI = 0.49-0.82; p = 3.37-04) independent of LD with DRB1*15:01. The Bw4I variant was not associated with MS. Overall, we find specific class I HLA polymorphisms to be protective for MS, independent of the strong predisposition conferred by DRB1*15:01.

Correction: High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis.

Since the publication of this article, the authors have found that the numbers of patients and controls were reversed. This study included 412 MS patients and 419 controls. This correction applies to the Abstract, the final paragraph of the Introduction, and the first paragraph of the Materials and Methods. This was entirely a reporting error and does not impact the Results or Conclusions.

Correction: Shelly Y. Shih; et al.; Applications of Probe Capture Enrichment Next Generation Sequencing for Whole Mitochondrial Genome and 426 Nuclear SNPs for Forensically Challenging Samples. Genes 2018, 9, 49.

The authors wish to make the following change to their paper [1][...].

Applications of Probe Capture Enrichment Next Generation Sequencing for Whole Mitochondrial Genome and 426 Nuclear SNPs for Forensically Challenging Samples.

The application of next generation sequencing (NGS) for the analysis of mitochondrial (mt) DNA, short tandem repeats (STRs), and single nucleotide polymorphism (SNPs) has demonstrated great promise for challenging forensic specimens, such as degraded, limited, and mixed samples. Target enrichment using probe capture rather than PCR amplification offers advantages for analysis of degraded DNA since two intact PCR primer sites in the template DNA molecule are not required. Furthermore, NGS software programs can help remove PCR duplicates to determine initial template copy numbers of a shotgun library. Moreover, the same shotgun library prepared from a limited DNA source can be enriched for mtDNA as well as nuclear markers by hybrid capture with the relevant probe panels. Here, we demonstrate the use of this strategy in the analysis of limited and mock degraded samples using our custom probe capture panels for massively parallel sequencing of the whole mtgenome and 426 SNP markers. We also applied the mtgenome capture panel in a mixed sample and analyzed using both phylogenetic and variant frequency based bioinformatics tools to resolve the minor and major contributors. Finally, the results obtained on individual telogen hairs demonstrate the potential of probe capture NGS analysis for both mtDNA and nuclear SNPs for challenging forensic specimens.

A phylogenetic approach for haplotype analysis of sequence data from complex mitochondrial mixtures.

Massively parallel (next-generation) sequencing provides a powerful method to analyze DNA from many different sources, including degraded and trace samples. A common challenge, however, is that many forensic samples are often known or suspected mixtures of DNA from multiple individuals. Haploid lineage markers, such as mitochondrial (mt) DNA, are useful for analysis of mixtures because, unlike nuclear genetic markers, each individual contributes a single sequence to the mixture. Deconvolution of these mixtures into the constituent mitochondrial haplotypes is challenging as typical sequence read lengths are too short to reconstruct the distinct haplotypes completely. We present a powerful computational approach for determining the constituent haplotypes in massively parallel sequencing data from potentially mixed samples. At the heart of our approach is an expectation maximization based algorithm that co-estimates the overall mixture proportions and the source haplogroup for each read individually. This approach, implemented in the software package mixemt, correctly identifies haplogroups from mixed samples across a range of mixture proportions. Furthermore, our method can separate fragments in a mixed sample by the most likely originating contributor and generate reconstructions of the constituent haplotypes based on known patterns of mtDNA diversity.

The Role of Human Papillomavirus Genotyping in Cervical Cancer Screening: A Large-Scale Evaluation of the cobas HPV Test.

BACKGROUND: The cobas HPV Test ("cobas"; Roche Molecular Systems) detects HPV16 and HPV18 individually, and a pool of 12 other high-risk (HR) HPV types. The test is approved for (i) atypical squamous cells of undetermined significance (ASC-US) triage to determine need for colposcopy, (ii) combined screening with cytology ("cotesting"), and (iii) primary HPV screening. METHODS: To assess the possible value of HPV16/18 typing, >17,000 specimens from a longitudinal cohort study of initially HPV-positive women (HC2, Qiagen) were retested with cobas. To study accuracy, cobas genotyping results were compared with those of an established method, the Linear Array HPV Genotyping Test (LA, Roche Molecular Systems). Clinical value of the typing strategy was evaluated by linking the cobas results (supplemented by other available typing results) to 3-year cumulative risks of CIN3+. RESULTS: Grouped hierarchically (HPV16, else HPV18, else other HR types, else negative), the κ statistic for agreement between cobas and LA was 0.86 [95% confidence interval (CI), 0.86-0.87]. In all three scenarios, HPV16-positive women were at much higher 3-year risk of CIN3+ than HPV16-negative women: women ages 21 and older with ASC-US (14.5%; 95% CI, 13.5%-15.5% vs. 3.5%; 95% CI, 3.3-3.6); women ages 30 years and older that were HPV-positive cytology-negative (10.3%; 95% CI, 9.6-11.1 vs. 2.3%; 95% CI, 2.2-2.4); and all women 25 years and older that were HPV-positive (18.5%; 95% CI, 17.8-19.2 vs. 4.3%; 95% CI, 4.2-4.4). CONCLUSION: The cobas and LA results show excellent agreement. The data support HPV16 typing. IMPACT: HPV16 typing is useful in the management of HPV-positive/cytology-negative women in cotesting, of all HPV-positive women in primary HPV testing, and perhaps in the management of HPV-positive women with ASC-US. Cancer Epidemiol Biomarkers Prev; 24(9); 1304-10.

Analysis of mixtures using next generation sequencing of mitochondrial DNA hypervariable regions.

AIM: To apply massively parallel and clonal sequencing (next generation sequencing or NGS) to the analysis of forensic mixed samples. METHODS: A duplex polymerase chain reaction (PCR) assay targeting the mitochondrial DNA (mtDNA) hypervariable regions I/II (HVI/HVII) was developed for NGS analysis on the Roche 454 GS Junior instrument. Eight sets of multiplex identifier-tagged 454 fusion primers were used in a combinatorial approach for amplification and deep sequencing of up to 64 samples in parallel. RESULTS: This assay was shown to be highly sensitive for sequencing limited DNA amounts (~100 mtDNA copies) and analyzing contrived and biological mixtures with low level variants (~1%) as well as "complex" mixtures (≥3 contributors). PCR artifact "hybrid" sequences generated by jumping PCR or template switching were observed at a low level (<2%) in the analysis of mixed samples but could be eliminated by reducing the PCR cycle number. CONCLUSION: This study demonstrates the power of NGS technologies targeting the mtDNA HVI/HVII regions for analysis of challenging forensic samples, such as mixtures and specimens with limited DNA.

Human NK cells licensed by killer Ig receptor genes have an altered cytokine program that modifies CD4+ T cell function.

NK cells are innate immune cells known for their cytolytic activities toward tumors and infections. They are capable of expressing diverse killer Ig-like receptors (KIRs), and KIRs are implicated in susceptibility to Crohn's disease (CD), a chronic intestinal inflammatory disease. However, the cellular mechanism of this genetic contribution is unknown. In this study, we show that the "licensing" of NK cells, determined by the presence of KIR2DL3 and homozygous HLA-C1 in host genome, results in their cytokine reprogramming, which permits them to promote CD4(+) T cell activation and Th17 differentiation ex vivo. Microfluidic analysis of thousands of NK single cells and bulk secretions established that licensed NK cells are more polarized to proinflammatory cytokine production than unlicensed NK cells, including production of IFN-γ, TNF-α, CCL-5, and MIP-1ß. Cytokines produced by licensed NK augmented CD4(+) T cell proliferation and IL-17A/IL-22 production. Ab blocking indicated a primary role for IFN-γ, TNF-α, and IL-6 in the augmented T cell-proliferative response. In conclusion, NK licensing mediated by KIR2DL2/3 and HLA-C1 elicits a novel NK cytokine program that activates and induces proinflammatory CD4(+) T cells, thereby providing a potential biologic mechanism for KIR-associated susceptibility to CD and other chronic inflammatory diseases.

Receiver operating characteristic analysis of HLA, CTLA4, and insulin genotypes for type 1 diabetes.

OBJECTIVE: This study assessed the ability to distinguish between type 1 diabetes-affected individuals and their unaffected relatives using HLA and single nucleotide polymorphism (SNP) genotypes. RESEARCH DESIGN AND METHODS: Eight models, ranging from only the high-risk DR3/DR4 genotype to all significantly associated HLA genotypes and two SNPs mapping to the cytotoxic T-cell-associated antigen-4 gene (CTLA4) and insulin (INS) genes, were fitted to high-resolution class I and class II HLA genotyping data for patients from the Type 1 Diabetes Genetics Consortium collection. Pairs of affected individuals and their unaffected siblings were divided into a "discovery" (n = 1,015 pairs) and a "validation" set (n = 318 pairs). The discriminating performance of various combinations of genetic information was estimated using receiver operating characteristic (ROC) curve analysis. RESULTS: The use of only the presence or absence of the high-risk DR3/DR4 genotype achieved very modest discriminating ability, yielding an area under the curve (AUC) of 0.62 in the discovery set and 0.59 in the validation set. The full model-which included HLA information from the class II loci DPB1, DRB1, and DQB1; selected alleles from HLA class I loci A and B; and SNPs from the CTLA4 and INS genes-increased the AUC to 0.74 in the discovery set and to 0.71 in the validation set. A cost-effective alternative is proposed, using genotype information equivalent to typing four SNPs (DR3, DR4-DQB1*03:02, CTLA-4, and INS), which achieved an AUC of 0.72 in the discovery set and 0.69 in the validation set. CONCLUSIONS: Genotyping data sufficient to tag DR3, DR4-DQB1*03:02, CTLA4, and INS were shown to distinguish between subjects with type 1 diabetes and their unaffected siblings adequately to achieve clinically utility to identify children in multiplex families to be considered for early intervention.

Next generation sequencing reveals the association of DRB3*02:02 with type 1 diabetes.

The primary associations of the HLA class II genes, HLA-DRB1 and HLA-DQB1, and the class I genes, HLA-A and HLA-B, with type 1 diabetes (T1D) are well established. However, the role of polymorphism at the HLA-DRB3, HLA-DRB4, and HLA-DRB5 loci remains unclear. In two separate studies, one of 500 subjects and 500 control subjects and one of 366 DRB1*03:01-positive samples from selected multiplex T1D families, we used Roche 454 sequencing with Conexio Genomics ASSIGN ATF 454 HLA genotyping software analysis to analyze sequence variation at these three HLA-DRB loci. Association analyses were performed on the two HLA-DRB loci haplotypes (DRB1-DRB3, -DRB4, or -DRB5). Three common HLA-DRB3 alleles (*01:01, *02:02, *03:01) were observed. DRB1*03:01 haplotypes carrying DRB3*02:02 conferred a higher T1D risk than did DRB1*03:01 haplotypes carrying DRB3*01:01 in DRB1*03:01/*03:01 homozygotes with two DRB3*01:01 alleles (odds ratio [OR] 3.4 [95% CI 1.46-8.09]), compared with those carrying one or two DRB3*02:02 alleles (OR 25.5 [3.43-189.2]) (P = 0.033). For DRB1*03:01/*04:01 heterozygotes, however, the HLA-DRB3 allele did not significantly modify the T1D risk of the DRB1*03:01 haplotype (OR 7.7 for *02:02; 6.8 for *01:01). These observations were confirmed by sequence analysis of HLA-DRB3 exon 2 in a targeted replication study of 281 informative T1D family members and 86 affected family-based association control (AFBAC) haplotypes. The frequency of DRB3*02:02 was 42.9% in the DRB1*03:01/*03:01 patients and 27.6% in the DRB1*03:01/*04 (P = 0.005) compared with 22.6% in AFBAC DRB1*03:01 chromosomes (P = 0.001). Analysis of T1D-associated alleles at other HLA loci (HLA-A, HLA-B, and HLA-DPB1) on DRB1*03:01 haplotypes suggests that DRB3*02:02 on the DRB1*03:01 haplotype can contribute to T1D risk.

A sequence-based approach demonstrates that balancing selection in classical human leukocyte antigen (HLA) loci is asymmetric.

Balancing selection has maintained human leukocyte antigen (HLA) allele diversity, but it is unclear whether this selection is symmetric (all heterozygotes are comparable and all homozygotes are comparable in terms of fitness) or asymmetric (distinct heterozygote genotypes display greater fitness than others). We tested the hypothesis that HLA is under asymmetric balancing selection in populations by estimating allelic branch lengths from genetic sequence data encoding peptide-binding domains. Significant deviations indicated changes in the ratio of terminal to internal branch lengths. Such deviations could arise even if no individual alleles present a strikingly altered branch length (e.g. if there is an overall distortion, with all or many terminal branches being longer than expected). DQ and DP loci were also analyzed as haplotypes. Using allele frequencies for 419 distinct populations in 10 geographical regions, we examined population differentiation in alleles within and between regions, and the relationship between allelic branch length and frequency. The strongest evidence for asymmetrical balancing selection was observed for HLA-DRB1, HLA-B and HLA-DPA1, with significant deviation (P ≤ 1.1 × 10(-4)) in about half of the populations. There were significant results at all loci except HLA-DQB1/DQA1. We observed moderate genetic variation within and between geographic regions, similar to the rest of the genome. Branch length was not correlated with allele frequency. In conclusion, sequence data suggest that balancing selection in HLA is asymmetric (some heterozygotes enjoy greater fitness than others). Because HLA polymorphism is crucial for pathogen resistance, this may manifest as a frequency-dependent selection with fluctuation in the fitness of specific heterozygotes over time.

HLA-DP genetic variation, proxies for early life immune modulation and childhood acute lymphoblastic leukemia risk.

The human leukocyte antigen (HLA) genes are candidate genetic susceptibility loci for childhood acute lymphoblastic leukemia (ALL). We examined the effect of HLA-DP genetic variation on risk and evaluated its potential interaction with 4 proxies for early immune modulation, including measures of infectious exposures in infancy (presence of older siblings, daycare attendance, ear infections) and breastfeeding. A total of 585 ALL cases and 848 controls were genotyped at the HLA-DPA1 and DPB1 loci. Because of potential heterogeneity in effect by race/ethnicity, we included only non-Hispanic white (47%) and Hispanic (53%) children and considered these 2 groups separately in the analysis. Logistic regression analyses showed an increased risk of ALL associated with HLA-DPB1*01:01 (odds ratio [OR] = 1.43, 95% CI, 1.01-2.04) with no heterogeneity by Hispanic ethnicity (P = .969). Analyses of DPB1 supertypes showed a marked childhood ALL association with DP1, particularly for high-hyperdiploid ALL (OR = 1.83; 95% CI, 1.20-2.78). Evidence of interaction was found between DP1 and older sibling (P = .036), and between DP1 and breastfeeding (P = .094), with both showing statistically significant DP1 associations within the lower exposure categories only. These findings support an immune mechanism in the etiology of childhood ALL involving the HLA-DPB1 gene in the context of an insufficiently modulated immune system.

Evidence of gene-gene interaction and age-at-diagnosis effects in type 1 diabetes.

The common genetic loci that independently influence the risk of type 1 diabetes have largely been determined. Their interactions with age-at-diagnosis of type 1 diabetes, sex, or the major susceptibility locus, HLA class II, remain mostly unexplored. A large collection of more than 14,866 type 1 diabetes samples (6,750 British diabetic individuals and 8,116 affected family samples of European descent) were genotyped at 38 confirmed type 1 diabetes-associated non-HLA regions and used to test for interaction of association with age-at-diagnosis, sex, and HLA class II genotypes using regression models. The alleles that confer susceptibility to type 1 diabetes at interleukin-2 (IL-2), IL2/4q27 (rs2069763) and renalase, FAD-dependent amine oxidase (RNLS)/10q23.31 (rs10509540), were associated with a lower age-at-diagnosis (P = 4.6 × 10⁻6 and 2.5 × 10⁻5, respectively). For both loci, individuals carrying the susceptible homozygous genotype were, on average, 7.2 months younger at diagnosis than those carrying the protective homozygous genotypes. In addition to protein tyrosine phosphatase nonreceptor type 22 (PTPN22), evidence of statistical interaction between HLA class II genotypes and rs3087243 at cytotoxic T-lymphocyte antigen 4 (CTLA4)/2q33.2 was obtained (P = 7.90 × 10⁻5). No evidence of differential risk by sex was obtained at any loci (P ≥ 0.01). Statistical interaction effects can be detected in type 1 diabetes although they provide a relatively small contribution to our understanding of the familial clustering of the disease.