Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma

Zhang, Chenan; Smith, Adam J. de; Смирнов, Иван; Wiencke, John K.; Witte, John S.; Walsh, Kyle M.

doi:10.1007/s11060-017-2569-7

Cited by 14 publications

(20 citation statements)

References 42 publications

(59 reference statements)

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“…Fastq file quality was estimated using FASTQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). All BAM files were processed using GATK best practices (Van der Auwera et al, 2013; Zhang et al, 2017), as described in DeBoever et al (2017) to detect single nucleotide polymorphisms (SNPs) genome-wide. For chromosome 6, the chromosome-wide SNP density (79 SNPs per 10 kb) was calculated by dividing the total number of SNPs in the 273 iPSCORE individuals by the length of the chromosome, excluding undefined ‘N’ nucleotides.…”

Section: Methodsmentioning

confidence: 99%

Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease

D’Antonio

Reyna

Jakubosky

et al. 2019

eLife

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The MHC region is highly associated with autoimmune and infectious diseases. Here we conduct an in-depth interrogation of associations between genetic variation, gene expression and disease. We create a comprehensive map of regulatory variation in the MHC region using WGS from 419 individuals to call eight-digit HLA types and RNA-seq data from matched iPSCs. Building on this regulatory map, we explored GWAS signals for 4083 traits, detecting colocalization for 180 disease loci with eQTLs. We show that eQTL analyses taking HLA type haplotypes into account have substantially greater power compared with only using single variants. We examined the association between the 8.1 ancestral haplotype and delayed colonization in Cystic Fibrosis, postulating that downregulation of RNF5 expression is the likely causal mechanism. Our study provides insights into the genetic architecture of the MHC region and pinpoints disease associations that are due to differential expression of HLA genes and non-HLA genes.

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Section: Methodsmentioning

confidence: 99%

Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease

D’Antonio

Reyna

Jakubosky

et al. 2019

eLife

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“…HLA-B * 67:01 is a genetic risk factor for Takayasu arteritis ( 13 ), while HLA-DRB1 * 16:02, HLA-DQB1 * 05:02 and HLA-B * 67:01 are associated with relapsing polychondritis (RPC) ( 14 ), which may suggest a patient with a high susceptibility to another autoimmune disease ( 13 ). Interestingly, Chenan Zhang ( 15 ) reported that the DRB1 * 1501-DQA1 * 0102-DQB1 * 0602 haplotype may contribute to the risk of glioma in a non-additive manner. The type of role that DQA1 * 0102 plays in the process of disease pathogenesis is unclear.…”

Section: Discussionmentioning

confidence: 99%

Multiple Distinctive Demyelinating Lesions Caused by Eosinophilic Granulomatosis With Polyangiitis: Case Report and Literature Review

Wang

et al. 2019

Front. Neurol.

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Eosinophilic granulomatosis with polyangiitis (EGPA) is an extremely rare rheumatic immune disease characterized by vasculitis of small- and medium-sized blood vessels. Central nervous system (CNS) involvement frequently consists of cerebrovascular disease; a manifestation with multiple demyelinating lesions has never been reported in detail. This report describes a 38-year-old man, who presented with progressive memory deterioration and underwent microsurgery; EGPA was subsequently confirmed. Unique clinical and radiological features as well as immunohistological outcomes and DNA sequencing revealed a potential disease-associated human leukocyte antigen (HLA) type, and single-nucleotide polymorphisms (SNPs) are described for this uncommon case. Although EGPA rarely involves the CNS, this differential diagnosis should be considered when patients present with a history of nasosinusitis, elevated eosinophil percentage, clinical pulmonitis, and neurological manifestations. Microsurgery is necessary for precise diagnosis and effective treatment.

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“…We imputed four-digit classical HLA alleles of the three main class I genes (HLA-A, HLA-B, and HLA-C) and the five class II genes (HLA-DRB1, -DPA1, -DPB1, -DQA1, and -DQB1), as well as 5,695 HLA intragenic SNPs using SNP2HLA(30), which uses a reference panel of 5,225 individuals of European ancestry from the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. We used the SNP2HLA imputed allele dosage data for the primary MHC-wide association analyses, and phased best guess genotypes for the non-additive effect analyses, as previously described(22). Association analyses were restricted to classic four-digit HLA class I and class II alleles with imputation quality score INFO>0.80, allele frequency>0.05 (19 class I alleles, 27 class II alleles).…”

Section: Methodsmentioning

confidence: 99%

“…We investigated non-additive effects of the HLA alleles by assessing dominance-effect models as described in prior studies(22,24). In brief, we tested the improvement in model fit comparing the additive effect model with a model that additionally included a dominance term representing heterozygous status for each HLA allele investigated.…”

Section: Methodsmentioning

confidence: 99%

“…We subsequently attempted replication in an independent set of osteosarcoma cases and controls and performed meta-analysis of these two datasets, totaling 864 cases and 1879 controls. We further assessed non-additive genetic associations in the MHC region as a complementary approach given the observation of widespread non-additive and epistatic effects among HLA variants for a number of diseases(22–24), as well as any potential modification by subject sex or clinical presentation ( e.g. tumor location, presence of metastasis, age at diagnosis) to seek further insight into the etiology, progression, and prognosis of this aggressive cancer.…”

Section: Introductionmentioning

confidence: 99%

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Two HLA Class II Gene Variants Are Independently Associated with Pediatric Osteosarcoma Risk

Zhang

Hansen

Gonzalez-Maya

et al. 2018

Cancer Epidemiology, Biomarkers &Amp; Prevention

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The genetic etiology of osteosarcoma remains poorly understood despite the publication of a genome-wide association study. Association between HLA genetic variants and risk of several cancers has been observed, but HLA variation is not well captured by standard SNP arrays. We genotyped 207 Californian pediatric osteosarcoma cases and 696 controls of European ancestry using a custom genome-wide array supplemented with approximately 6,000 additional probes across the MHC region. We subsequently imputed 4-digit classical HLA alleles using a reference panel of 5,225 individuals who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for ancestry-informative principal components, and top associations from the discovery analysis underwent replication in an independent dataset of 657 cases and 1,183 controls. Three highly correlated HLA class II variants ( = 0.33-0.98) were associated with osteosarcoma risk in discovery analyses, including (OR = 0.52; = 3.2 × 10), (OR = 0.74; = 0.031), and (OR = 0.51; = 2.7 × 10). Similar associations were observed in the replication data ( = 0.011-0.037). Meta-analysis of the two datasets identified as the most significantly associated variant (OR = 0.62; = 1.5 × 10), reaching Bonferroni-corrected statistical significance. The meta-analysis also revealed a second significant independent signal at (OR = 1.33, = 1.2 × 10), and a third suggestive association at (OR = 0.73, = 6.4 × 10). Multiple independent HLA class II alleles may influence osteosarcoma risk. Additional work is needed to extend our observations to other patient populations and to clarify the potential causal mechanisms underlying these associations. Understanding immunologic contributions to the etiology of osteosarcoma may inform rational therapeutic targets. .

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Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma

Cited by 14 publications

References 42 publications

Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease

Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease

Multiple Distinctive Demyelinating Lesions Caused by Eosinophilic Granulomatosis With Polyangiitis: Case Report and Literature Review

Two HLA Class II Gene Variants Are Independently Associated with Pediatric Osteosarcoma Risk

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