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HLA Variants and Inhibitor Development in Hemophilia A: A Retrospective Case-Controlled Study Using the ATHNdataset.

ABSTRACT: In hemophilia A (HA) patients, F8 gene-defects as genetic risk-factors for developing inhibitors to Factor VIII have been extensively studied. Here we provide estimates of inhibitor-risk associated with the patient's Human Leukocyte Antigen (HLA). We used next generation sequencing for high-resolution HLA Class II typing of 997 HA patients. Using inhibitor prevalence reports from the My Life Our Future (MLOF) research repository, we calculated Odds Ratios (OR) for inhibitor development in a multivariate model considering HLA-DRB1/3/4/5, HLA-DPB1, HLA-DQB1, race, F8 pathogenic variant type, and age. Participants with 1 HLA variant (DPB1*02:02) had developed inhibitors at a higher rate while participants with 2 HLA variants (DRB1*04:07; DRB1*11:04) had developed inhibitors at a lower rate. Additionally, patients with missense variants had developed inhibitors at a lower rate and participants with large structural changes (>50 bp) had developed inhibitors at a higher rate (both compared to Intron 22 inversion). Using a cohort of participants with a distribution of HLA-DRB1 alleles comparable to that in the North American population we show that the HLA repertoire of a HA patient can be a risk-factor for inhibitor development.

SUBMITTER: McGill JR

PROVIDER: S-EPMC8139405 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: MicroRNAs (miRNAs) are small, non-coding RNA molecules involved in post-transcriptional gene regulation and have recently been shown to play a role in cancer metastasis. In solid tumors, especially breast cancer, alterations in miRNA expression contribute to cancer pathogenesis, including metastasis. Considering the emerging role of miRNAs in metastasis, the identification of predictive markers is necessary to further understanding of stage-specific breast cancer development. This is a retrospective analysis that aimed to identify molecular biomarkers related to distant breast cancer metastasis development. Methods: A retrospective case cohort study was performed in 64 breast cancer patients treated during the period from 1998-2001. The case group (n=29) consisted of patients with a poor prognosis who presented with breast cancer recurrence or metastasis during follow up. The control group (n=35) consisted of a random sample of patients with a good prognosis who did not develop breast cancer recurrence or metastasis. These patient groups were stratified according to TNM clinical stage (CS) I, II and III, and the main clinical features of the patients were homogeneous. miRNA profiling was performed using formalin-fixed, paraffin-embedded tumors. Biomarkers related to metastatic potential were identified independent of clinical stage, and a cutoff point was selected based on the optimal sensitivity and specificity (ROC curve). Finally, a hazard risk analysis of these biomarkers was performed to evaluate their relation to metastatic potential. Results: miRNA expression profiling identified several miRNAs that were either specific and shared across all clinical stages (p?0.05). Among these, we identified miRNAs previously associated with cell motility (let-7 family), cell proliferation and invasion (hsa-miR-16 and has-miR-205) and distant metastasis (hsa-miR-21). In addition, hsa-miR-494 and hsa-miR-21 were up-regulated in metastatic cases of CSI and II. Furthermore, the combination of the 3 miRNAs identified for CSII (hsa-miR-494, hsa-miR-183 and hsa-miR-21) was significant and were a more effective risk marker compared to the single miRNAs. Conclusions: Women with metastatic breast cancer, especially CSII, presented up-regulated levels of miR-183, miR-494 and miR-21, which were associated with a poor prognosis. These miRNAs therefore represent new risk biomarkers of breast cancer metastasis and may be useful for future targeted therapies.

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HLA Variants and Inhibitor Development in Hemophilia A: A Retrospective Case-Controlled Study Using the ATHNdataset.

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