BackgroundBisphosphonate-induced osteonecrosis of the jaw (BRONJ) presents with a typical pattern of jaw necrosis in patients who have been prescribed bisphosphonates (BPs) and other antiangiogenetic drugs to treat osteoporosis or bone-related complications of cancer.MethodsThis study divided 38 patients with BRONJ into two groups according to the prescribing causes: cancer (n = 13) and osteoporosis (n = 25), and underwent whole exome sequencing and compared them with normal controls (n = 90). To identify candidate genes and variants, we conducted three analyses: a traditional genetic model, gene-wise variant score burden, and rare-variant analysis methods.ResultsThe stop-gain mutation (rs117889746) of the PZP gene in the BRONJ cancer group was significantly identified in the additive trend model analysis. In the cancer group, ARIDS, HEBP1, LTBP1, and PLVAP were identified as candidate genes. In the osteoporosis group, VEGFA, DFFA, and FAM193A genes showed a significant association. No significant genes were identified in the rare-variant analysis pipeline. Biologically accountable functions related to BRONJ occurrence-angiogenesis-related signaling (VEGFA and PLVAP genes), TGF-β signaling (LTBP1 and PZP genes), heme toxicity (HEBP1) and osteoblast maturation (ARIDS)-were shown in candidate genes.ConclusionThis study showed that the candidate causative genes contributing to the development of BRONJ differ according to the BP dose and background disease.

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in light of recent developments in genomic technology and the rapid accumulation of genomic information, a major transition toward precision medicine is anticipated. However, the clinical applications of genomic information remain limited. This lag can be attributed to several complex factors, including the knowledge gap between medical experts and bioinformaticians, the distance between bioinformatics workflows and clinical practice, and the unique characteristics of genomic data, which can make interpretation difficult. Here we present a novel genomic data model that allows for more interactive support in clinical decision-making. Informational modelling was used as a basis to design a communication scheme between sophisticated bioinformatics predictions and the representative data relevant to a clinical decision. This study was conducted by a multidisciplinary working group who carried out clinico-genomic workflow analysis and attribute extraction, through Failure Mode and Effects Analysis (FMEA). Based on those results, a clinical genome data model (cGDM) was developed with 8 entities and 46 attributes. The cGDM integrates reliability-related factors that enable clinicians to access the reliability problem of each individual genetic test result as clinical evidence. The proposed cGDM provides a data-layer infrastructure supporting the intellectual interplay between medical experts and informed decision-making.

Background Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation. Methods Trough(C 0 ) and 1.5-hour blood levels (C 1.5 ) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C 1.5 /C 0 < 1.5 and > 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks. Results Twenty-eight patients showed flat pattern peaks. The mean C 1.5 /C 0 values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change ( P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate ( P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks ( P = 0.019 and P = 0.027, respectively). Conclusion Both of C 1.5 and C 0 should be measured to distinguish the patients showing unique initial absorption. A C 1.5 /C 0 ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

FOLFIRINOX is currently one of the standard chemotherapy regimens for pancreatic cancer patients, but little is known about the factors that can predict a response to it. We performed a study to discover novel DNA damage repair (DDR) gene variants associated with the response to FOLFIRINOX chemotherapy in patients with pancreatic cancer. We queried a cohort of pancreatic cancer patients who received FOLFIRINOX chemotherapy as the first treatment and who had tissue obtained through an endoscopic ultrasound-guided biopsy that was suitable for DNA sequencing. We explored variants of 148 DDR genes based on whole exome sequencing and performed multivariate Cox regression to find genetic variants associated with progression-free survival (PFS). Overall, 103 patients were included. Among 2384 variants of 141 DDR genes, 612 non-synonymous variants of 123 genes were selected for Cox regression analysis. The multivariate Cox model showed that rs2228528 in ERCC6 was significantly associated with improved PFS (hazard ratio 0.54, p = 0.001). The median PFS was significantly longer in patients with rs2228528 genotype AA vs. genotype GA and GG (23.5 vs. 16.2 and 8.6 months; log-rank p < 0.001). This study suggests that rs2228528 in ERCC6 could be a potential predictor of response to FOLFIRINOX chemotherapy in patients with pancreatic cancer.