Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs

MergeReference: A Tool for Merging Reference Panels for HLA Imputation

Recently developed computational methods allow the imputation of human leukocyte antigen (HLA) genes using intergenic single nucleotide polymorphism markers. To improve the imputation accuracy in HLA imputation, it is essential to increase the sample size and the diversity of alleles in the reference panel. Our software, MergeReference, helps achieve this goal by providing a streamlined pipeline for combining multiple reference panels into one

Analysis of differences in human leukocyte antigen between the two wellcome trust case control consortium control datasets

© 2019, Korea Genome Organization.The Wellcome Trust Case Control Consortium (WTCCC) study was a large genome-wide association study that aimed to identify common variants associated with seven diseases. That study combined two control datasets (58C and UK Blood Services) as shared controls. Prior to using the combined controls, the WTCCC performed analyses to show that the genomic content of the control datasets was not significantly different. Recently, the analysis of human leukocyte antigen (HLA) genes has become prevalent due to the development of HLA imputation technology. In this project, we extended the between-control homogeneity analysis of the WTCCC to HLA. We imputed HLA information in the WTCCC control dataset and showed that the HLA content was not significantly different between the two control datasets, suggesting that the combined controls can be used as controls for HLA fine-map-ping analysis based on HLA imputation.Y

Accurate imputation of human leukocyte antigens with CookHLA

The recent development of imputation methods enabled the prediction of human leukocyte antigen (HLA) alleles from intergenic SNP data, allowing studies to fine-map HLA for immune phenotypes. Here we report an accurate HLA imputation method, CookHLA, which has superior imputation accuracy compared to previous methods. CookHLA differs from other approaches in that it locally embeds prediction markers into highly polymorphic exons to account for exonic variability, and in that it adaptively learns the genetic map within MHC from the data to facilitate imputation. Our benchmarking with real datasets shows that our method achieves high imputation accuracy in a wide range of scenarios, including situations where the reference panel is small or ethnically unmatched. Human leukocyte antigen (HLA) genes influence many immune phenotypes, however methods to impute HLA type have been limited in accuracy. Here, the authors present an HLA imputation method, CookHLA, which uses locally embedded prediction markers to adaptively impute HLA genes across a range of scenarios.Y

Efficacy of nano‐particulated, water‐soluble erlotinib against intracranial metastases of EGFR‐mutant lung cancer

Central nervous system (CNS) metastasis is one of the serious complications of epidermal growth factor receptor (EGFR)‐mutant lung cancer, which arises due to poor penetration of the brain–blood barrier by EGFR‐tyrosine kinase inhibitors (EGFR‐TKIs). Although osimertinib, a third‐generation EGFR‐TKI, has efficacy against CNS metastases, further treatment modalities are still needed as some of these lesions do not respond to osimertinib, or undergo progression after an initial response to this drug if radiotherapy has already been conducted. Here, we investigated the efficacy of water‐soluble erlotinib (NUFS‐sErt) against these metastases. This agent was synthesized using a nano‐particulation platform technology utilizing fat and supercritical fluid (NUFS™) to resolve the low solubility problem that typically prevents the creation of injectable forms of EGFR‐TKIs. The average NUFS‐sErt particle size was 236.4 nm, and it showed time‐dependent dissolution in culture media. The effects of NUFS‐sErt were similar to those of conventional erlotinib in terms of inhibiting the proliferation of EGFR‐mutant lung cancer cells and suppressing EGFR signaling. In an intraperitoneal xenograft model of HCC827 cells, intraperitoneal administration of NUFS‐sErt produced a dose‐dependent inhibition of tumor growth and enhanced survival rate. Notably, the injection of NUFS‐sErt into the brain ventricle caused significant tumor growth inhibition in an intracranial xenograft model. Hence, our current findings indicate that NUFS‐sErt is a novel, water‐soluble form of erlotinib that can be administered using intraventricular or intrathecal injections. The target cases would be patients with a progressive CNS metastasis and no other therapeutic options. This drug could also be given intravenously to patients with swallowing difficulties or an inability to ingest due to a medical condition

Amino acid position 37 of HLA-DR beta 1 affects susceptibility to Crohn's disease in Asians

Crohn's disease (CD) and ulcerative colitis (UC) are the major types of chronic inflammatory bowel disease (IBD) characterized by recurring episodes of inflammation of the gastrointestinal tract. Although it is well established that human leukocyte antigen (HLA) is a major risk factor for IBD, it is yet to be determined which HLA alleles or amino acids drive the risks of CD and UC in Asians. To define the roles of HLA for IBD in Asians, we fine-mapped HLA in 12 568 individuals from Korea and Japan (3294 patients with CD, 1522 patients with UC and 7752 controls). We identified that the amino acid position 37 of HLA-DR beta 1 plays a key role in the susceptibility to CD (presence of serine being protective, P = 3.6 x 10(-67), OR = 0.48 [0.45-0.52]). For UC, we confirmed the known association of the haplotype spanning HLA-C*12:02, HLA-B*52:01 and HLA-DRB1*1502 (P = 1.2 x 10(-28), OR = 4.01 [3.14-5.12]).N

Low energy radioactivity BG model in Super-Kamiokande detector from SK-IV data

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Follow-up of GWTC-2 gravitational wave events with neutrinos from the Super-Kamiokande detector

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Combined Pre-Supernova Alert System with Kamland and Super-Kamiokande

International audiencePreceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector is developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance