DOCK2 is involved in the host genetics and biology of severe COVID-19.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1-5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

Impaired tumor immune response in metastatic tumors is a selective pressure for neutral evolution in CRC cases.

A Darwinian evolutionary shift occurs early in the neutral evolution of advanced colorectal carcinoma (CRC), and copy number aberrations (CNA) are essential in the transition from adenoma to carcinoma. In light of this primary evolution, we investigated the evolutionary principles of the genome that foster postoperative recurrence of CRC. CNA and neoantigens (NAG) were compared between early primary tumors with recurrence (CRCR) and early primary tumors without recurrence (precancerous and early; PCRC). We compared CNA, single nucleotide variance (SNV), RNA sequences, and T-cell receptor (TCR) repertoire between 9 primary and 10 metastatic sites from 10 CRCR cases. We found that NAG in primary sites were fewer in CRCR than in PCRC, while the arm level CNA were significantly higher in primary sites in CRCR than in PCRC. Further, a comparison of genomic aberrations of primary and metastatic conditions revealed no significant differences in CNA. The driver mutations in recurrence were the trunk of the evolutionary phylogenic tree from primary sites to recurrence sites. Notably, PD-1 and TIM3, T cell exhaustion-related molecules of the tumor immune response, were abundantly expressed in metastatic sites compared to primary sites along with the increased number of CD8 expressing cells. The postoperative recurrence-free survival period was only significantly associated with the NAG levels and TCR repertoire diversity in metastatic sites. Therefore, CNA with diminished NAG and diverse TCR repertoire in pre-metastatic sites may determine postoperative recurrence of CRC.

Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers.

BACKGROUND: Intratumor heterogeneity (ITH) in microsatellite instability-high (MSI-H) colorectal cancer (CRC) has been poorly studied. We aimed to clarify how the ITH of MSI-H CRCs is generated in cancer evolution and how immune selective pressure affects ITH. METHODS: We reanalyzed public whole-exome sequencing data on 246 MSI-H CRCs. In addition, we performed a multi-region analysis from 6 MSI-H CRCs. To verify the process of subclonal immune escape accumulation, a novel computational model of cancer evolution under immune pressure was developed. RESULTS: Our analysis presented the enrichment of functional genomic alterations in antigen-presentation machinery (APM). Associative analysis of neoantigens indicated the generation of immune escape mechanisms via HLA alterations. Multiregion analysis revealed the clonal acquisition of driver mutations and subclonal accumulation of APM defects in MSI-H CRCs. Examination of variant allele frequencies demonstrated that subclonal mutations tend to be subjected to selective sweep. Computational simulations of tumour progression with the interaction of immune cells successfully verified the subclonal accumulation of immune escape mutations and suggested the efficacy of early initiation of an immune checkpoint inhibitor (ICI) -based treatment. CONCLUSIONS: Our results demonstrate the heterogeneous acquisition of immune escape mechanisms in MSI-H CRCs by Darwinian selection, providing novel insights into ICI-based treatment strategies.

Convergent genomic diversity and novel BCAA metabolism in intrahepatic cholangiocarcinoma.

BACKGROUND: Driver alterations may represent novel candidates for driver gene-guided therapy; however, intrahepatic cholangiocarcinoma (ICC) with multiple genomic aberrations makes them intractable. Therefore, the pathogenesis and metabolic changes of ICC need to be understood to develop new treatment strategies. We aimed to unravel the evolution of ICC and identify ICC-specific metabolic characteristics to investigate the metabolic pathway associated with ICC development using multiregional sampling to encompass the intra- and inter-tumoral heterogeneity. METHODS: We performed the genomic, transcriptomic, proteomic and metabolomic analysis of 39-77 ICC tumour samples and eleven normal samples. Further, we analysed their cell proliferation and viability. RESULTS: We demonstrated that intra-tumoral heterogeneity of ICCs with distinct driver genes per case exhibited neutral evolution, regardless of their tumour stage. Upregulation of BCAT1 and BCAT2 indicated the involvement of 'Val Leu Ile degradation pathway'. ICCs exhibit the accumulation of ubiquitous metabolites, such as branched-chain amino acids including valine, leucine, and isoleucine, to negatively affect cancer prognosis. We revealed that this metabolic pathway was almost ubiquitously altered in all cases with genomic diversity and might play important roles in tumour progression and overall survival. CONCLUSIONS: We propose a novel ICC onco-metabolic pathway that could enable the development of new therapeutic interventions.

Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types.

Microsatellites are repeats of 1- to 6-bp units, and approximately 10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2717 whole genomes of pan-cancer samples across 21 tissue types. First, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with a higher proportion of mutated microsatellite (≥0.03), which we defined as microsatellite instability (MSI) cancers of genome-wide level. Next, we found 20 highly mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of microsatellites. Last, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impacts than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

Protease-digested egg-white products induce oral tolerance in mice but elicit little IgE production upon epicutaneous exposure.

BACKGROUND: Early food introduction induces tolerance, but epicutaneous exposure, especially via eczema lesions, promotes IgE sensitization. Aiming for safe and effective primary prevention of egg allergy, we examined several protease-digested egg-white (EW) products for three properties: 1) induction of oral tolerance that prevents IgE sensitization, 2) weak IgE binding that can prevent allergic reactions even in IgE-sensitized mice, and 3) minimal epicutaneous IgE sensitization even when in contact with inflamed skin. METHODS: Heated EW was digested with several proteases under optimal conditions. First, three-week-old BALB/c female mice were intragastrically administered EW or each protease-digested EW product, followed by intraperitoneal ovalbumin (OVA) or ovomucoid (OVM) injection with alum. Serum OVA- and OVM-specific IgE titers were measured. Second, six-week-old mice were sensitized with OVA/OVM, and the rectal temperature was measured after intraperitoneal administration of EW or each protease-digested EW. Third, EW or each protease-digested EW product was applied to the tape-stripped skin for 3 days/week for 3 weeks. Serum OVA- and OVM-specific IgE titers were measured. RESULTS: Orally administered pepsin-digested EW product (PDEW) and Thermoase PC10F-digested EW product (TDEW) significantly suppressed OVA-/OVM-specific IgE production. Neither product elicited a body temperature decline (anaphylaxis) in OVA-/OVM-sensitized mice. Serum OVA-/OVM-specific IgE levels were significantly lower in mice epicutaneously exposed to PDEW or TDEW than in EW-exposed mice. CONCLUSIONS: Two protease-digested EWs showed potential as optimal EW products for early introduction for primary prevention of egg allergy.

Neoantimon: a multifunctional R package for identification of tumor-specific neoantigens.

SUMMARY: It is known that some mutant peptides, such as those resulting from missense mutations and frameshift insertions, can bind to the major histocompatibility complex and be presented to antitumor T cells on the surface of a tumor cell. These peptides are termed neoantigen, and it is important to understand this process for cancer immunotherapy. Here, we introduce an R package termed Neoantimon that can predict a list of potential neoantigens from a variety of mutations, which include not only somatic point mutations but insertions, deletions and structural variants. Beyond the existing applications, Neoantimon is capable of attaching and reflecting several additional information, e.g. wild-type binding capability, allele specific RNA expression levels, single nucleotide polymorphism information and combinations of mutations to filter out infeasible peptides as neoantigen. AVAILABILITY AND IMPLEMENTATION: The R package is available at http://github/hase62/Neoantimon.

Tet DNA demethylase is required for plasma cell differentiation by controlling expression levels of IRF4.

Antibodies produced by plasma cells are critical for protection from infection. It has been demonstrated that global epigenetic modification, such as changes in DNA methylation, occurs during differentiation of plasma cells from B cells. However, the precise mechanisms by which DNA methylation controls plasma cell differentiation are not fully understood. We examined the effect of deficiency of DNA demethylases, Tet2 and Tet3, on B-cell activation and plasma cell differentiation, by generating conditional Tet2/3 double-KO (Tet dKO) B cells. We found that Tet dKO B cells failed to differentiate into plasma cells upon immunization with antigens. Tet dKO B cells proliferated normally and were capable of generating cells with IRF4int, but not with IRF4hi, the majority of which were CD138+ plasma cells. IRF4 overexpression rescued the defect of Tet dKO B cells in plasma cell differentiation, suggesting that Tet2/3-dependent high IRF4 expression is required for plasma cell differentiation. We identified CpG sites in the Irf4 locus that were demethylated specifically in plasma cells and in a Tet2/3-dependent manner. Our results suggest that Tet2/3-dependent demethylation of these CpG sites is dispensable for initial IRF4 expression but is essential for high IRF4 expression which is prerequisite for plasma cell differentiation.

Metagenomic profiling of gut microbiome in early chronic kidney disease.

BACKGROUND: The relationship between chronic kidney disease (CKD) and the gut microbiome, which interact through chronic inflammation, uraemic toxin production and immune response regulation, has gained interest in the development of CKD therapies. However, reports using shotgun metagenomic analysis of the gut microbiome are scarce, especially for early CKD. Here we characterized gut microbiome differences between non-CKD participants and ones with early CKD using metagenomic sequencing. METHODS: In total, 74 non-CKD participants and 37 participants with early CKD were included based on propensity score matching, controlling for various factors including dietary intake. Stool samples were collected from participants and subjected to shotgun sequencing. Bacterial and pathway abundances were profiled at the species level with MetaPhlAn2 and HUMAnN2, respectively, and overall microbiome differences were determined using Bray-Curtis dissimilarities. Diabetic and non-diabetic populations were analysed separately. RESULTS: For diabetic and non-diabetic participants, the mean estimated glomerular filtration rates of the CKD group were 53.71 [standard deviation (SD) 3.87] and 53.72 (SD 4.44), whereas those of the non-CKD group were 72.63 (SD 7.72) and 76.10 (SD 9.84), respectively. Alpha and beta diversities were not significantly different between groups. Based on taxonomic analysis, butyrate-producing species Roseburia inulinivorans, Ruminococcus torques and Ruminococcus lactaris were more abundant in the non-CKD group, whereas Bacteroides caccae and Bacteroides coprocora were more abundant in the non-diabetic CKD group. CONCLUSIONS: Although gut microbiome changes in individuals with early CKD were subtle, the results suggest that changes related to producing short-chain fatty acids can already be observed in early CKD.

Mechanisms of carnosine-induced activation of neuronal cells.

Carnosine (ß-Ala-l-His), an imidazole dipeptide, is known to have many functions. Recently, we demonstrated in a double-blind randomized controlled trial that carnosine is capable of preserving cognitive function in elderly people. In the current study, we assessed the ability of carnosine to activate the brain, and we tried to clarify the molecular mechanisms behind this activation. Our results demonstrate that carnosine permeates the blood brain barrier and activates glial cells within the brain, causing them to secrete neurotrophins, including BDNF and NGF. These results point to a novel mechanism of carnosine-induced neuronal activation. Our results suggest that carnosine should be recognized as a functional food factor that helps achieve anti-brain aging.

AP-SKAT: highly-efficient genome-wide rare variant association test.

BACKGROUND: Genome-wide association studies have revealed associations between single-nucleotide polymorphisms (SNPs) and phenotypes such as disease symptoms and drug tolerance. To address the small sample size for rare variants, association studies tend to group gene or pathway level variants and evaluate the effect on the set of variants. One of such strategies, known as the sequential kernel association test (SKAT), is a widely used collapsing method. However, the reported p-values from SKAT tend to be biased because the asymptotic property of the statistic is used to calculate the p-value. Although this bias can be corrected by applying permutation procedures for the test statistics, the computational cost of obtaining p-values with high resolution is prohibitive. RESULTS: To address this problem, we devise an adaptive SKAT procedure termed AP-SKAT that efficiently classifies significant SNP sets and ranks them according to the permuted p-values. Our procedure adaptively stops the permutation test when the significance level is outside some confidence interval of the estimated p-value for a binomial distribution. To evaluate the performance, we first compare the power and sample size calculation and the type I error rates estimate of SKAT, SKAT-O, and the proposed procedure using genotype data in the SKAT R package and from 1000 Genome Project. Through computational experiments using whole genome sequencing and SNP array data, we show that our proposed procedure is highly efficient and has comparable accuracy to the standard procedure. CONCLUSIONS: For several types of genetic data, the developed procedure could achieve competitive power and sample size under small and large sample size conditions with controlling considerable type I error rates, and estimate p-values of significant SNP sets that are consistent with those estimated by the standard permutation test within a realistic time. This demonstrates that the procedure is sufficiently powerful for recent whole genome sequencing and SNP array data with increasing numbers of phenotypes. Additionally, this procedure can be used in other association tests by employing alternative methods to calculate the statistics.

Short tandem repeat number estimation from paired-end reads for multiple individuals by considering coalescent tree.

BACKGROUND: Two types of approaches are mainly considered for the repeat number estimation in short tandem repeat (STR) regions from high-throughput sequencing data: approaches directly counting repeat patterns included in sequence reads spanning the region and approaches based on detecting the difference between the insert size inferred from aligned paired-end reads and the actual insert size. Although the accuracy of repeat numbers estimated with the former approaches is high, the size of target STR regions is limited to the length of sequence reads. On the other hand, the latter approaches can handle STR regions longer than the length of sequence reads. However, repeat numbers estimated with the latter approaches is less accurate than those with the former approaches. RESULTS: We proposed a new statistical model named coalescentSTR that estimates repeat numbers from paired-end read distances for multiple individuals simultaneously by connecting the read generative model for each individual with their genealogy. In the model, the genealogy is represented by handling coalescent trees as hidden variables, and the summation of the hidden variables is taken on coalescent trees sampled based on phased genotypes located around a target STR region with Markov chain Monte Carlo. In the sampled coalescent trees, repeat number information from insert size data is propagated, and more accurate estimation of repeat numbers is expected for STR regions longer than the length of sequence reads. For finding the repeat numbers maximizing the likelihood of the model on the estimation of repeat numbers, we proposed a state-of-the-art belief propagation algorithm on sampled coalescent trees. CONCLUSIONS: We verified the effectiveness of the proposed approach from the comparison with existing methods by using simulation datasets and real whole genome and whole exome data for HapMap individuals analyzed in the 1000 Genomes Project.

Generating a transgenic mouse line stably expressing human MHC surface antigen from a HAC carrying multiple genomic BACs.

The human artificial chromosome (HAC) vector is a promising tool to improve the problematic suppression and position effects of transgene expression frequently seen in transgenic cells and animals produced by conventional plasmid or viral vectors. We generated transgenic mice maintaining a single HAC vector carrying two genomic bacterial artificial chromosomes (BACs) from human HLA-DR loci (DRA and DRB1). Both transgenes on the HAC in transgenic mice exhibited tissue-specific expression in kidney, liver, lung, spleen, lymph node, bone marrow, and thymus cells in RT-PCR analysis. Stable functional expression of a cell surface HLA-DR marker from both transgenes, DRA and DRB1 on the HAC, was detected by flow cytometric analysis of splenocytes and maintained through at least eight filial generations. These results indicate that the de novo HAC system can allow us to manipulate multiple BAC transgenes with coordinated expression as a surface antigen through the generation of transgenic animals.

Membrane-bound human SCF/KL promotes in vivo human hematopoietic engraftment and myeloid differentiation.

In recent years, advances in the humanized mouse system have led to significantly increased levels of human hematopoietic stem cell (HSC) engraftment. The remaining limitations in human HSC engraftment and function include lymphoid-skewed differentiation and inefficient myeloid development in the recipients. Limited human HSC function may partially be attributed to the inability of the host mouse microenvironment to provide sufficient support to human hematopoiesis. To address this problem, we created membrane-bound human stem cell factor (SCF)/KIT ligand (KL)-expressing NOD/SCID/IL2rgKO (hSCF Tg NSG) mice. hSCF Tg NSG recipients of human HSCs showed higher levels of both human CD45(+) cell engraftment and human CD45(+)CD33(+) myeloid development compared with NSG recipients. Expression of hSCF/hKL accelerated the differentiation of the human granulocyte lineage cells in the recipient bone marrow. Human mast cells were identified in bone marrow, spleen, and gastrointestinal tissues of the hSCF Tg NSG recipients. This novel in vivo humanized mouse model demonstrates the essential role of membrane-bound hSCF in human myeloid development. Moreover, the hSCF Tg NSG humanized recipients may facilitate investigation of in vivo differentiation, migration, function, and pathology of human mast cells.

Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study.

BACKGROUND: Traditional surveillance systems rely on routine collection of data. The inherent delay in retrieval and analysis of data leads to reactionary rather than preventive measures. Forecasting and analysis of behavior-related data can supplement the information from traditional surveillance systems. OBJECTIVE: We assessed the use of behavioral indicators, such as the general public's interest in the risk of contracting SARS-CoV-2 and changes in their mobility, in building a vector autoregression model for forecasting and analysis of the relationships of these indicators with the number of COVID-19 cases in the National Capital Region. METHODS: An etiologic, time-trend, ecologic study design was used to forecast the daily number of cases in 3 periods during the resurgence of COVID-19. We determined the lag length by combining knowledge on the epidemiology of SARS-CoV-2 and information criteria measures. We fitted 2 models to the training data set and computed their out-of-sample forecasts. Model 1 contains changes in mobility and number of cases with a dummy variable for the day of the week, while model 2 also includes the general public's interest. The forecast accuracy of the models was compared using mean absolute percentage error. Granger causality test was performed to determine whether changes in mobility and public's interest improved the prediction of cases. We tested the assumptions of the model through the Augmented Dickey-Fuller test, Lagrange multiplier test, and assessment of the moduli of eigenvalues. RESULTS: A vector autoregression (8) model was fitted to the training data as the information criteria measures suggest the appropriateness of 8. Both models generated forecasts with similar trends to the actual number of cases during the forecast period of August 11-18 and September 15-22. However, the difference in the performance of the 2 models became substantial from January 28 to February 4, as the accuracy of model 2 remained within reasonable limits (mean absolute percentage error [MAPE]=21.4%) while model 1 became inaccurate (MAPE=74.2%). The results of the Granger causality test suggest that the relationship of public interest with number of cases changed over time. During the forecast period of August 11-18, only change in mobility (P=.002) improved the forecasting of cases, while public interest was also found to Granger-cause the number of cases during September 15-22 (P=.001) and January 28 to February 4 (P=.003). CONCLUSIONS: To the best of our knowledge, this is the first study that forecasted the number of COVID-19 cases and explored the relationship of behavioral indicators with the number of COVID-19 cases in the Philippines. The resemblance of the forecasts from model 2 with the actual data suggests its potential in providing information about future contingencies. Granger causality also implies the importance of examining changes in mobility and public interest for surveillance purposes.

The current status of emergency departments in secondary emergency medical institutions in Japan: a questionnaire survey.

BACKGROUND: While emergency medicine (ER)-based emergency care is prevalent in many countries, in Japan, the "department-specific emergency care model" and the "emergency center model" are mainstream. We hypothesized that many secondary emergency medical institutions in Japan have inadequate systems. Using a questionnaire, we investigated the status of and problems in the emergency medical services system in secondary emergency medical institutions in Japan. Until date, there has not been an exhaustive survey of emergency facilities on a countrywide scale. The main objective of this study was to investigate problems in the Japanese emergency medical services system and thereby improve optimal care for emergency patients. RESULTS: A nationwide questionnaire survey involving 4063 facilities (all government-approved emergency medical facilities certified by prefectural governors) in Japan was conducted. Of the facilities that responded, all secondary emergency facilities were included in the analysis. Responses from 1289 facilities without a tertiary emergency medical care center were analyzed. Among them, 61% (792/1289) had ≤ 199 beds, and 8% were emergency department specialty training program core facilities. Moreover, 42% had an annual patient acceptance number of ≤ 500, 19% did not calculate the number of acceptances, 29% had an acceptance rate of ≥ 81%, and 25% had an acceptance rate of 61-80%. Pregnant women (63%) and children (56%) were the major types of patients that affected the acceptance rate. Factors affecting facilities with a response rate of 81% or higher were "hospitals designated for residency training" and "facilities making some efforts to improve the quality of emergency care and the emergency medical system" (logistic analysis, P < .001). CONCLUSION: Relevant authorities and core regional facilities should consider and implement specific measures for regions and hospitals with a shortage of emergency medicine specialists and physicians (e.g., development of ER-based emergency medicine and provision of education). This study may lead to further improvement in the optimal care of emergency patients through the nationwide establishment of the proposed measures as well as through grouping and integrating the structures and systems in emergency and other medical facilities.

Estimating gene-level false discovery probability improves eQTL statistical fine-mapping precision.

Statistical fine-mapping prioritizes putative causal variants from a large number of candidate variants, and is widely used in expression quantitative loci (eQTLs) studies. In eQTL fine-mapping, the existence of causal variants for gene expression is not guaranteed, since the genetic heritability of gene expression explained by nearby (cis-) variants is limited. Here we introduce a refined fine-mapping algorithm, named Knockoff-Finemap combination (KFc). KFc estimates the probability that the causal variant(s) exist in the cis-window of a gene through construction of knockoff genotypes (i.e. a set of synthetic genotypes that resembles the original genotypes), and uses it to adjust the posterior inclusion probabilities (PIPs). Utilizing simulated gene expression data, we show that KFc results in calibrated PIP distribution with improved precision. When applied to gene expression data of 465 genotyped samples from the Japan COVID-19 Task Force (JCTF), KFc resulted in significant enrichment of a functional score as well as reporter assay hits in the top PIP bins. When combined with functional priors derived from an external fine-mapping study (GTEx), KFc resulted in a significantly higher proportion of hematopoietic trait putative causal variants in the top PIP bins. Our work presents improvements in the precision of a major fine-mapping algorithm.

Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population.

Amylase genes reside in a structurally complex locus, and their copy numbers vary greatly, and several studies have reported their association with obesity. The mechanism of this effect was partially explained by changes in the oral and gut microbiome compositions; however, a detailed mechanism has been unclarified. In this study, we showed their association with diabetes in addition to obesity, and further discovered a plausible mechanism of this association based on the function of commensal bacteria. First, we confirmed that the amylase copy number in the population tends to be larger than that reported in other studies and that there is a positive association between obesity and diabetes (p = 1.89E-2 and 8.63E-3). Second, we identified that relative abundance of some genus level microbiome, Capnocytophaga, Dialister, and previously reported bacteria, were significantly associated with amylase copy numbers. Finally, through functional gene-set analysis using shotgun sequencing, we observed that the abundance of genes in the Acarbose pathway in the gut microbiome was significantly decreased with an increase in the amylase copy number (p-value = 5.80E-4). Our findings can partly explain the mechanism underlying obesity and diabetes in populations with high amylase copy numbers.

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force.

Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.

Establishment of a novel method of screening anti-allergic lactic acid bacteria.

In this study, we attempted to establish a novel method of screening anti-allergic lactic acid bacteria (LAB). We cloned the human histidine decarboxylase (HDC) promoter into the promoter-less pPhi-Yellow-RPL-dest1 vector and established KU812F cells transduced with this vector (pHDCp-Phi-Yellow/KU812F). After adding LAB to these cells, the change in fluorescence intensity was monitored by flow cytometry. After screening, we identified several LAB strains that downregulated HDC promoter activity. Functional analysis of these LAB strains indicated that two LAB strains inhibited histamine release from KU812F cells, indicating that this assay system can be used to screen for anti-allergic LAB in a high-throughput manner.