Assessment of Artificial MiRNA Architectures for Higher Knockdown Efficiencies without the Undesired Effects in Mice.

RNAi-based strategies have been used for hypomorphic analyses. However, there are technical challenges to achieve robust, reproducible knockdown effect. Here we examined the artificial microRNA (amiRNA) architectures that could provide higher knockdown efficiencies. Using transient and stable transfection assays in cells, we found that simple amiRNA-expression cassettes, that did not contain a marker gene (-MG), displayed higher amiRNA expression and more efficient knockdown than those that contained a marker gene (+MG). Further, we tested this phenomenon in vivo, by analyzing amiRNA-expressing mice that were produced by the pronuclear injection-based targeted transgenesis (PITT) method. While we observed significant silencing of the target gene (eGFP) in +MG hemizygous mice, obtaining -MG amiRNA expression mice, even hemizygotes, was difficult and the animals died perinatally. We obtained only mosaic mice having both -MG amiRNA cells and amiRNA low-expression cells but they exhibited growth retardation and cataracts, and they could not transmit the -MG amiRNA allele to the next generation. Furthermore, +MG amiRNA homozygotes could not be obtained. These results suggested that excessive amiRNAs transcribed by -MG expression cassettes cause deleterious effects in mice, and the amiRNA expression level in hemizygous +MG amiRNA mice is near the upper limit, where mice can develop normally. In conclusion, the PITT-(+MG amiRNA) system demonstrated here can generate knockdown mouse models that reliably express highest and tolerable levels of amiRNAs

A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: “leukocyte activation and differentiation”, “pattern-recognition receptor signaling pathway”, and “chemokines and their receptors”

HLA-DPB1*04:01 allele is associated with non-obstructive azoospermia in Japanese patients

Azoospermia is defined by absence of sperm in the semen and can either be caused by obstruction of the seminal tract (obstructive azoospermia) or by defects in spermatogenesis (non-obstructive azoospermia, NOA). Previous studies reported that specific alleles and single nucleotide polymorphisms (SNPs) in the human leukocyte antigen (HLA) region were associated with NOA in East Asians. We attempt to expand upon previous findings by genotyping more HLA genes and to replicate SNP associations by focusing on Japanese NOA patients. HLA typing of six genes (HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1) was done on 355 NOA patients using SSO-Luminex assay while genotyping of two previously reported SNPs (rs498422 and rs3129878) was done on 443 patients and 544 fertile males using TaqMan assay. Association was assessed with Chi squared and logistic regression tests. We found that HLA-DPB1*04:01 [corrected p value, Pc 7.13 9 10-6 ; odds ratio (OR) 2.52], DRB1*13:02 (Pc 4.93 9 10-4 , OR 1.97), DQB1*06:04 (Pc 8.94 9 10-4 , OR 1.91) and rs3129878 (p value 3.98 9 10-4 ; OR 1.32) showed significant association with NOA, however, these loci are in linkage disequilibrium with each other. The conditional logistic regression tests showed that DPB1*04:01 is independently associated with NOA, confirming the involvement of the HLA region in the etiology of NOA in Japanese patients

Multiomics Investigation Revealing the Characteristics of HIV-1-Infected Cells In Vivo

For eradication of HIV-1 infection, it is important to elucidate the detailed features and heterogeneity of HIV-1-infected cells in vivo. To reveal multiple characteristics of HIV-1-producing cells in vivo, we use a hematopoietic-stem-cell-transplanted humanized mouse model infected with GFP-encoding replication-competent HIV-1. We perform multiomics experiments using recently developed technology to identify the features of HIV-1-infected cells. Genome-wide HIV-1 integration-site analysis reveals that productive HIV-1 infection tends to occur in cells with viral integration into transcriptionally active genomic regions. Bulk transcriptome analysis reveals that a high level of viral mRNA is transcribed in HIV-1-infected cells. Moreover, single-cell transcriptome analysis shows the heterogeneity of HIV-1-infected cells, including CXCL13high cells and a subpopulation with low expression of interferon-stimulated genes, which can contribute to efficient viral spread in vivo. Our findings describe multiple characteristics of HIV-1-producing cells in vivo, which could provide clues for the development of an HIV-1 cure

A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2–3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies

Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout

Objective The first ever genome-wide association study (GWAS) of clinically defined gout cases and asymptomatic hyperuricaemia (AHUA) controls was performed to identify novel gout loci that aggravate AHUA into gout. Methods We carried out a GWAS of 945 clinically defined gout cases and 1003 AHUA controls followed by 2 replication studies. In total, 2860 gout cases and 3149 AHUA controls (all Japanese men) were analysed. We also compared the ORs for each locus in the present GWAS (gout vs AHUA) with those in the previous GWAS (gout vs normouricaemia). Results This new approach enabled us to identify two novel gout loci (rs7927466 of CNTN5 and rs9952962 of MIR302F) and one suggestive locus (rs12980365 of ZNF724) at the genome-wide significance level (p<5.0×10– 8). The present study also identified the loci of ABCG2, ALDH2 and SLC2A9. One of them, rs671 of ALDH2, was identified as a gout locus by GWAS for the first time. Comparing ORs for each locus in the present versus the previous GWAS revealed three ‘gout vs AHUA GWAS’-specific loci (CNTN5, MIR302F and ZNF724) to be clearly associated with mechanisms of gout development which distinctly differ from the known gout risk loci that basically elevate serum uric acid level. Conclusions This meta-analysis is the first to reveal the loci associated with crystal-induced inflammation, the last step in gout development that aggravates AHUA into gout. Our findings should help to elucidate the molecular mechanisms of gout development and assist the prevention of gout attacks in high-risk AHUA individuals

Subtype-specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome-wide meta-analyses of clinically defined gout patients

Objectives Genome-wide meta-analyses of clinically defined gout were performed to identify subtype-specific susceptibility loci. Evaluation using selection pressure analysis with these loci was also conducted to investigate genetic risks characteristic of the Japanese population over the last 2000–3000 years. Methods Two genome-wide association studies (GWASs) of 3053 clinically defined gout cases and 4554 controls from Japanese males were performed using the Japonica Array and Illumina Array platforms. About 7.2 million single-nucleotide polymorphisms were meta-analysed after imputation. Patients were then divided into four clinical subtypes (the renal underexcretion type, renal overload type, combined type and normal type), and meta-analyses were conducted in the same manner. Selection pressure analyses using singleton density score were also performed on each subtype. Results In addition to the eight loci we reported previously, two novel loci, PIBF1 and ACSM2B, were identified at a genome-wide significance level (p<5.0×10–8) from a GWAS meta-analysis of all gout patients, and other two novel intergenic loci, CD2-PTGFRN and SLC28A3-NTRK2, from normal type gout patients. Subtype-dependent patterns of Manhattan plots were observed with subtype GWASs of gout patients, indicating that these subtype-specific loci suggest differences in pathophysiology along patients’ gout subtypes. Selection pressure analysis revealed significant enrichment of selection pressure on ABCG2 in addition to ALDH2 loci for all subtypes except for normal type gout. Conclusions Our findings on subtype GWAS meta-analyses and selection pressure analysis of gout will assist elucidation of the subtype-dependent molecular targets and evolutionary involvement among genotype, phenotype and subtype-specific tailor-made medicine/prevention of gout and hyperuricaemia

Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms

Background-Intracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co-occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs. Methods and Results-We performed a mega-analysis of 1000 Genomes Project-imputed genome-wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA-, AAA-, and TAA-associated SNPs and tested these scores for association to case-control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium-score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single-nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]= 1.11; P=4.1 x 10(-5)) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1 x 10(-3)). Conclusions-Although there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication.Peer reviewe