腫瘍内ストレス環境への適応応答ならびにその遺伝子発現ネットワークに関する研究

学位の種別: 論文博士審査委員会委員 : （主査）東京大学教授 菅野 純夫, 東京大学教授 松田 浩一, 東京大学教授 古川 洋一, 東京大学客員教授 冨田 章弘, 東京大学准教授 宮田 完二郎University of Tokyo(東京大学

Polygenic architecture informs potential vulnerability to drug-induced liver injury

Drug-Induced-Liver-Injury (DILI) is a leading cause of termination in drug development programs and removal of drugs from the market, and this is partially due to the inability to identify patients who are at risk1. Here, we developed a polygenic risk score (PRS) for DILI by aggregating effects of numerous genome-wide loci identified from previous large-scale genome-wide association studies (GWAS)2. The PRS predicted the susceptibility to DILI in patients treated with fasiglifam, amoxicillin-clavulanate or flucloxacillin, and in primary hepatocytes and stem cell-derived organoids from multiple donors treated with over 10 different drugs. Pathway analysis highlighted processes previously implicated in DILI, including unfolded protein responses and oxidative stress. In silico screening identified compounds that elicit transcriptomic signatures present in hepatocytes from individuals with elevated PRS, supporting mechanistic links and suggesting a novel screen for safety of new drug candidates. This genetic-, cellular-, organoid- and human-scale evidence underscored the polygenic architecture underlying DILI vulnerability at the level of hepatocytes, thus facilitating future mechanistic studies. Moreover, the proposed “polygenicity-in-a-dish” strategy might potentially inform designs of safer, more efficient, and robust clinical trials

Genetic Risk Score for Intracranial Aneurysms:Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

BACKGROUND: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. METHODS: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. RESULTS: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=-4.82×10(-3) per year [95% CI, -6.49×10(-3) to -3.14×10(-3)]; P=1.82×10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). CONCLUSIONS: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH

Stroke

BACKGROUND: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. METHODS: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. RESULTS: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=-4.82×10(-3) per year [95% CI, -6.49×10(-3) to -3.14×10(-3)]; P=1.82×10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). CONCLUSIONS: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH

Evidence of causality of low body mass index on risk of adolescent idiopathic scoliosis: a Mendelian randomization study

IntroductionAdolescent idiopathic scoliosis (AIS) is a disorder with a three-dimensional spinal deformity and is a common disease affecting 1-5% of adolescents. AIS is also known as a complex disease involved in environmental and genetic factors. A relation between AIS and body mass index (BMI) has been epidemiologically and genetically suggested. However, the causal relationship between AIS and BMI remains to be elucidated.Material and methodsMendelian randomization (MR) analysis was performed using summary statistics from genome-wide association studies (GWASs) of AIS (Japanese cohort, 5,327 cases, 73,884 controls; US cohort: 1,468 cases, 20,158 controls) and BMI (Biobank Japan: 173430 individual; meta-analysis of genetic investigation of anthropometric traits and UK Biobank: 806334 individuals; European Children cohort: 39620 individuals; Population Architecture using Genomics and Epidemiology: 49335 individuals). In MR analyses evaluating the effect of BMI on AIS, the association between BMI and AIS summary statistics was evaluated using the inverse-variance weighted (IVW) method, weighted median method, and Egger regression (MR-Egger) methods in Japanese.ResultsSignificant causality of genetically decreased BMI on risk of AIS was estimated: IVW method (Estimate (beta) [SE] = -0.56 [0.16], p = 1.8 × 10-3), weighted median method (beta = -0.56 [0.18], p = 8.5 × 10-3) and MR-Egger method (beta = -1.50 [0.43], p = 4.7 × 10-3), respectively. Consistent results were also observed when using the US AIS summary statistic in three MR methods; however, no significant causality was observed when evaluating the effect of AIS on BMI.ConclusionsOur Mendelian randomization analysis using large studies of AIS and GWAS for BMI summary statistics revealed that genetic variants contributing to low BMI have a causal effect on the onset of AIS. This result was consistent with those of epidemiological studies and would contribute to the early detection of AIS

Contribution of Common Genetic Variants to Risk of Early-Onset Ischemic Stroke

Background and Objectives Current genome-wide association studies of ischemic stroke have focused primarily on late-onset disease. As a complement to these studies, we sought to identify the contribution of common genetic variants to risk of early-onset ischemic stroke. Methods We performed a meta-analysis of genome-wide association studies of early-onset stroke (EOS), ages 18-59 years, using individual-level data or summary statistics in 16,730 cases and 599,237 nonstroke controls obtained across 48 different studies. We further compared effect sizes at associated loci between EOS and late-onset stroke (LOS) and compared polygenic risk scores (PRS) for venous thromboembolism (VTE) between EOS and LOS. Results We observed genome-wide significant associations of EOS with 2 variants in ABO, a known stroke locus. These variants tag blood subgroups O1 and A1, and the effect sizes of both variants were significantly larger in EOS compared with LOS. The odds ratio (OR) for rs529565, tagging O1, was 0.88 (95% confidence interval [CI]: 0.85-0.91) in EOS vs 0.96 (95% CI: 0.92-1.00) in LOS, and the OR for rs635634, tagging A1, was 1.16 (1.11-1.21) for EOS vs 1.05 (0.99-1.11) in LOS; p-values for interaction = 0.001 and 0.005, respectively. Using PRSs, we observed that greater genetic risk for VTE, another prothrombotic condition, was more strongly associated with EOS compared with LOS (p = 0.008). Discussion The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with EOS than with LOS, supporting a stronger role of prothrombotic factors in EOS.Peer reviewe

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Human iPSC-Derived Posterior Gut Progenitors Are Expandable and Capable of Forming Gut and Liver Organoids

Summary: Early endoderm progenitors naturally possess robust propagating potential to develop a majority of meter-long gastrointestinal tracts and are therefore considered as a promising source for therapy. Here, we demonstrated the reproducible generation of human CDX2+ posterior gut endoderm cells (PGECs) from five induced pluripotent stem cell clones by manipulating FGF, TGF, and WNT signaling. Transcriptome analysis suggested that putative PGECs harbored an intermediate signature profile between definitive endoderm and organ-specific endoderm. We found that combinatorial EGF, VEGF, FGF2, Chir99021, and A83-01 treatments selectively amplify storable PGECs up to 1021 cell scale without any gene transduction or feeder use. PGECs, compared with induced pluripotent stem cells, showed stable differentiation propensity into multiple endodermal lineages without teratoma formation. Furthermore, transplantation of PGEC-derived liver bud organoids showed therapeutic potential against fulminant liver failure. Together, the robustly amplified PGECs may be a promising cellular source for endoderm-derived organoids in studying human development, modeling disease, and, ultimately, therapy. : In this article, Takebe, Taniguchi, and colleagues derived a unique population of CDX2+ posterior endoderm progenitors (PGECs) from human pluripotent stem cells that are highly expandable and storable in a chemically defined condition. CDX2+ endoderm progenitors can form multiple endodermal organoids. Transplantation of human liver bud organoids from robustly propagated PGECs rescued lethal liver failure of immunodeficient mice. Keywords: progenitors, posterior gut endoderm cells, organoid, liver bud, transplant, human, pluripotent stem cells, iPSC, CDX2, intestin