Factors Associated With the Prevalence of Irritable Bowel Syndrome: The Miyagi Part of the Tohoku Medical Megabank Project Community-based Cohort Study.

Background/Aims: The objective of this research is to examine factors related to irritable bowel syndrome (IBS) prevalence in a large population-based study. Methods: A cross-sectional study was conducted with participants in the Miyagi part of the Tohoku Medical Megabank Project Community-Based cohort study who completed the Rome II Modular Questionnaire. Multivariate odds ratios (ORs) for the presence of IBS and 95% confidence intervals (95% CIs) for the reference group were calculated for each factor. Additionally, a stratified analysis was performed by sex and age group (20-49 years, 50-64 years, and ≥ 65 years). Results: Among 16 252 participants, 3025 (18.6%) had IBS, comprising 750 men (15.5%) and 2275 women (19.9%). Multivariate ORs for the presence of IBS decreased significantly with each year of age (OR, 0.98; 95% CI, 0.98-0.99). Moreover, compared with the reference group, ORs for the presence of IBS were significantly higher in individuals whose home was partially damaged by the Great East Japan Earthquake, those with < 16 years of education, those who spent less time walking, those with high perceived stress (1.77, 1.57-2.01), those with high psychological distress (1.58, 1.36-1.82), and those with high symptoms of depression (1.76, 1.60-1.94). In stratified analyses, a significant relationship was found between psychological factors and IBS prevalence in all sex and age groups. Conclusions: This large cross-sectional population-based cohort study identified several factors associated with IBS prevalence. Psychological factors were significantly associated with IBS prevalence across all age groups and sexes.

Low Hemoglobin Level and Elevated Inflammatory Hematological Ratios Associated With Depression and Sleep Disturbance.

BACKGROUND: The relationship between blood cell profiles, including hemoglobin (Hb) levels and inflammatory hematological ratios, and mental health problems currently remains unclear. AIM: This study aimed to investigate the relationship between blood cell profiles and mental health issues, including depressive state and sleep disturbance, while adjusting for potential demographic confounders. METHODOLOGY: This retrospective, cross-sectional, observational study used a population-based medical database from the Tohoku Medical Megabank Project with more than 60,000 volunteers. Data on age, sex, daily tobacco use, body mass index, and self-reported scores on the Kessler Psychological Distress Scale (K6), Athens Insomnia Scale (AIS), and the Center for Epidemiologic Studies Depression Scale (CES-D) were collected. RESULTS: A total of 62,796 volunteers (23,663 males and 39,133 females), aged ≥20 years at the time of the blood test, agreed to participate in this study. Among the evaluated blood cell profiles, Hb, hematocrit, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were significantly correlated with the K6, AIS, and CES-D scores, with strong statistical significance (p<0.0001 for all) in bivariate correlation analyses. A significant adjusted odds ratio (aOR) of the Hb level for elevated CES-D scores (aOR=0.965 [95% CI: 0.949-0.981], p<0.0001) was confirmed after adjusting for demographic data and daily tobacco use using a logistic regression model. Sensitivity analyses revealed that these associations existed in both males and females but were more prominent in the former. In male participants, a low Hb level was significantly associated with an elevated AIS score. The evaluated inflammatory hematological ratios, including NLR, PLR, and monocyte-to-lymphocyte ratio (MLR), also showed significant aORs with the K6, AIS, and CES-D scores after adjusting for demographic background. CONCLUSION: Low Hb levels and elevated inflammatory hematological ratios (NLR, MLR, and PLR) were associated with depressive state and sleep disturbances in the general population.

Development of phenotyping algorithms for hypertensive disorders of pregnancy (HDP) and their application in more than 22,000 pregnant women.

Recently, many phenotyping algorithms for high-throughput cohort identification have been developed. Prospective genome cohort studies are critical resources for precision medicine, but there are many hurdles in the precise cohort identification. Consequently, it is important to develop phenotyping algorithms for cohort data collection. Hypertensive disorders of pregnancy (HDP) is a leading cause of maternal morbidity and mortality. In this study, we developed, applied, and validated rule-based phenotyping algorithms of HDP. Two phenotyping algorithms, algorithms 1 and 2, were developed according to American and Japanese guidelines, and applied into 22,452 pregnant women in the Birth and Three-Generation Cohort Study of the Tohoku Medical Megabank project. To precise cohort identification, we analyzed both structured data (e.g., laboratory and physiological tests) and unstructured clinical notes. The identified subtypes of HDP were validated against reference standards. Algorithms 1 and 2 identified 7.93% and 8.08% of the subjects as having HDP, respectively, along with their HDP subtypes. Our algorithms were high performing with high positive predictive values (0.96 and 0.90 for algorithms 1 and 2, respectively). Overcoming the hurdle of precise cohort identification from large-scale cohort data collection, we achieved both developed and implemented phenotyping algorithms, and precisely identified HDP patients and their subtypes from large-scale cohort data collection.

Progress report of the Tohoku Medical Megabank Community-Based Cohort Study: Study profile of the repeated center-based survey during second period in Miyagi Prefecture.

BACKGROUND: The purpose of this study was to report the basic profile of the Miyagi Prefecture part of a repeated center-based survey during the second period (2nd period survey) of the Tohoku Medical Megabank Community-Based Cohort Study (TMM CommCohort Study), as well as the participants' characteristics based on their participation type in the baseline survey. METHODS: The 2nd period survey, conducted from June 2017 to March 2021, included participants of the TMM CommCohort Study (May 2013 to March 2016). In addition to the questionnaire, blood, urine, and physiological function tests were performed during the 2nd period survey. There were three main ways of participation in the baseline survey: Type 1, Type 1 additional, or Type 2 survey. The 2nd period survey was conducted in the same manner as the Type 2 survey, which was based on the community support center (CSC). RESULTS: In Miyagi Prefecture, 29,383 (57.7%) of 50,967 participants participated in the 2nd period survey. The participation rate among individuals who had visited the CSC was approximately 80%. Although some factors differed depending on the participation type in the baseline survey, the 2nd period survey respondents in the Type 1 and Type 2 survey groups at baseline had similar traits. CONCLUSIONS: The 2nd period survey of the TMM CommCohort Study provided detailed follow-up information. Following up on the health conditions of the participants will clarify the long-term effects of disasters and contribute to personalized prevention.

Relationships of Fat Mass Index and Fat-Free Mass Index with Low-Density Lipoprotein Cholesterol Levels in the Tohoku Medical Megabank Community-Based Cohort Study.

AIMS: Although fat mass (FM) and fat-free mass (FFM) have an impact on lipid metabolism, the relationship between different body composition phenotypes and lipid profiles is still unclear. By dividing the FM and FFM by the square of the height, respectively, the f at mass index (FMI) and fat-free mass index (FFMI) can be used to determine the variations in body composition. This study aimed to investigate the relationship of combined FMI and FFMI with low-density lipoprotein cholesterol (LDL-C) levels. METHODS: This cross-sectional study comprised 5,116 men and 13,630 women without cardiovascular disease and without treatment for hypertension, and diabetes. Following sex-specific quartile classification, FMI and FFMI were combined into 16 groups. Elevated LDL-C levels were defined as LDL-C ≥ 140 mg/dL and/or dyslipidemia treatment. Multivariable logistic regression models were used to examine the relationships between combined FMI and FFMI and elevated LDL-C levels. RESULTS: Overall, elevated LDL-C levels were found in 1,538 (30.1%) men and 5,434 (39.9%) women. In all FFMI subgroups, a higher FMI was associated with elevated LDL-C levels. Conversely, FFMI was inversely associated with elevated LDL-C levels in most FMI subgroups. Furthermore, the groups with the highest FMI and lowest FFMI had higher odds ratios for elevated LDL-C levels than those with the lowest FMI and highest FFMI. CONCLUSIONS: Regardless of FFMI, FMI was positively associated with elevated LDL-C levels. Conversely, in the majority of FMI subgroups, FFMI was inversely associated with elevated LDL-C levels.

Relationship between traditional risk factors for hypertension and systolic blood pressure in the Tohoku Medical Megabank Community-based Cohort Study.

Risk factors for hypertension have been emphasized in the Japanese Society of Hypertension Guidelines for the Management of Hypertension. However, large-scale studies on the association of smoking, potassium excretion, and gamma-glutamyl transferase level with BP in the Japanese population are limited. We conducted a cross-sectional study to examine the association between hypertension risk factors and systolic blood pressure in the Tohoku Medical Megabank Community-based Cohort Study (23,446 men and 38,921 women aged ≥20 years). A model adjusted for age, body mass index, smoking status, drinking status, estimated daily salt intake, potassium excretion, (or urinary sodium-to-potassium ratio), gamma-glutamyl transferase, physical activity, education level, status of damage to homes during the Great East Japan Earthquake, and residential areas was used. The average age and systolic blood pressure were 62.5 (10.3) years for men and 59.6 (11.3) years for women, 128.9 (16.7) mmHg for men and 124.7 (17.5) mmHg for women, respectively. Body mass index estimated daily salt intake, urinary sodium-to-potassium ratio and gamma-glutamyl transferase levels were positively associated with systolic blood pressure. Compared with never-drinkers, current drinkers who consumed 23-45 g/day and ≥46.0 g/day had significantly increased systolic blood pressure. Conversely, current smokers (1-10 cigarettes/day and 11-20 cigarettes/day) were inversely associated with systolic blood pressure compared to never-smokers. Overall, systolic blood pressure was associated with gamma-glutamyl transferase and hypertension risk factors, including body mass index, alcohol consumption, estimated daily salt intake, urinary sodium-to-potassium ratio, and potassium excretion. Our findings support the notion that lifestyle modifications should be attempted to prevent hypertension.

The association between depressive symptoms and masked hypertension in participants with normotension measured at research center.

Masked hypertension is a risk factor for cardiovascular diseases. However, masked hypertension is sometimes overlooked owing to the requirement for home blood pressure measurements for diagnosing. Mental status influences blood pressure. To reduce undiagnosed masked hypertension, this study assessed the association between depressive symptoms and masked hypertension. This cross-sectional study used data from the Tohoku Medical Megabank Project Community-Based Cohort Study (conducted in Miyagi Prefecture, Japan, from 2013) and included participants with normotension measured at the research center (systolic blood pressure<140 mmHg and diastolic blood pressure <90 mmHg). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (Japanese version). Masked hypertension was defined as normotension measured at the research center and home hypertension (home systolic blood pressure ≥135 mmHg or home diastolic blood pressure ≥85 mmHg). The study comprised 6705 participants (mean age: 55.7 ± 13.7 years). Of these participants, 1106 (22.1%) without depressive symptoms and 393 (23.2%) with depressive symptoms were categorized to have masked hypertension. Sex-specific and age-adjusted least mean squares for home blood pressure, not for research blood pressure were significantly higher in the group with depressive symptoms in both sex categories. The multivariate odds ratio for masked hypertension in the patients with depressive symptoms was 1.72 (95% confidence interval: 1.26-2.34) in male participants and 1.30 (95% confidence interval: 1.06-1.59) in female ones. Depressive symptoms were associated with masked hypertension in individuals with normotension measured at the research center. Depressive symptoms may be one of the risk factors for masked hypertension. Depressive symptoms were associated with masked hypertension in individuals with normotension measured at research center.

Influence of Diabetes Family History on the Associations of Combined Genetic and Lifestyle Risks with Diabetes in the Tohoku Medical Megabank Community-Based Cohort Study.

AIM: The influence of family history of diabetes, probably reflecting genetic and lifestyle factors, on the association of combined genetic and lifestyle risks with diabetes is unknown. We examined these associations. METHODS: This cross-sectional study included 9,681 participants in the Tohoku Medical Megabank Community-based Cohort Study. A lifestyle score, which was categorized into ideal, intermediate, and poor lifestyles, was given. Family history was obtained through a self-reported questionnaire. A polygenic risk score (PRS) was constructed in the target data (n=1,936) using publicly available genome-wide association study summary statistics from BioBank Japan. For test data (n=7,745), we evaluated PRS performance and examined the associations of combined family history and genetic and lifestyle risks with diabetes. Diabetes was defined as non-fasting blood glucose ≥ 200 mmHg, HbA1c ≥ 6.5%, and/or self-reported diabetes treatment. RESULTS: In test data, 467 (6.0%) participants had diabetes. Compared with a low genetic risk and an ideal lifestyle without a family history, the odds ratio (OR) was 3.73 (95% confidence interval [CI], 1.92-7.00) for a lower genetic risk and a poor lifestyle without a family history. Family history was significantly associated with diabetes (OR, 3.58 [95% CI, 1.73-6.98]), even in those with a low genetic risk and an ideal lifestyle. Even among participants who had an ideal lifestyle without a family history, a high genetic risk was associated with diabetes (OR, 2.49 [95% CI, 1.65-3.85]). Adding PRS to family history and conventional lifestyle risk factors improved the prediction ability for diabetes. CONCLUSIONS: Our findings support the notion that a healthy lifestyle is important to prevent diabetes regardless of genetic risk.

Establishment of the early prediction models of low-birth-weight reveals influential genetic and environmental factors: a prospective cohort study.

BACKGROUND: Low birth weight (LBW) is a leading cause of neonatal morbidity and mortality, and increases various disease risks across life stages. Prediction models of LBW have been developed before, but have limitations including small sample sizes, absence of genetic factors and no stratification of neonate into preterm and term birth groups. In this study, we challenged the development of early prediction models of LBW based on environmental and genetic factors in preterm and term birth groups, and clarified influential variables for LBW prediction. METHODS: We selected 22,711 neonates, their 21,581 mothers and 8,593 fathers from the Tohoku Medical Megabank Project Birth and Three-Generation cohort study. To establish early prediction models of LBW for preterm birth and term birth groups, we trained AI-based models using genetic and environmental factors of lifestyles. We then clarified influential environmental and genetic factors for predicting LBW in the term and preterm groups. RESULTS: We identified 2,327 (10.22%) LBW neonates consisting of 1,077 preterm births and 1,248 term births. Our early prediction models archived the area under curve 0.96 and 0.95 for term LBW and preterm LBW models, respectively. We revealed that environmental factors regarding eating habits and genetic features related to fetal growth were influential for predicting LBW in the term LBW model. On the other hand, we identified that genomic features related to toll-like receptor regulations and infection reactions are influential genetic factors for prediction in the preterm LBW model. CONCLUSIONS: We developed precise early prediction models of LBW based on lifestyle factors in the term birth group and genetic factors in the preterm birth group. Because of its accuracy and generalisability, our prediction model could contribute to risk assessment of LBW in the early stage of pregnancy and control LBW risk in the term birth group. Our prediction model could also contribute to precise prediction of LBW based on genetic factors in the preterm birth group. We then identified parental genetic and maternal environmental factors during pregnancy influencing LBW prediction, which are major targets for understanding the LBW to address serious burdens on newborns' health throughout life.

Reduced antiviral seropositivity among patients with inflammatory bowel disease treated with immunosuppressive agents.

BACKGROUND: Although live-attenuated vaccines are contraindicated under immunosuppression, the immune status of patients with inflammatory bowel disease (IBD) has not been fully assessed prior to immunosuppressive therapy. AIMS: To investigate antiviral serostatus against viruses requiring live vaccines for prevention in IBD patients undergoing immunosuppressive therapy. METHODS: This multicenter study included IBD patients who were aged <40 years and were treated with thiopurine monotherapy, molecular-targeted monotherapy, or combination therapy. Gender- and age-matched healthy subjects (HS) living in the same areas were included as control group. Antibody titers against measles, rubella, mumps, and varicella were measured by enzyme-linked immunosorbent assays. RESULTS: A total of 437 IBD patients (163 ulcerative colitis [UC] and 274 Crohn's disease [CD]) and 225 HS were included in the final analysis. Compared with HS, IBD patients had lower seropositivity rates for measles (IBD vs. HS = 83.91% vs. 85.33%), rubella (77.55% vs. 84.89%), mumps (37.50% vs. 37.78%), and varicella (91.26% vs. 96.44%). Gender- and age-adjusted seropositivity rates were lower in UC patients than in both CD patients and HS for measles (UC, CD, and HS = 81.60%, 85.29%, and 85.33%), rubella (76.40%, 78.23%, and 84.89%), mumps (27.16%, 43.70%, and 37.78%), and varicella (90.80%, 91.54%, and 96.44%); the difference was significant for all viruses except measles. Divided by the degree of immunosuppression, there were no significant differences in seropositivity rates among IBD patients. CONCLUSIONS: IBD patients, especially those with UC, exhibit reduced seropositivity rates and may benefit from screening prior to the initiation of immunosuppressive therapy.

dbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project.

To reveal gene-environment interactions underlying common diseases and estimate the risk for common diseases, the Tohoku Medical Megabank (TMM) project has conducted prospective cohort studies and genomic and multiomics analyses. To establish an integrated biobank, we developed an integrated database called "dbTMM" that incorporates both the individual cohort/clinical data and the genome/multiomics data of 157,191 participants in the Tohoku Medical Megabank project. To our knowledge, dbTMM is the first database to store individual whole-genome data on a variant-by-variant basis as well as cohort/clinical data for over one hundred thousand participants in a prospective cohort study. dbTMM enables us to stratify our cohort by both genome-wide genetic factors and environmental factors, and it provides a research and development platform that enables prospective analysis of large-scale data from genome cohorts.

The Data Use Ontology to streamline responsible access to human biomedical datasets.

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design.

BACKGROUND: With the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement. METHODS: Biospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis. RESULTS: We established the T ohoku M edical M egabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections. CONCLUSION: The mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing.

Integrated Database And Knowledge Base For Genomic Prospective Cohort Study In Tohoku Medical Megabank Toward Personalized Prevention And Medicine.

The Tohoku Medical Megabank project is a national project to revitalization of the disaster area in the Tohoku region by the Great East Japan Earthquake, and have conducted large-scale prospective genome-cohort study. Along with prospective genome-cohort study, we have developed integrated database and knowledge base which will be key database for realizing personalized prevention and medicine.

A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.

UNLABELLED: Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. ABBREVIATIONS: GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.

CELLPEDIA: a repository for human cell information for cell studies and differentiation analyses.

CELLPEDIA is a repository database for current knowledge about human cells. It contains various types of information, such as cell morphologies, gene expression and literature references. The major role of CELLPEDIA is to provide a digital dictionary of human cells for the biomedical field, including support for the characterization of artificially generated cells in regenerative medicine. CELLPEDIA features (i) its own cell classification scheme, in which whole human cells are classified by their physical locations in addition to conventional taxonomy; and (ii) cell differentiation pathways compiled from biomedical textbooks and journal papers. Currently, human differentiated cells and stem cells are classified into 2260 and 66 cell taxonomy keys, respectively, from which 934 parent-child relationships reported in cell differentiation or transdifferentiation pathways are retrievable. As far as we know, this is the first attempt to develop a digital cell bank to function as a public resource for the accumulation of current knowledge about human cells. The CELLPEDIA homepage is freely accessible except for the data submission pages that require authentication (please send a password request to cell-info@cbrc.jp). Database URL: http://cellpedia.cbrc.jp/

Mutations in the interferon sensitivity determining region and virological response to combination therapy with pegylated-interferon alpha 2b plus ribavirin in patients with chronic hepatitis C-1b infection.

BACKGROUND: Pegylated-interferon-alpha 2b (PEG-IFN) plus ribavirin (RBV) therapy is currently the de-facto standard treatment for hepatitis C virus (HCV) infection. The aims of this study were to analyze the clinical and virological factors associated with a higher rate of response in patients with HCV genotype 1b infection treated with combination therapy. METHODS: We analyzed, retrospectively, 239 patients with chronic hepatitis C-1b infection who received 48 weeks of combination therapy. We assessed clinical and laboratory parameters, including age, gender, pretreatment hemoglobin, platelet counts, HCV RNA titer, liver histology, the number of interferon sensitivity determining region (ISDR) mutations and substitutions of the core amino acids 70 and 91. Drug adherence was monitored in each patient. We carried out univariate and multivariate statistical analyses of these parameters and clinical responses. RESULTS: On an intention-to-treat (ITT) analysis, 98 of the 239 patients (41%) had sustained virological responses (SVRs). Patients with more than two mutations in the ISDR had significantly higher SVR rates (P<0.01). Univariate analyses showed that stage of fibrosis, hemoglobin, platelet counts, ISDR mutations, serum HCV RNA level, and adherence to PEG-IFN plus RBV were significantly correlated with SVR rates. Multivariate analysis in subjects with good drug adherence extracted the number of ISDR mutations (two or more: odds ratio [OR] 5.181). CONCLUSIONS: The number of mutations in the ISDR sequence of HCV-1b (>or=2) is the most effective parameter predicting a favorable clinical outcome of 48-week PEG-IFN plus RBV therapy in patients with HCV genotype 1b infection.

Comparison of HCV-associated gene expression and cell signaling pathways in cells with or without HCV replicon and in replicon-cured cells.

BACKGROUND: Hepatitis C virus (HCV) replication is affected by several host factors. Here, we screened host genes and molecular pathways that are involved in HCV replication by comprehensive analyses using two genotypes of HCV replicon-expressing cells, their cured cells and naïve Huh7 cells. METHODS: Huh7 cell lines that stably expressed HCV genotype 1b or 2a replicon were used. The cured cells were established by treating HCV replicon cells with interferon-alpha. Expression of 54,675 cellular genes was analyzed by GeneChip DNA microarray. The data were analyzed by using the KEGG Pathway database. RESULTS: Hierarchical clustering analysis showed that the gene-expression profiles of each cell group constituted clear clusters of naïve, HCV replicon-expressed, and cured cell lines. The pathway process analysis between the replicon-expressing and the cured cell lines identified significantly altered pathways, including MAPK, steroid biosynthesis and TGF-beta signaling pathways, suggesting that these pathways were affected directly by HCV replication. Comparison of cured and naïve Huh7 cells identified pathways, including steroid biosynthesis and sphingolipid metabolism, suggesting that these pathways were required for efficient HCV replication. Cytoplasmic lipid droplets were obviously increased in replicon-expressing and cured cells as compared to naïve cells. HCV replication was significantly suppressed by peroxisome proliferator-activated receptor (PPAR)-alpha agonists but augmented by PPAR-gamma agonists. CONCLUSION: Comprehensive gene expression and pathway analyses show that lipid biosynthesis pathways are crucial to support proficient virus replication. These metabolic pathways could constitute novel antiviral targets against HCV.