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.

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.

Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project.

Population-based prospective cohort studies are indispensable for modern medical research as they provide important knowledge on the influences of many kinds of genetic and environmental factors on the cause of disease. Although traditional cohort studies are mainly conducted using questionnaires and physical examinations, modern cohort studies incorporate omics and genomic approaches to obtain comprehensive physical information, including genetic information. Here, we report the design and midterm results of multi-omics analysis on population-based prospective cohort studies from the Tohoku Medical Megabank (TMM) Project. We have incorporated genomic and metabolomic studies in the TMM cohort study as both metabolome and genome analyses are suitable for high-throughput analysis of large-scale cohort samples. Moreover, an association study between the metabolome and genome show that metabolites are an important intermediate phenotype connecting genetic and lifestyle factors to physical and pathologic phenotypes. We apply our metabolome and genome analyses to large-scale cohort samples in the following studies.

A training and education program for genome medical research coordinators in the genome cohort study of the Tohoku Medical Megabank Organization.

BACKGROUND: Genome cohort studies are used to analyze interactions between genetic and environmental factors, providing valuable information for personalized healthcare. Large-scale and long-term cohort studies require a number of specially trained personnel, of whom those involved in obtaining informed consent play a vital role, especially during the initial phase of such studies. The Japanese Society of Human Genetics (JSHG) previously established a certification system for genome medical research coordinators (GMRCs) responsible for obtaining written consent via face-to-face explanation. Meanwhile, in the Tohoku Medical Megabank Organization (ToMMo), GMRCs are expected to play important roles not only in obtaining informed consent and conducting various assessments, but also in communicating with participants throughout the long-term follow-up. Based on the JSHG program, we therefore developed a specific education and training program for ToMMo GMRCs consisting of 17 lectures, one practical training session on the informed consent procedure, and written and interview examinations. Re-education workshops aimed at self-improvement are also carried out following certification. In this study, we evaluated the education and training program in terms of overall understanding, usefulness, and satisfaction using an anonymous questionnaire. METHODS: An anonymous questionnaire addressing each aspect of the education and training program (understanding, usefulness, and satisfaction) was distributed among 152 qualified ToMMo GMRCs. Responses were received from 94 participants (61.8%). RESULTS: There was a significant association between the level of overall understanding of lectures and medical qualification (nurse or clinical laboratory technologist), but not with age or educational background. The level of understanding and overall usefulness were lower in sessions related to genetics and epidemiology than those dealing with ToMMo practices. In the re-education workshops, GMRCs showed a preference for and hoped to learn more about both background knowledge and research progress in the ToMMo. CONCLUSIONS: The results of our questionnaire suggest that not all ToMMo GMRCs are able to understand everything during the initial education and training program, especially in terms of genomic medicine. Continuous re-education is therefore vital in improving knowledge, skills and motivation, and preparing GMRCs for a specialist role in community-based personalized healthcare.

Regional genetic differences among Japanese populations and performance of genotype imputation using whole-genome reference panel of the Tohoku Medical Megabank Project.

BACKGROUND: Genotype imputation from single-nucleotide polymorphism (SNP) genotype data using a haplotype reference panel consisting of thousands of unrelated individuals from populations of interest can help to identify strongly associated variants in genome-wide association studies. The Tohoku Medical Megabank (TMM) project was established to support the development of precision medicine, together with the whole-genome sequencing of 1070 human genomes from individuals in the Miyagi region (Northeast Japan) and the construction of the 1070 Japanese genome reference panel (1KJPN). Here, we investigated the performance of 1KJPN for genotype imputation of Japanese samples not included in the TMM project and compared it with other population reference panels. RESULTS: We found that the 1KJPN population was more similar to other Japanese populations, Nagahama (south-central Japan) and Aki (Shikoku Island), than to East Asian populations in the 1000 Genomes Project other than JPT, suggesting that the large-scale collection (more than 1000) of Japanese genomes from the Miyagi region covered many of the genetic variations of Japanese in mainland Japan. Moreover, 1KJPN outperformed the phase 3 reference panel of the 1000 Genomes Project (1KGPp3) for Japanese samples, and IKJPN showed similar imputation rates for the TMM and other Japanese samples for SNPs with minor allele frequencies (MAFs) higher than 1%. CONCLUSIONS: 1KJPN covered most of the variants found in the samples from areas of the Japanese mainland outside the Miyagi region, implying 1KJPN is representative of the Japanese population's genomes. 1KJPN and successive reference panels are useful genome reference panels for the mainland Japanese population. Importantly, the addition of whole genome sequences not included in the 1KJPN panel improved imputation efficiencies for SNPs with MAFs under 1% for samples from most regions of the Japanese archipelago.

Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals.

Clarifying allele frequencies of disease-related genetic variants in a population is important in genomic medicine; however, such data is not yet available for the Japanese population. To estimate frequencies of actionable pathogenic variants in the Japanese population, we examined the reported pathological variants in genes recommended by the American College of Medical Genetics and Genomics (ACMG) in our reference panel of genomic variations, 2KJPN, which was created by whole-genome sequencing of 2049 individuals of the resident cohort of the Tohoku Medical Megabank Project. We searched for pathogenic variants in 2KJPN for 57 autosomal ACMG-recommended genes responsible for 26 diseases and then examined their frequencies. By referring to public databases of pathogenic variations, we identified 143 reported pathogenic variants in 2KJPN for the 57 ACMG recommended genes based on a classification system. At the individual level, 21% of the individuals were found to have at least one reported pathogenic allele. We then conducted a literature survey to review the variants and to check for evidence of pathogenicity. Our results suggest that a substantial number of people have reported pathogenic alleles for the ACMG genes, and reviewing variants is indispensable for constructing the information infrastructure of genomic medicine for the Japanese population.

GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes.

OBJECTIVE: A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. METHODS: Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were replicated with 1396 cases and 1268 controls using a custom chip of 1961 single nucleotide polymorphisms (SNPs). We also first conducted GWASs of gout subtypes. Replication with Caucasian and New Zealand Polynesian samples was done to further validate the loci identified in this study. RESULTS: In addition to the five loci we reported previously, further susceptibility loci were identified at a genome-wide significance level (p<5.0×10-8): urate transporter genes (SLC22A12 and SLC17A1) and HIST1H2BF-HIST1H4E for all gout cases, and NIPAL1 and FAM35A for the renal underexcretion gout subtype. While NIPAL1 encodes a magnesium transporter, functional analysis did not detect urate transport via NIPAL1, suggesting an indirect association with urate handling. Localisation analysis in the human kidney revealed expression of NIPAL1 and FAM35A mainly in the distal tubules, which suggests the involvement of the distal nephron in urate handling in humans. Clinically ascertained male patients with gout and controls of Caucasian and Polynesian ancestries were also genotyped, and FAM35A was associated with gout in all cases. A meta-analysis of the three populations revealed FAM35A to be associated with gout at a genome-wide level of significance (p meta =3.58×10-8). CONCLUSIONS: Our findings including novel gout risk loci provide further understanding of the molecular pathogenesis of gout and lead to a novel concept for the therapeutic target of gout/hyperuricaemia.

Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes.

OBJECTIVE: Gout, caused by hyperuricaemia, is a multifactorial disease. Although genome-wide association studies (GWASs) of gout have been reported, they included self-reported gout cases in which clinical information was insufficient. Therefore, the relationship between genetic variation and clinical subtypes of gout remains unclear. Here, we first performed a GWAS of clinically defined gout cases only. METHODS: A GWAS was conducted with 945 patients with clinically defined gout and 1213 controls in a Japanese male population, followed by replication study of 1048 clinically defined cases and 1334 controls. RESULTS: Five gout susceptibility loci were identified at the genome-wide significance level (p<5.0×10(-8)), which contained well-known urate transporter genes (ABCG2 and SLC2A9) and additional genes: rs1260326 (p=1.9×10(-12); OR=1.36) of GCKR (a gene for glucose and lipid metabolism), rs2188380 (p=1.6×10(-23); OR=1.75) of MYL2-CUX2 (genes associated with cholesterol and diabetes mellitus) and rs4073582 (p=6.4×10(-9); OR=1.66) of CNIH-2 (a gene for regulation of glutamate signalling). The latter two are identified as novel gout loci. Furthermore, among the identified single-nucleotide polymorphisms (SNPs), we demonstrated that the SNPs of ABCG2 and SLC2A9 were differentially associated with types of gout and clinical parameters underlying specific subtypes (renal underexcretion type and renal overload type). The effect of the risk allele of each SNP on clinical parameters showed significant linear relationships with the ratio of the case-control ORs for two distinct types of gout (r=0.96 [p=4.8×10(-4)] for urate clearance and r=0.96 [p=5.0×10(-4)] for urinary urate excretion). CONCLUSIONS: Our findings provide clues to better understand the pathogenesis of gout and will be useful for development of companion diagnostics.

Japonica array: improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals.

The Tohoku Medical Megabank Organization constructed the reference panel (referred to as the 1KJPN panel), which contains >20 million single nucleotide polymorphisms (SNPs), from whole-genome sequence data from 1070 Japanese individuals. The 1KJPN panel contains the largest number of haplotypes of Japanese ancestry to date. Here, from the 1KJPN panel, we designed a novel custom-made SNP array, named the Japonica array, which is suitable for whole-genome imputation of Japanese individuals. The array contains 659,253 SNPs, including tag SNPs for imputation, SNPs of Y chromosome and mitochondria, and SNPs related to previously reported genome-wide association studies and pharmacogenomics. The Japonica array provides better imputation performance for Japanese individuals than the existing commercially available SNP arrays with both the 1KJPN panel and the International 1000 genomes project panel. For common SNPs (minor allele frequency (MAF)>5%), the genomic coverage of the Japonica array (r(2)>0.8) was 96.9%, that is, almost all common SNPs were covered by this array. Nonetheless, the coverage of low-frequency SNPs (0.5%

Identification of a unique hepatocellular carcinoma line, Li-7, with CD13(+) cancer stem cells hierarchy and population change upon its differentiation during culture and effects of sorafenib.

BACKGROUNDS: Cancer stem cell (CSC) research has highlighted the necessity of developing drugs targeting CSCs. We investigated a hepatocellular carcinoma (HCC) cell line that not only has CSC hierarchy but also shows phenotypic changes (population changes) upon differentiation of CSC during culture and can be used for screening drugs targeting CSC. METHODS: Based on a hypothesis that the CSC proportion should decrease upon its differentiation into progenitors (population change), we tested HCC cell lines (HuH-7, Li-7, PLC/PRF/5, HLF, HLE) before and after 2 months culture for several markers (CD13, EpCAM, CD133, CD44, CD90, CD24, CD166). Tumorigenicity was tested using nude mice. To evaluate the CSC hierarchy, we investigated reconstructivity, proliferation, ALDH activity, spheroid formation, chemosensitivity and microarray analysis of the cell populations sorted by FACS. RESULTS: Only Li-7 cells showed a population change during culture: the proportion of CD13 positive cells decreased, while that of CD166 positive cells increased. The high tumorigenicity of the Li-7 was lost after the population change. CD13(+)/CD166(-) cells showed slow growth and reconstructed the bulk Li-7 populations composed of CD13(+)/CD166(-), CD13(-)/CD166(-) and CD13(-)/CD166(+) fractions, whereas CD13(-)/CD166(+) cells showed rapid growth but could not reproduce any other population. CD13(+)/CD166(-) cells showed high ALDH activity, spheroid forming ability and resistance to 5-fluorouracil. Microarray analysis demonstrated higher expression of stemness-related genes in CD166(-) than CD166(+) fraction. These results indicated a hierarchy in Li-7 cells, in which CD13(+)/CD166(-) and CD13(-)/CD166(+) cells serve as slow growing CSCs and rapid growing progenitors, respectively. Sorafenib selectively targeted the CD166(-) fraction, including CD13(+) CSCs, which exhibited higher mRNA expression for FGF3 and FGF4, candidate biomarkers for sorafenib. 5-fluorouracil followed by sorafenib inhibited the growth of bulk Li-7 cells more effectively than the reverse sequence or either alone. CONCLUSIONS: We identified a unique HCC line, Li-7, which not only shows heterogeneity for a CD13(+) CSC hierarchy, but also undergoes a "population change" upon CSC differentiation. Sorafenib targeted the CSC in vitro, supporting the use of this model for screening drugs targeting the CSC. This type of "heterogeneous, unstable" cell line may prove more useful in the CSC era than conventional "homogeneous, stable" cell lines.

Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population.

BACKGROUND: Validation of single nucleotide variations in whole-genome sequencing is critical for studying disease-related variations in large populations. A combination of different types of next-generation sequencers for analyzing individual genomes may be an efficient means of validating multiple single nucleotide variations calls simultaneously. RESULTS: Here, we analyzed 12 independent Japanese genomes using two next-generation sequencing platforms: the Illumina HiSeq 2500 platform for whole-genome sequencing (average depth 32.4×), and the Ion Proton semiconductor sequencer for whole exome sequencing (average depth 109×). Single nucleotide polymorphism (SNP) calls based on the Illumina Human Omni 2.5-8 SNP chip data were used as the reference. We compared the variant calls for the 12 samples, and found that the concordance between the two next-generation sequencing platforms varied between 83% and 97%. CONCLUSIONS: Our results show the versatility and usefulness of the combination of exome sequencing with whole-genome sequencing in studies of human population genetics and demonstrate that combining data from multiple sequencing platforms is an efficient approach to validate and supplement SNP calls.

A Pilot Study for Return of Individual Pharmacogenomic Results to Population-Based Cohort Study Participants.

Introduction: Pharmacogenomic (PGx) testing results provide valuable information on drug selection and appropriate dosing, maximization of efficacy, and minimization of adverse effects. Although the number of large-scale, next-generation-sequencing-based PGx studies has recently increased, little is known about the risks and benefits of returning PGx results to ostensibly healthy individuals in research settings. Methods: Single-nucleotide variants of three actionable PGx genes, namely, MT-RNR1, CYP2C19, and NUDT15, were returned to 161 participants in a population-based Tohoku Medical Megabank project. Informed consent was obtained from the participants after a seminar on the outline of this study. The results were sent by mail alongside sealed information letter intended for clinicians. As an exception, genetic counseling was performed for the MT-RNR1 m.1555A > G variant carriers by a medical geneticist, and consultation with an otolaryngologist was encouraged. Questionnaire surveys (QSs) were conducted five times to evaluate the participants' understanding of the topic, psychological impact, and attitude toward the study. Results: Whereas the majority of participants were unfamiliar with the term PGx, and none had undergone PGx testing before the study, more than 80% of the participants felt that they could acquire basic PGx knowledge sufficient to understand their genomic results and were satisfied with their potential benefit and use in future prescriptions. On the other hand, some felt that the PGx concepts or terminology was difficult to fully understand and suggested that in-person return of the results was desirable. Conclusions: These results collectively suggest possible benefits of returning preemptive PGx information to ostensibly healthy cohort participants in a research setting.

Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs.

Ethnic-specific SNP arrays are becoming more important to increase the power of genome-wide association studies in diverse population. In the Tohoku Medical Megabank Project, we have been developing a series of Japonica Arrays (JPA) for genotyping participants based on reference panels constructed from whole-genome sequence data of the Japanese population. Here, we designed a novel version of the SNP array for the Japanese population, called Japonica Array NEO (JPA NEO), comprising a total of 666,883 markers. Among them, 654,246 tag SNPs of autosomes and X chromosome were selected from an expanded reference panel of 3,552 Japanese, 3.5KJPNv2, using pairwise r2 of linkage disequilibrium measures. Additionally, 28,298 markers were included for the evaluation of previously identified disease risk markers from the literature and databases, and those present in the Japanese population were extracted using the reference panel. Through genotyping 286 Japanese samples, we found that the imputation quality r2 and INFO score in the minor allele frequency bin >2.5-5% were >0.9 and >0.8, respectively, and >12 million markers were imputed with an INFO score >0.8. From these results, JPA NEO is a promising tool for genotyping the Japanese population with genome-wide coverage, contributing to the development of genetic risk scores.

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.

Oral Microbiome Analysis in Prospective Genome Cohort Studies of the Tohoku Medical Megabank Project.

A baseline oral microbiome study of the Tohoku Medical Megabank Organization (TMM) was planned to characterize the profile of the oral microbiome in the Japanese population. The study also aimed to clarify risk factors for multifactorial diseases by integrated analysis of the oral microbiome and host genome/omics information. From 2013 to 2016, we collected three types of oral biospecimens, saliva, supragingival plaque, and tongue swab, from a total of 25,101 participants who had a dental examination in TMM. In this study, we used two independent cohorts; the Community-Based Cohort and Birth and Three-Generation Cohort as discovery and validation cohorts, respectively, and we selected participants examined by a single dentist. We found through the 16S ribosomal RNA gene sequencing analysis of 834 participants of the Community-Based Cohort Study that there are differences in the microbial composition and community structure between saliva and plaque. The species diversities in both saliva and plaque were increased in correlation with the severity of periodontal disease. These results were nicely reproduced in the analysis of 455 participants of the Birth and Three-Generation Cohort Study. In addition, strong positive and negative associations of microbial taxa in both plaque and saliva with periodontitis-associated biofilm formation were detected by co-occurrence network analysis. The classes Actinobacteria and Bacilli, including oral health-associated bacterial species, showed a positive correlation in saliva. These results revealed differences in microbial composition and community structure between saliva and plaque and a correlation between microbial species and the severity of periodontal disease. We expect that the large database of the oral microbiome in the TMM biobank will help in the discovery of novel targets for the treatment and prevention of oral diseases, as well as for the discovery of therapeutic and/or preventive targets of systemic diseases.

Establishment of Integrated Biobank for Precision Medicine and Personalized Healthcare: The Tohoku Medical Megabank Project.

The Tohoku Medical Megabank (TMM) project was established to provide creative reconstruction of the Tohoku area that suffered from a huge earthquake and ensuing tsunami (the Great East Japan Earthquake, GEJE). TMM aims to establish two large-scale genome cohorts and an integrated biobank managing biospecimen and related information. It supports community medicine by establishing next-generation medical systems through a combination of the prospective genome cohort studies with a total of 150,000 participants and genomic medicine. The strategies for genome analyses in TMM are to develop an elaborate genome reference panel by means of high-fidelity Japanese whole-genome sequence, to design custom single nucleotide polymorphism (SNP) arrays based on the reference panel, and to obtain genotype data for all the TMM cohort participants subsequently. Disease-associated genomic information and omics data, including metabolomics and microbiome analysis, provide an essential platform for precision medicine and personalized healthcare (PHC). Ethical, legal, and social issues (ELSI) and education are important for implementing genomic medicine. The major considerations of ELSI regarding each participant of the cohort studies are the respect for the autonomy and the protection of privacies. Moreover, developing and provide human resources not only for the TMM project but also for the social implementation of precision medicine and PHC is required. We started a pilot study of the return of genomic results for familial hypercholesterolemia (FH) as a target disease. TMM aims to establish solid platforms that support precision medicine and PHC based on the genomic and omics information and environmental and lifestyle factors of the individuals, which is one of the most advanced medical care beyond the evidenced-based medicine in the near future.

Identification of genetic alterations in extramammary Paget disease using whole exome analysis.

BACKGROUND: Extramammary Paget disease (EMPD) is a rare cutaneous malignant neoplasm, and the genomic alterations underlying its pathogenesis are unknown. OBJECTIVE: To identify tumor-specific genomic alterations in EMPD. METHODS: Exome analysis was performed in specimens from three EMPD patients, and target amplicon sequencing was done for genes frequently mutated in other adenocarcinomas. RESULTS: Exome analysis revealed recurrent somatic mutations in several genes, includingTP53, PIK3CA, and ERBB2. We identified additional candidate exons by searching the COSMIC database for exons that are frequently mutated in other adenocarcinomas. We obtained 19 exons in 12 genes as candidate exons, and performed target amplicon sequencing in samples obtained from EMPD patients. New somatic mutations in the TP53 gene were identified in six EMPD patients. Single nucleotide polymorphism analysis revealed multiple chromosomal alterations in three EMPD specimens, and two specimens exhibited amplification of chromosome 12p13 and losses of 3p21-24, 7q22 and 13q12-21. CONCLUSION: Our comprehensive genetic analysis identified novel genomic alterations, and will inform treatment options for EMPD.

3.5KJPNv2: an allele frequency panel of 3552 Japanese individuals including the X chromosome.

The first step towards realizing personalized healthcare is to catalog the genetic variations in a population. Since the dissemination of individual-level genomic information is strictly controlled, it will be useful to construct population-level allele frequency panels with easy-to-use interfaces. In the Tohoku Medical Megabank Project, we sequenced nearly 4000 individuals from a Japanese population and constructed an allele frequency panel of 3552 individuals after removing related samples. The panel is called the 3.5KJPNv2. It was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. Our database is the first large-scale panel providing the frequencies of variants present on the X chromosome and on the mitochondria in the Japanese population. All the data are available on our original database at https://jmorp.megabank.tohoku.ac.jp.

Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare.

Personalized healthcare (PHC) based on an individual's genetic make-up is one of the most advanced, yet feasible, forms of medical care. The Tohoku Medical Megabank (TMM) Project aims to combine population genomics, medical genetics and prospective cohort studies to develop a critical infrastructure for the establishment of PHC. To date, a TMM CommCohort (adult general population) and a TMM BirThree Cohort (birth+three-generation families) have conducted recruitments and baseline surveys. Genome analyses as part of the TMM Project will aid in the development of a high-fidelity whole-genome Japanese reference panel, in designing custom single-nucleotide polymorphism (SNP) arrays specific to Japanese, and in estimation of the biological significance of genetic variations through linked investigations of the cohorts. Whole-genome sequencing from >3,500 unrelated Japanese and establishment of a Japanese reference genome sequence from long-read data have been done. We next aim to obtain genotype data for all TMM cohort participants (>150,000) using our custom SNP arrays. These data will help identify disease-associated genomic signatures in the Japanese population, while genomic data from TMM BirThree Cohort participants will be used to improve the reference genome panel. Follow-up of the cohort participants will allow us to test the genetic markers and, consequently, contribute to the realization of PHC.