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Bipolar disorder (BD) is a global medical issue, afflicting around 1% of the population with manic and depressive episodes. Despite various genetic studies, the genetic architecture and pathogenesis of BD have not been fully resolved. Besides germline variants, postzygotic mosaic variants are proposed as new candidate mechanisms contributing to BD. Here, we performed extensive deep exome sequencing (DES, ~300×) and validation experiments to investigate the roles of mosaic variants in BD with 235 BD cases (194 probands of trios and 41 single cases) and 39 controls. We found an enrichment of developmental disorder (DD) genes in the genes hit by deleterious mosaic variants in BD (P = 0.000552), including a ClinVar-registered pathogenic variant in ARID2. An enrichment of deleterious mosaic variants was also observed for autism spectrum disorder (ASD) genes (P = 0.000428). The proteins coded by the DD/ASD genes with non-synonymous mosaic variants in BD form more protein-protein interaction than expected, suggesting molecular mechanisms shared with DD/ASD but restricted to a subset of cells in BD. We also found significant enrichment of mitochondrial heteroplasmic variants, another class of mosaic variants, in mitochondrial tRNA genes in BD (P = 0.0102). Among them, recurrent m.3243 A > G variants known as causal for mitochondrial diseases were found in two unrelated BD probands with allele fractions of 5–12%, lower than in mitochondrial diseases. Despite the limitation of using peripheral tissues, our DES investigation supports the possible contribution of deleterious mosaic variants in the nuclear genome responsible for severer phenotypes, such as DD/ASD, to the risk of BD and further demonstrates that the same paradigm can be applied to the mitochondrial genome. These results, as well as the enrichment of heteroplasmic mitochondrial tRNA variants in BD, add a new piece to the understanding of the genetic architecture of BD and provide general insights into the pathological roles of mosaic variants in human diseases.

Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (ntotal = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.

Long-read sequencing technology enable better characterization of structural variants (SVs). To adapt the technology to population-scale analyses, one critical issue is to obtain sufficient amount of high-molecular-weight genomic DNA. Here, we propose utilizing activated T lymphocytes, which can be established efficiently in a biobank to stably supply high-grade genomic DNA sufficiently. We conducted nanopore sequencing of 333 individuals constituting 111 trios with high-coverage long-read sequencing data (depth 22.2x, N50 of 25.8 kb) and identified 74,201 SVs. Our trio-based analysis revealed that more than 95% of the SVs were concordant with Mendelian inheritance. We also identified SVs associated with clinical phenotypes, all of which appear to be stably transmitted from parents to offspring. Our data provide a catalog of SVs in the general Japanese population, and the applied approach using the activated T-lymphocyte resource will contribute to biobank-based human genetic studies focusing on SVs at the population scale.

Alzheimer’s disease (AD) has no cure, but early detection and risk prediction could allow earlier intervention. Genetic risk factors may differ between ethnic populations. To discover novel susceptibility loci of AD in the Japanese population, we conducted a genome-wide association study (GWAS) with 3962 AD cases and 4074 controls. Out of 4,852,957 genetic markers that passed stringent quality control filters, 134 in nine loci, including APOE and SORL1, were convincingly associated with AD. Lead SNPs located in seven novel loci were genotyped in an independent Japanese AD case–control cohort. The novel locus FAM47E reached genome-wide significance in a meta-analysis of association results. This is the first report associating the FAM47E locus with AD in the Japanese population. A trans-ethnic meta-analysis combining the results of the Japanese data sets with summary statistics from stage 1 data of the International Genomics of Alzheimer’s Project identified an additional novel susceptibility locus in OR2B2. Our data highlight the importance of performing GWAS in non-European populations.

Bone dysplasias are a group of rare hereditary diseases, with up to 436 disease types. Perinatal diagnosis is clinically important for adequate personalized management and counseling. There are no reports focused on pathogenic variants of bone dysplasias in the general population. In this study, we focused on autosomal recessive bone dysplasias. We identified pathogenic variants using whole-genome reference panel data from 3552 Japanese individuals. For the first time, we were able to estimate the carrier frequencies and the proportions of potential patients. For autosomal recessive bone dysplasias, we detected 198 pathogenic variants of 54 causative genes. We estimated the variant carrier frequencies and the proportions of potential patients with variants associated with four clinically important bone dysplasias: osteogenesis imperfecta (OI), hypophosphatasia (HPP), asphyxiating thoracic dysplasia (ATD), and Ellis–van Creveld syndrome (EvC). The proportions of potential patients with OI, ATD, and EvC based on pathogenic variants classified as “pathogenic” and “likely pathogenic” by InterVar were closer to the reported incidence rates in Japanese subjects. Furthermore, the proportions of potential patients with HPP variants classified as “pathogenic” and “likely pathogenic” in InterVar and “pathogenic” in ClinVar were closer to the reported incidence rates. For bone dysplasia, the findings of this study will provide a better understanding of the variant types and frequencies in the Japanese general population, and should be useful for clinical diagnosis, genetic counseling, and personalized medicine., Bone dysplasia: Estimating carrier frequency with bioinformatics A bioinformatics approach helps estimate carrier frequency of a rare inherited bone disease which causes abnormalities in skeletal shape and structure. Autosomal recessive bone dysplasias affect bone and cartilage development and result from inheriting two mutated genes, one from each parent. Junichi Sugawara, Tohoku University, Sendai, Japan, and colleagues used mutation databases and a bioinformatics tool for variant interpretation to detect 198 pathogenic variants in 54 genes associated with autosomal recessive bone dysplasia in a whole-genome reference panel of 3,552 general Japanese individuals (3.5KJPNv2). They then estimated the frequency of people in the sample carrying bone dysplasia mutations and the expected proportion in whom the disorder could manifest, which compared well with reported incidence rates in the general population. These findings could prove useful for calculating the risk of bone dysplasia in the future children of carrier parents.

The complete human genome sequence is used as a reference for next-generation sequencing analyses. However, some ethnic ancestries are under-represented in the reference genome (e.g., GRCh37) due to its bias toward European and African ancestries. Here, we perform de novo assembly of three Japanese male genomes using > 100× Pacific Biosciences long reads and Bionano Genomics optical maps per sample. We integrate the genomes using the major allele for consensus and anchor the scaffolds using genetic and radiation hybrid maps to reconstruct each chromosome. The resulting genome sequence, JG1, is contiguous, accurate, and carries the Japanese major allele at most loci. We adopt JG1 as the reference for confirmatory exome re-analyses of seven rare-disease Japanese families and find that re-analysis using JG1 reduces total candidate variant calls versus GRCh37 while retaining disease-causing variants. These results suggest that integrating multiple genomes from a single population can aid genome analyses of that population., Human reference genomes are typically constructed from few individuals, and are biased towards European and African genomes. Here, the authors assemble three Japanese genomes to create a population-specific reference genome. They then demonstrate improved variant calling from exome sequencing with this reference genome.

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.

Deep learning algorithms have been successfully used in medical image classification. In the next stage, the technology of acquiring explainable knowledge from medical images is highly desired. Here we show that deep learning algorithm enables automated acquisition of explainable features from diagnostic annotation-free histopathology images. We compare the prediction accuracy of prostate cancer recurrence using our algorithm-generated features with that of diagnosis by expert pathologists using established criteria on 13,188 whole-mount pathology images consisting of over 86 billion image patches. Our method not only reveals findings established by humans but also features that have not been recognized, showing higher accuracy than human in prognostic prediction. Combining both our algorithm-generated features and human-established criteria predicts the recurrence more accurately than using either method alone. We confirm robustness of our method using external validation datasets including 2276 pathology images. This study opens up fields of machine learning analysis for discovering uncharted knowledge., Technologies for acquiring explainable features from medical images need further development. Here, the authors report a deep learning based automated acquisition of explainable features from pathology images, and show a higher accuracy of their method as compared to pathologist based diagnosis of prostate cancer recurrence.

We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervention study with 17 persons. First, we focused on signs and biomarkers that have been identified as candidates for vitamin B6 responsiveness indicators. Second, we conducted hypothesis testing among these selected variables and their combinations. Finally, we further investigated the results by conducting cluster analyses with two different algorithms, affinity propagation and k-medoids. Statistically significant variables for vitamin B6 responsiveness, including combination of hypersensitivity to sound and clumsiness, and plasma glutamine level, were included. As an a priori variable, the Pervasive Developmental Disorders Autism Society Japan Rating Scale (PARS) scores was also included. The affinity propagation analysis showed good classification of three potential vitamin B6-responsive persons with ASD. The k-medoids analysis also showed good classification. To our knowledge, this is the first study to attempt to identify subgroup of persons with ASD who show specific treatment responsiveness using selected phenotype variables. We applied machine learning methods to further investigate these variables’ ability to identify this subgroup of ASD, even when only a small sample size was available.

Biased mating due to female preferences towards certain traits in males is a major mechanism driving sexual selection, and may constitute an important evolutionary force in organisms with sexual reproduction. In birds, although the role of male ornamentation, plumage coloration, genetic dissimilarity, and body size have on mate selection by females have been examined extensively, few studies have clarified exactly how these characteristics affect female mate preferences. Here, we show that testosterone (T)-dependent male attractiveness enhances female preference for males of a polygamous species, the Japanese quail. A significant positive correlation between female mating preference and circulating T in the male was observed. The cheek feathers of attractive males contained higher levels of melanin and were more brightly colored. The ability of females to distinguish attractive males from other males was negated when the light source was covered with a sharp cut filter (cutoff

Lipoprotein glomerulopathy (LPG) is a hereditary disease characterized by lipoprotein thrombi in the glomerulus, hyperlipoproteinemia, and a marked increase in serum apolipoprotein E (APOE). More than 12 APOE mutations have been identified as causes of LPG, and APOE-Sendai (Arg145Pro) mutation was frequently detected in patients from the eastern part of Japan including Yamagata prefecture. Recently, effective therapy with intensive lipid-lowering agents was established, and epidemiologic data are required for early diagnosis. We determined the haplotype structure of APOE-Sendai in 13 patients from 9 unrelated families with LPG, and found that the haplotype of all APOE-Sendai mutations was identical, suggesting that APOE-Sendai mutation is common in Japanese patients probably through a founder effect. We also studied the gene frequency of APOE-Sendai in 2023 control subjects and 418 patients receiving hemodialysis in Yamagata prefecture using the TaqMan method, but did not identify any subjects carrying the mutation, indicating that it is very rare in the general population even in the eastern part of Japan. In addition to APOE mutation, other genetic and/or epigenetic factors are considered to be involved in the pathogenesis of LPG because of its low penetrance. The patients did not have a common haplotype of the counterpart APOE allele, and some patients had the same haplotype of the counterpart APOE allele as the asymptomatic carriers. These results suggest that the counterpart APOE allele is not likely associated with the onset of LPG. Further study is required to clarify the pathogenesis of LPG.

Breastfeeding jaundice is a well-known phenomenon, but its pathogenesis is still unclear. Increased production of bilirubin, impaired hepatic uptake and metabolism of bilirubin, and increased enterohepatic circulation of bilirubin account for most cases of pathological neonatal hyperbilirubinemia. We previously reported that 211G>A (G71R) mutation of the UGT1A1 gene is prevalent in East Asians and is associated with the development of neonatal hyperbilirubinemia. Recently, significant association of G71R mutation with hyperbilirubinemia in breast-fed neonates was reported. We enrolled 401 full-term Japanese infants, who were exclusively breast-fed without supplementation of formula before developing hyperbilirubinemia, and classified them into two groups based on the degree of maximal body weight loss during the neonatal period. We analyzed the sex, gestational age, delivery mode, body weight at birth, maximal body weight loss and genotypes of G71R and (TA)(7) polymorphic mutations of UGT1A1. Statistical analysis revealed that maximal body weight loss during the neonatal period is the only independent risk factor for the development of neonatal hyperbilirubinemia. The effect of G71R mutation on neonatal hyperbilirubinemia is significant in neonates with 5% or greater maximal body weight loss and its influence increases in parallel with the degree of maximal body weight loss. Our study indicates that G71R mutation is a risk factor for neonatal hyperbilirubinemia only in infants with inadequate breastfeeding and suggests that adequate breastfeeding may overcome the genetic predisposing factor, G71R mutation, for the development of neonatal hyperbilirubinemia.

We have identified and characterized a new gene sequence, TXNRD3NT1, whose transcripts, corresponding to the EST AA430236, were found by Affymetrix DNA chip analysis to be significantly down regulated in affected psoriatic tissue. The full-length cDNA of TXNRD3NT1 was isolated and characterized by combining 5'- and 3'-RACE (rapid amplication of cDNA ends) with screening a keratinocyte cDNA library, designing appropriate PCR primers, cloning amplified products, sequencing, and sequence analysis. Because part of this gene overlaps the previously described thioredoxin reductase 3 (TXNRD3) gene, we have named it TXNRD3NT1 (TXNRD3 new transcript 1). The full-length TXNRD3NT1 cDNA has 1133 nucleotides with a 251-bp 3-UTRand 2 poly(A)signal variants and 2 poly (A) sites. The TXNRD3NT1 cDNA ORF encodes for 133 amino acids, with the first four residues coding for a tubulin-beta mRNA autoregulation signal. Mapping the cDNA nucleotide sequence to the human genome sequence revealed that the TXNRD3NT1 gene has 4 exons located on Chromosome 3, at position 3q21. Exons 1 and 2 of the TXNRD3NT1 gene overlap with exons 15 and 16 of the thioredoxin reductase 2 gene which has different ORFs to that of TXNRD3NT1. The translation initiation codon ATG was found in exon 3 of the TXNRD3NT1 gene. RT-PCR showed that the full-length variant of the TXNRD3NT1 gene was expressed in only four issues (pancreas, esophagus, bone marrow, and keratinocytes) of the 30 different tissues tested. In most other tissues, an aberrant and truncated form of the transcript (i.e., missing exon 3 and part of exon 4) was detected. The result of a preliminary association study between psoriasis and single microsatellite marker of the TXNRD3NT1 gene suggests that it may not be a significant genetic determinant of psoriasis. However, we cannot exclude the possibility that other sequence variants may still exist within the TXNRD3NT1 gene. Sequence analysis of the TXNRD3NT1 gene from 8 psoriasis patients and 8 healthy controls revealed a number of synonymous SNPs that may be useful markers for future disease association studies.

Constructing a contemporary gene–environmental cohort: study design of the Yamagata Molecular Epidemiological Cohort Study

Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs) is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS) however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS) for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units) technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium) data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

To identify susceptibility genes for Parkinson's disease (PD) and to establish tailor-made medicine for PD, we studied 20 single nucleotide polymorphisms (SNPs) in 18 candidate genes for association with PD. We found that homozygosity for the V66M polymorphism of the BDNF gene occurs more frequently in PD patients than in unaffected controls and confirmed an association with the S18Y polymorphism of the UCHL1 gene. We further started microsatellite marker-based genome-wide association studies by using the pooled DNA method. We have finished checking approximately 6800 markers and found some significant associations (p=3.9 x 10(-6)) on chromosome 1 where other studies showed a linkage. Genes in linkage disequilibrium with these markers may be associated with pathogenesis of PD.