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Maternal dietary zinc intake and childhood allergy have inconsistent relationships. Thus, this study aimed to evaluate the influence of low maternal dietary zinc intake during pregnancy on developing pediatric allergic diseases. This study was designed using the Japan Environment and Children’s Study dataset. The model building used data from 74,948 mother–child pairs. Maternal dietary zinc intake was estimated based on the food frequency questionnaire, collecting the intake information of 171 food and beverage items. Fitted logistic regression models and generalized estimating equation models (GEEs) estimated the association between energy-adjusted zinc intake and childhood allergic conditions. The energy-adjusted zinc intake did not affect the risk of developing allergic disorders (wheeze, asthma, atopic dermatitis, rhinitis, and food allergy) in offspring. The GEE model revealed similar insignificant odds ratios. No significant association was found between zinc intake during pregnancy and allergic diseases in offspring in early childhood. Further study remains necessary to examine the association between zinc and allergy with reliable zinc status biomarkers in the body.

A cell’s function is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here, we combine single-cell and spatial transcriptomic data to discover cellular niches within eight regions of the human heart. We map cells to micro-anatomic locations and integrate knowledge-based and unsupervised structural annotations. For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors, and cell interactions using a customCellPhoneDB.orgmodule. We show that the sinoatrial node is compartmentalised, with a core of pacemaker cells, fibroblasts and glial cells supporting paracrine glutamatergic signalling. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions, providing unexpected mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches which may contribute to infection defence. We define a ventricular myocardial-stress niche enriched for activated fibroblasts and stressed cardiomyocytes, cell states that are expanded in cardiomyopathies. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be deployed to other tissues and organs.

Although endotoxin concentration in the environment is negatively associated with atopic dermatitis (AD) onset in early childhood, the association between endotoxin concentration in the environment and eczema resolution in children with preexisting eczema is unclear. The aim of this study was to evaluate the association between endotoxin concentration in house dust and eczema persistence in young children. The authors used data from children participating in JECS (Japan Environment and Children's Study). In children who had AD or AD-like lesions at the age of 1 year, the authors investigated the association between the prevalence of eczema at the age of 3 years and endotoxin concentration (categorized by quartiles) in the dust on children's mattresses at the ages of 1.5 and 3 years. This study included 605 children. Eczema was significantly less prevalent among children whose mattresses were in the second and third quartiles of endotoxin concentration when they were 18 months old than among children whose mattresses were in the first quartile (adjusted odds ratio, 0.57 [95% confidence interval, 0.35-0.93] and adjusted odds ratio, 0.49 [95% confidence interval, 0.29-0.83], respectively). Moreover, of the children with eczema at age 3 years, those whose mattresses had endotoxin concentrations in the first quartile had significantly worse sleep disturbance caused by itchy rash (1 time per week) than did those whose mattresses were in the third and fourth quartiles (20.0% vs 3.3% and 3.7%, both p values 0.01). The findings indicate that low endotoxin exposure is associated with a higher prevalence of persistent eczema during early childhood.

The influence of family allergic history on food allergy in offspring in Japan is unknown. We analyzed data from a nationwide birth cohort study using logistic regression models to examine the associations of maternal, paternal, and both parental histories of allergic diseases (food allergy, atopic dermatitis, asthma, and rhinitis) with their child’s food allergy at 1.5 and 3 years of age. This analysis included 69,379 singleton full-term mothers and 37,179 fathers and their children. All parental histories of allergic diseases showed significant positive associations with their child’s food allergy. When both parents had a history of allergic diseases, the adjusted odds ratio (aOR) tended to be higher than when either parent had allergic diseases (p for trend < 0.0001). The highest aOR was detected when both parents had food allergy (2.60; 95% confidential interval, 1.58–4.27), and the aOR was 1.71 when either parent had food allergy (95% confidential interval, 1.54–1.91). The aORs were attenuated but still had significant positive associations after adjusting for the child’s atopic dermatitis, a risk factor for allergy development. In conclusion, all parental allergic diseases were significantly positively associated with their child’s food allergy. The effect of family history showed a stepwise increase in risk from either parent to both parents, and the highest risk of allergic disease was a parental history of food allergy.

Previous epidemiological studies have reported an increased risk of anemia in people with allergic disorders. However, previous studies have followed a cross-sectional design. The aim of this study was to investigate the association between the two conditions with a cohort dataset. We used data of 80,943 children in the Japan Environment and Children’s Study, the largest birth cohort in Japan. The association between anemia and allergic disorders was evaluated with a logistic regression model and propensity score analysis. After adjusting for potential confounders, children with asthma (odds ratio [OR], 1.85; 95% confidence interval [CI], 1.32–2.60), atopic dermatitis (OR, 2.18; 95% CI, 1.66–2.85), allergic rhinitis (OR, 1.35; 95% CI, 1.05–1.74), allergic rhinoconjunctivitis (OR, 2.95; 95% CI, 1.91–4.54), and food allergies (OR, 1.92; 95% CI, 1.44–2.56) at 2 years of age predicted high odds of developing anemia in the next year. Any allergy at 2 years of age was associated with an increased risk of anemia at the age of 3 years (OR, 1.80; 95% CI, 1.41–2.29). The findings remained stable in the propensity score analysis. Results suggest that allergic diseases were related to caregiver-reported anemia in children.

Skeletal muscle ageing increases the incidence of age-associated frailty and sarcopenia in the elderly worldwide, leading to increased morbidity and mortality. However, our understanding of the cellular and molecular mechanisms of muscle ageing is still far from complete. Here, we generate a single-cell and single-nucleus transcriptomic atlas of skeletal muscle ageing from 15 donors across the adult human lifespan, accompanied by myofiber typing using imaging. Our atlas reveals ageing mechanisms acting across different compartments of the muscle, including muscle stem cells (MuSCs), myofibers and the muscle microenvironment. Firstly, we uncover two mechanisms driving MuSC ageing, namely a decrease in ribosome biogenesis and an increase in inflammation. Secondly, we identify a set of nuclei populations explaining the preferential degeneration of the fast-twitch myofibers and suggest two mechanisms acting to compensate for their loss. Importantly, we identify a neuromuscular junction accessory population, which helps myofiber to compensate for aged-related denervation. Thirdly, we reveal multiple microenvironment cell types contributing to the inflammatory milieu of ageing muscle by producing cytokines and chemokines to attract immune cells. Finally, we provide a comparable mouse muscle ageing atlas and further investigate conserved and specific ageing hallmarks across species. In summary, we present a comprehensive human skeletal muscle ageing resource by combining different data modalities, which significantly expands our understanding of muscle biology and ageing.

To (re)define tissue architecture of the lung and airways at the cellular and molecular level, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and Visium Spatial Transcriptomics. Using computational data integration and analysis, we extend beyond the suspension cell paradigm of lung atlases to date, to define and discover macro and micro-anatomical tissue compartments. We describe novel cell types and states in vascular, stromal and nerve bundle microenvironments. From our spatial transcriptomics, we discover and validate a novel survival niche for IgA plasma cells in the airway submucosal glands (SMG). In this niche we define a supporting role for SMG epithelial cells in mucosal immunity through recruitment and maintenance of IgA plasma, B and CD4 T cells locally at the airway SMG. We identify an immune-supporting role for SMG duct and serous cells with distinct signalling circuits to recruit B cells and IgA plasma cells, promoting longevity and antibody secretion through expression of CCL28, APRIL and IL6. We find high expression of MHC-II in SMG duct and serous cells, which are localised closely with memory CD4 T cells, suggesting local modulation of antigen specific immune responses locally at the glands. This new tissue microenvironment, which we term the “gland-associated immune niche” (GAIN) has major implications for respiratory immunity and infection response. Our single cell and spatial data is available for download and query at lungcellatlas.org.

SummaryMultiple distinct cell types of the human lung and airways have been defined by single cell RNA sequencing (scRNAseq). Here we present a multi-omics spatial lung atlas to define novel cell types which we map back into the macro- and micro-anatomical tissue context to define functional tissue microenvironments. Firstly, we have generated single cell and nuclei RNA sequencing, VDJ-sequencing and Visium Spatial Transcriptomics data sets from 5 different locations of the human lung and airways. Secondly, we define additional cell types/states, as well as spatially map novel and known human airway cell types, such as adult lung chondrocytes, submucosal gland (SMG) duct cells, distinct pericyte and smooth muscle subtypes, immune-recruiting fibroblasts, peribronchial and perichondrial fibroblasts, peripheral nerve associated fibroblasts and Schwann cells. Finally, we define a survival niche for IgA-secreting plasma cells at the SMG, comprising the newly defined epithelial SMG-Duct cells, and B and T lineage immune cells. Using our transcriptomic data for cell-cell interaction analysis, we propose a signalling circuit that establishes and supports this niche. Overall, we provide a transcriptional and spatial lung atlas with multiple novel cell types that allows for the study of specific tissue microenvironments such as the newly defined gland-associated lymphoid niche (GALN).

T1 Figure 1ConclusionsOverall, this largest paediatric single cell COVID-19 study to date showed significant differences in response to SARS-CoV-2 between children and adults, reflecting the changes of the immune landscape over developmental time, which in children are dominated by naive and innate responses.

Funder: Medical Research Council, The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung's disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease.

Common genetic variants modulate the cellular response to viruses and are implicated in a range of immune pathologies, including infectious and autoimmune diseases. The transcriptional antiviral response is known to vary between infected cells from a single individual, yet how genetic variants across individuals modulate the antiviral response (and its cell-to-cell variability) is not well understood. Here, we triggered the antiviral response in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-seq. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), the first statistical approach designed to identify dynamic eQTLs across a transcriptional trajectory of cell populations, without aggregating single-cell data into pseudo-bulk. This allows us to uncover the underlying architecture and variability of antiviral response across responding cells, and to identify more than two thousands eQTLs modulating the dynamic changes during this response. Many of these eQTLs colocalise with risk loci identified in GWAS of infectious and autoimmune diseases. As a case study, we focus on a COVID-19 susceptibility locus, colocalised with the antiviral OAS1 splicing QTL. We validated it in blood cells from a patient cohort and in the infected nasal cells of a patient with the risk allele, demonstrating the utility of GASPACHO to fine-map and functionally characterise a genetic locus. In summary, our novel analytical approach provides a new framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.

The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. To comprehensively map cell lineages in the healthy developing, pediatric and adult human gut from ten distinct anatomical regions, as well as draining lymph nodes, we used singlecell RNA-seq and VDJ analysis of roughly one third of a million cells. This reveals the presence of BEST4+ absorptive cells throughout the human intestinal tract, demonstrating the existence of this cell type beyond the colon for the first time. Furthermore, we implicate IgG sensing as a novel function of intestinal tuft cells, and link these cells to the pathogenesis of inflammatory bowel disease. We define novel glial and neuronal cell populations in the developing enteric nervous system, and predict cell-type specific expression of Hirschsprung’s disease-associated genes. Finally, using a systems approach, we identify key cell players across multiple cell lineages driving secondary lymphoid tissue formation in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. These data provide an unprecedented catalogue of intestinal cells, and new insights into cellular programs in development, homeostasis and disease.

While a substantial proportion of adults infected with SARS-CoV-2 progress to develop severe disease, children rarely manifest respiratory complications. Therefore, understanding differences in the local and systemic response to SARS-CoV-2 infection between children and adults may provide important clues about the pathogenesis of SARS-CoV-2 infection. To address this, we first generated a healthy reference multi-omics single cell data set from children (n=30) in whom we have profiled triple matched samples: nasal and tracheal brushings and PBMCs, where we track the developmental changes for 42 airway and 31 blood cell populations from infancy, through childhood to adolescence. This has revealed the presence of naive B and T lymphocytes in neonates and infants with a unique gene expression signature bearing hallmarks of innate immunity. We then contrast the healthy reference with equivalent data from severe paediatric and adult COVID-19 patients (total n=27), from the same three types of samples: upper and lower airways and blood. We found striking differences: children with COVID-19 as opposed to adults had a higher proportion of innate lymphoid and non-clonally expanded naive T cells in peripheral blood, and a limited interferon-response signature. In the airway epithelium, we found the highest viral load in goblet and ciliated cells and describe a novel inflammatory epithelial cell population. These cells represent a transitional regenerative state between secretory and ciliated cells; they were found in healthy children and were enriched in paediatric and adult COVID-19 patients. Epithelial cells display an antiviral and neutrophil-recruiting gene signature that is weaker in severe paediatricversusadult COVID-19. Our matched blood and airway samples allowed us to study the spatial dynamics of infection. Lastly, we provide a user-friendly interface for this data1as a highly granular reference for the study of immune responses in airways and blood in children.

Genome-wide association studies (GWAS) have discovered numerous genomic loci associated with Alzheimer’s disease (AD), yet the causal genes and variants remain incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including novel associations near CCDC6, TSPAN14, NCK2, and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with greater than 50% probability each of being causally involved in AD risk, and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci (eQTL) datasets, and prioritization of genes using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we find that evidence converges on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA, and CASS4.

Common genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

Tobacco smoke exposure is known to lower serum 25-hydroxyvitamin D (25(OH)D) concentrations. This study evaluated the association between passive smoking and vitamin D deficiency (VDD) in young children using data from the Japan Environment and Children’s Study (JECS), the largest birth cohort study in Japan. Information on parental smoking status was extracted from a survey of JECS for children aged 1.5 years and data for serum 25(OH)D concentrations were obtained from blood tests in the Sub-Cohort Study of JECS performed at age 2 years. Logistic regression and linear models were fitted to evaluate the association between these variables. Data were analyzed for 4593 children. After adjusting for covariates, smoke exposure was significantly associated with increased incidence of VDD (OR 1.35; 95% CI, 1.14–1.59) according to the logistic model. The linear model indicated that passive smoking negatively predicted de-seasonalized serum 25(OH)D concentrations (β −0.5; 95% CI −0.95 to −0.08) in children aged 2 years. The results suggest that smoke exposure is a risk factor for VDD in children. Given that VD plays a crucial role in bone metabolism and the immune system, our findings are significant for clinical and public health.

The COVID-19 pandemic, caused by SARS coronavirus 2 (SARS-CoV-2), has resulted in excess morbidity and mortality as well as economic decline. To characterise the systemic host immune response to SARS-CoV-2, we performed single-cell RNA-sequencing coupled with analysis of cell surface proteins, providing molecular profiling of over 800,000 peripheral blood mononuclear cells from a cohort of 130 patients with COVID-19. Our cohort, from three UK centres, spans the spectrum of clinical presentations and disease severities ranging from asymptomatic to critical. Three control groups were included: healthy volunteers, patients suffering from a non-COVID-19 severe respiratory illness and healthy individuals administered with intravenous lipopolysaccharide to model an acute inflammatory response. Full single cell transcriptomes coupled with quantification of 188 cell surface proteins, and T and B lymphocyte antigen receptor repertoires have provided several insights into COVID-19: 1. a new non-classical monocyte state that sequesters platelets and replenishes the alveolar macrophage pool; 2. platelet activation accompanied by early priming towards megakaryopoiesis in immature haematopoietic stem/progenitor cells and expansion of megakaryocyte-primed progenitors; 3. increased clonally expanded CD8+ effector:effector memory T cells, and proliferating CD4+ and CD8+ T cells in patients with more severe disease; and 4. relative increase of IgA plasmablasts in asymptomatic stages that switches to expansion of IgG plasmablasts and plasma cells, accompanied with higher incidence of BCR sharing, as disease severity increases. All data and analysis results are available for interrogation and data mining through an intuitive web portal. Together, these data detail the cellular processes present in peripheral blood during an acute immune response to COVID-19, and serve as a template for multi-omic single cell data integration across multiple centers to rapidly build powerful resources to help combat diseases such as COVID-19.

Physical interaction of regulatory elements in three-dimensional space poses a challenge for studies of disease because non-coding risk variants may be great distances from the genes they regulate. Experimental methods to capture these interactions, such as chromosome conformation capture, usually cannot assign causal direction of effect between regulatory elements, an important component of fine-mapping studies. We developed a Bayesian hierarchical approach that uses two-stage least squares and applied it to an ATAC-seq (assay for transposase-accessible chromatin using sequencing) data set from 100 individuals, to identify over 15,000 high-confidence causal interactions. Most (60%) interactions occurred over

Genome-wide association studies (GWAS) have discovered numerous genomic loci associated with Alzheimer’s disease (AD), yet the causal genes and variants remain incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including novel associations near genes CCDC6, TSPAN14, NCK2, and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with greater than 50% probability each of being causally involved in AD risk, and others strongly suggested by functional annotation. We followed this with colocalisation analyses across 109 gene expression quantitative trait loci (eQTL) datasets, and prioritization of genes using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we find that evidence converges on likely causal genes, including the above four genes, and those at previously discovered AD loci including BIN1, APH1B, PTK2B, PILRA, and CASS4.

Microglia, the tissue resident macrophages of the CNS, are implicated in a broad range of neurological pathologies, from acute brain injury to dementia. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single cell and bulk RNA sequencing, we defined distinct cellular populations of acutelyin vivo-activated microglia, and characterised a dramatic switch in microglial population composition in patients suffering from acute brain injury. We mapped expression quantitative trait loci (eQTLs) in human microglia and show that many disease-associated eQTLs in microglia replicate well in a human induced pluripotent stem cell (hIPSC) derived macrophage model system. Using ATAC-seq from 95 individuals in this hIPSC model we fine-map candidate causal variants at risk loci for Alzheimer’s disease, the most prevalent neurodegenerative condition in acute brain injury patients. Our study provides the first population-scale transcriptional map of a critically important cell for neurodegenerative disorders.

Primary sclerosing cholangitis (PSC) is a rare progressive disorder leading to bile duct destruction; similar to 75% of patients have comorbid inflammatory bowel disease (IBD). We undertook the largest genome-wide association study of PSC (4,796 cases and 19,955 population controls) and identified four new genome-wide significant loci. The most associated SNP at one locus affects splicing and expression of UBASH3A, with the protective allele (C) predicted to cause nonstop-mediated mRNA decay and lower expression of UBASH3A. Further analyses based on common variants suggested that the genome-wide genetic correlation (r(G)) between PSC and ulcerative colitis (UC) (r(G) = 0.29) was significantly greater than that between PSC and Crohn's disease (CD) (r(G) = 0.04) (P = 2.55 x 10(-15)). UC and CD were genetically more similar to each other (r(G) = 0.56) than either was to PSC (P

When cellular traits are measured using high-throughput DNA sequencing quantitative trait loci (QTLs) manifest at two levels: population level differences between individuals and allelic differences between cis-haplotypes within individuals. We present RASQUAL (Robust Allele Specific QUAntitation and quality controL), a novel statistical approach for association mapping that integrates genetic effects and robust modelling of biases in next generation sequencing (NGS) data within a single, probabilistic framework. RASQUAL substantially improves causal variant localisation and sensitivity of association detection over existing methods in RNA-seq, DNaseI-seq and ChIP-seq data. We illustrate how RASQUAL can be used to maximise association detection by generating the first map of chromatin accessibility QTLs (caQTLs) in a European population using ATAC-seq. Despite a modest sample size, we identified 2,706 independent caQTLs (FDR 10%) and illustrate how RASQUAL's improved causal variant localisation provides powerful information for fine-mapping disease-associated variants. We also map “multipeak” caQTLs, identical genetic associations found across multiple, independent open chromatin regions and illustrate how genetic signals in ATAC-seq data can be used to link distal regulatory elements with gene promoters. Our results highlight how joint modelling of population and allele-specific genetic signals can improve functional interpretation of noncoding variation.

Physical interaction of distal regulatory elements in three-dimensional space poses a significant challenge for studies of common disease, because noncoding risk variants may be substantial distances from the genes they regulate. Experimental methods to capture these interactions, such as chromosome conformation capture (CCC), usually cannot assign causal direction of effect between regulatory elements, an important component of disease fine-mapping. Here, we developed a statistical model that uses Mendelian Randomisation within a Bayesian hierarchical model framework, and applied it to a novel ATAC-seq data from 100 individuals mapping over 15,000 putatively causal interactions between distal regions of open chromatin. Strikingly, the majority (>60%) of interactions we detected were over distances of

The accuracy of replicating the genetic code is fundamental. DNA repair mechanisms protect the fidelity of the genome ensuring a low error rate between generations. This sustains the similarity of individuals whilst providing a repertoire of variants for evolution. The mutation rate in the human genome has recently been measured to be 50–70 de novo single nucleotide variants (SNVs) between generations. During development mutations accumulate in somatic cells so that an organism is a mosaic. However, variation within a tissue and between tissues has not been analysed. By reprogramming somatic cells into induced pluripotent stem cells (iPSCs), their genomes and the associated mutational history are captured. By sequencing the genomes of polyclonal and monoclonal somatic cells and derived iPSCs we have determined the mutation rates and show how the patterns change from a somatic lineage in vivo through to iPSCs. Somatic cells have a mutation rate of 14 SNVs per cell per generation while iPSCs exhibited a ten-fold lower rate. Analyses of mutational signatures suggested that deamination of methylated cytosine may be the major mutagenic source in vivo, whilst oxidative DNA damage becomes dominant in vitro. Our results provide insights for better understanding of mutational processes and lineage relationships between human somatic cells. Furthermore it provides a foundation for interpretation of elevated mutation rates and patterns in cancer., Author Summary The mutation load of human tissues is unknown and represents the genetic divergence from the fertilised egg. Reprogramming of somatic cells generates induced pluripotent stem cells (iPSCs), a cell type being considered for clinical applications. We generated iPSCs from tissues of healthy individuals and used whole genome sequencing to identify in vivo mutations accrued in a somatic cell during the lifetime of the individual. Next we identified in vitro mutations introduced during reprogramming and cell culture. Each has a unique mutation signature suggesting different mutagenic processes. Our study demonstrates the use of reprogramming as a tool to elucidate mutational processes within normal cells and highlights the importance of genetic characterisation of iPSCs prior to clinical translation.

Although the Japanese population has a rather low genetic diversity, we recently confirmed the presence of two main clusters (the Hondo and Ryukyu clusters) through principal component analysis of genome-wide single-nucleotide polymorphism (SNP) genotypes. Understanding the genetic differences between the two main clusters requires further genome-wide analyses based on a dense SNP set and comparison of haplotype frequencies. In the present study, we determined haplotypes for the Hondo cluster of the Japanese population by detecting SNP homozygotes with 388,591 autosomal SNPs from 18,379 individuals and estimated the haplotype frequencies. Haplotypes for the Ryukyu cluster were inferred by a statistical approach using the genotype data from 504 individuals. We then compared the haplotype frequencies between the Hondo and Ryukyu clusters. In most genomic regions, the haplotype frequencies in the Hondo and Ryukyu clusters were very similar. However, in addition to the human leukocyte antigen region on chromosome 6, other genomic regions (chromosomes 3, 4, 5, 7, 10 and 12) showed dissimilarities in haplotype frequency. These regions were enriched for genes involved in the immune system, cell-cell adhesion and the intracellular signaling cascade. These differentiated genomic regions between the Hondo and Ryukyu clusters are of interest because they (1) should be examined carefully in association studies and (2) likely contain genes responsible for morphological or physiological differences between the two groups.

We present a statistical model for allele-specific patterns of copy number polymorphisms (CNPs) in commercial single nucleotide polymorphism (SNP) array data. This model is based on the observation that fluorescent signal intensities tend to cluster into clouds of similar allele-specific copy number (ASCN) genotypes at each SNP locus. To capture the tendency of this clustering to be made vague by instrumental errors, our model allows for cluster memberships to overlap each other, according to a Bayesian Gaussian mixture model (GMM). This approach is flexible, allowing for both absolute scale differences and X/Y scale imbalances of fluorescent signal intensities. The resulting model is also robust toward unobserved ASCN genotypes, which can be problematic for ordinary GMMs. We illustrated the utility of the model by applying it to commercial SNP array intensity data obtained from the Illumina HumanHap 610K platform. We retrieved more than 4,000 allele-specific CNPs, though 99% of them showed rather simple allele-specific CNP patterns with only a single aneuploid haplotype among the normal haplotypes. The genotyping accuracy was assessed by two approaches, quantitative PCR and replicated subjects. The results of both of these approaches demonstrated mean genotyping error rates of 1%. We demonstrated a preliminary genome-wide association study of three hematological traits. The result exhibited that it could form the foundation for new, more effective statistical methods for the mapping of both disease genes and quantitative trait loci with genome-wide CNPs. The methods described in this work are implemented in a software package, PlatinumCNV, available on the Internet.

Finding gene interaction models is one of the most important issues in genotype-phenotype association studies. This paper presents a model-free nonparametric statistical interaction analysis known as Parallel Haplotype Configuration Reduction (pHCR). This technique extends the original Multifactor Dimensionality Reduction (MDR) algorithm by using haplotype contribution values (c-values) and a haplotype interaction scheme instead of analyzing interactions among single-nucleotide polymorphisms. The proposed algorithm uses the statistical power of haplotypes to obtain a gene-gene interaction model. pHCR computes a statistical value for each haplotype, which contributes to the phenotype, and then performs haplotype interaction analysis on the basis of the cumulative c-value of each individual haplotype. To address the high computational complexity of pHCR, this paper also presents a scalable parallel computing solution. Nine common two-locus disease models were used to evaluate the algorithm performance under different scenarios. The results from all cases showed that pHCR shows higher power to detect gene-gene interaction in comparison with the results obtained from running MDR on the same data set. We also compared pHCR with FAMHAP, which mainly considers haplotype in the association analysis. For every experiment on the simulated data set, pHCR correctly produced haplotype interactions with much fewer false positives. We also challenged pHCR with a real data set input of beta-thalassemia/Hemoglobin E (HbE) disease. The result suggested the interaction between two previously reported quantitative trait loci of the fetal hemoglobin level, which is a major modifying factor, and disease severity of beta-thalassemia/HbE disease.

Human iPS cells have been generated using a diverse range of tissues from a variety of donors using different reprogramming vectors. However, these cell lines are heterogeneous, which presents a limitation for their use in disease modeling and personalized medicine. To explore the basis of this heterogeneity we generated 25 iPS cell lines under normalised conditions from the same set of somatic tissues across a number of donors. RNA-seq data sets from each cell line were compared to identify the majority contributors to transcriptional heterogeneity. We found that genetic differences between individual donors were the major cause of transcriptional variation between lines. In contrast, residual signatures from the somatic cell of origin, so called epigenetic memory, contributed relatively little to transcriptional variation. Thus, underlying genetic background variation is responsible for most heterogeneity between human iPS cell lines. We conclude that epigenetic effects in hIPSCs are minimal, and that hIPSCs are a stable, robust and powerful platform for large-scale studies of the function of genetic differences between individuals. Our data also suggest that future studies using hIPSCs as a model system should focus most effort on collection of large numbers of donors, rather than generating large numbers of lines from the same donor., Author Summary Human induced pluripotent stem (hiPS) cells are a potentially powerful model system for studying human disease and development, and a resource for personalized medicine. However, it has been reported that hiPS cells exhibit substantial heterogeneity which could limit their use as model systems. Clearly, knowledge of the source of heterogeneity is key for deeper understanding of the use of human iPS cells for basic and therapeutic applications. One source of this heterogeneity has been presumed to be “memory” of the adult somatic cell from which the hIPS cells were derived, but the evidence to support this view is scant. We have generated a set of human iPS cells from a set of somatic cell types from different donors. Our study shows that cell lines from different somatic sources but from the same donor (i.e. with the same genome) are more similar than cell lines isolated from the same tissue type but from different donors. Once genetic changes are accounted for, all aspects of gene expression, including mRNA levels, splicing and imprinting are highly similar between iPS cells derived from different human tissues. Thus, most of the previously described transcriptional variation between cell lines is likely to be genetic in origin.

Nat. Genet. 48, 206–213 (2016); published online 14 December 2015; corrected after print 8 February 2016 In the version of this article initially published, the accession code for the ATAC-seq data was omitted. These data have been deposited in the European Nucleotide Archive under accession ERP011141.

Smoking is a major public health problem, but the genetic factors associated with smoking behaviors are not fully elucidated. Here, we have conducted an integrated genome-wide association study to identify common copy number polymorphisms (CNPs) and single nucleotide polymorphisms (SNPs) associated with the number of cigarettes smoked per day (CPD) in Japanese smokers (N = 17,158). Our analysis identified a common CNP with a strong effect on CPD (rs8102683; P=3.8 x 10(-42)) in the 19q13 region, encompassing the CYP2A6 locus. After adjustment for the associated CNP, we found an additional associated SNP (rs11878604; P=9.7 x 10(-30)) located 30 kb downstream of the CYP2A6 gene. Imputation of the CYP2A6 locus revealed that haplotypes underlying the CNP and the SNP corresponded to classical, functional alleles of CYP2A6 gene that regulate nicotine metabolism and explained 2% of the phenotypic variance of CPD (ANOVA F-test P=9.5 x 10(-52)). These haplotypes were also associated with smoking-related diseases, including lung cancer, chronic obstructive pulmonary disease and arteriosclerosis obliterans.

Background & Aims Crohn's disease is an inflammatory bowel disease induced by multiple genetic and environmental factors. Genome-wide association studies have identified genetic factors that affect the risk for Crohn's disease in European populations, but information from other ethnic groups is scarce. We therefore investigated genetic factors associated with Crohn's disease in the Japanese population. Methods We performed a genome-wide association study with 372 individuals with Crohn's disease (cases) and 3389 controls, all from the Japanese population. To confirm identified associations, we performed a replication study with an independent panel of 1151 Crohn's disease cases and 15,800 controls. We also performed an association analysis using genome-wide genotype imputation in the discovery cohort. Results We confirmed associations of Crohn's disease with variants in MHC (rs7765379, P = 2.11 × 10 −59 ), TNFSF15 (rs6478106, P = 3.87 × 10 −45 ), and STAT3 (rs9891119, P = 2.24 × 10 −14 ). We identified 2 new susceptibility loci: on chromosome 4p14 (rs1487630, P = 2.40 × 10 −11 ; odds ratio, 1.33), and in the SLC25A15–ELF1-WBP4 region on 13q14 (rs7329174 in ELF1, P = 5.12 × 10 −9 ; odds ratio, 1.27). Conclusions In a genome-wide association study, we identified 2 new susceptibility loci for Crohn's disease in a Japanese population. These findings could increase our understanding of the pathogenesis of Crohn's disease.

We present a statistical model for allele-specific patterns of copy number polymorphisms (CNPs) in commercial single nucleotide polymorphism (SNP) array data. This model is based on the observation that fluorescent signal intensities tend to cluster into clouds of similar allele-specific copy number (ASCN) genotypes at each SNP locus. To capture the tendency of this clustering to be made vague by instrumental errors, our model allows for cluster memberships to overlap each other, according to a Bayesian Gaussian mixture model (GMM). This approach is flexible, allowing for both absolute scale differences and X/Y scale imbalances of fluorescent signal intensities. The resulting model is also robust toward unobserved ASCN genotypes, which can be problematic for ordinary GMMs. We illustrated the utility of the model by applying it to commercial SNP array intensity data obtained from the Illumina HumanHap 610K platform. We retrieved more than 4,000 allele-specific CNPs, though 99% of them showed rather simple allele-specific CNP patterns with only a single aneuploid haplotype among the normal haplotypes. The genotyping accuracy was assessed by two approaches, quantitative PCR and replicated subjects. The results of both of these approaches demonstrated mean genotyping error rates of 1%. We demonstrated a preliminary genome-wide association study of three hematological traits. The result exhibited that it could form the foundation for new, more effective statistical methods for the mapping of both disease genes and quantitative trait loci with genome-wide CNPs. The methods described in this work are implemented in a software package, PlatinumCNV, available on the Internet.

White blood cells (WBCs) mediate immune systems and consist of various subtypes with distinct roles. Elucidation of the mechanism that regulates the counts of the WBC subtypes would provide useful insights into both the etiology of the immune system and disease pathogenesis. In this study, we report results of genome-wide association studies (GWAS) and a replication study for the counts of the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects enrolled in the BioBank Japan Project. We identified 12 significantly associated loci that satisfied the genome-wide significance threshold of P

Background & Aims There are many genetic factors that are associated with both ulcerative colitis (UC) and Crohn's disease (CD). However, genetic factors that have distinct effects on UC and CD have not been examined. Methods We performed a comparative genome-wide association study (GWAS) and a replication study using data from 748 patients with UC and 979 with CD, selected from a Japanese population. We conducted high-resolution (4-digit) genotyping of human leukocyte antigen (HLA) alleles in patients with UC and CD and additional 905 healthy individuals (controls). We performed haplotype-based analysis using data from the GWAS and HLA alleles to associate them with UC or CD. Results The comparative GWAS and the replication study identified significant associations in the major histocompatibility complex region at 6p21 with UC and CD (rs9271366, P = 1.6 × 10 –70 ; odds ratio [OR] = 4.44). Haplotype-based analysis in the major histocompatibility complex region showed that HLA-Cw*1202-B*5201-DRB1*1502 haplotype was significantly associated with increased risk of UC compared with CD ( P = 1.1 × 10 −33 ; OR=6.58), accounting for most of the associations observed in the GWAS. Compared with the controls, this HLA haplotype significantly increases susceptibility to UC ( P = 4.0 × 10 −21 ; OR=2.65), but reduces risk for CD ( P = 1.1 × 10 −7 ; OR=0.40). Distinct effects of this HLA haplotype on UC and CD were independent of other HLA alleles and haplotypes ( P = 2.0 × 10 −19 and P = 7.2 × 10 −5 , respectively). Conclusions The HLA-Cw*1202-B*5201-DRB1*1502 haplotype increases susceptibility to UC but reduces risk for CD, based on a GWAS of a Japanese population.

Obesity is a disorder with a complex genetic etiology, and its epidemic is a worldwide problem. Although multiple genetic loci associated with body mass index, the most common measure of obesity, have been identified in European populations, few studies have focused on Asian populations. Here we report a genome-wide association study and replication studies with 62,245 east Asian subjects, which identified two new body mass index-associated loci in the CDKAL1 locus at 6p22 (rs2206734, P = 1.4 × 10(-11)) and the KLF9 locus at 9q21 (rs11142387, P = 1.3 × 10(-9)), as well as several previously reported loci (the SEC16B, BDNF, FTO, MC4R and GIPR loci, P < 5.0 × 10(-8)). We subsequently performed gene-gene interaction analyses and identified an interaction (P = 2.0 × 10(-8)) between a SNP in the KLF9 locus (rs11142387) and one in the MSTN (also known as GDF8) locus at 2q32 (rs13034723). These findings should provide useful insights into the etiology of obesity.

White blood cells (WBCs) mediate immune systems and consist of various subtypes with distinct roles. Elucidation of the mechanism that regulates the counts of the WBC subtypes would provide useful insights into both the etiology of the immune system and disease pathogenesis. In this study, we report results of genome-wide association studies (GWAS) and a replication study for the counts of the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects enrolled in the BioBank Japan Project. We identified 12 significantly associated loci that satisfied the genome-wide significance threshold of P, Author Summary White blood cells (WBCs) are blood cells that mediate immune systems and defend the body against foreign microorganisms. It is well known that WBCs consist of various subtypes of cells with distinct roles, although the genetic background of each of the WBC subtypes has yet to be examined. In this study, we report genome-wide association studies (GWAS) for the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects. We identified 12 significantly associated genetic loci, and 9 of them were novel. Evaluation of the associations of these identified loci in cohorts of Caucasian populations demonstrated both ethnically common and divergent genetic backgrounds of the WBC subtypes. These loci also indicated a variety of patterns of pleiotropic associations within the hematological traits, including the other WBC subtypes, total WBC count, platelet count, or red blood cell-related traits, which suggests unique and common functional roles of these loci in the processes of hematopoiesis.

Recent studies have demonstrated that principal component analysis (PCA) can detect the presence of population mixture and admixture in a sample and thus can be used to correct population stratification in genome-wide association studies (GWAS). We propose a complementary approach to PCA that compensates for potential weaknesses associated with PCA, so that one can perform population structure analyses using limited numbers of subjects and single-nucleotide polymorphisms (SNPs). Our method first requires a PCA of the largest reference sample from a population to standardize the system. Once the system is established, it can perform PCA for each individual with a much smaller number of SNPs drawn from the same population. This is because of the introduction of the probabilistic PCA, so that the prediction of the principal components (PCs) is performed under a rigorous probabilistic framework. The subsequent linear discriminant analysis also helps to understand from which ancestries or subpopulations a given individual is more likely to derive, in terms of posterior probabilities given the predicted PCs. A real-world prototype of the system for the Japanese population is developed based on 19 260 subjects, which illustrates the potential usefulness of the system as an aid in the detection of population structures in validation samples, or to help with the correction of population stratification in GWAS.