Natsuhiko Kumasaka

The majority of immune-mediated disease (IMD) risk loci are located in non-coding regions of the genome, making it difficult to decipher their functional effects in relevant physiological contexts. To assess the extent to which alternative splicing contributes to IMD risk, we mapped genetic variants associated with alternative splicing (splicing quantitative trait loci or sQTL) in macrophages exposed to a wide range of environmental stimuli. We found that genes involved in innate immune response pathways undergo extensive differential splicing in response to stimulation and detected significant sQTL effects for over 5734 genes across all stimulation conditions. We colocalised sQTL signals for over 700 genes with IMD-associated risk loci from 22 IMDs with high confidence (PP4 ≥ 0.75). Approximately half of the colocalisations implicate lowly-used splice junctions (mean usage ratio PTPN2, a negative regulator of inflammation. Together, our findings highlight the role alternative splicing plays in IMD risk, and suggest that lowly-used splicing events significantly contribute to complex disease risk.

Background: Particulate matter (PM) exposure is associated with adverse health outcomes. However, the association between PM exposure and thyroid hormone concentrations in children has not been comprehensively evaluated. Objectives: Using an ongoing birth cohort dataset, the association between PM exposure and blood free T4 (fT4) and TSH concentrations in children aged 2 to 4 years was assessed. Methods: Data were obtained from the Japan Environment and Children's Study. Children aged 2 years and those aged 4 years were analyzed separately, with 3599 and 3431 cases included in each dataset. The generalized linear model and the quantile g-computation models were fitted. Results: Neither indoor nor outdoor PM exposures at 1.5 years were significantly associated with fT4 and TSH levels at 2 years of age. Indoor and outdoor PM10-2.5 exposures at 3 years of age were negatively associated with fT4 concentrations at 4 years of age. A simultaneous increase in PM concentrations by 1 quartile at 3 years of age resulted in a significant decrease in fT4 levels of 0.011 ng/dL at 4 years of age. Conclusion: Using a large sample, the statistical modeling results suggested an opposite association between PM exposure and fT4. However, since this association is very weak, from a clinical and epidemiological point of view, we can entirely ignore the effect of PM exposure on fT4. Therefore, we conclude that PM does not significantly influence thyroid parameters in daily life.

Understanding the influence of both genetics and environment on human health, especially early in life, is essential for shaping long-term health. Here, we utilize a nationwide prospective birth cohort, the Japan Environment and Children’s Study (JECS), to conduct a large-scale population-based genetic study using biannual questionnaire surveys and biological and physical measurements collected from both parents and their children up to the age of 4, since the participant mothers were pregnant. Analyses of genome-wide genotyping for 80,639 child participants with parental consent and sufficient DNA from cord blood samples represent the genetic diversity of the general population in Japan. Systematic genome-wide association studies of 1,255 child health and developmental traits (including, e.g., food allergy, anthropometry measurements or ASQ-3 developmental screening) and parental environmental exposure traits (including, e.g., mercury or PFAS exposure) identify 6,073 common genomic loci (2,332 of which passed the phenome-wide significance threshold P = 4. 0 × 10 ⁻¹¹ ), of which 18-20% of loci represent novel associations not previously reported, including loci with potential therapeutic relevance. Additional longitudinal GWAS of BMI, using Gaussian process regression, identified 158 independent loci, of which 41 were not identified by age-stratified cross-sectional GWAS. These associations can also be used to predict an individual’s growth trajectory based on their genetic background. In addition, proxy-based genetic correlation analysis identified composite genetic signals linking maternal environmental exposures during pregnancy and child traits after birth. Together with studies of genetic risk factors and environmental exposures, across time and multiple outcomes, these demonstrate the uniqueness and value of the JECS data.

Gaussian processes (GPs) are a powerful and useful approach for modelling nonlinear phenomena in various scientific fields, including genomics and genetics. This review focuses on the application of GPs in genetic association mapping. The aim is to identify genetic variants that alter gene regulation along continuous cellular states at the molecular level, as well as disease susceptibility over time and space at the population level. The challenges and opportunities in this field are also addressed.

The mutation of the X-linked protocadherin (PCDH) 19 gene in heterozygous females causes epilepsy. However, because of the erosion of X-chromosome inactivation (XCI) in female human pluripotent stem cells, precise disease modeling often leads to failure. In this study, using a mathematical approach and induced pluripotent stem cells retaining XCI derived from patients with PCDH19 missense mutations, we found that heterotypic conditions, which are composed of wild-type and missense PCDH19, led to significant cell-to-cell proximity and impaired neuronal differentiation, accompanied by the aberrant accumulation of doublecortin, a microtubule-associated protein. Our findings suggest that ease of adhesion between cells expressing either wild-type or missense PCDH19 might lead to aberrant cell aggregation in early embryonic phases, causing poor neuronal development.

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system¹. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug–target interactions to provide 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 that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

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 custom CellPhoneDB.org module. 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.