Citations

Abstract The trabecular meshwork (TM) and ciliary body (CB) regulate aqueous humor dynamics and intraocular pressure (IOP), and TM/Schlemm’s canal (SC) dysfunction underlies glaucoma. Here, we present a spatially resolved multi-omics atlas of human TM and CB, integrating snRNA-seq, scRNA-seq, and snATAC-seq from over one million cells and nuclei across 112 donors with Xenium spatial transcriptomics. We identified 9 major cell classes and 21 cell types, revealing heterogeneity, including undercharacterized fibroblast and epithelial subpopulations. Spatial mapping supported TM fibroblast zonation and CB epithelial organization. Regulatory analyses identified cell type–specific programs, including OTX/PAX networks in CB epithelium and SMAD3/TGF-β signaling in fibroblasts. Integration with glaucoma loci showed enrichment of non-coding variants in regulatory elements associated with POAG and PACG. Age- and ancestry-associated remodeling revealed divergent fibroblast aging with increased PIEZO1 , suggesting impaired outflow and elevated IOP. Together, this high-resolution atlas links cellular, regulatory, and genetic variation to anterior segment function and glaucoma susceptibility.

Abstract Recent research suggests higher circulating lymphocyte counts may protect against colorectal cancer (CRC). However, the role of specific lymphocyte subtypes and activation states remain unclear. CD4+ T cells—a highly dynamic lymphocyte subtype—undergo gene expression changes upon activation that are critical to their effector function. Previous studies using bulk tissue have limited our understanding of their role in CRC risk to static associations. We applied Mendelian randomization (MR) and genetic colocalisation to evaluate causal relationships of gene expression on CRC risk across multiple CD4+ T cell subtypes and activation states. Genetic proxies were obtained from single-cell transcriptomic data, allowing us to investigate the causal effect of expression of 1,805 genes across CD4+ T cell activation states on CRC risk (78,473 cases; 107,143 controls). Analyses were stratified by CRC anatomical subsites and sex, with sensitivity analyses assessing whether the observed effect estimates were likely to be CD4+ T cell-specific. We identified 6 genes—FADS2, FHL3, HLA-DRB1, HLA-DRB5, RPL28, and TMEM258—with strong evidence for a causal role in CRC development (FDR-P < 0.05; colocalisation H4 > 0.8). Causal estimates varied by CD4+ T cell subtype, activation state, CRC subsite and sex. However, many of genetic proxies used to instrument gene expression in CD4+ T cells also act as eQTLs in other tissues, highlighting the challenges of using genetic proxies to instrument tissue-specific expression changes. We demonstrate the importance of capturing the dynamic nature of CD4+ T cells in understanding CRC risk, and prioritize genes for further investigation in cancer prevention.

Abstract With the increasing volume of biomedical experimental data, standardizing, sharing, and integrating heterogeneous experimental data across domains has become a major challenge. To address this challenge, we have developed an ontology-supported Study-Experiment-Assay (SEA) common data model (CDM), which includes 10 core and 3 auxiliary classes based on object-oriented modeling. SEA CDM uses interoperable ontologies for data standardization and knowledge inference. Building on the SEA CDM, we developed the Ontology-based SEA Network (OSEAN) relational database and knowledge graph, along with a set of ETL (Extract, Transform, Load) and query tools, and further applied them to represent 1,278 immune studies with over two million samples from three resources: VIGET, ImmPort, and CELLxGENE. Using simple, robust queries and analyses, our research identified multiple scientific insights into sex-specific immune responses, such as neutrophil degranulation and TNF binding to physiological receptors, following live attenuated and trivalent inactivated influenza vaccination. The novel SEA CDM system lays a foundation for establishing an integrative biodata ecosystem across biological and biomedical domains.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Background Left ventricular aneurysm (LVA) is a significant complication of myocardial infarction that may lead to global left ventricular (LV) dysfunction. However, the exact mechanism underlying the abnormal function has not been elucidated. In this study we tested the hypothesis that changes in LV geometry cause both an increase in wall stress and a change in the temporal distribution of stress in the LVA border zone (BZ) during systole. Methods Transmural anteroapical infarcts were created in adult Dorsett sheep (n=8) and were allowed to mature into LVAs for 10 weeks. Animals were imaged subsequently using MRI with simultaneous recording of intraventricular pressures. Cardiac models were constructed from the MRI images at end-diastole, isovolumic systole, peak-systole and end-systole. Two short-axis slices, 1 basal and 1 apical were analyzed. The apical slice included the septal and anterior component of the aneurysm as well as the corresponding BZs and normal myocardium. Regional wall stresses were calculated using finite element analysis and compared with stresses in corresponding regions from normal control sheep (n=7). Results In the LVA group, stress was significantly increased in the BZ at the end-diastolic, isovolumic, peak-systolic, and end-systolic instants ( P <0.001 for all). In addition the temporal distribution of stress was significantly altered with maximum stress occurring at peak instead of isovolumic systole. Conclusions Geometric changes in the LVA hearts increased wall stress and altered its temporal distribution in the BZ region. Correlation of this finding with the corresponding regional blood flow, oxygen consumption, and mechanical systolic performance may help elucidate the mechanism underlying the observed global LV dysfunction.

Abstract Background: Evidence for aspirin's chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk. Methods: Human colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labeling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N = 3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N = 31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). Results: Altered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2, and ARFIP2 expression, and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR: 1.08, 95% CI, 1.03–1.13; OR: 3.33, 95% CI, 2.46–4.50; and OR: 1.15, 95% CI, 1.02–1.29, respectively). Conclusions: MCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation, indicating a possible role in aspirin's reduction of metastasis. Impact: Our approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

Abstract Background: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer–metabolite associations using two-sample Mendelian randomization (MR). Methods: The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Results: Thirty-five metabolites were strongly associated with prostate cancer (P &lt; 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. Conclusions: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. Impact: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi‐institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application‐specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48–61, 2018. © 2017 International Society for Magnetic Resonance in Medicine.