Biology subjects

O'Connor, L.

Publications and source records attributed to O'Connor, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Human development and inequality shape global threat patterns for terrestrial biodiversity

Biodiversity loss is driven by unsustainable human activities, yet the contextual conditions and underlying drivers of threats remain poorly understood. We assessed how protected areas, socioeconomic conditions, and biophysical factors explain global patterns of threat probabilities across six major threat types and four vertebrate taxa. We identified key explanatory variables and their associations with threats using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP). Socioeconomic conditions, specifically human development and income inequality, were the strongest predictors. Their associations were complex and non-linear: notably, high human development index (HDI) was associated with both higher and lower threat probabilities, depending on inequality and regional context. Second, land cover and biophysical variables, such as shrubland cover, tree cover, and elevation range, explained additional, but taxon-specific variation. Finally, protected areas showed limited ability to explain threat patterns. By linking threat probabilities to their contextual and socioecological conditions, we aim to build a better understanding of the systemic drivers of biodiversity loss.

ecology↗

bioRxiv2025

Staphylococcus aureus inhibits the NLRP3 inflammasome in macrophages during the early phases of intracellular infection, but not the late phases

Staphylococcus aureus (S. aureus) is a highly virulent pathogen responsible for chronic infections such as osteomyelitis. Although its interaction with the host immune system has been widely studied, the specific role of inflammasomes in regulating the infection within macrophages remains unclear. We investigated this question using bone marrow-derived macrophages infected with S. aureus and observed a significant reduction in intracellular bacterial load beginning at 18 hours post-infection (hpi), which continued through 96 hpi. Notably, robust activation of the NLRP3 inflammasome--including inflammasome assembly, IL-1{beta} and GSDMD maturation, and pyroptosis--occurred only after 18 hpi. This led us to hypothesize that S. aureus suppresses inflammasome activation during early infection. Supporting this, infected BMDMs failed to respond robustly to LPS and nigericin up to 18 hpi, with partial recovery at later timepoints, suggesting that S. aureus initially inhibits NLRP3 signaling to persist within macrophages but is later counteracted by the host response.

immunology↗

bioRxiv2025

Proteomic characterisation of three independent series of sequential cystic fibrosis strains in an international Pseudomonas aeruginosa reference panel indicates positive selection in late infection strains.

Pseudomonas aeruginosa is a frequent cause of chronic opportunistic infections in people with cystic fibrosis (CF). It is a highly diverse and adaptable Gram-negative bacterium that thrives in many environments. It is well recognised that P. aeruginosa adapts over time of colonisation to facilitate chronic infection including loss of virulence factors, however proteomic analyses of the adaptation to chronic infection have been limited. We previously collated and characterised an international panel of P. aeruginosa strains from different clinical presentations and geographical regions. Within this panel were three series of sequential isolates from people with CF, comprising eight strains in total which present an excellent opportunity to seek potential conserved adaptations that may be involved in driving chronic colonisation in the CF lung. We compared the proteomes of all eight strains (early versus respective late) to examine whether there were any changes in the proteomes over time of colonisation that were common to the three series of chronic P. aeruginosa infection isolates from three different patients. We identified 11 proteins that showed increased abundance in late isolates from all three patient series, many of which are reported to be involved in virulence, regulation of virulence or response to hypoxia and include cystic fibrosis inhibitory factor repressor (CifR), WspR, two two-component response regulators (PA2572 and PA3702), and transcriptional regulator (PA2551). Moreover, we identified three proteins (PA2572, PA3819 and PA5028) that showed increased abundance in all five late isolates from three people with CF. The probability of this being a random event is 5.06 x 10-53 and consequently is very strong evidence of positive selection. The increased abundance of PA2573 and PA3819 appears to improve the fitness P. aeruginosa to antibiotics and oxidative stress. Overall, despite the diversity within this species, there appear to be common mechanisms of adaptation in the cystic fibrosis lung.

microbiology↗

bioRxiv2024

Long-term adaptation to hypoxia provides insight into mechanisms facilitating the switch of Pseudomonas aeruginosa to chronic lung infections

Opportunistic bacterial infections are an increasing threat, especially for immunocompromised individuals such as people with cystic fibrosis (CF), driving morbidity and mortality. Pseudomonas aeruginosa is a key pathogen associated with chronic lung infections, that has been extensively studied in this context, but the mechanism(s) driving its adaptation towards chronic colonisation in the lung are not fully understood. This work focuses on the adaptations of P. aeruginosa to long-term hypoxia, one of the important environmental pressures present in the CF lung, to investigate whether it drives the development of persistence in CF patients. We used an experimental evolution approach to investigate how an early CF strain adapted to 6% oxygen over 28 days. We focussed on the impact of long-term hypoxia on the proteome and investigated the emergence of stable changes in phenotype. Changes in the abundance of >140 proteins were observed compared to the ancestral strain, including proteins involved in antibiotic resistance, stress response, iron homeostasis, biofilm formation and those previously associated with chronic infection. Significant changes in the abundance of proteins regulating cellular c-di-GMP levels were also observed. We show that two distinct P. aeruginosa small colony variants (SCVs) emerged, one exclusively in hypoxia exposed cultures. Hypoxia-adapted cultures developed resistance to 8 out of 13 antibiotics tested; increased biofilm and exopolysaccharide production; and decreased pyocyanin production, consistent with the changes in the proteome. All hypoxia-adapted cultures showed decreased siderophore production. Overall, we demonstrate that long-term hypoxia exposure contributes to multiple changes in phenotype and proteome that are frequently observed in P. aeruginosa CF lung chronic infection isolates. This suggests that hypoxia is driving these adaptations, at least in part, and opens a new path to treatment. Author SummaryOpportunistic antibiotic-resistant bacterial infections are an increasing threat, particularly for immunocompromised individuals such as people with cystic fibrosis (CF). These infections increase disease severity, the number of deaths and healthcare costs. Pseudomonas aeruginosa is a major pathogen in this context, causing persistent infections, yet the mechanisms driving its adaptation towards chronic colonisation in the CF lung are not understood. We investigated the adaptations that P. aeruginosa exposed to low oxygen conditions (an important environmental pressure in the CF lung) for 28 days, to examine whether it drives adaptations that lead to chronic infection. We found that prolonged exposure to hypoxia induced stable changes in P. aeruginosa, which are distinct from those reported after short term exposure. We observed multiple adaptations in hypoxia adapted cultures, many of which were associated with important signalling networks linked to lifestyle shifts in bacteria and several were also observed in isolates that had adapted to chronic infection. Similar adaptive responses in other opportunistic environmental pathogens suggest that this process of adaptation could be targeted to create universal therapeutic approaches preventing antibiotic overuse and improving patient outcomes.

microbiology↗

bioRxiv2024

Narratives for positive nature futures in Europe

O_LIThe Nature Futures Framework (NFF) is a novel tool for the development of positive scenarios centred on the relationship of nature and people, emphasising biodiversity as part of the solution to environmental challenges across various spatial and temporal scales, explicitly addressing a plurality of values for nature. C_LIO_LIIn this work, we describe the process that has led to the formulation of continental-scale positive narratives for conservation in Europe based on the NFF and its value perspectives (Nature for Nature; Nature for Society; Nature as Culture), through a stakeholder group elicitation. We focused on 6 topics in the narratives: Nature Protection and Restoration; Forestry; Freshwater Ecosystems; Urban Systems; Agriculture, and Energy. We analyse differences and similarities among the narratives across these topics. C_LIO_LIWe develop three novel Nature Futures narratives for Europe with contrasting perspectives and priorities for the six topics. Within the EU socioeconomic trends and policy framework, common solutions that simultaneously tackle biodiversity conservation and instrumental and cultural Natures Contributions to People (NCP) provision emerged. C_LIO_LIThis set of narratives may integrate preferences concerning EU-level conservation targets and plausible socio-ecological development pathways, supporting the modelling of positive scenarios for nature that can be crucial in guiding policy decisions towards recovery of nature. C_LI

ecology↗

bioRxiv2024

ExPOSE: A comprehensive toolkit to perform expansion microscopy in plant protoplast systems

Expansion microscopy (ExM) achieves nanoscale imaging by physical expansion of fixed biological tissues embedded in a swellable hydrogel, enhancing the resolution of any optical microscope several-fold. While ExM is commonly used in animal cells and tissues, there are few plant specific protocols. Protoplasts are a widely used cell system across plant species, especially in studying biomolecule localization. Here, we present an approach to achieve robust expansion of plant protoplasts, termed Expansion microscopy in plant PrOtoplast SystEms (ExPOSE). We demonstrate that coupling ExPOSE with other imaging techniques, immunofluorescence and in situ hybridization chain reaction to visualize proteins and mRNAs, respectively, greatly enhances the spatial resolution of endogenous biomolecules. Additionally, in this study, we tested the effectiveness and versatility of this technique to observe biomolecular condensates in Arabidopsis protoplasts and transcription factors in maize protoplasts at increased resolution. ExPOSE can be relatively inexpensive, fast, and simple to implement.

plant biology↗

bioRxiv2024

Luminal breast epithelial cells from wildtype and BRCA mutation carriers harbor copy number alterations commonly associated with breast cancer

Cancer-associated mutations have been documented in normal tissues, but the prevalence and nature of somatic copy number alterations and their role in tumor initiation and evolution is not well understood. Here, using single cell DNA sequencing, we describe the landscape of CNAs in >42,000 breast epithelial cells from women with normal or high risk of developing breast cancer. Accumulation of individual cells with one or two of a specific subset of CNAs (e.g. 1q gain and 16q, 22q, 7q, and 10q loss) is detectable in almost all breast tissues and, in those from BRCA1 or BRCA2 mutations carriers, occurs prior to loss of heterozygosity (LOH) of the wildtype alleles. These CNAs, which are among the most common associated with ductal carcinoma in situ (DCIS) and malignant breast tumors, are enriched almost exclusively in luminal cells not basal myoepithelial cells. Allele-specific analysis of the enriched CNAs reveals that each allele was independently altered, demonstrating convergent evolution of these CNAs in an individual breast. Tissues from BRCA1 or BRCA2 mutation carriers contain a small percentage of cells with extreme aneuploidy, featuring loss of TP53, LOH of BRCA1 or BRCA2, and multiple breast cancer-associated CNAs in addition to one or more of the common CNAs in 1q, 10q or 16q. Notably, cells with intermediate levels of CNAs are not detected, arguing against a stepwise gradual accumulation of CNAs. Overall, our findings demonstrate that chromosomal alterations in normal breast epithelium partially mirror those of established cancer genomes and are chromosome- and cell lineage-specific.

cancer biology↗

bioRxiv2023

Genomic analysis reveals the presence of emerging pathogenic Klebsiella lineages aboard the International Space Station.

Klebsiella species, including Klebsiella pneumoniae, Klebsiella aerogenes, and Klebsiella quasipneumoniae, are opportunistic pathogens that are known to cause infections in humans. Hypervirulent Klebsiella pneumoniae (hvKP) is a subgroup of K. pneumoniae that has gained attention due to its global dissemination and its ability to cause invasive infections in community settings amongst immunocompetent individuals as well as its increasing levels of antibiotic resistance. Our study reports the first complete genotypic analysis including mobile genetic elements (MGEs) of Klebsiella isolates from the International Space Station (ISS). The genomes of K. pneumoniae, K. aerogenes, and K. quasipneumoniae provided valuable insights into their antimicrobial resistance, virulence, thermotolerance, disinfectant resistance, and MGEs. All isolates belonged to emerging lineages with pathogenic potential, with K. quasipneumoniae ST138 presenting spatial and temporal persistence aboard the ISS, possibly due to its genotypic profile encoding for numerous resistance genes to disinfectants and heavy metals. We also report on the isolation of a yersiniabactin encoding K. pneumoniae, belonging to the emerging high-risk ST101 clone, aboard the ISS. Potential dissemination of hvKp strains on ISS could pose a putative risk to the immunocompromised crew. The presence of MGEs containing virulent loci could facilitate horizontal gene transfer to other benign microorganisms on the ISS, potentially increasing their virulence. In addition, genetic divergence from their respective lineages for some Klebsiella genomes was predicted and hypothesized to be due to the unique spaceflight environmental pressures. These findings highlight the importance of monitoring problematic microbial communities in space to understand their surviving abilities and potential impact on human health. ImportanceThe International Space Station (ISS) is a unique hermetically sealed environment that poses environmental pressures not encountered on Earth, including microgravity and radiation While the adaptability of bacteria during spaceflight is not fully understood, recent research has suggested that it may be species and even clone specific. Given the spaceflight-induced suppression of the human immune system, it is essential to understand the genomics of potential human pathogens in spaceflight. Such understanding could provide valuable insights into species and lineages of medical astromicrobiological importance. Here, we used hybrid assembly approaches and comparative genomics to provide the first comprehensive genomic characterisation of 10 Klebsiella isolates retrieved from the ISS. Our findings revealed that K. quasipneumoniae ST138 exhibits spatial and temporal persistence aboard the ISS, with evidence of genomic divergence from the ST138 lineage on Earth. Additionally, we characterized plasmids from Klebsiella species of ISS origin, which encoded disinfectant and thermoresistance genes suggesting that these might aid adaptability. Furthermore, we identified an MGE containing a hypervirulence-associated locus belonging to a Klebsiella pneumoniae isolate of the "high risk" ST101 clone. Our work provides valuable insights into the adaptability and persistence of Klebsiella species during spaceflight, highlighting the importance of understanding the behaviour of potential pathogenic bacteria in space.

microbiology↗

bioRxiv2022

A second generation capture panel for cost-effective sequencing of genome regulatory regions in wheat and relatives

As genome resources for wheat expand at a rapid pace, it is important to update targeted sequencing tools to incorporate improved sequence assemblies and regions of previously unknown significance. Here, we developed an updated regulatory region enrichment capture for wheat (Triticum L.) and other Triticeae species. The core target space includes sequences from two Kbp upstream of each gene predicted in the Chinese Spring wheat genome (IWGSC RefSeq Annotation v1.1) and regions of open chromatin identified with ATAC-seq from wheat leaf and root samples. To improve specificity, we aggressively filtered candidate repetitive sequences using a combination of BLASTN searches to the Triticeae Repetitive Sequence Database (TREP), identification of regions with read over-coverage from previous target enrichment experiments, and k-mer frequency analyses. The final design comprises 216 Mbp of predicted hybridization space in hexaploid wheat and showed increased specificity and coverage of targeted sequences relative to previous protocols. Test captures on hexaploid and tetraploid wheat and other diploid cereals show that the assay has broad potential utility for cost-effective promoter and open chromatin resequencing and general-purpose genotyping of various Triticeae species.

genomics↗

bioRxiv2021

Partitioning gene-mediated disease heritability without eQTLs

Unknown SNP-to-gene regulatory architecture complicates efforts to link noncoding GWAS associations with genes implicated by sequencing or functional studies. eQTLs are used to link SNPs to genes, but expression in bulk tissue explains a small fraction of disease heritability. A simple but successful approach has been to link SNPs with nearby genes, but the fraction of heritability mediated by these genes is unclear, and gene-proximal (vs. gene-mediated) heritability enrichments are attenuated accordingly. We propose the Abstract Mediation Model (AMM) to estimate (1) the fraction of heritability mediated by the closest or kth-closest gene to each SNP and (2) the mediated heritability enrichment of a gene set (e.g. genes with rare-variant associations). AMM jointly estimates these quantities by matching the decay in SNP enrichment with distance from genes in the gene set. Across 47 complex traits and diseases, we estimate that the closest gene to each SNP mediates 27% (SE: 6%) of heritability, and that a substantial fraction is mediated by genes outside the ten closest. Mendelian disease genes are strongly enriched for common-variant heritability; for example, just 21 dyslipidemia genes mediate 25% of LDL heritability (211x enrichment, P = 0.01). Among brain-related traits, genes involved in neurodevelopmental disorders are only about 4x enriched, but gene expression patterns are highly informative, with detectable differences in per-gene heritability even among weakly brain-expressed genes.

genetics↗

bioRxiv2021

Identification of beneficial and detrimental bacteria that impact sorghum responses to drought using multi-scale and multi-system microbiome comparisons

BackgroundDrought is a major abiotic stress that limits agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere and may lead to enrichment of specific groups of microbes, such as Actinobacteria. How these changes ultimately affect plant health is not well understood. In parallel, model systems have been used to tease apart the specific interactions between plants and single, or small groups of microbes. However, translating this work into crop species and achieving increased crop yields within noisy field settings remains a challenge. Thus, the next scientific leap forward in microbiome research must cross the great lab-to-field divide. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key beneficial and detrimental, root associated microbes that robustly affect drought stressed plant phenotypes. ResultsFifty-three bacterial strains, originally characterized for association with Arabidopsis, were applied to sorghum seeds and their effect on root growth was monitored for seven days. Two Arthrobacter strains, members of the Actinobacteria phylum, caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, strains of Variovorax were able to protect both Arabidopsis and sorghum from the RGI caused by Arthrobacter. As a transitional system, we tested the synthetic communities through a 24-day high-throughput sorghum phenotyping assay and found that during drought stress, plants colonized by Arthrobacter were significantly smaller and had reduced leaf water content as compared to control plants. However, plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across well-watered and drought conditions. Drought responsive microbes were identified, including an enrichment in Actinobacteria, consistent with previous findings. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a newly developed method and were then able to observe that the abundance of Arthrobacter strains negatively correlated with plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of high confidence bacterial taxa that positively associated with plant growth under drought stress. ConclusionsA three-tiered experimental system connected reductionist and ecological approaches and identified beneficial and deleterious bacterial strains for sorghum under drought stress.

microbiology↗

bioRxiv2021

Contemporary clinical isolates of Staphylococcus aureus from pediatric osteomyelitis patients display unique characteristics in a mouse model of hematogenous osteomyelitis

Osteomyelitis can result from the direct inoculation of pathogens into bone during injury or surgery, or from spread via the bloodstream, a condition called hematogenous osteomyelitis (HOM). HOM disproportionally affects children, and more than half of cases are caused by Staphylococcus (S.) aureus. Laboratory models of osteomyelitis mostly utilize direct injection of bacteria into the bone or the implantation of foreign material, and therefore do not directly interrogate the pathogenesis of pediatric hematogenous osteomyelitis. In this study, we inoculated mice intravenously and characterized resultant musculoskeletal infections using two strains isolated from adults (USA300-LAC and NRS384) and five new methicillin-resistant S. aureus isolates from pediatric osteomyelitis patients. All strains were capable of creating stable infections over five weeks, although the incidence varied. Micro-computed tomography (microCT) analysis demonstrated decreases in trabecular bone volume fraction but little effect on bone cortices. Histologic assessment revealed differences in the precise focus of musculoskeletal infection, with varying mixtures of bone-centered osteomyelitis and joint-centered septic arthritis. Whole genome sequencing of three new isolates demonstrated distinct strains, two within the USA300 lineage and one USA100 isolate. Interestingly, the USA100 strain showed a distinct predilection for septic arthritis, compared to the USA300 strains, including NRS384 and LAC, which more frequently led to osteomyelitis or mixed bone and joint infections. Collectively, these data outline the feasibility of using pediatric osteomyelitis clinical isolates to study the pathogenesis of HOM in murine models and lay the groundwork for future studies investigating strain-dependent differences in musculoskeletal infection. ImportanceThe inflammation of bone tissue is called osteomyelitis, and more than half of cases are caused by an infection with the bacterium Staphylococcus aureus. In children, the most common route of infection is hematogenous, wherein bacteria seed the bone from the bloodstream without another known site of infection. Although these infections pose a significant health problem, they are understudied in the laboratory because of a dearth of robust animal models. In this study, we utilized several previously uncharacterized clinical isolates of S. aureus derived from children with bone infections to generate reproducible and stable musculoskeletal infection in mice with many features seen in human osteomyelitis, making them a valuable resource for future mechanistic and therapeutic studies.

pathology↗

bioRxiv2021

Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

IntroductionCortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subjects data from 29 cohorts in five countries (n=3439). MethodsUsing Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. ResultsNotable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. ConclusionUnlike previous studies with smaller sample sizes ([≤]318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into a nodes relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

neuroscience↗

bioRxiv2018

Functional disease architectures reveal unique biological role of transposable elements

Transposable elements (TE) comprise roughly half of the human genome. Though initially derided as \"junk DNA\", they have been widely hypothesized to contribute to the evolution of gene regulation. However, the contribution of TE to the genetic architecture of diseases and complex traits remains unknown. Here, we analyze data from 41 independent diseases and complex traits (average N=320K) to draw three main conclusions. First, TE are uniquely informative for disease heritability. Despite overall depletion for heritability (54% of SNPs, 39{+/-}2% of heritability; enrichment of 0.72{+/-}0.03; 0.38-1.23 enrichment across four main TE classes), TE explain substantially more heritability than expected based on their depletion for known functional annotations (expected enrichment of 0.35{+/-}0.03; 2.11x ratio of true vs. expected enrichment). This implies that TE acquire function in ways that differ from known functional annotations. Second, older TE contribute more to disease heritability, consistent with acquiring biological function; SNPs inside the oldest 20% of TE explain 2.45x more heritability than SNPs inside the youngest 20% of TE. Third, Short Interspersed Nuclear Elements (SINE; one of the four main TE classes) are far more enriched for blood traits (2.05{+/-}0.30) than for other traits (0.96{+/-}0.09); this difference is far greater than expected based on the weaker depletion of SINEs for regulatory annotations in blood compared to other tissues. Our results elucidate the biological roles that TE play in the genetic architecture of diseases and complex traits.

genetics↗

bioRxiv2018

Genes with high network connectivity are enriched for disease heritability

Recent studies have highlighted the role of gene networks in disease biology. To formally assess this, we constructed a broad set of pathway, network, and pathway+network annotations and applied stratified LD score regression to 42 independent diseases and complex traits (average N=323K) to identify enriched annotations. First, we constructed annotations from 18,119 biological pathways, including 100kb windows around each gene. We identified 156 pathway-trait pairs whose disease enrichment was statistically significant (FDR < 5%) after conditioning on all genes and on annotations from the baseline-LD model, a stringent step that greatly reduced the number of pathways detected; most of the significant pathway-trait pairs were previously unreported. Next, for each of four published gene networks, we constructed probabilistic annotations based on network connectivity using closeness centrality, a measure of how close a gene is to other genes in the network. For each gene network, the network connectivity annotation was strongly significantly enriched. Surprisingly, the enrichments were fully explained by excess overlap between network annotations and regulatory annotations from the baseline-LD model, validating the informativeness of the baseline-LD model and emphasizing the importance of accounting for regulatory annotations in gene network analyses. Finally, for each of the 156 enriched pathway-trait pairs, for each of the four gene networks, we constructed pathway+network annotations by annotating genes with high network connectivity to the input pathway. For each gene network, these pathway+network annotations were strongly significantly enriched for the corresponding traits. Once again, the enrichments were largely explained by the baseline-LD model. In conclusion, gene network connectivity is highly informative for disease architectures, but the information in gene networks may be subsumed by regulatory annotations, such that accounting for known annotations is critical to robust inference of biological mechanisms.

genetics↗

bioRxiv2017

Distinguishing genetic correlation from causation across 52 diseases and complex traits

Mendelian randomization (MR) is widely used to identify causal relationships among heritable traits, but it can be confounded by genetic correlations reflecting shared etiology. We propose a model in which a latent causal variable mediates the genetic correlation between two traits. Under the latent causal variable (LCV) model, trait 1 is fully genetically causal for trait 2 if it is perfectly genetically correlated with the latent causal variable, implying that the entire genetic component of trait 1 is causal for trait 2; it is partially genetically causal for trait 2 if it has a high genetic correlation with the latent variable, implying that part of the genetic component of trait 1 is causal for trait 2. To quantify the degree of partial genetic causality, we define the genetic causality proportion (gcp). We fit this model using mixed fourth moments E([Formula]12) and E([Formula]12) of marginal effect sizes for each trait, exploiting the fact that if trait 1 is causal for trait 2 then SNPs affecting trait 1 (large [Formula]) will have correlated effects on trait 2 (large 12), but not vice versa. We performed simulations under a wide range of genetic architectures and determined that LCV, unlike state-of-the-art MR methods, produced well-calibrated false positive rates and reliable gcp estimates in the presence of genetic correlations and asymmetric genetic architectures; we also determined that LCV is well-powered to detect a causal effect. We applied LCV to GWAS summary statistics for 52 traits (average N=331k), identifying partially or fully genetically causal effects (1% FDR) for 59 pairs of traits, including 30 pairs of traits with high gcp estimates (g[c]p > 0.6). Results consistent with the published literature included genetically causal effects on myocardial infarction (MI) for LDL, triglycerides and BMI. Novel findings included a genetically causal effect of LDL on bone mineral density, consistent with clinical trials of statins in osteoporosis. These results demonstrate that it is possible to distinguish between genetic correlation and causation using genetic data.

genetics↗

bioRxiv2017

Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk

Biological interpretation of GWAS data frequently involves analyzing unsigned genomic annotations comprising SNPs involved in a biological process and assessing enrichment for disease signal. However, it is often possible to generate signed annotations quantifying whether each SNP allele promotes or hinders a biological process, e.g., binding of a transcription factor (TF). Directional effects of such annotations on disease risk enable stronger statements about causal mechanisms of disease than enrichments of corresponding unsigned annotations. Here we introduce a new method, signed LD profile regression, for detecting such directional effects using GWAS summary statistics, and we apply the method using 382 signed annotations reflecting predicted TF binding. We show via theory and simulations that our method is well-powered and is well-calibrated even when TF binding sites co-localize with other enriched regulatory elements, which can confound unsigned enrichment methods. We further validate our method by showing that it recovers known transcriptional regulators when applied to molecular QTL in blood. We then apply our method to eQTL in 48 GTEx tissues, identifying 651 distinct TF-tissue expression associations at per-tissue FDR < 5%, including 30 associations with robust evidence of tissue specificity. Finally, we apply our method to 46 diseases and complex traits (average N = 289,617) and identify 77 annotation-trait associations at per-trait FDR < 5% representing 12 independent TF-trait associations, and we conduct gene-set enrichment analyses to characterize the underlying transcriptional programs. Our results implicate new causal disease genes (including causal genes at known GWAS loci), and in some cases suggest a detailed mechanism for a causal genes effect on disease. Our method provides a new way to leverage functional data to draw inferences about disease etiology.

genetics↗

bioRxiv2017

Leveraging molecular QTL to understand the genetic architecture of diseases and complex traits

There is increasing evidence that many GWAS risk loci are molecular QTL for gene ex-pression (eQTL), histone modification (hQTL), splicing (sQTL), and/or DNA methylation (meQTL). Here, we introduce a new set of functional annotations based on causal posterior prob-abilities (CPP) of fine-mapped molecular cis-QTL, using data from the GTEx and BLUEPRINT consortia. We show that these annotations are very strongly enriched for disease heritability across 41 independent diseases and complex traits (average N = 320K): 5.84x for GTEx eQTL, and 5.44x for eQTL, 4.27-4.28x for hQTL (H3K27ac and H3K4me1), 3.61x for sQTL and 2.81x for meQTL in BLUEPRINT (all P [≤] 1.39e-10), far higher than enrichments obtained using stan-dard functional annotations that include all significant molecular cis-QTL (1.17-1.80x). eQTL annotations that were obtained by meta-analyzing all 44 GTEx tissues generally performed best, but tissue-specific blood eQTL annotations produced stronger enrichments for autoimmune dis-eases and blood cell traits and tissue-specific brain eQTL annotations produced stronger enrich-ments for brain-related diseases and traits, despite high cis-genetic correlations of eQTL effect sizes across tissues. Notably, eQTL annotations restricted to loss-of-function intolerant genes from ExAC were even more strongly enriched for disease heritability (17.09x; vs. 5.84x for all genes; P = 4.90e-17 for difference). All molecular QTL except sQTL remained significantly enriched for disease heritability in a joint analysis conditioned on each other and on a broad set of functional annotations from previous studies, implying that each of these annotations is uniquely informative for disease and complex trait architectures.

genetics↗