Biology subjects

Ng, B.

Publications and source records attributed to Ng, B..

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bioRxiv2022

The molecular genetic landscape of human brain size variation

Human brain size increases dynamically through early development, peaks in adolescence, and varies up to two-fold among adults. Although previous studies have elucidated changes in brain size across evolution, development, traits, and diseases, the molecular underpinnings of interindividual variation in brain size remain unknown. Here, we leverage postmortem brain RNA sequencing and estimates of brain weight (BW) in 2,531 individuals across three independent datasets, to identify 928 genes that show genome-wide significant associations with either higher or lower BW (BW+, BW-, respectively). These BW gene sets showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto developmental, functional and cellular axes of brain organization. Expression differences among evolutionarily conserved BW genes were predictive of interspecies differences in brain size, and functional annotation of BW genes revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses of in vivo neuroimaging phenotypes confirmed that the genetic regulation of BW-transcripts influences cortical surface area and volume, as well as behavioral traits related to brain function and disease. Cumulatively, our study represents a major step towards the goal of delineating the causal mechanisms of human brain size variation in health and disease.

neuroscience↗

bioRxiv2021

Neurons derived from individual early Alzheimer's disease patients reflect clinical vulnerability

Establishing preclinical models of Alzheimers disease that predict clinical outcomes remains a critically important, yet to date not fully realised, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimers disease where we sought a match between individual disease characteristics in cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-{beta} burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-{beta} in vitro as measured by synapse loss and function. Our findings indicate that patient induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimers disease pathology, but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individuals in-life clinical vulnerability thus represent a tractable method of Alzheimers disease modelling using clinical data in combination with cellular phenotypes.

neuroscience↗

bioRxiv2020

Similarities and differences between IL11 and IL11RA1 knockout mice for lung fibro-inflammation, fertility and craniosynostosis

Genetic loss of function (LOF) in IL11RA infers IL11 signaling as important for fertility, fibrosis, inflammation and craniosynostosis. The impact of genetic LOF in IL11 has not been characterized. We generated IL11-knockout (Il11-/-) mice, which are born in normal Mendelian ratios, have normal hematological profiles and are protected from bleomycin-induced lung fibro-inflammation. Noticeably, baseline IL6 levels in the lungs of Il11-/- mice are lower than those of wild-type mice and are not induced by bleomycin damage, placing IL11 upstream of IL6. Lung fibroblasts from Il11-/- mice are resistant to pro-fibrotic stimulation and show evidence of reduced autocrine IL11 activity. Il11-/- female mice are infertile. Unlike Il11ra1-/- mice, Il11-/- mice do not have a craniosynostosis-like phenotype and exhibit mildly reduced body weights. These data highlight similarities and differences between LOF in IL11 or IL11RA while establishing further the role of IL11 signaling in fibrosis and stromal inflammation.

molecular biology↗

bioRxiv2020

Genetic variation in CSMD1 affects amygdala connectivity and prosocial behavior

The amygdala is one of the most widely connected structures in the primate brain and plays a key role in social and emotional behavior. Here, we present the first genome-wide association study (GWAS) of whole-brain resting-state amygdala networks to discern whether connectivity in these networks could serve as an endophenotype for social behavior. Leveraging published resting-state amygdala networks as a priori endophenotypes in a GWAS meta-analysis of two adolescent cohorts, we identified a common polymorphism on chr.8p23.2 (rs10105357 A/G, MAF (G)=0.35) associated with stronger connectivity in the medial amygdala network (beta=0.20, p=2.97x10-8). This network contains regions that support reward processes and affiliative behavior. People carrying two copies of the minor allele for rs10105357 participate in more prosocial behaviors (t=2.644, p=0.008) and have higher CSMD1 expression in the temporal cortex (t=3.281, p=0.002) than people with one or no copy of the allele. In post-mortem brains across the lifespan, we found that CSMD1 expression is relatively high in the amygdala (2.79 fold higher than white matter, p=1.80x10-29), particularly so for nuclei in the medial amygdala, reaching a maximum in later stages of development. Amygdala network endophenotyping has the potential to accelerate genetic discovery in disorders of social function, such as autism, in which CSMD1 may serve as a diagnostic and therapeutic target.

neuroscience↗

bioRxiv2019

Learning immune cell differentiation

The mammalian genome contains several million cis-regulatory elements, whose differential activity marked by open chromatin determines organogenesis and differentiation. This activity is itself embedded in the DNA sequence, decoded by sequence-specific transcription factors. Leveraging a granular ATAC-seq atlas of chromatin activity across 81 immune cell-types we show that a convolutional neural network ("AI-TAC") can learn to infer cell-type-specific chromatin activity solely from the DNA sequence. AI-TAC does so by rediscovering, with astonishing precision, binding motifs for known regulators, and some unknown ones, mapping them with high concordance to positions validated by ChIP-seq data. AI-TAC also uncovers combinatorial influences, establishing a hierarchy of transcription factors (TFs) and their interactions involved in immunocyte specification, with intriguingly different strategies between lineages. Mouse-trained AI-TAC can parse human DNA, revealing a strikingly similar ranking of influential TFs. Thus, Deep Learning can reveal the regulatory syntax that drives the full differentiative complexity of the immune system.

genomics↗

bioRxiv2019

Cascading Epigenomic Model for GWAS

The majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, comprises two types of models: one for linking cis genetic effects to epigenomic variation and another for linking cis epigenomic variation to gene expression. Applying these models in cascade to GWAS summary statistics generates gene level statistics that reflect genetically-driven epigenomic effects. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. CEWAS thus presents a novel means for exploring the regulatory landscape of GWAS variants in uncovering disease mechanisms. SummaryThe majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, combines the effect of genetic variants on DNA methylation as well as gene expression. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes.

bioinformatics↗

bioRxiv2019

A cryo-tomography-based volumetric model of the actin core of mouse vestibular hair cell stereocilia lacking plastin 1

Electron cryo-tomography allows for high-resolution imaging of stereocilia in their native state. Because their actin filaments have a higher degree of order, we imaged stereocilia from mice lacking the actin crosslinker plastin 1 (PLS1). We found that while stereocilia actin filaments run 13 nm apart in parallel for long distances, there were gaps of significant size that were stochastically distributed throughout the actin core. Actin crosslinkers were distributed through the stereocilium, but did not occupy all possible binding sites. At stereocilia tips, protein density extended beyond actin filaments, especially on the side of the tip where a tip link should anchor. Along the shaft, repeating density was observed that corresponds to actin-to-membrane connectors. In the taper region, most actin filaments terminated near the plasma membrane. The remaining filaments twisted together to make a tighter bundle than was present in the shaft region; the spacing between them decreased from 13 nm to 9 nm. Our models illustrate detailed features of distinct structural domains that are present within the stereocilium.

neuroscience↗

bioRxiv2019

Fibroblast-specific IL11 signaling is required for lung fibrosis and inflammation

Tissue injury leads to activation of resident stromal, parenchymal and immune cells to initiate reparative processes that, if unresolved, can lead to fibrosis and organ damage. The directionality of effect between fibrosis and inflammation in the lung has been a point of debate for many years. Here, we tested the hypothesis that Interleukin 11 (IL11) signaling in fibroblasts is of primary importance for pulmonary fibrosis and that this event is upstream of lung inflammation. We generated mice with loxP-flanked Il11ra1 alleles and crossed them to a Col1a2-CreERT strain to enable Il11ra1 deletion in adult fibroblasts (Il11ra1-CKO mice). Lung fibroblasts from Il11ra1-CKO mice were selectively deleted for Il11ra1 and refractory to TGF{beta}1 stimulation. In the mouse model of bleomycin-induced lung fibrosis, Il11ra1-CKO mice had markedly reduced pulmonary fibrosis and lesser lung damage, which was accompanied by diminished ERK activation in the stromal compartment. Bleomycin lung injury in Il11ra1-CKO mice was also associated with diminished STAT3 activation in inflammatory cells, fewer pulmonary immune cell infiltrates and almost complete inhibition of NF-kB activation. These data reveal an essential role for IL11 signaling in fibroblasts for lung fibrosis and show that inflammation in the lung can be secondary to stromal activation.

cell biology↗

bioRxiv2019

Interleukin 11 expression causes murine inflammatory bowel disease

Interleukin 11 (IL11) is a profibrotic cytokine, secreted by myofibroblasts and damaged epithelial cells. Smooth muscle cells (SMCs) also secrete IL11 under pathological conditions and express the IL11 receptor. Here we examined the effects of SMC-specific, conditional expression of murine IL11 in a transgenic mouse (Il11SMC). Within days of transgene activation, Il11SMC mice developed loose stools and progressive bleeding and rectal prolapse, which was associated with a 65% mortality by two weeks. The bowel of Il11SMC mice was inflamed, fibrotic and had a thickened wall, which was accompanied by activation of ERK and STAT3. In other organs, including heart, lung, liver, kidney and skin there was a phenotypic spectrum of fibro-inflammation, together with consistent ERK activation. To investigate further the importance of stromal-derived IL11 in the inflammatory bowel phenotype we used a second model with fibroblast-specific expression of IL11, the Il11Fib mouse. This additional model largely phenocopied the Il11SMC bowel phenotype. These data show that IL11 secretion from the stromal niche is sufficient to drive inflammatory bowel disease in mice. Given that IL11 expression in colonic stromal cells predicts anti-TNF therapy failure in patients with ulcerative colitis or Crohns disease, we suggest IL11 as a therapeutic target for inflammatory bowel disease.

pathology↗

bioRxiv2019

Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease

Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in the HTT gene. In an attempt to identify genomic modifiers that contribute towards the age of onset of HD, we performed a transcriptome wide association study assessing heritable differences in genetically determined expression in diverse tissues, employing genome wide data from over 4,000 patients. This identified genes that showed evidence for colocalization and replication, with downstream functional validation being performed in isogenic HD stem cells and patient brains. Enrichment analyses detected associations with various biologically-relevant gene sets and striatal coexpression modules that are mediated by CAG length. Further, cortical coexpression modules that are relevant for HD onset were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder.

genomics↗

bioRxiv2019

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression

Complexity of cell-type composition has created much skepticism surrounding the interpretation of brain bulk-tissue transcriptomic studies. We generated paired tissue genome-wide gene expression data and immunohistochemistry data, enabling us to assess statistical methods for modeling and estimating cellular heterogeneity in the brain. We demonstrate that several algorithms that rely on single-cell and cell-sorted data to define cell marker gene sets yield accurate relative and absolute estimates of constituent cell-type proportions.

neuroscience↗

bioRxiv2018

IL-11 neutralising therapies target hepatic stellate cell-induced liver inflammation and fibrosis in NASH

The transformation of hepatic stellate cells (HSCs) into myofibroblasts is the defining pathobiology in non-alcoholic steatohepatitis (NASH). Here we show that key NASH factors induce IL-11, which drives an autocrine and ERK-dependent activation loop to initiate and maintain HSC-to-myofibroblast transformation, causing liver fibrosis. IL-11 is upregulated in NASH and Il11ra1-deleted mice are strongly protected from liver fibrosis, inflammation and steatosis in murine NASH. Therapeutic inhibition of IL11RA or IL-11 with novel neutralizing antibodies robustly inhibits NASH pathology in preclinical models and reverses established liver fibrosis by promoting HSC senescence and favourable matrix remodelling. When given early in NASH, IL-11 inhibition prevents liver inflammation and steatosis, reverses severe hepatocyte damage and reduces hepatic immune cells and TGF{beta}1 levels. Our findings show an unappreciated and central role for IL-11 in HSCs and prioritise IL-11 signalling as a new therapeutic target in NASH while revealing an unexpected pro-inflammatory function for IL-11 in stromal immunity.

molecular biology↗

bioRxiv2018

The costs of misdiagnosed asthma in a longitudinal study of the general population

ObjectivesA current diagnosis of asthma cannot be objectively confirmed in many patients with physician-diagnosed asthma. Estimates of resource use in overdiagnosed cases of asthma are necessary to measure the burden of overdiagnosis and evaluate strategies to reduce this burden. We assessed the difference in asthma-related healthcare resource use between patients with a confirmed asthma diagnosis and those with asthma ruled out.\n\nDesignPopulation-based prospective cohort study.\n\nSettingParticipants were recruited through random-digit dialling of both landlines and mobile phones in BC, Canada.\n\nParticipantsWe included 345 individuals [≥]12 years of age with a self-reported physician diagnosis of asthma which was confirmed by a bronchodilator reversibility or methacholine challenge test at the end of the 12-month follow-up.\n\nPrimary and secondary outcome measuresSelf-reported annual asthma-related direct healthcare costs (2017 Canadian dollars), outpatient physician visits, and medication use from the Canadian healthcare system perspective.\n\nResultsAsthma was ruled out in 86 (24.9%) participants. Average annual asthma-related direct healthcare costs for participants with confirmed asthma were $497.9 (SD $677.9), and $307.7 (SD $424.1) for participants with asthma ruled out. In the adjusted analyses, a confirmed diagnosis was associated with higher direct healthcare costs (Relative Ratio [RR]=1.60, 95%CI 1.14-2.22), increased rate of specialist visits (RR=2.41, 95%CI 1.05-5.40) and reliever medication use (RR=1.62, 95%CI 1.09-2.35), but not primary care physician visits (p=0.10) or controller medication use (p=0.11).\n\nConclusionsA quarter of individuals with a physician diagnosis of asthma did not have asthma after objective re-evaluation. These participants still consumed a significant amount of asthma-related healthcare resources. The population-level economic burden of asthma overdiagnosis could be substantial.\n\nStrengths and limitations of this studyO_LIParticipants were recruited through random sampling of the general population in the province of British Columbia.\nC_LIO_LIAsthma diagnosis was confirmed or ruled out using sequential guideline-recommended objective airway tests.\nC_LIO_LIHealthcare resource use was self-reported, potential recall bias may have led to reduced accuracy.\nC_LIO_LIThe study was unable to evaluate the indirect costs of overdiagnosis or the cost-savings from correcting the diagnosis.\nC_LIO_LIThe generalizability of the results may be limited by regional differences in medical costs and practices.\nC_LI

epidemiology↗

bioRxiv2018

DNA Methylation Network Estimation with Sparse Latent Gaussian Graphical Model

Inferring molecular interaction networks from genomics data is important for advancing our understanding of biological processes. Whereas considerable research effort has been placed on inferring such networks from gene expression data, network estimation from DNA methylation data has received very little attention due to the substantially higher dimensionality and complications with result interpretation for non-genic regions. To combat these challenges, we propose here an approach based on sparse latent Gaussian graphical model (SLGGM). The core idea is to perform network estimation on q latent variables as opposed to d CpG sites, with q<<d. To impose a correspondence between the latent variables and genes, we use the distance between CpG sites and transcription starting sites of the genes to generate a prior on the CpG sites latent class membership. We evaluate this approach on synthetic data, and show on real data that the gene network estimated from DNA methylation data significantly explains gene expression patterns in unseen datasets.

genomics↗

bioRxiv2018

IL-11 is a therapeutic target in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) remains a progressive disease despite best medical management. We previously identified IL-11 as a critical factor for cardiovascular fibrosis and examine here its role in pulmonary fibrosis. IL-11 is consistently upregulated in IPF genomic datasets, which we confirmed by histology. Pulmonary fibroblasts stimulated with IL-11 transform into invasive myofibroblasts whereas fibroblasts from Il11ra deleted mice did not respond to pro-fibrotic stimuli. In the mouse, injection of recombinant Il-11 or fibroblast-specific expression of Il-11 caused pulmonary fibrosis. We then generated a neutralising IL-11 binding antibody that blocks lung fibroblast activation across species. In a mouse model of IPF, anti-IL-11 therapy attenuated lung fibrosis and specifically blocked Erk activation. These data prioritise IL-11 as an accessible drug target in IPF.\n\nOne Sentence SummaryNon-canonical IL-11 signalling is a central hallmark of idiopathic pulmonary fibrosis and represents a novel target for antibody therapies.

molecular biology↗

bioRxiv2017

Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease

We use deep sequencing to identify sources of variation in mRNA splicing in the dorsolateral prefrontal cortex (DLFPC) of 450 subjects from two prospective cohort studies of aging. Hundreds of aberrant pre-mRNA splicing events are reproducibly associated with Alzheimers Disease (AD). We also generate a catalog of splicing quantitative trait loci (sQTL) effects in the human cortex: splicing of 3,198 genes is influenced by genetic variation. sQTLs are enriched among those variants influencing DNA methylation and histone acetylation. In assessing known AD loci, we report that altered splicing is the mechanism for the effects of the PICALM, CLU, and PTK2B susceptibility alleles. Further, we leverage our sQTL catalog to identify genes whose aberrant splicing is associated with AD and mediated by genetics. This transcriptome-wide association study identified 21 genes with significant associations, many of which are found in AD GWAS loci, but 8 are in novel AD loci, including FUS, which is a known amyotrophic lateral sclerosis (ALS) gene. This highlights an intriguing shared genetic architecture that is further elaborated by the convergence of old and new AD genes in autophagy-lysosomal-related pathways already implicated in AD and other neurodegenerative diseases. Overall, this study of the aging brains transcriptome provides evidence that dysregulation of mRNA splicing is a feature of AD and is, in some genetically-driven cases, causal.

genomics↗

bioRxiv2017

Brain xQTL Map: Integrating The Genetic Architecture Of The Human Brain Transcriptome And Epigenome

We perform quantitative trait locus (xQTL) analyses on a multi-omic dataset, comprising RNA sequence, DNA methylation, and histone acetylation ChIP sequence data from the dorsolateral prefrontal cortex of 411 older adult individuals. We identify SNPs that are significantly associated with gene expression, DNA methylation, and histone modification levels. Many SNPs influence more than one type of molecular feature, and epigenetic features are shown to mediate eQTLs in a number of (9%) such loci. We illustrate the utility of our new resource, xQTL Serve, in prioritizing the cell type most affected by an xQTL and in enhancing genome wide association studies (GWAS) as we report 18 additional CNS disease susceptibility loci after re-analyzing published studies.

bioinformatics↗