Biology subjects

Morris, A. P.

Publications and source records attributed to Morris, A. P..

17 recordsLinked to original sources

bioRxiv2024

Combining functional annotation and multi-trait fine-mapping methods improves fine-mapping resolution at glycaemic trait loci

The Meta-Analysis of Glucose and Insulin-related traits Consortium (MAGIC) identified 242 loci associated with glycaemic traits fasting insulin (FI), fasting glucose (FG), 2h-Glucose (2hGlu), and glycated haemoglobin (HbA1c). However, for the majority, the causal variant(s) remain(s) unknown. Modelling multiple traits and integrating functional annotations have each been shown to improve fine-mapping resolution. Here, we aimed to determine whether combining these techniques would further improve fine-mapping resolution. Using single-trait fine-mapping results from FINEMAP as input, we performed multi-trait fine-mapping with flashfm at 50 loci significantly associated with more than one glycaemic trait. We used fGWAS to build models of enriched annotations by considering 32 cell-type specific and 28 static annotations. We used the prior probabilities from these models to perform annotation informed fine-mapping with both FINEMAP (single-trait) and flashfm (multi-trait). Multi-trait fine-mapping of 106 locus-trait associations significantly (p=1.23 x 10-17) reduced the median size of the credible sets accounting for 99% of the posterior probability of being causal (99CS) to 21.5 variants compared to the 60.5 variants in single-trait fine-mapping. Annotation informed single-trait fine-mapping of 211 locus-trait associations reduced (p=4.24x10-12) the median 99CS size from 72 in agnostic single-trait fine-mapping to 52 variants. Annotation informed multi-trait fine-mapping of 110 locus-trait associations led to a further significant (p=2.69x10-18) decrease in median 99CS size to 14.5 variants compared to 51.0 in annotation informed single-trait fine-mapping. In conclusion, we found that multi-trait and annotation informed fine-mapping can help to further narrow down likely causal variants at glycaemic trait loci, both separately and when combined. Author SummaryLarge-scale studies such as the Meta-analysis of glucose and insulin-related traits consortium (MAGIC) identified regions in our DNA which affect glycaemic measures related to type 2 diabetes, such as glucose and insulin levels measured after fasting overnight. However, these regions contain many DNA changes within them that are close to each other and that are inherited together. This makes identifying the DNA change responsible for the effect on glycaemic measures challenging. Fine-mapping is a statistical approach that helps to narrow down the list of DNA changes that are likely to be responsible for the association with glycaemic measures, referred to as causal DNA changes. Here we used multiple types of fine-mapping approaches together to combine their advantages. We showed that both combining data from multiple related glycaemic measures as well as including information about the likely function of DNA changes helps to narrow down the number of likely causal DNA changes. Combining both approaches led to the biggest improvement in the list of likely causal DNA changes. While this study focuses on glycaemic measures, the approaches can be applied to other measures used to monitor human health, for example blood pressure or cholesterol levels. This study highlights the benefits of combining multiple approaches to find likely causal DNA changes.

genetics↗

bioRxiv2022

Neural responses to broadband visual flicker in marmoset primary visual cortex

Temporal information is ubiquitous in natural vision and must be represented accurately in the brain to allow us to interact with a constantly changing world. Recent studies have employed a random stimulation paradigm to map the temporal response function (TRF) to luminance changes in the human EEG. This approach has revealed that the visual system, when presented with broadband visual input, actively selects distinct temporal frequencies, and retains their phase-information for prolonged periods of time. This non-linear response likely originates in primary visual cortex (V1), yet, so far it has not been investigated on a neural level. Here, we characterize the steady-state response to random broadband visual flicker in marmoset V1. In two experiments, we recorded from i) marmosets passively stimulated under general anesthesia, and ii) awake marmosets, under free viewing conditions. Our results show that LFP coupling to the stimulus was broadband and unselective under anesthesia, whereas in awake animals, it was restricted to two distinct frequency components, in the alpha and beta range. Within these frequency bands, coupling adhered to the receptive field (RF) boundaries of the local populations. The responses outside the RF did not provide evidence for a propagation of stimulus information across the cortex, contrary to results in human EEG studies. This result may be explained by short fixation durations, warranting further investigation. In summary, our findings show that during awake behavior V1 neural responses to broadband information are selective for distinct frequency bands, and that this selectivity is likely controlled actively by top-down mechanisms.

neuroscience↗

bioRxiv2021

Visual perturbation of balance suggests impaired neuromuscular stability but intact visuo-motor control in Parkinson's disease

Postural instability marks one of the most disabling features of Parkinsons disease (PD), but only reveals itself after affected brain areas have already been significantly damaged. Thus, there is a need to detect deviations in balance and postural control before visible symptoms occur. In this study, we visually perturbed balance in the anterior-posterior direction using sinusoidal oscillations of a moving room in virtual reality at different frequencies. We tested three groups: individuals with PD under dopaminergic medication, an age-matched control group, and a group of young healthy adults. We tracked their centre of pressure and their full-body motion. We investigated sway amplitudes and applied newly introduced phase-locking analyses to investigate responses across participants bodies. Patients exhibited significantly higher sway amplitudes as compared to the control subjects. However, their sway was phase-locked to the visual motion like that of age-matched and young healthy adults. Furthermore, all groups successfully compensated for the visual perturbation by - most likely reflexively - phase-locking their sway to the stimulus. As frequency of the perturbation increased, distribution of phase-locking (PL) across the body revealed a shift of the highest PL-values from the upper body towards the hip-region for young healthy adults, which could not be observed in patients and elderly healthy adults. Our findings suggest an impaired neuromuscular stability, but intact visuomotor processing in early stages of PD, while less flexibility to adapt postural strategy to different perturbations revealed to be an effect of age rather than disease. New & NoteworthyA better understanding of visuomotor control in Parkinsons disease (PD) potentially serves as a tool for earlier diagnosis, which is crucial for improving patients quality of life. In our study, we assess body sway responses to visual perturbations of the balance control system in patients with early-to-mid stage PD, using motion tracking along with recently established phase-locking techniques. Our findings suggest patients at this stage to have an impaired muscular stability but intact visuomotor control.

neuroscience↗

bioRxiv2020

Discovery and fine-mapping of kidney function loci in first genome-wide association study in Africans

Genome-wide association studies (GWAS) for kidney function have uncovered hundreds of risk loci, primarily in populations of European ancestry. We conducted the first GWAS of estimated glomerular filtration rate (eGFR) in Africa in 3288 Ugandans and replicated the findings in 8224 African Americans. We identified two loci associated with eGFR at genome-wide significance (p<5x10-8). The most significantly associated variant (rs2433603, p=2.4x10-9) in GATM was distinct from previously reported signals. A second association signal mapping near HBB (rs141845179, p=3.0x10-8) was not significant after conditioning on a previously reported SNP (rs334) for eGFR. However, fine-mapping analyses highlighted rs141845179 to be the most likely causal variant at the HBB locus (posterior probability of 0.61). A trans-ethnic GRS of eGFR constructed from previously reported lead SNPs was not predictive into the Ugandan population, indicating that additional large-scale efforts in Africa are necessary to gain further insight into the genetic architecture of kidney disease.

genetics↗

bioRxiv2019

Simultaneous analysis of open chromatin, promoter interactions and gene expression in stimulated T cells implicates causal genes for rheumatoid arthritis

Genome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T-cells over 24 hours, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T-cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.

genomics↗

bioRxiv2019

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality1,2. We performed multi-ancestry (N=293,051) and European only (N=271,570) genome-wide association (GWAS) meta-analyses for the PR interval, discovering 210 loci of which 149 are novel. Variants at all loci nearly doubled the percentage of heritability explained, from 33.5% to 62.6%. We observed enrichment for genes involved in cardiac muscle development/contraction and the cytoskeleton highlighting key regulation processes for atrioventricular conduction. Additionally, 19 novel loci harbour genes underlying inherited monogenic heart diseases suggesting the role of these genes in cardiovascular pathology in the general population. We showed that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease risk, including distal conduction disease, AF, atrioventricular pre-excitation, non-ischemic cardiomyopathy, and coronary heart disease. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

genetics↗

bioRxiv2019

Identification of type 2 diabetes loci in 433,540 East Asian individuals

Meta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.\n\nType 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic {beta} cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

genetics↗

bioRxiv2019

methylSCOPA and META-methylSCOPA: software for the analysis and aggregation of epigenome-wide association studies of multiple correlated phenotypes

BackgroundMulti-phenotype genome-wide association studies (MP-GWAS) of correlated traits have greater power to detect genotype-phenotype associations than single-trait GWAS. However, no multi-phenotype analysis method exists for epigenome-wide association studies (EWAS).\n\nResultsWe extended the SCOPA approach developed by us to \"methylSCOPA\" software in C++ by reversely regressing DNA hyper/hypo-methylation information on a linear combination of phenotypes. We evaluated two models of association between DNA methylation and fasting glucose (FG) and insulin (FI) levels: Model 1, including FG, FI, and three measured potential confounders (body mass index [BMI], fasting serum triglyceride levels [TG], and waist/hip ratio [WHR]), and Model 2, including FG and FI corrected for the effects of BMI, TG, and WHR. Both models were additionally corrected for participant sex and smoking status (current/ever/never). We meta-analyzed the cohort-specific MP-EWAS results with our novel software META-methylSCOPA, mapped genomic locations to CGCh37/hg19, and adopted P<1x10-7 to denote epigenome-wide significance. We used the Illumina Infinium HumanMethylation450K BeadChip array data from the Northern Finland Birth Cohorts (NFBC) 1966/1986. We quality-controlled the data, regressed out the effects of measured potential confounders, and normalized the methylation signal intensity and FI data. The MP-EWAS included data for 643/457 individuals from NFBC1966 and NFBC1986, respectively (total N=1,100).\n\nIn Model 1, we detected epigenome-wide significant association in the MP-EWAS meta-analysis at cg13708645 (chr12:121,974,305; P=1.2x10-8) within KDM2B gene. Single-trait effects within KDM2B were on FI, BMI, and WHR. Model with effect on BMI and WHR showed the strongest association at this locus, while effect on FI in single-phenotype analysis was driven by the effect of adiposity. In Model 2, the strongest association was at cg05063096 (chr3:143,689,810; P=2.3x10-7) annotated to C3orf58 with strongest effect on FI in single-trait analysis and multi-phenotype effect on FI and WHI within Model 1.\n\nWe characterized the effects of established EWAS loci for diabetes and its risk factors and detected suggestive (p<0.01) associations at six markers including PHGDH, TXNIP, SLC7A11, CPT1A, MYO5C and ABCG1, through the dissection of the multi-phenotype effects in Model 1.\n\nConclusionsWe implemented MP-EWAS in methylSCOPA and demonstrated its enhanced power over single-trait EWAS for correlated phenotypes in large-scale data.

bioinformatics↗

bioRxiv2019

The genetic architecture of sporadic and recurrent miscarriage

Miscarriage is a common complex trait that affects 10-25% of clinically confirmed pregnancies1,2. Here we present the first large-scale genetic association analyses with 69,118 cases from five different ancestries for sporadic miscarriage and 750 cases of European ancestry for recurrent miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association on chromosome 13 (rs146350366, minor allele frequency (MAF) 1.2%, Pmeta=3.2x -8 (CI) 1.2-1.6) for sporadic miscarriage in our European ancestry meta-analysis (50,060 cases and 174,109 controls), located near FGF9 involved in pregnancy maintenance3 and progesterone production4. Additionally, we identified three genome-wide significant associations for recurrent miscarriage, including a signal on chromosome 9 (rs7859844, MAF=6.4%, Pmeta=1.3x -8 in controlling extravillous trophoblast motility5. We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability and, genetic correlation analyses. Our results implicate that miscarriage etiopathogenesis is partly driven by genetic variation related to gonadotropin regulation, placental biology and progesterone production.

genetics↗

bioRxiv2018

MR-TRYX: Exploiting horizontal pleiotropy to infer novel causal pathways

In Mendelian randomization (MR) analysis, variants that exert horizontal pleiotropy are typically treated as a nuisance. However, they could be valuable in identifying novel pathways to the traits under investigation. Here, we developed the MR-TRYX framework, following the advice of William Bateson to \"TReasure Your eXceptions\". We begin by detecting outliers in a single exposure-outcome MR analysis, hypothesising they are due to horizontal pleiotropy. We search across thousands of complete GWAS summary datasets in the MR-Base database to systematically identify other (\"candidate\") traits that associate with the outliers. We developed a multi-trait pleiotropy model of the heterogeneity in the exposure-outcome analysis due to pathways through candidate traits. Through detailed investigation of several causal relationships, many pleiotropic pathways were uncovered with already established causal effects, validating the approach, but also novel putative causal pathways. Adjustment for pleiotropic pathways reduced the heterogeneity across the analyses.

bioinformatics↗

bioRxiv2018

An intrinsic neural eye tracker in primary visual cortex

Humans and other primates rely on eye movements to explore visual scenes and to track moving objects. As a result, the image that is projected onto the retina - and propagated throughout the visual cortical hierarchy - is almost constantly changing and makes little sense without taking into account the momentary direction of gaze. How is this achieved in the visual system? Here we show that in primary visual cortex (V1), the earliest stage of cortical vision, neural representations carry an embedded \"eye tracker\" that signals the direction of gaze associated with each image. Using chronically implanted multi-electrode arrays, we recorded the activity of neurons in V1 during tasks requiring fast (exploratory) and slow (pursuit) eye movements. Neurons were stimulated with flickering, full-field luminance noise at all times. As in previous studies 1-4, we observed neurons that were sensitive to gaze direction during fixation, despite comparable stimulation of their receptive fields. We trained a decoder to translate neural activity into metric estimates of (stationary) gaze direction. This decoded signal not only tracked the eye accurately during fixation, but also during fast and slow eye movements, even though the decoder had not been exposed to data from these behavioural states. Moreover, this signal lagged the real eye by approximately the time it took for new visual information to travel from the retina to cortex. Using simulations, we show that this V1 eye position signal could be used to take into account the sensory consequences of eye movements and map the fleeting positions of objects on the retina onto their stable position in the world.

neuroscience↗

bioRxiv2018

Trans-ethnic genome-wide association study provides insight into effector genes and molecular mechanisms for kidney function and highlights a causal effect on kidney-specific disease aetiologies

Chronic kidney disease (CKD) affects [~]10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

genetics↗

bioRxiv2018

Genome-wide association analysis identifies 27 novel loci associated with uterine leiomyomata revealing common genetic origins with endometriosis

Uterine leiomyomata (UL), also known as uterine fibroids, are the most common neoplasms of the reproductive tract and the primary cause for hysterectomy, leading to considerable impact on womens lives as well as high economic burden1,2. Genetic epidemiologic studies indicate that heritable risk factors contribute to UL pathogenesis3. Previous genome-wide association studies (GWAS) identified five loci associated with UL at genome-wide significance (P < 5 x 10-8)4-6. We conducted GWAS meta-analysis in 20,406 cases and 223,918 female controls of white European ancestry, identifying 24 genome-wide significant independent loci; 17 replicated in an unrelated cohort of 15,068 additional cases and 43,587 female controls. Aggregation of discovery and replication studies (35,474 cases and 267,505 female controls) revealed six additional significant loci. Interestingly, four of the 17 loci identified and replicated in these analyses have also been associated with risk for endometriosis - another common gynecologic disorder. These findings increase our understanding of the biological mechanisms underlying UL development, and suggest overlapping genetic origins with endometriosis.

genomics↗

bioRxiv2018

Genome Wide Association Scan identifies new variants associated with a cognitive predictor of dyslexia.

Developmental dyslexia (DD) is one of the most prevalent learning disorders among children and is characterized by deficits in different cognitive skills, including reading, spelling, short term memory and others. To help unravel the genetic basis of these skills, we conducted a Genome Wide Association Study (GWAS), including nine cohorts of reading-impaired and typically developing children of European ancestry, recruited across different countries (N=2,562-3,468).\n\nWe observed a genome-wide significant effect (p<1x10-8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2 within MIR924HG (micro-RNA 924 host gene; p = 4.73x10-9), and a suggestive association on 8q12.3 within NKAIN3 (encoding a cation transporter; p = 2.25 x10-8). RAN represents one of the best universal predictors of reading fluency across orthographies and linkage to RAN has been previously reported within CELF4 (18q12.2), a gene highly expressed in the fetal brain which is co-expressed with NKAIN3 and predicted to be a target of MIR924. These findings suggest new candidate DD susceptibility genes and provide insights into the genetics and neurobiology of dyslexia.

genomics↗

bioRxiv2018

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

genetics↗

bioRxiv2017

Refining The Accuracy Of Validated Target Identification Through Coding Variant Fine-Mapping In Type 2 Diabetes

Identification of coding variant associations for complex diseases offers a direct route to biological insight, but is dependent on appropriate inference concerning the causal impact of those variants on disease risk. We aggregated exome-array and exome sequencing data for 81,412 type 2 diabetes (T2D) cases and 370,832 controls of diverse ancestry, identifying 40 distinct coding variant association signals (at 38 loci) reaching significance (p<2.2x10-7). Of these, 16 represent novel associations mapping outside known genome-wide association study (GWAS) signals. We make two important observations. First, despite a threefold increase in sample size over previous efforts, only five of the 40 signals are driven by variants with minor allele frequency <5%, and we find no evidence for low-frequency variants with allelic odds ratio >1.36. Second, we used GWAS data from 50,160 T2D cases and 465,272 controls to fine-map associated coding variants in their regional context, with and without additional weighting, to account for the global enrichment of complex trait association signals in coding exons. We demonstrate convincing support (posterior probability >80% under the \"annotation-weighted\" model) that coding variants are causal for the association at 16 of the 40 signals (including novel signals involving POC5 p.His36Arg, ANKH p.Arg187Gln, WSCD2 p.Thr113Ile, PLCB3 p.Ser778Leu, and PNPLA3 p.Ile148Met). However, one third of coding variant association signals represent \"false leads\" at which naive analysis would have led to an erroneous inference regarding the effector transcript mediating the signal. Accurate identification of validated targets is dependent on correct specification of the contribution of coding and non-coding mediated mechanisms at associated loci.

genetics↗

bioRxiv2017

Integrative cross tissue analysis of gene expression identifies novel type 2 diabetes genes

To understand the mechanistic underpinnings of type 2 diabetes (T2D) loci mapped through GWAS, we performed a tissue-specific gene association study in a cohort of over 100K individuals (ncases {approx} 26K,ncontrols {approx} 84K) across 44 human tissues using MetaXcan, a summary statistics extension of PrediXcan. We found that 90 genes significantly (FDR < 0.05) associated with T2D, of which 24 are previously reported T2D genes, 29 are novel in established T2D loci, and 37 are novel genes in novel loci. Of these, 13 reported genes, 15 novel genes in known loci, and 6 genes in novel loci replicated (FDRrep < 0.05) in an independent study (ncases {approx} 10K, ncontrols {approx} 62K). We also found enrichment of significant associations in expected tissues such as liver, pancreas, adipose, and muscle but also in tibial nerve, fibroblasts, and breast. Finally, we found that monogenic diabetes genes are enriched in T2D genes from our analysis suggesting that moderate alterations in monogenic (severe) diabetes genes may promote milder and later onset type 2 diabetes.

genetics↗