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Bracher-Smith, M.

Publications and source records attributed to Bracher-Smith, M..

9 recordsLinked to original sources

drugMR: A multi-omics pipeline for genetically anchored drug-target discovery

Motivation: Genetically supported drug targets are an estimated 2.6 times more likely to succeed clinically, yet a disease association alone does not show which protein to target, in which direction, or what other effects may follow. This currently requires chaining separate tools. Results: drugMR is a Nextflow pipeline that, from GWAS and pQTL summary statistics, runs cis-Mendelian randomisation, colocalisation, SMR-HEIDI with bulk and/or single-cell QTLs, three-trait colocalisation and a phenome-wide screen for adverse effects and repurposing. Datasets are added through a manifest, every step runs in containers on a laptop, cluster or cloud, and results are explored in a dashboard. Applied to schizophrenia with brain pQTLs, drugMR tested 2,019 proteins in 4 h 19 min and prioritised 58 proteogenomic targets, 22 with multi-omic support; 4 had potential adverse effects. Availability and implementation: drugMR: https://github.com/guillermocomesanacimadevila/drugMR; documentation: https://guillermocomesanacimadevila.github.io/drugMR/. Demo data: https://doi.org/10.5281/zenodo.22917384.

bioinformatics↗

Complementary MR measures of white matter and their relation to cardiovascular health and cognition

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.

neuroscience↗

Analysis of diffusion tensor imaging data from UK Biobank confirms dosage effect of 15q11.2 copy-number variation on white matter and shows association with cognition

BackgroundCopy-number variations at the 15q11.2 BP1-BP2 locus are present in 0.5 to 1.0% of the population, and the deletion is associated with a range of neurodevelopmental disorders. Previously, we showed a reciprocal effect of 15q11.2 copy-number variation on fractional anisotropy, with widespread increases in deletion carriers. We aim to replicate and expand these findings, using a larger sample of participants (n=30,930), higher resolution imaging, and examining the implications for cognitive performance. MethodsDiffusion tensor imaging measures from participants with no neurological/psychiatric diagnoses were obtained from the UK Biobank database. We compared 15q11.2 BP1-BP2 deletion (n=103) and duplication (n=119) carriers to a large cohort of control individuals with no neuropsychiatric copy-number variants (n=29,870). Additionally, we assessed how changes in white matter mediated the association between carrier status and cognitive performance. ResultsDeletion carriers showed increases in fractional anisotropy in the internal capsule and cingulum, and decreases in the posterior thalamic radiation, compared to both duplication carriers and controls (who had intermediate values). Deletion carriers had lower scores across cognitive tasks compared to controls, which were mildly influenced by white matter alterations. Reduced fractional anisotropy in the posterior thalamic radiation partially contributed to worse cognitive performance in deletion carriers. ConclusionsThis study, together with our previous findings, provides convergent evidence for a dosage-dependent effect of 15q11.2 BP1-BP2 on white matter microstructure. Additionally, changes in white matter were found to partially mediate cognitive ability in deletion carriers, providing a link between white matter changes in 15q11.2 BP1-BP2 carriers and cognitive function.

neuroscience↗

The rate of de novo CNVs in healthy controls

BackgroundCopy number variation (CNV) is an important cause for human disease. Due to relatively high selection pressure operating against pathogenic CNVs, their rate is maintained in the population by de novo formation. The rates of de novo CNVs are increased in neurodevelopmental disorders. However only a few studies have been performed on relatively healthy individuals, making it problematic to calculate the magnitude of this increased rate. MethodsThe UK Biobank recruited about half a million randomly selected middle-aged members of the general population of the UK. We re-constructed family relationships from the genotypic data and identified 923 parent-offspring trios that passed out quality control filters. Potential de novo CNVs of >100 kb in size were identified and the log R ratios (LRR) and B allele frequency (BAF) traces of the trio members were visually inspected for those regions. We had no opportunity to validate CNVs with a laboratory method, but the traces appeared conclusive. Results and DiscussionWe identified 10 CNVs >100kb in size, a rate of 1.1%. These rates are very similar to those in previous large studies. Using previous large studies, we provide overall rates among 4844 trios for different size ranges that are expected in relatively healthy populations. These rates can be used for comparison in studies on disease populations.

genomics↗

Effects of pathogenic CNVs on biochemical markers: a study on the UK Biobank

BackgroundPathogenic copy number variants (CNVs) increase risk for medical disorders, even among carriers free from neurodevelopmental disorders. The UK Biobank recruited half a million adults who provided samples for biochemical and haematology tests which have recently been released. We wanted to assess how the presence of pathogenic CNVs affects these biochemical test results. MethodsWe called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and present in five or more persons. We used linear regression analysis to establish their association with 28 biochemical and 23 haematology tests. ResultsWe analysed 421k participants who passed our CNV quality control filters and self-reported as white British or Irish descent. There were 268 associations between CNVs and biomarkers that were significant at a false discovery rate of 0.05. Deletions at 16p11.2 had the highest number of significant associations, but several rare CNVs had higher effect sizes indicating that the lack of significance was likely due to the reduced statistical power for rarer events. The distribution of values can be visualised on our interactive website: http://kirov.psycm.cf.ac.uk/. ConclusionsCarriers of many pathogenic CNVs have changes in biochemical and haematology tests, and many of those are associated with adverse health consequences. These changes did not always correlate with increases in diagnosed medical disorders in this population. Carriers should have regular blood tests in order to identify and treat adverse medical consequences early. Levels of cholesterol and related lipids were unexpectedly lower in carriers of CNVs associated with increased weight gain, most likely due to the use of statins by such people.

genomics↗

Genetic association study of psychotic experiences in UK Biobank

Psychotic experiences, such as hallucinations and delusions, are reported by approximately 5%-10% of the general population, though only a small proportion of individuals develop psychotic disorders such as schizophrenia or bipolar disorder. Studying the genetic aetiology of psychotic experiences in the general population, and its relationship with the genetic aetiology of other disorders, may increase our understanding of their pathological significance. Using the population-based UK Biobank sample, we performed the largest genetic association study of psychotic experiences in individuals without a psychotic disorder. We conducted three genome-wide association studies (GWAS) for (i) any psychotic experience (6123 cases vs. 121,843 controls), (ii) distressing psychotic experiences (2143 cases vs. 121,843 controls), and (iii) multiple occurrence psychotic experiences (3337 cases vs. 121,843 controls). Analyses of polygenic risk scores (PRS), genetic correlation, and copy number variation (CNV) were conducted to assess whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits. GWAS analyses identified four loci associated with psychotic experiences including a locus in Ankyrin-3 (ANK3, OR=1.16, p=3.06 x 10-8) with any psychotic experience and a locus in cannabinoid receptor 2 gene (CNR2, OR=0.66, p=3.78x10-8) with distressing psychotic experiences. PRS analyses identified associations between psychotic experiences and genetic liability for schizophrenia, major depressive disorder, and bipolar disorder, and these associations were stronger for distressing psychotic experiences. Genetic correlation analysis identified significant genetic correlations between psychotic experiences and major depressive disorder, schizophrenia, autism spectrum disorder and a cross-disorder GWAS. Individuals reporting psychotic experiences had an increased burden of CNVs previously associated with schizophrenia (OR=2.04, p=2.49x10-4) and of those associated with neurodevelopmental disorders more widely (OR=1.75, p=1.41x10-3). In conclusion, we identified four genome-wide significant loci in the largest GWAS of psychotic experiences from the population-based UK Biobank sample and found support for a shared genetic aetiology between psychotic experiences and schizophrenia, but also major depressive disorder, bipolar disorder and neurodevelopmental disorders.

genetics↗

The role of rare copy number variants in depression

The role of large, rare copy number variants (CNVs) in neurodevelopmental disorders is well-established,1-5 but their contribution to common psychiatric disorders, such as depression, remains unclear. We have previously shown that a substantial proportion of CNV enrichment in schizophrenia is explained by CNVs associated with neurodevelopmental disorders.6, 7 Depression shares genetic risk with schizophrenia8, 9 and is frequently comorbid with neurodevelopmental disorders10, 11, suggesting to us the hypothesis that if CNVs play a role in depression, neurodevelopmental CNVs are those most likely to be associated. We confirmed this in UK Biobank by showing that neurodevelopmental CNVs were associated with depression (24,575 cases, 5.87%; OR=1.36, 95% CI 1.22-1.51, p=1.61x10-8), whilst finding no evidence implicating other CNVs. Four individual neurodevelopmental CNVs increased risk of depression (1q21.1 duplication, PWS duplication, 16p13.11 deletion, 16p11.2 duplication). The association between neurodevelopmental CNVs and depression was partially explained by social deprivation but not by education attainment or physical illness.

neuroscience↗

Effects of pathogenic CNVs on physical traits in participants of the UK Biobank

BackgroundCopy number variants (CNVs) have been shown to increase risk for physical anomalies, developmental, psychiatric and medical disorders. Some of them have been associated with changes in weight, height, and other physical traits. As most studies have been performed on children and young people, these effects of CNVs in adulthood are not well established.\n\nMethodsThe UK Biobank recruited half a million adults who provided a variety of physical measurements. We called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and that were present in five or more persons. Linear regression analysis was used to establish their association with 16 physical traits, relevant to human health.\n\nResults396,725 participants of white British or Irish descent (excluding first-degree relatives) passed our quality control filters. There were 214 CNV/trait associations significant at a false discovery rate of 0.1, most of them novel. These traits are associated with adverse health outcomes: e.g. increased weight, waist-to-hip ratio, pulse rate and body fat composition. Deletions at 16p11.2, 16p12.1, NRXN1 and duplications at 16p13.11 and 22q11.2 produced the highest numbers of significant associations. CNVs at 1q21.1, 2q13, 16p11.2, 16p11.2 distal, 16p12.1, 17p12 and 17q12 demonstrated one or more mirror image effects of deletions versus duplications.\n\nConclusionsCarriers of many CNVs should be monitored for physical traits that increase morbidity and mortality. Genes within these CNVs can give insights into biological processes and therapeutic interventions.

genetics↗

Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank.

BackgroundGenomic copy number variants (CNVs) increase risk for early-onset neurodevelopmental disorders but their impact on medical outcomes in later life is poorly understood. The UK Biobank, with half a million well-phenotyped adults, presents an opportunity to study the medical consequences of CNV in middle and old age.\n\nMethodsWe called 54 CNVs associated with clinical phenotypes or genomic disorders, including their reciprocal deletions or duplications, in all Biobank participants. We used logistic regression analysis to test CNVs for associations with 58 common medical phenotypes.\n\nFindingsCNV carriers had an increased risk of developing 37 of the 58 phenotypes at nominal levels of statistical significance, with 19 associations surviving Bonferroni correction (p<8{middle dot}6x10-4). Tests of each of the 54 CNVs for association with each of the 58 phenotypes identified 18 associations that survived Bonferroni correction (p<1{middle dot}6x10-5) and a further 57 that were associated at a false discovery rate (FDR) threshold of 0{middle dot}1. Thirteen CNVs had three or more significant associations at FDR=0{middle dot}1, with the largest number of phenotypes (N=15) found for deletions at 16p11{middle dot}2. The most common CNVs (frequency 0{middle dot}5-0{middle dot}7%) have no or minimal impact on medical outcomes in adults.\n\nInterpretationSome of the 54 tested CNVs have profound effects on physical health, even in people who have largely escaped early neurodevelopmental outcomes. Our work provides clinicians with a morbidity map of potential outcomes among carriers of these CNVs.\n\nFundingMRC UK, Wellcome Trust UK

genomics↗