Biology subjects

Schmidt, A. F.

Publications and source records attributed to Schmidt, A. F..

7 recordsLinked to original sources

bioRxiv2022

Single-nucleus RNA-seq reveals disrupted cell maturation by chorioamnionitis in the preterm cerebellum of nonhuman primates

Preterm birth is often associated with chorioamnionitis and increased risk of neurodevelopmental disorders. Preterm birth also leads to cerebellar underdevelopment but the mechanisms of disrupted cerebellar development in preterm infants are little understood. Here, we leveraged single-nuclei RNA-sequencing of the cerebellum in a rhesus macaque model of chorioamnionitis and preterm birth, to show that chorioamnionitis leads to Purkinje cell loss and disrupted maturation of granule cells and oligodendrocytes in the fetal cerebellum at late gestation. Purkinje cell loss is accompanied by decreased sonic hedgehog signaling from Purkinje cells to granule cells, which show an accelerated maturation. Chorioamnionitis also accelerated pre-oligodendrocyte maturation into myelinating oligodendrocytes, confirmed by increased expression of myelin basic protein in the cerebellum of chorioamnionitis-exposed fetuses. These findings are consistent with reported histopathological findings in individuals with autism and suggest a novel mechanism through which perinatal inflammation contributes to neurodevelopmental disorders.

neuroscience↗

bioRxiv2021

Fetal maturation revealed by amniotic fluid cell-free transcriptome in rhesus macaques

Accurate estimate of fetal maturity could provide individualized guidance for delivery of complicated pregnancies. However, current methods are invasive, have low accuracy, and are limited to fetal lung maturation. To identify diagnostic gestational biomarkers, we performed transcriptomic profiling of lung and brain, as well as cell-free RNA from amniotic fluid of preterm and term rhesus macaque fetuses. These data predict new and prior associated gestational age differences in distinct lung and neuronal cell populations when compared to existing single-cell and bulk RNA-Seq data. Comparative analyses found over 200 genes coincidently induced in lung and amniotic fluid, and dozens in brain and amniotic fluid. This data enabled creation of computational models that accurately predicted lung compliance from amniotic fluid and lung transcriptome of preterm fetuses treated with antenatal corticosteroids. Cell-free RNA in amniotic fluid may provide a substrate of global fetal maturation markers for personalized management of at-risk pregnancies.

systems biology↗

bioRxiv2020

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter its expression or function, as a tool to anticipate the effect of drug action on the same target. Here, we applied MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets were further prioritized using genetic co-localization, protein expression profiles from the Human Protein Atlas and, for targets with a licensed drug or an agent in clinical development, by sourcing data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with circulating blood lipids (HDL-C, LDL-C and triglycerides), we were able to robustly prioritize 30 targets that might elicit beneficial treatment effects in the prevention or treatment of CHD. The prioritized list included NPC1L1 and PCSK9, the targets of licensed drugs whose efficacy has been already proven in clinical trials. To conclude, we discuss how this approach can be generalized to other targets, disease biomarkers and clinical end-points to help prioritize and validate targets during the drug development process. One Sentence SummaryWe provide genetic support for lipid-modifying drug targets for coronary heart disease prevention using drug target Mendelian randomization and further prioritization based on clinical and biological evidence.

genetics↗

bioRxiv2019

Genetic drug target validation using Mendelian randomization

Mendelian randomisation analysis has emerged as an important tool to elucidate the causal relevance of a range of environmental and biological risk factors for human disease. However, inference on cause is undermined if the genetic variants used to instrument a risk factor of interest also associate with other traits that open alternative pathways to the disease (horizontal pleiotropy). We show how the no horizontal pleiotropy assumption in MR analysis is strengthened when proteins are the risk factors of interest. Proteins are the proximal effectors of biological processes encoded in the genome, and are becoming assayable on an-omics scale. Moreover, proteins are the targets of most medicines, so Mendelian randomization (MR) studies of drug targets are becoming a fundamental tool in drug development. To enable such studies we introduce a formal mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. Finally, we illustrate key model decisions and introduce an analytical framework for maximizing power and elucidating the robustness of drug target MR analyses.

genetics↗

bioRxiv2018

Adjustment for index event bias in genome-wide association studies of subsequent events

Following numerous genome-wide association studies of disease susceptibility, there is increasing interest in genetic associations with disease prognosis, survival or other subsequent events. Such associations are vulnerable to index event bias, by which selection of subjects according to their disease status creates biased associations if common causes of incidence and prognosis are not accounted for. We propose a novel adjustment for index event bias using the residuals from the regression of genetic effects on prognosis on genetic effects on incidence. Our approach eliminates this bias when direct genetic effects on incidence and prognosis are independent, and otherwise reduces bias in realistic situations. In a study of idiopathic pulmonary fibrosis, we resolved a paradoxical association of the strong susceptibility gene MUC5B with increased survival, identifying instead a significant association with decreased survival. In re-analysis of a study of Crohns disease prognosis, four regions remained associated at genome-wide significance albeit with increased P-values.

epidemiology↗

bioRxiv2018

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9

BackgroundWe characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9.\n\nMethodsPublished and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Fourteen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration\n\nResultsThe PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95%CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95%CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95%CI 0.57; 1.22) for the GS, compared to 0.85 (95%CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95%CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimers disease - outcomes for which large-scale trial data were unavailable.\n\nConclusionsGenetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. Apparent discordance between genetic associations and trial outcome for T2DM might be explained lack by a of statistical precision, or differences in the nature and duration of genetic versus pharmacological perturbation of PCSK9.\n\nFundingThis research was funded by the British Heart Foundation (SP/13/6/30554, RG/10/12/28456, FS/18/23/33512), UCL Hospitals NIHR Biomedical Research Centre, by the Rosetrees and Stoneygate Trusts.\n\nCondensed abstractEvidence on the long-term efficacy and safety of therapeutic inhibition of PCSK9 is lacking. To explore potential long-term effects of PCSK9 inhibition, we characterised the phenotypic consequence of LDL-cholesterol lowering variants at the PCSK9 locus. A PCSK9 gene score comprising 4 SNPs recapitulated the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and risk of myocardial infarction, and was associated with an increased risk of type 2 diabetes. No associations with safety outcomes such as cancer, COPD, Alzheimers disease or atrial fibrillation were identified. Our findings suggest PCSK9 inhibition may be safe and effective during prolonged use.

genetics↗

bioRxiv2018

The median and the mode as robust meta-analysis methods in the presence of small study effects

Meta-analyses based on systematic literature reviews are commonly used to obtain a quantitative summary of the available evidence on a given topic. Despite its attractive simplicity, and its established position at the summit of the evidence-based medicine hierarchy, the reliability of any meta-analysis is largely constrained by the quality of its constituent studies. One major limitation is small study effects, whose presence can often easily be detected, but not so easily adjusted for. Here, robust methods of estimation based on the median and mode are proposed as tools to increase the reliability of findings in a meta-analysis. By re-examining data from published meta-analyses, and by conducting a detailed simulation study, we show that these two simple methods offer notable robustness to a range of plausible bias mechanisms, without making any explicit modelling assumptions. In conclusion, when performing a meta-analysis with suspected small study effects, we recommend reporting the mean, median and modal pooled estimates as a simple but informative sensitivity analyses.

epidemiology↗