Biology subjects

Forde, A.

Publications and source records attributed to Forde, A..

4 recordsLinked to original sources

bioRxiv2026

Environmental Drivers and Distribution of Pathogenic Vibrio Species in the Teign Estuary, UK

Climate-driven increases in sea surface temperature have been associated with the expansion of Vibrio species and a corresponding rise in vibriosis cases in both human populations and aquaculture systems. Coastal waters across the south of England are increasingly becoming suitable for the growth and establishment of both human- and aquaculture-associated Vibrio species, potentially increasing vulnerability to the types of infections and disease outbreaks already reported elsewhere in the world. In this study, we report the presence of a diverse and well-established Vibrio community within the Teign Estuary, (Southwest, UK), including the human-pathogenic species V. parahaemolyticus, V. cholerae (non-O1/non-O139), V. alginolyticus, and V. diabolicus, as well as the important aquaculture pathogens V. jasicida, V. aestuarianus, and V. anguillarum. We identified V. diabolicus, a species that was indistinguishable from V. alginolyticus using conventional biochemical identification methods and could only be accurately resolved by whole-genome sequencing and developed novel PCR targets to differentiate these species in the lab. Using the insect infection model Galleria mellonella, we demonstrate that environmental isolates of V. cholerae (non-O1/non-O139), V. parahaemolyticus, and V. alginolyticus possess virulence potential. We also investigated the effects of sewage effluent on the growth of Vibrio isolates from the Teign Estuary and found that sewage can preferentially promote the growth of Vibrio species. Furthermore, several Vibrio isolates were multidrug resistant and carried antimicrobial resistance genes, highlighting the potential role of environmental Vibrio populations in the Teign Estuary as reservoirs of antimicrobial resistance. Together, these findings demonstrate how rising sea surface temperatures and sewage pollution may influence the emergence, persistence, and public health and aquaculture significance of Vibrio species in UK coastal waters.

microbiology↗

bioRxiv2025

Simulated sample splitting approach to address biases due to instrument selection and participant overlap in two-sample Mendelian Randomization studies

Mendelian randomization (MR) is a popular statistical technique that uses genetic variants to explore causal relationships in observational epidemiology. Summary-level MR, the most common form, relies on published GWAS summary statistics to estimate causal effects between exposures and outcomes. However, empirical analyses tend to ignore issues relating to Winners Curse of instrument effects, weak instrument bias and sample overlap. Our simulations and empirical examinations using the UK Biobank indicate that such mechanisms can induce substantial bias in routine MR approaches. We propose MR Simulated Sample Splitting (MR-SimSS), a novel method that corrects this bias requiring no additional data beyond the exposure and outcome GWAS summary statistics under examination. It operates by simulating statistically independent sets of summary statistics, analogous to what would be produced by splitting the individual-level data into independent subsets, which can then be plugged into existing pleiotropy-robust MR methods. With sufficient instrument variants, MR-SimSS is robust to a range of sample overlap scenarios, providing a practical and modular solution to Winners Curse and weak instrument bias. Author summaryA central challenge in epidemiology is determining whether an observed association reflects a true cause- and-effect relationship. Mendelian randomization (MR) addresses this by using genetic variants as natural experiments to test whether a particular trait or exposure genuinely influences disease risk. However, when the same genetic data are used both to select and to estimate genetic instruments, MR results can become biased due to a phenomenon known as the Winners Curse. This problem, along with weak instruments and sample overlap between datasets, can distort causal estimates even in large studies. We introduce MR Simulated Sample Splitting (MR-SimSS), a new framework that overcomes these issues using only publicly available genome-wide association study (GWAS) summary statistics. MR-SimSS works by statistically simulating independent subsets of the data, without requiring access to individual-level information, allowing existing MR methods to be applied without bias. Through extensive simulations and analyses using UK Biobank data, we show that MR-SimSS provides more accurate and reliable causal estimates, offering a practical tool for robust causal inference in modern genetic epidemiology.

genetics↗

bioRxiv2022

Review and further developments in statistical corrections for Winner's Curse in genetic association studies

Genome-wide association studies (GWAS) are commonly used to identify genomic variants that are associated with complex traits, and estimate the magnitude of this association for each variant. However, it has been widely observed that the association estimates of variants tend to be lower in a replication study than in the study that discovered those associations. A phenomenon known as Winners Curse is responsible for this upward bias present in association estimates of significant variants in the discovery study. We review existing Winners Curse correction methods which require only GWAS summary statistics in order to make adjustments. In addition, we propose modifications to improve existing methods and propose a novel approach which uses the parametric bootstrap. We evaluate and compare methods, first using a wide variety of simulated data sets and then, using real data sets for three different traits. The metric, estimated mean squared error (MSE) over significant SNPs, was primarily used for method assessment. Our results indicate that widely used conditional likelihood based methods tend to perform poorly. The other considered methods behave much more similarly, with our proposed bootstrap method demonstrating very competitive performance. To complement this review, we have developed an R package, winnerscurse which can be used to implement these various Winners Curse adjustment methods to GWAS summary statistics. Author SummaryA genome-wide association study is designed to analyse many common genetic variants in thousands of samples and identify which variants are associated with a trait of interest. It provides estimates of association strength for each variant and variants are classified as associated if their test statistics obtained in the study pass a chosen significance threshold. However, due to a phenomenon known as Winners Curse, the association estimates of these significant variants tend to be upward biased and greater in magnitude than their true values. Naturally, this bias has adverse consequences for downstream statistical techniques which use these estimates. In this paper, we look at current methods which have been designed to combat Winners Curse and propose modifications to these methods in order to improve performance. Using a wide variety of simulated data sets as well as real data, we perform a thorough evaluation of these methods. We use a metric which allows us to identify which methods, on average, produce adjusted estimates for significant variants that are closest to the true values. To accompany our work, we have created an R package, winnerscurse, which allows users to easily apply Winners Curse correction methods to their data sets.

genetics↗

bioRxiv2019

The human gut virome is highly diverse, stable and individual-specific

The human gut contains a vast array of viruses, mostly bacteriophages. The majority remain uncharacterised and their roles in shaping the gut microbiome and in impacting on human health remain poorly understood. Here we performed a longitudinal focused metagenomic study of faecal bacteriophage populations in healthy adults. Our results reveal high temporal stability and individual specificity of bacteriophage consortia which correlates with the bacterial microbiome. We report the existence of a stable, numerically predominant individual-specific persistent personal virome. Clustering of bacteriophage genomes and de novo taxonomic annotation identified several groups of crAss-like and Microviridae bacteriophages as the most stable colonizers of the human gut. CRISPR-based host prediction highlighted connections between these stable viral communities and highly predominant gut bacterial taxa such as Bacteroides, Prevotella and Faecalibacterium. This study provides insights into the structure of the human gut virome and serves as an important baseline for hypothesis-driven research.

microbiology↗