Biology subjects

Fiorito, G.

Publications and source records attributed to Fiorito, G..

3 recordsLinked to original sources

bioRxiv2026

A configuration-resolved benchmark of differential abundance analysis methods for human gut 16S rRNA microbiome data

Tools for differential abundance testing of 16S rRNA data are conventionally treated as discrete methods, and benchmarks have accordingly sought to determine which tool performs best. However, each tool offers an array of configurations based on different normalisation, transformation, reference choice, and sensitivity filtering methods, and the specific impact of these configurations on performance has rarely been systematically investigated. We benchmarked five widely used tools (MaAsLin 2, MaAsLin 3, edgeR, ALDEx2, and ANCOM-BC2) across 18 configurations, using simulated communities and human gut profiles with implanted signals, at two taxonomic resolutions and across several design factors. Configuration accounted for as much performance variation as the choice of tool itself, with the ranking of two tools depending on which of their settings are compared. Individual parameters behaved as switches between opposite error regimes rather than as graded adjustments, and the settings carrying this weight are identifiable in advance. These behaviours were reproducible across data sources and resolutions. Our results define a configuration-aware framework for matching a tool and its settings to the cohort, study design, and feature resolution, establishing that a differential abundance result is interpretable only if the configuration used for the analysis is reported.

microbiology↗

bioRxiv2018

Determinants of accelerated metabolomic and epigenetic ageing in a UK cohort

Markers of biological ageing have potential utility in primary care and public health. We developed an elastic net regression model of age based on untargeted metabolic profiling across multiple platforms, including nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry in urine and serum (almost 100,000 features assayed), within a large sample (N=2,239) from the UK occupational Airwave cohort. We investigated the determinants of accelerated ageing, including genetic, lifestyle and psychological risk factors for premature mortality. The metabolomic age model was well correlated with chronological age (r=0.85 in independent test set). Increased metabolomic age acceleration (mAA) was associated (p<0.0025) with overweight/obesity and depression and nominally associated (p<0.05) with high alcohol use and low income. DNA methylation age acceleration (N=1,102) was nominally associated (p<0.05) with high alcohol use, anxiety and post-traumatic stress disorder, but not correlated with mAA. Biological age acceleration may present an important mechanism linking psycho-social stress to age-related disease.

epidemiology↗

bioRxiv2017

An epigenome-wide association study of educational attainment (n = 10,767)

The epigenome has been shown to be influenced by biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption, and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here, we provide evidence on the associations between epigenetic modifications--in our case, CpG methylation--and educational attainment (EA), a biologically distal environmental factor that is arguably among of the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10,767 individuals. While we find that 9 CpG probes are significantly associated with EA, only two remain associated when we restrict the sample to never-smokers. These two are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, their effect sizes on EA are far smaller than the known associations between CpG probes and biologically proximal environmental factors. Two analyses that combine the effects of many probes--polygenic methylation score and epigenetic-clock analyses--both suggest small associations with EA. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

genetics↗