Biology subjects

Austin, T.

Publications and source records attributed to Austin, T..

6 recordsLinked to original sources

bioRxiv2026

Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKBs original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.

bioinformatics↗

bioRxiv2025

Co-Activation Patterns in Neonates using High-Density Diffuse Optical Tomography: Insights into Early Dynamic Functional Connectivity

SignificanceDynamic functional connectivity (FC) in neonates is a growing area of interest due to the developmental significance of early functional networks. There are several emerging techniques to measure dynamic FC, adding new perspectives to well-studied static FC networks. Recent dynamic FC studies suggest that adult resting-state networks are driven by key moments of dynamic activity rather than sustained correlations. Co-activation pattern (CAP) analysis leverages this theory, clustering high-activity frames to identify recurring configurations of significant activity. High-density diffuse optical tomography (HD-DOT) is an infant-friendly modality that measures hemodynamic changes in the cortex and has been used to investigate static FC in term-aged infants. CAP analysis has not yet been applied to neonatal HD-DOT and may reveal temporal features of early functional networks that are not apparent from static methods. AimThis study applies CAP analysis to neonatal HD-DOT to characterize transient co-activation states and provide new insight into early functional brain networks beyond what is known from static FC methods alone. ApproachTask-free HD-DOT data were acquired from a cohort of sleeping term newborns at the Rosie Hospital, Cambridge UK (n = 44, postmenstrual age = 40+3 (range: 38+2-42+6) weeks). In each recording, the top 15% of seed-selected frames were clustered using the K-means algorithm for three regions of interest (ROIs: frontal, central, and parietal) to identify significant seed-associated patterns of co-activation or co-deactivation. These co-activation patterns (CAPs) were characterized for each infant using four metrics: consistency, fractional occupancy, dwell time, and transition likelihood. ResultsDistinct CAPs, reflecting the dynamic organization of neonatal cortical networks, were identified for frontal, central, and parietal regions. These CAPs showed high consistency scores, reflecting high intra-cluster spatial correlation and validating the efficacy of CAP analysis for newborn HD-DOT data. The CAP decomposition revealed significant patterns not observed in conventional static functional connectivity analyses. Several neonatal CAPs exhibited frontoparietal co-activation, potentially reflecting early default mode network activity, which is immature and modular for the first year after birth. ConclusionsThis work demonstrates the utility of CAP analysis with newborn HD-DOT and provides new insight into the dynamics of neonatal functional connectivity.

neuroscience↗

bioRxiv2024

Sex differences in auditory function of the desert locust

Age-related auditory decline manifests across the animal kingdom, from humans and mice to zebrafish and insects. Sex differences in auditory decline are established for humans, but there is now evidence in mice and even zebrafish. Here, we found sex differences in auditory decline in an insect, the Desert Locust and investigated its biological basis. We profiled gene expression in a dedicated auditory organ, Mullers organ to understand the genetic underpinning of sex differences and measured sound-evoked transduction currents and electrophysiological properties of auditory neurons to quantify auditory decline. We analysed gene expression in Mullers organ of young locusts where sex differences were absent and in older, noise-exposed locusts where sex differences were maximal. The largest differences in gene expression between the sexes was between young and stressed (aged and noise-exposed) auditory organs. We found sex-specific genes and gene ontology terms for juvenile hormone (JH) and sex-specific estrogen-related steroids. We hypothesise that sex differences in auditory decline are due to differences in hormones which then affect metabolic processes in and mitochondria. HighlightsO_LIFemale Desert Locusts have less auditory decline than males. C_LIO_LIFemales auditory organs maintain better metabolism under stressed conditions. C_LIO_LISex differences in gene expression are maximal during aging and noise-exposure. C_LIO_LISex differences are minimal between the sexes for young and stressed auditory organs. C_LI

neuroscience↗

bioRxiv2024

Sex Differences in Human Brain Structure at Birth

Sex differences in human brain anatomy have been well-documented; however, their underlying causes remain controversial. Neonatal research offers a pivotal opportunity to address this long-standing debate. Given that postnatal environmental influences (e.g., gender socialisation) are minimal at birth, any sex differences observed at this stage can be more readily attributed to prenatal influences. Here, we assessed on-average sex differences in global and regional brain volumes in 514 newborns (236 birth-assigned females and 278 birth-assigned males) using data from the developing Human Connectome Project. On average, males had significantly larger intracranial and total brain volumes, even after controlling for birth weight. After controlling for total brain volume, females showed higher total cortical gray matter volumes, whilst males showed higher total white matter volumes. After controlling for total brain volume in regional comparisons, females had increased white matter volumes in the corpus callosum and increased gray matter volumes in the bilateral parahippocampal gyri (posterior parts), left anterior cingulate gyrus, bilateral parietal lobes, and left caudate nucleus. Males had increased gray matter volumes in the right medial and inferior temporal gyrus (posterior part) and right subthalamic nucleus. Effect sizes ranged from small for regional comparisons to large for global comparisons. While postnatal experiences likely amplify sex differences in the brain, our findings demonstrate that several global and regional on-average sex differences are already present at birth.

neuroscience↗

bioRxiv2022

Genetic, clinical underpinnings of subtle early brain change along Alzheimer's dimensions

Alzheimers disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised clustering technique known as Surreal-GAN, through which we identified two dominant dimensions of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE {varepsilon}4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE {varepsilon}4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction - driven by genes different from APOE - which may collectively contribute to the early pathogenesis of AD.

bioengineering↗

bioRxiv2018

Complex Structural Variants Resolved by Short-Read and Long-Read Whole Genome Sequencing in Mendelian Disorders

Complex structural variants (cxSVs) are genomic rearrangements comprising multiple structural variants, typically involving three or more breakpoint junctions. They contribute to human genomic variation and can cause Mendelian disease, however they are not typically considered during genetic testing. Here, we investigate the role of cxSVs in Mendelian disease using short-read whole genome sequencing (WGS) data from 1,324 individuals with neurodevelopmental or retinal disorders from the NIHR BioResource project. We present four cases of individuals with a cxSV affecting Mendelian disease-associated genes. Three of the cxSVs are pathogenic: a de novo duplication-inversion-inversion-deletion affecting ARID1B in an individual with Coffin-Siris syndrome, a deletion-inversion-duplication affecting HNRNPU in an individual with intellectual disability and seizures, and a homozygous deletion-inversion-deletion affecting CEP78 in an individual with cone-rod dystrophy. Additionally, we identified a de novo duplication-inversion-duplication overlapping CDKL5 in an individual with neonatal hypoxic-ischaemic encephalopathy. Long-read sequencing technology used to resolve the breakpoints demonstrated the presence of both a disrupted and an intact copy of CDKL5 on the same allele; therefore, it was classified as a variant of uncertain significance. Analysis of sequence flanking all breakpoint junctions in all the cxSVs revealed both microhomology and longer repetitive sequences, suggesting both replication and homology based processes. Accurate resolution of cxSVs is essential for clinical interpretation, and here we demonstrate that long-read WGS is a powerful technology by which to achieve this. Our results show cxSVs are an important although rare cause of Mendelian disease, and we therefore recommend their consideration during research and clinical investigations.

genomics↗