Biology subjects

Unwin, R.

Publications and source records attributed to Unwin, R..

6 recordsLinked to original sources

bioRxiv2026

stably: error-controlled stability selection for biomarker panel discovery

Motivation Data-independent acquisition mass spectrometry (DIA-MS) has become increasingly popular for clinical proteomics due to its sensitivity and reproducibility. Univariate statistical analysis tools, such as limma and MSstats, are widely used for identifying differentially abundant proteins but cannot capture multivariate relationships between proteins that may provide greater discriminatory power as a panel. Machine learning approaches can address this gap, but typically prioritise predictive performance over feature stability, producing biomarker panels for downstream validation that vary depending on data splitting and are poorly suited to clinical translation. Results We developed stably, a Python package that implements stability selection with formal false positive control for DIA proteomics data. Using synthetic data with known ground-truth biomarkers, we show that the Shah and Samworth complementary pairs stability selection framework recovers more true synthetic biomarkers than the Meinshausen and Buhlmann framework at moderate effect sizes typical of proteomics (d = 0.5 - 2.0), while both maintain false positive rates well below their theoretical guarantees. Applied to a publicly available serum proteomics dataset from patients with all stages of pancreatic ductal adenocarcinoma (n=176), stably identified a stable 17-protein biomarker panel in the discovery cohort (n=120), which achieved higher predictive power (AUC = 0.93) in the validation cohort (n=56) than the panel selected by Byeon et al. (2024)(AUC 0.82). stably represents a principled, error-controlled method for biomarker panel discovery for translation into second cohorts. Availability and implementation stably is available on GitHub (https://github.com/byrnedaniel5-eng/stably); the version used in this study is archived on PyPI (https://pypi.org/project/stably/).

bioinformatics↗

bioRxiv2026

Enhanced proteome relative quantification using refined quantotypic spectral libraries

Plasma proteomics is used for a variety of applications including biomarker discovery, disease monitoring, and drug development. Data-independent acquisition (DIA) has vastly improved the breadth of proteins that are identified from samples; however, given challenges in reproducibility and translation, it is critical that the quantitative performance of these methods is reliable. Analysis of global proteomics data typically incorporates information from all detected peptides. However, some peptides do not reflect their parent protein amount, due to irreproducible digestion, modification, analytical interferences or instability. We hypothesise that including these peptides impacts protein relative quantification, and thus, a refined spectral library containing only quantitatively representative peptides provides superior protein quantification. By analysing a defined multi-species spike-in model, we show that refining a plasma spectral library by removing precursors that fail to meet quality control metrics (25.4% of all identified precursors) reduces noise and variability, improving precision, accuracy and differential abundance analysis by up to [~]11%, with minimal identification losses and substantial reduction in computational demand. This demonstrates proof-of-concept that refining spectral libraries produces results that prioritize quantification quality over quantity. This approach could enable development of universal tissue-specific refined spectral libraries able to improve quantification quality with easy implementation and minimal processing time. Significance of the StudyAs DIA mass spectrometry proteome depth increases, the quality of the associated protein quantifications must be considered alongside identification breadth, particularly in complex matrices such as plasma, which presents additional technical challenges. The spectral library used for protein identification and quantification is a critical determinant of DIA performance, and its composition requires considerable consideration. This work illustrates an initial step toward improving protein quantification starting at the spectral library level by filtering precursors which are poor quantitative representatives of their parent proteins. In doing so, the resulting data is more reliable for downstream and biological interpretation, with fewer false differential abundance assignments and reduced quantitative noise. As such, this work represents a broader shift away from the habitual focus of MS workflows on maximising the number of protein and differential abundance identifications and instead prioritises the quality of quantification over quantity. These initial findings lay the groundwork for further development of spectral library refinement strategies, with the potential to continue improving the accuracy and precision of protein quantification in DIA-based proteomics.

bioinformatics↗

bioRxiv2025

Elevated urea levels in human frontotemporal dementia and amyotrophic lateral sclerosis post-mortem brain tissue: Evidence of a multi-dementia pathogenic mechanism

1Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) represent two neurodegenerative diseases on opposite sides of a movement disorder continuum. However, like many other neurodegenerative diseases, the molecular pathogenesis of FTD and ALS is not fully understood. Our group has previously reported evidence for a pervasive elevation of brain urea levels in five other dementia-causing diseases. However, brain urea levels have yet to be measured in ALS and FTD. Here, we employed ultra-high-performance liquid chromatography-tandem mass spectrometry to characterise brain urea differences between control (n=14/12) and ALS/FTD (FTD: n=8/9; ALS: n=13/14) cases in post-mortem tissue from two brain regions with different levels of neuropathological burden (high vs. low). Elevated urea levels were observed in both the frontal cortex (high neuropathological burden) and primary visual cortex (low neuropathological burden) in cases with FTD. Contrastingly, in cases with ALS, elevated urea was observed in the primary motor cortex (high neuropathological burden), but not the dentate nucleus (low neuropathological burden). These results not only suggest that elevated urea levels are also present in ALS and FTD but imply that elevated brain urea is linked to a multi-dementia pathogenic mechanism. In contrast to ALS, the observation of elevated urea in regions of both high and low neuropathological burden in FTD implies that this phenotype is likely widespread and, therefore, may play a larger role in the pathogenesis of disease. Such a mechanism could offer new directions for developing treatments targeting this underlying pathology.

neuroscience↗

bioRxiv2025

CTx001 for geographic atrophy: a gene therapy expressing soluble, truncated complement receptor 1 (mini-CR1)

Over-activation of the complement system is strongly associated with geographic atrophy (GA), a late-stage form of age-related macular degeneration (AMD) and major cause of blindness. Here we report the development of a candidate GA treatment that is a potent complement modifier (mini-CR1) that addresses consequences of complement over-activation including membrane attack complex (MAC) formation. Mini-CR1 acts a potent cofactor for factor I driven proteolysis of C3b leading to iC3b and then C3dg formation; iC3b itself remains a potent opsonin. As well as inhibiting the alternative complement pathway, mini-CR1 acts as a cofactor for C4b degradation thereby inhibiting the classical pathway. Mini-CR1 prevents MAC formation in activated human serum with an IC50 of 125 nM. Mini-CR1 was shown to cross human Bruchs membrane ex vivo, implying the ability to cross into the choroidal space. Transduction of RPE cell lines with rAAV2-mini-CR1 (CTx001) resulted in dose-dependent transcription, and both basolateral and apical secretion of mini-CR1 by monolayers of human iPSC derived RPE cells. Mini-CR1 transduction of ARPE19 cells resulted in increased consumption of C3b and iC3b1 in activated culture media and decreased MAC formation on the cell surfaces. Subretinal injection of CTx001 in rats resulted in dose-dependent mini-CR1 production as demonstrated by solid-phase immunoassay. MAC formation following laser induced CNV in a rat model was reduced by 75% in CTx001-treated animals relative to null vector (p<0.01). This first generation of CTx001 represents a potent single administration complement modifier capable of effectively addressing pathologic complement amplification in the retina/choroid.

biochemistry↗

bioRxiv2022

CLN7 mutation causes aberrant redistribution of protein isoforms and contributes to Batten disease pathobiology

The variant late infantile form of the inherited neurodegenerative Batten disease (BD) is caused by mutations in the CLN7/MFSD8 gene and represents a strong candidate for gene therapy. Post-natal intracerebral administration of AAV9-hCLN7 to Cln7{Delta}ex2 knockout mice resulted in extended lifespan but dose escalation resulted in reduced acuity in neurophysiology tests, cerebral atrophy and elevated neuroinflammation. Comparing patient and control iPSC-derived neural progenitor cells (iNPC) we discovered that CLN7 localizes to the nucleus as well as the endolysosomal network and is differentially distributed in BD iNPC. Proteomics identified a profound nuclear defect in BD iNPC that compounds with mitochondrial and lysosomal metabolic defects resulting in elevated apoptosis. We further identified a 50kDa common nuclear CLN7 isoform and a 37kDa isoform that accumulates only in BD iNPC nuclei. Our findings suggest that successful treatment of CLN7 BD will require combinatorial therapies addressing both loss and aberrant gain of protein function.

cell biology↗

bioRxiv2018

Regional protein expression in human Alzheimer’s brain correlates with disease severity

Alzheimers disease (AD) is a progressive neurodegenerative disorder that currently affects 36 million people worldwide with no effective treatment available. Development of AD follows a distinctive pattern in the brain and is poorly modelled in animals. Therefore, it is vital to widen both the spatial scope of the study of AD and prioritise the study of human brains. Here we show that functionally distinct human brain regions show varying and region-specific changes in protein expression. These changes provide novel insights into the progression of disease, novel AD-related pathways, the presence of a gradient of protein expression change from less to more affected regions, and the presence of a protective protein expression profile in the cerebellum. This spatial proteomics analysis provides a framework which can underpin current research and opens new avenues of interest to enhance our understanding of molecular pathophysiology of AD, provides new targets for intervention and broadens the conceptual frameworks for future AD research.

neuroscience↗