Search bioRxiv⌕ Search

Biology subjects

Bauermeister, S.

Publications and source records attributed to Bauermeister, S..

9 recordsLinked to original sources

Divergent transcriptomic transition programs in Alzheimer disease: immune priming and synaptic collapse in females versus organelle membrane bifurcation in males

Alzheimers disease (AD) disproportionately affects women, who account for approximately two-thirds of prevalent cases. Despite decades of research, the mechanistic basis for this profound sex disparity remains poorly resolved. Prior transcriptomic studies have predominantly used pooled or female-enriched cohorts, obscuring whether the transition from normal cognition (NCI) to AD follows a common molecular program across sexes or reflects fundamentally divergent biology. Here, we analyzed bulk RNA-sequencing data from the dorsolateral prefrontal cortex of 624 individuals (401 females, 223 males) in the ROSMAP cohort using a transition-aware framework that separates variance instability along the disease axis from mean expression changes. We demonstrate that female and male brains exhibit structurally distinct transcriptomic transition programs. Females display a sequential, multi-tier architecture: interferon and immune variance priming (628 genes) is detectable early at the NCI-to-mild cognitive impairment (MCI) interval, which structurally precedes a massive mean-level synaptic and neuropeptide loss (8,935 genes) in AD. The female NCI-to-MCI interval alone produces 1,249 variance bifurcation events entirely absent in males. Conversely, males exhibit no early immune priming or powered mean-level changes. Instead, they collapse into a single large variance bifurcation pool (8,237 genes) heavily enriched for system-wide organelle membrane fusion, post-translational modification, and intracellular trafficking. These findings reveal that the AD transcriptomic transition is not a unitary program quantitatively modified by sex, but two distinct biological trajectories. This fundamental divergence motivates sex-stratified mechanistic models and independent biomarker development for each sex, cautioning against analytical pooling in transition-stage cohorts.

bioinformatics↗

Transcriptomic phase transitions along the Alzheimer's disease continuum using riemmaninan tensor model: a bifurcation-intermediate variance framework on the ROSMAP cohort

Alzheimers disease (AD) progression involves systemic network transitions. To capture these using ROSMAP bulk RNA-seq (n=624), we focused on the geometry of the covariance structure, performing a Riemannian (Log-Euclidean) analysis of stage-wise covariance matrices as points on the manifold of symmetric positive-definite (SPD) matrices. On the SPD manifold the three stages were non-collinear: geodesic distances were non-uniform and MCI was displaced from the NCI-AD chord, while the von Neumann entropy of the covariance structure dipped at MCI (S = 2.760, 2.639, 2.647 for normal cognitive intact NCI, mild cognitive impairment MCI, AD) and the path-curvature profile reached a minimum there -- together identifying MCI as a saddle/bifurcation state. The differential covariance spectrum (CAD - CNCI) separated AD-amplified ("structural collapse") from AD-suppressed ("protective loss") modes. Ultimately, second-order statistics analyzed through Riemannian geometry, rather than Euclidean summaries, reveal AD progression structure invisible to mean-level analysis.

bioinformatics↗

Riemannian Tensor Analysis Identifies a Bifurcation State in the Single-Cell Transcriptomic Landscape of Parkinson's Disease

The transition from healthy aging to Parkinsons disease (PD) involves highly volatile transcriptomic rewiring that remains invisible to conventional mean-based analyses. To decode this critical tipping point, we integrated single-cell RNA-sequencing with a novel Log-Euclidean Riemannian tensor framework. By conceptualizing distinct transcriptomic states as symmetric positive definite (SPD) covariance tensors, we bypassed Euclidean geometric artifacts to accurately map the macroscopic network architecture of the human prefrontal cortex. Our analysis identified a highly unstable, intermediate bifurcation (BIF) state. Thermodynamic and topological validation demonstrated that this BIF state operates as a definitive geometric saddle point, characterized by maximal von Neumann entropy and positioned perfectly equidistant between the healthy (HC) and pathological (PD) Frechet means on the non-Euclidean manifold. Furthermore, spectral deconstruction of differential covariance networks [Formula] isolated the exact topological drivers of this transition--revealing the catastrophic structural collapse of core synaptic and electrophysiological hubs prior to overt pathological commitment. Ultimately, this ab initio geometric framework fundamentally redefines PD progression, providing a quantitative blueprint to intercept neurodegenerative trajectories during their final reversible window.

systems biology↗

Semantic harmonization of Alzheimer's disease datasets using AD-Mapper

INTRODUCTIONDespite numerous past endeavors for the semantic harmonization of Alzheimers disease (AD) cohort studies, an automatic tool has yet to be developed. As cohort studies form the basis of data-driven analysis, harmonizing them is crucial for cross-cohort analysis. We aimed to accelerate this task by constructing an automatic harmonization tool. METHODSWe created a common data model (CDM) through cross-mapping data from 20 cohorts, three CDMs, and ontology terms, which was then used to fine-tune a BioBERT model. Finally, we evaluated the model using three previously unseen cohorts and compared its performance to a string-matching baseline model. RESULTSHere, we present our AD-Mapper interface for automatic harmonization of AD cohort studies, which outperformed a string-matching baseline on previously unseen cohort studies. We showcase our CDM comprising 1218 unique variables. DISCUSSIONAD-Mapper leverages semantic similarities in naming conventions across cohorts to improve mapping performance.

bioinformatics↗

The long arm of childhood socioeconomic deprivation on mid- to later-life cognitive trajectories : A cross-cohort analysis

INTRODUCTIONEarlier studies of the effects of childhood socioeconomic status (SES) on later life cognitive function consistently report a social gradient in later life cognitive function. Evidence for their effects on cognitive decline is, however, less clear. METHODSThe sample consists of 5,324 participants in the Whitehall II Study, 8,572 in the Health and Retirement Study, and 1,413 in the Kame Project, who completed self-report questionnaires on their early-life experiences and underwent repeated cognitive assessments. We characterised cognitive trajectories using latent class mixed models, and explored associations between childhood SES and latent class membership using logistic regressions. RESULTSWe identified distinct trajectories classes for all cognitive measures examined. Childhood socioeconomic deprivation was associated with an increased likelihood of being in a lower trajectory class. DISCUSSIONOur findings support the notions that cognitive ageing is a heterogeneous process and early-life circumstances may have lasting effects on cognition across the life-course. Research in contextO_LISystematic review: We reviewed the literature on childhood socioeconomic status (SES) as a predictor for cognitive decline in mid- to later-life using PubMed. Studies generally reported lower childhood SES is associated with poorer baseline cognition, but not a faster rate of decline. These studies generally focused on the mean rate of decline in the population; no study to date has explored associations between childhood SES and different cognitive trajectories. Relevant studies have been appropriately cited. C_LIO_LIInterpretation: Our findings suggest that cognitive trajectories differ between individuals and across cognitive domains. Individuals of lower childhood SES were more likely to be in a lower cognitive trajectory class, which may or may not involve more rapid decline. C_LIO_LIFuture directions: Future studies should include more cognitive outcomes and longer follow-ups, as well as investigate the impact of social mobility to further improve our understanding on how early-life circumstances influence cognitive decline. C_LI

neuroscience↗

Sex differences in interrelationships between arterial stiffness, carotid intima-media thickness, white matter hyperintensities, depression and cognition: A UK Biobank study

ObjectiveTo explore sex differences in the associations between arterial stiffness index, carotid intima-media thickness, white matter hyperintensities, depression and cognition.\n\nMethodsUK Biobank is a population-based cohort study of 502,664 healthy community dwelling adults aged 37-73 years. A select number of participants were recalled to participate in an online reassessment and imaging study, both of which included repeat cognitive assessments. A total of 7,394 volunteers aged 45-73 years (55% female) participated in the imaging visit and completed the self-report mental health questionnaire in the online follow-up were included in the analyses reported here. The main outcome measure of depression was measured using the PHQ-9 and cognition was assessed through measures of reaction time, verbal-numeric reasoning and visual memory. Pulse wave velocity (PWV) was assessed non-invasively using finger photoplethysmography, carotid intima-media thickness (CIMT) with automated ultrasound, and white matter hyperintensity volume with combined T1 and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI).\n\nResultsCross-sectionally, greater arterial stiffness was associated with greater depression in men but with better cognition in women. When white matter hyperintensities burden was added to the model, it mediated the relationships of carotid intima-media thickness with depression and cognition only in men.\n\nConclusionsWe report sex differences in brain microvascular changes, depression and cognition in ageing, and suggest that they may be partly explained by sex-specific effects of vascular ageing.\n\nSummary boxesSection 1: What is already known on this topic O_LIArterial stiffness and carotid intima-media thickness are two non-invasive vascular ageing markers that have been shown to be associated with depression, cognitive impairment and dementia.\nC_LIO_LISome studies report sex differences in arterial stiffness and carotid intima-media thickness.\nC_LIO_LIThere is, however, a paucity of research on sex differences in the associations between these vascular ageing markers, white matter hyperintensities, depression and cognition.\nC_LI\n\nSection 2: What this study adds O_LICross-sectionally, greater arterial stiffness was associated with greater depression in men but with better cognition in women. When white matter hyperintensities burden was added to the model, it mediated the relationships of carotid intima-media thickness with depression and cognition only in men.\nC_LIO_LIOur findings add to the existing evidence base of sex differences in brain microvascular changes, depression and cognition in ageing, and suggest that they may be partly explained by sex-specific effects of vascular ageing.\nC_LI

neuroscience↗

Associations of adverse lifetime experiences with brain structure in 7003 UK Biobank participants

BackgroundExperiences of chronic stress and trauma are major risk factors for psychiatric illness. Evidence suggests that adversity-related changes in brain structure and function accelerate this vulnerability. It is yet to be determined whether neuroendocrine effects on the brain are a result of the interference with neural development during sensitive periods or a consequence of cumulative lifetime adversity. To address this question, the present study investigated the associations between brain structure and self-reported data of childhood and adult adversity using machine learning techniques and structural equation models (SEM).\n\nMethodsThe UK Biobank resource was used to access Imaging Derived Phenotypes (IDPs) of grey matter and white matter tract integrity of 7003 participants, together with selected childhood and adult adversity data. Latent measures of adversity and imaging phenotypes were estimated to evaluate their associations using SEM.\n\nResultsWe demonstrated that increased incidence of childhood adversity events may be associated with smaller grey matter in frontal, insular, subcallosal and cerebellar regions of the brain. There were no significant associations between brain phenotypes and negative experiences during adulthood.\n\nConclusionsUsing a large population cohort dataset, this study contributes to the suggestion that childhood adversity may determine grey matter reductions in brain regions, which are putatively sensitive to the neurotoxic effects of chronic stress. Furthermore, it provides novel evidence to support the \"sensitive periods\" model though which adversity affects the brain.

neuroscience↗

A psychometric evaluation of the 12-item EPQ-R neuroticism scale in 384,183 UK Biobank participants using item response theory (IRT)

Neuroticism has been described as a broad and pervasive personality dimension or heterogeneous trait measuring components of mood instability, such as worry; anxiety; irritability; moodiness; self-consciousness and sadness. Consistent with depression and anxiety-related disorders, increased neuroticism places an individual vulnerable for other unipolar and bipolar mood disorders and therefore highly relevant in epidemiologic research. However, the measurement of neuroticism remains a challenge. We aimed to adapt the 12-item Eysenck Personality Questionnaire-Revised Neuroticism (EPQ-RN) scale for use in epidemiologic studies by identifying psychometrically efficient items using item response theory. The 12-item EPQ-RN scale was evaluated by estimating an IRT model on data from 401,527 UK Biobank participants aged 39 to 73 years (M = 56.41 years; SD = 8.06), 53.68% female. The IRT model yielded two item characteristics: item discrimination, an indicator of how well an item differentiates between respondents, and item difficulty, an indicator of the amount of the latent construct (neuroticism) needed to endorse an item. The EPQ-RN exhibited psychometric inefficiency with poor discrimination at extremes of the scale range. High and low scores are relatively poorly represented and uninformative suggesting that high neuroticism scores derived from the scale are a function of cumulative mid-range values. Following systematic item deletion, a 3-item scale was found to have high levels of discrimination, but offered a narrow range of difficulty i.e. was not sensitive to low levels of neuroticism. A 7-item scale was found to be most informative; providing high levels of discrimination across the range of neuroticism scores.

neuroscience↗

Data Resource Profile:The Dementias Platform UK (DPUK) Data Portal

The Dementias Platform UK (DPUK) Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform (UKSeRP) infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure lab using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Project are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

neuroscience↗