Biology subjects

Graf, S.

Publications and source records attributed to Graf, S..

18 recordsLinked to original sources

bioRxiv2026

Cellular and mitochondrial correlates of regional glucose metabolism in the human cortex

Regional differences in human brain glucose metabolism reflect local energy demands, but their cellular and mitochondrial determinants remain unclear. We combined [18F]FDG positron emission tomography in healthy human participants with estimates of cellular composition and mitochondrial density to unravel (sub)cellular correlates of heterogeneity in brain glucose metabolism. By correcting for RNA content and differential gene expression due to postmortem sampling, we addressed methodological shortcomings in multimodal neuroimaging integration. We introduce transcriptionally derived cytoarchitectonic maps of the human cortex that are consistent with histological findings, providing a biologically grounded framework for relating in vivo neuroimaging signals. Accordingly, mitochondrial distribution showed strong association with the intrinsic energy requirements at resting state. In contrast, relations between metabolism and neuronal composition were driven by sensory input and mitochondria-sparse thin-axon neurons, suggesting that stimulation-induced energy demand is met rather by neuronal processes that are independent of mitochondrial abundance to maintain efficient information processing.

neuroscience↗

bioRxiv2026

Network-specific metabolic cost of functional connectivity in the human brain

Despite decades of extensive research, the complex architecture underlying human brain signaling remains incompletely understood. Previous work investigating the relationship between brain glucose metabolism and functional connectivity (FC) employed whole-brain analysis, without accounting for network interactions, dependencies or hierarchies. Here, we assess network-specific differences in the relationship between FC and metabolic demand, using [18F]FDG PET/MR data from three independent datasets. The metabolic cost of FC, i.e., the change in glucose demand associated with corresponding changes in FC, was modeled at rest, during cognitive task performance and in Alzheimer's disease (AD). Our findings reveal network-specific differences in metabolic cost, with the default mode (DM), somatomotor (SM) and fronto-temporal networks accounting for highest, intermediate and lowest metabolic demands, respectively. Similarly, time-resolved variability of FC demonstrated highest costs for states with DM network involvement and lowest for SM network participation. This relationship was reversed in participants with AD, who exhibited decreased demands in the DM network and increased costs in the SM network. Cognitive performance consistently revealed cost reductions in the DM and SM networks, as well as increases in task relevant networks. Together, these results highlight the flexibility of functional network architecture associated with cognitive demands and neuropathology, and shed light on the complex interplay between glucose metabolism and network interactions.

neuroscience↗

bioRxiv2026

Sex-divergent responses to microglial depletion suggest distinct regulatory dependencies in the aged brain

Microglia are essential for brain homeostasis, yet their roles in the aged brain remain poorly defined. Using microRNA (miRNA) profiling, cellular-resolution spatial transcriptomics, and bulk proteomics in 21-month-old mice, we characterize sex-dimorphic responses to microglial depletion via CSF1R inhibition (PLX5622 treatment). Microglia-enriched miRNAs, notably miR-146a-5p and miR-223-3p, were downregulated across different brain regions in both sexes. Transcriptional responses were sex dimorphic: females showed predominantly cell-type-specific downregulation, while males showed bidirectional changes including upregulation of Lzts3, Shank3, and Fgfbp1 alongside downregulation of Ang. Proteomic changes were larger in magnitude and independent from mRNA changes: males exhibited 295 differentially expressed proteins (DEPs) versus 34 in females (8.7-fold difference). Male DEPs had opposing directional shifts in synaptic vesicle proteins (upregulated) and mitochondrial ATP synthesis machinery (downregulated). These data describe sex-dimorphic molecular consequences of microglial loss in the aged brain and identify candidate post-transcriptional mechanisms warranting further investigation.

neuroscience↗

bioRxiv2026

Differential upregulation of metabolic demands and functional integration of the default mode network during stress

Psychosocial stress engages coordinated physiological and neural responses that enable adaptation to environmental challenges. However, maladaptive stress and reduced resilience are major risk factors for psychiatric and neurodegenerative disorders. As the brains metabolic response to stress remains largely unexplored, we used simultaneous [18F]FDG PET/MRI during performance of the Montreal Imaging Stress Task to assess cerebral glucose metabolism, BOLD activation and functional connectivity. On top of activation in relation to cognitive processing, psychosocial stress specifically recruits the posterior cingulate cortex (PCC) with increased glucose metabolism and attenuated BOLD deactivations. This was accompanied by reduced PCC integration within the default mode network and increased influence onto frontoparietal and dorsal attention networks. Moreover, individuals exhibiting an endocrine stress response showed lower resilience scores, failed to downregulate anterior cingulate cortex (ACC) metabolism during stress, and displayed an inverse relationship between ACC glucose metabolism and anterior insula functional connectivity. Together, these results demonstrate that acute psychosocial stress induces coordinated alterations in brain metabolism and large-scale network organization. Our findings show that metabolic imaging provides complementary information, revealing stress-related brain responses not captured by hemodynamics alone, thereby providing a multimodal framework for understanding human stress processing and individual vulnerability to stress-related psychiatric disorders.

neuroscience↗

bioRxiv2025

A Comparative Evaluation of Molecular Connectivity and Covariance Approaches

Advances in high-temporal-resolution functional positron emission tomography (fPET) now enable the assessment of metabolic associations between brain regions, providing a molecular complement to functional connectivity derived from fMRI. However, the distinction between molecular connectivity (MC) and covariance (mCov) remains conceptually and methodologically inconsistent across studies. This work systematically compares major analytical approaches for MC and mCov to clarify their assumptions, dependencies, and interpretational boundaries with the most used radiotracer [18F]fluorodeoxyglucose to obtain metabolic connectivity (M-MC). Twenty healthy participants underwent ultra-high-sensitivity fPET acquisitions on a large axial field-of-view scanner. M-MC was estimated using CompCor, spatio-temporal filtering, third-order polynomial detrending, baseline normalization and Euclidean distance at multiple temporal resolutions. mCov was assessed from SUVR images with subsequent network- or subject-specific matrix computation using independent component analysis, principal component analysis, or jackknife perturbation. Results demonstrate that while all MC methods are valid, CompCor and Euclidean distance perform optimally at high temporal resolutions (1-16s), whereas polynomial and spatio-temporal filters are more robust at lower sampling rates (>16s). mCov offers a population-level characterization of metabolic organization with the option to derive relative-to-group single-subject maps. This comparison provides methodological clarity and supports standardized use of molecular network analyses now integrated into the open-source fPET toolbox.

neuroscience↗

bioRxiv2025

Test-Retest Reliability of Dopaminergic fPET and fMRI Measures During Reward Processing

Reward processing is essential to human brain function, with dopamine signalling in the nucleus accumbens (NAcc) as key element. The monetary incentive delay task is widely studied with functional magnetic resonance imaging (fMRI), measuring indirect hemodynamic changes. Functional positron emission tomography (fPET) with 6-[18F]FDOPA directly quantifies dopamine synthesis enabling dynamic assessment during task performance within a single scan. We investigated the reliability of 6-[18F]FDOPA fPET and blood oxygenation level dependent (BOLD) fMRI during a modified monetary incentive delay task in 25 healthy participants across two PET/MRI sessions. Intraclass correlation coefficients and coefficients of variance were computed for BOLD beta estimates and striatal dopamine synthesis at 30s and 2s resolutions. fPET showed fair to good reliability in the NAcc and putamen at rest, fair reliability during the win condition in the caudate and putamen, but poor reliability across the loss condition in all regions. Conversely, fMRI showed good reliability in the NAcc during feedback and in the caudate during feedback loss, but fair reliability elsewhere except for poor reliability in the caudate during cue loss. These findings indicate that both methods achieve comparable reliability but in different target areas, with the molecular specificity of fPET offering dynamic assessment of dopaminergic function. Clinicaltrials.gov IdentifierNCT06675851

neuroscience↗

bioRxiv2025

Angiopoietin signalling is a central axis of amyloid-driven vascular dysfunction in Alzheimer's disease

The neurovascular unit is critical for brain health, and its dysfunction has been linked to Alzheimers disease (AD). However, a cell-type-resolved understanding of how diverse vascular cells become dysfunctional and contribute to disease has been missing. Here, we applied Vessel Isolation and Nuclei Extraction for Sequencing (VINE-seq) to build a comprehensive transcriptomic atlas from 101 individuals along AD progression. Our analysis of over 842,646 parenchymal and vascular nuclei reveals that vascular dysfunction in AD is driven by transcriptional changes rather than shifts in cell proportions, with brain endothelial cells (BECs) and smooth muscle cells (SMCs) most affected. Strikingly, these molecular signatures emerge early at the mild cognitive impairment (MCI) stage, implicating vascular dysfunction early in AD pathogenesis. Stratifying by pathology reveals distinct vascular responses to {beta}-amyloid and tau: {beta}-amyloid burden primarily perturbs BECs and SMCs, while tau pathology predominantly impacts glial cells. We identify dysregulated angiopoietin signaling across multiple vascular cell types as a key axis, with antagonistic ANGPT2 in vascular cells and ANGPT1 in astrocytes becoming progressively dysregulated with AD. Together, this work provides a foundational resource that reveals early and pathology-specific pathways of vascular dysfunction in AD. Key MessagesO_LIVINE-seq analysis from 101 individuals creates a comprehensive human brain vascular atlas across Alzheimers disease (AD) progression. C_LIO_LIAD vascular dysfunction is driven by transcriptional changes rather than shifts in cell proportions, with BECs and SMCs most affected. C_LIO_LITranscriptional signatures of vascular dysfunction emerge early at the mild cognitive impairment (MCI) stage, preceding severe cognitive symptoms and aligning more closely with AD than cognitively normal individuals. C_LIO_LIA{beta} and tau associate with distinct vascular changes: A{beta} mainly perturbs endothelial and smooth muscle cells, while tau impacts microglia and astrocytes. C_LIO_LIAngiopoietin signaling (antagonistic ANGPT2 in vascular cells vs. ANGPT1 in astrocytes) becomes progressively dysregulated during AD progression. C_LI

neuroscience↗

bioRxiv2025

High-temporal resolution metabolic connectivity resolved by component-based noise correction

Recent advances in functional PET (fPET) allow for accurate modelling of metabolic processes with a temporal resolution in the range of seconds. This enables new applications such as imaging molecular connectivity at temporal resolutions comparable to fMRI. However, high-temporal resolution fPET data are more sensitive to noise and the extraction of a meaningful signal remains a challenge. We developed a component-based preprocessing approach adapted from fMRI, which models structured noise using tissue-specific regressors and removes low-frequency uptake trends from the fPET signal (CompCor). We applied this method to 20 high-temporal [18F]FDG fPET scans from a next-generation long-axial field of view PET/CT system (1s frames) and 16 scans from a conventional PET/MR scanner (3s frames). We compared filtering methods across frequency bands and examined their effects on metabolic connectivity (M-MC) estimates. Metabolic connectivity was markedly influenced by filtering strategy and scanner type. The CompCor filter produced more consistent and structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) yielded the most reliable connectivity patterns between PET/CT and PET/MR data (r=0.89). High sensitivity PET/CT data revealed structured connectivity patterns also at a higher frequency band (0.1-0.2 Hz). Compared to fMRI functional connectivity, fPET-derived networks were more spatially cohesive but less differentiated. High-temporal [18F]FDG fPET enables reliable estimation of individual resting-state M-MC when paired with appropriate denoising. Scanner choice and preprocessing significantly affect signal quality and interpretation, whereas the proposed physiologically informed pipeline improves comparability across systems and studies.

neuroscience↗

bioRxiv2025

Benchmarking Large Language Models for Pathogen-Disease Classification in Post-Acute Infection Syndromes

Post-Acute Infection Syndromes (PAIS) are medical conditions that persist following acute infections from pathogens such as SARS-CoV-2, Epstein-Barr virus, and Influenza virus. Despite growing global awareness of PAIS and the exponential increase in biomedical literature, only a small fraction of this literature pertains specifically to PAIS, making the identification of pathogen-disease associations within such a vast, heterogeneous, and unstructured corpus a significant challenge for researchers. This study evaluated the effectiveness of large language models (LLMs) in extracting these associations through a binary classification task using a curated dataset of 1,000 manually labeled PubMed abstracts. We benchmarked a wide range of open-source LLMs of varying sizes (4B-70B parameters), including generalist, reasoning, and biomedical-specific models. We also investigated the extent to which prompting strategies such as zero-shot, few-shot, and Chain of Thought (CoT) methods can improve classification performance. Our results indicate that model performance varied by size, architecture, and prompting strategy. Zero-shot prompting produced the most reliable results: Mistral-Small-Instruct-2409 and Nemotron-70B achieved balanced accuracy scores of 0.81 and 0.80, respectively, along with macro-F1 scores of up to 0.80, while maintaining minimal invalid outputs. While few-shot and CoT prompting often degraded performance in generalist models, reasoning models such as DeepSeek-R1-Distill-Llama-70B and QwQ-32B demonstrated improved accuracy and consistency when provided with additional context.

bioinformatics↗

bioRxiv2025

Single-cell Spatial Transcriptomics Reveals Disease-specificMicroenvironmental Niches in Neurodegeneration and COVID-19

Neurodegenerative diseases and infections can produce lasting effects on brain function, yet the spatial molecular mechanisms underlying these changes remain poorly understood. Here, we present high-resolution spatial transcriptomics of 40 postmortem brain samples from patients with Parkinsons disease, frontotemporal dementia, dementia with Lewy bodies, and severe COVID-19. Analyzing over 1.5 million spatially resolved cells across dorsolateral prefrontal cortex and anterior cingulate cortex revealed disease-specific transcriptional signatures with pronounced layer-and region-specificity. In Parkinsons disease, we identified stressed neurons creating distinctive microenvironmental gradients where metabolic and protein degradation pathways are elevated near stress epicenters, while regenerative processes increase with distance. COVID-19 brains displayed extensive peripheral immune cell infiltration, particularly in the subcortical white matter, accompanied by compromised blood-brain barrier and coordinated neuroinflammatory responses from microglia, astrocytes, and endothelial cells. Integration of miRNA sequencing with spatial transcriptomics uncovered layer-specific regulatory patterns, including neuroinflammation-associated miR-155. This atlas provides unprecedented insights into disease pathology and highlights the critical importance of spatial molecular context in understanding brain disorders. Key Messages[1] A high-resolution single-cell spatial transcriptomics atlas of the dorsolateral prefrontal cortex and anterior cingulate cortex across neurodegenerative conditions and severe COVID-19 [2] Region-and layer-specific transcriptional dysregulation across disease comparisons reveals disease-specific differential vulnerability [3] Metabolically stressed cells found selectively in the anterior cingulate cortex of Parkinsons disease patients but not in dementia with Lewy bodies, along with detailed characterization of their spatial microenvironment [4] Peripheral immune cell clusters identified in the white matter of the cerebral cortex of COVID-19 patients, with detailed characterization of their spatial microenvironment [5] Integration of bulk miRNA sequencing reveals cortical layer-specific miRNA regulatory patterns

neuroscience↗

bioRxiv2025

Multimodal brain cell atlas across the adult macaque lifespan

High-throughput single-cell omics of non-human primate tissues present a remarkable opportunity to study primate brain aging. Here, we introduce a transcriptomic and chromatin accessibility landscape of 1,985,317 cells from eight brain regions of 13 cynomolgus female monkeys spanning adult lifespan including exceptionally old individuals up to 29-years old. This dataset uncovers dynamic molecular changes in critical brain functions such as synaptic communication and axon myelination, exhibiting a high degree of cell type and brain region specificity. We identify the multicellular networks of the pons and medulla as a previously unrecognized hotspot for aging. Furthermore, comparative analyses with human neurodegeneration datasets highlight both shared and distinct mechanisms contributing to aging and disease. In addition, we uncover transcription factors implicated in monkey brain aging and pinpoint aging-regulated loci linked to longevity and neurodegeneration. This spatiotemporal atlas will advance our understanding of primate brain aging and its broader implications for health and disease.

neuroscience↗

bioRxiv2024

Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

Aging is a multifactorial and complex physiological process, affecting every organ with characteristic manifestations. Understanding the molecular mechanisms that drive aging processes is crucial to targeting age-related disorders. Recent reports suggest that severe post-infection syndromes can partially accelerate aging. However, the underlying gene-encoded regulatory interplay, whether being shared or distinct between aging and infection biology are poorly understood. Here, we employed spatial transcriptomics to establish a multi-organ atlas (brain, heart, kidney, liver, lung, and spleen) across the mouse lifespan (4, 17, and 26 months). Dissecting high-quality fresh-frozen tissue samples at unbiased molecular resolution, we found both organ-specific and cross-organ gene dysregulation upon aging. We identified age-related trajectories in gene expression and cell state, some only detectable within their spatial context, and provide validation at subcellular resolution. The most prominent effect was organ-wide immune system activation with spatially variable severity. We therefore evaluated how aging mimics the expression signatures observed in systemic infection, using spatial transcriptomics slices from young mice infected with Plasmodium berghei ANKA. While on the gene level the effect sizes caused by the infection outweighed those of aging, we reveal a shared activation of the early complement pathway (C4b) and serine protease inhibitors (Serpin gene family) within by phenotype distinct spatial niches. We show that this common RNA signature is driven by tissue-specific cell types and eventually affects protein levels in the aged brain, rendering them a target for future mechanistic and drug discovery studies. Taken together, our study provides a coherent in-depth and cross-organ transcriptomics atlas to systematically study aging and infection in the mouse at spatiotemporal resolution. Key highlightsO_LILarge-scale and high-resolution atlas of spatial transcriptomics from six organs to study aging and systemic infection across two mouse cohorts. C_LIO_LIStrong transcriptional alterations found in distinct organ-specific niches for aging and acute malaria, with organ- and cell type-associated immune responses. C_LIO_LIDysregulation of early complement proteases (C4b) and serine protease inhibitors (Serpina3n) as common theme across central nervous system and peripheral organs. C_LI

molecular biology↗

bioRxiv2023

Reversal of pulmonary veno-occlusive disease phenotypes by inhibition of the integrated stress response

Pulmonary veno-occlusive disease (PVOD) is a rare form of pulmonary hypertension arising from EIF2AK4 gene mutations or mitomycin C (MMC) administration. The lack of effective PVOD therapies is compounded by a limited understanding of the mechanisms driving the vascular remodeling in PVOD. We show that the administration of MMC in rats mediates the activation of protein kinase R (PKR) and the integrated stress response (ISR), which lead to the release of the endothelial adhesion molecule VE-Cadherin in the complex with Rad51 to the circulation, disruption of endothelial barrier, and vascular remodeling. Pharmacological inhibition of PKR or ISR attenuates the depletion of VE-Cadherin, elevation of vascular permeability, and vascular remodeling instigated by MMC, suggesting potential clinical intervention for PVOD. Finally, the severity of PVOD phenotypes was increased by a heterozygous BMPR2 mutation that truncates the carboxyl tail of BMPR2, underscoring the role of deregulated BMP signal in the development of PVOD.

cell biology↗

bioRxiv2023

ABC-HuMi: the Atlas of Biosynthetic Gene Clusters in the Human Microbiome

The human microbiome has emerged as a rich source of diverse and bioactive natural products, harboring immense potential for therapeutic applications. To facilitate systematic exploration and analysis of its biosynthetic landscape, we present ABC-HuMi: the Atlas of Biosynthetic Gene Clusters (BGCs) in the Human Microbiome. ABC-HuMi integrates data from major human microbiome sequence databases and provides an expansive repository of BGCs compared to the limited coverage offered by existing resources. Employing state-of-the-art BGC prediction and analysis tools, our database ensures accurate annotation and enhanced prediction capabilities. ABC-HuMi empowers researchers with advanced browsing, filtering, and search functionality, enabling efficient exploration of the resource. At present, ABC-HuMi boasts a catalog of 19,218 representative BGCs derived from the human gut, oral, skin, respiratory and urogenital systems. By capturing the intricate biosynthetic potential across diverse human body sites, our database fosters profound insights into the molecular repertoire encoded within the human microbiome and offers a comprehensive resource for the discovery and characterization of novel bioactive compounds. The database is freely accessible at https://www.ccb.uni-saarland.de/abc_humi/. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/558305v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@15af4f6org.highwire.dtl.DTLVardef@886a27org.highwire.dtl.DTLVardef@1f12de5org.highwire.dtl.DTLVardef@fc24be_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Ancient methicillin-resistant Staphylococcus aureus: expanding current knowledge using molecular epidemiological characterization of a Swiss legacy collection

Few methicillin-resistant Staphylococcus aureus (MRSA) from the early years of its global emergence have been sequenced. Knowledge about evolutionary factors promoting the success of specific MRSA multi-locus sequence types (MLSTs) remains scarce. We aimed to characterize a legacy MRSA collection isolated from 1965 to 1987 and compare it against publicly available international and local genomes. We accessed 451 ancient (1965-1987) Swiss MRSA isolates, stored in the Culture Collection of Switzerland. We determined phenotypic antimicrobial resistance (AMR) and performed Illumina short-read sequencing on all isolates and long-read sequencing on a selection with Oxford Nanopore Technology. For context, we included 103 publicly available international genomes from 1960 to 1992 and sequenced 1207 modern Swiss MRSA isolates from 2007 to 2022. We analyzed the core genome (cg)MLST and predicted SCCmec cassette types, AMR, and virulence genes. Among the 451 ancient Swiss MRSA isolates, we found 17 sequence types (STs) of which 11 have been previously described. Two STs were novel combinations of known loci and six isolates carried previously unsubmitted MLST alleles, representing five new STs (ST7843, ST7844, ST7837, ST7839, and ST7842). Most isolates (83% 376/451) represented ST247-MRSA-I isolated in the 1960s, followed by ST7844 (6% 25/451), a novel single locus variant (SLV) of ST239. Analysis by cgMLST indicated that isolates belonging to ST7844-MRSA-III cluster within the diversity of ST239-MRSA-IIII. Early MRSA were predominantly from clonal complex (CC) 8. From 1980 to the end of the 20th century we observed that CC22 and CC5 as well as CC8 were present, both locally and internationally. The combined analysis of 1761 ancient and contemporary MRSA isolates across more than 50 years uncovered novel STs and allowed us a glimpse into the lineage flux between Swiss and international MRSA across time.

microbiology↗

bioRxiv2023

Integrative Multiomics to Dissect the Lung Transcriptional Landscape of Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) remains an incurable and often fatal disease despite currently available therapies. Multiomics systems biology analysis can shed new light on PAH pathobiology and inform translational research efforts. Using RNA sequencing on the largest PAH lung biobank to date (96 disease and 52 control), we aim to identify gene co-expression network modules associated with PAH and potential therapeutic targets. Co-expression network analysis was performed to identify modules of co-expressed genes which were then assessed for and prioritized by importance in PAH, regulatory role, and therapeutic potential via integration with clinicopathologic data, human genome-wide association studies (GWAS) of PAH, lung Bayesian regulatory networks, single-cell RNA-sequencing data, and pharmacotranscriptomic profiles. We identified a co-expression module of 266 genes, called the pink module, which may be a response to the underlying disease process to counteract disease progression in PAH. This module was associated not only with PAH severity such as increased PVR and intimal thickness, but also with compensated PAH such as lower number of hospitalizations, WHO functional class and NT-proBNP. GWAS integration demonstrated the pink module is enriched for PAH-associated genetic variation in multiple cohorts. Regulatory network analysis revealed that BMPR2 regulates the main target of FDA-approved riociguat, GUCY1A2, in the pink module. Analysis of pathway enrichment and pink hub genes (i.e. ANTXR1 and SFRP4) suggests the pink module inhibits Wnt signaling and epithelial-mesenchymal transition. Cell type deconvolution showed the pink module correlates with higher vascular cell fractions (i.e. myofibroblasts). A pharmacotranscriptomic screen discovered ubiquitin-specific peptidases (USPs) as potential therapeutic targets to mimic the pink module signature. Our multiomics integrative study uncovered a novel gene subnetwork associated with clinicopathologic severity, genetic risk, specific vascular cell types, and new therapeutic targets in PAH. Future studies are warranted to investigate the role and therapeutic potential of the pink module and targeting USPs in PAH.

genomics↗

bioRxiv2020

Direct Antimicrobial Resistance Prediction from MALDI-TOF mass spectra profile in clinical isolates through Machine Learning

Early administration of effective antimicrobial treatments is critical for the outcome of infections. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques take up to 72 hours. We have developed a novel machine learning approach to predict antimicrobial resistance directly from MALDI-TOF mass spectra profiles of clinical samples. We trained calibrated classifiers on a newly-created publicly available database of mass spectra profiles from clinically most relevant isolates with linked antimicrobial susceptibility phenotypes. The dataset combines more than 300,000 mass spectra with more than 750,000 antimicrobial resistance phenotypes from four medical institutions. Validation against a panel of clinically important pathogens, including Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae, resulting in AUROC values of 0.8, 0.74, and 0.74 respectively, demonstrated the potential of using machine learning to substantially accelerate antimicrobial resistance determination and change of clinical management. Furthermore, a retrospective clinical case study found that implementation of this approach would have resulted in a beneficial change in the clinical treatment in 88% (8/9) of cases. MALDI-TOF mass spectra based machine learning may thus be an important new tool for antibiotic stewardship.

microbiology↗

bioRxiv2020

Rare variant analysis of 4,241 pulmonary arterial hypertension cases from an international consortium implicate FBLN2, PDGFD and rare de novo variants in PAH

BackgroundGroup 1 pulmonary arterial hypertension (PAH) is a lethal vasculopathy characterized by pathogenic remodeling of pulmonary arterioles leading to increased pulmonary pressures, right ventricular hypertrophy and heart failure. Recent high-throughput sequencing studies have identified additional PAH risk genes and suggested differences in genetic causes by age of onset. However, known risk genes explain only 15-20% of non-familial idiopathic PAH cases. MethodsTo identify new risk genes, we utilized an international consortium of 4,241 PAH cases with 4,175 sequenced exomes (n=2,572 National Biological Sample and Data Repository for PAH; n=469 Columbia University Irving Medical Center, enriched for pediatric trios) and 1,134 sequenced genomes (UK NIHR Bioresource - Rare Diseases Study). Most of the cases were adult-onset disease (93%), and 55% idiopathic (IPAH) and 35% associated with other diseases (APAH). We identified protein-coding variants and performed rare variant association analyses in unrelated participants of European ancestry, including 2,789 cases and 18,819 controls (11,101 unaffected parents from the Simons Powering Autism Research for Knowledge study and 7,718 gnomAD individuals). We analyzed de novo variants in 124 pediatric trios. ResultsSeven genes with rare deleterious variants were significantly associated (false discovery rate <0.1) with IPAH, including three known genes (BMPR2, GDF2, and TBX4), two recently identified candidate genes (SOX17, KDR), and two new candidate genes (FBLN2, fibulin 2; PDGFD, platelet-derived growth factor D). The candidate genes exhibit expression patterns in lung and heart similar to that of known PAH risk genes, and most of the variants occur in conserved protein domains. Variants in known PAH gene, ACVRL1, showed association with APAH. Predicted deleterious de novo variants in pediatric cases exhibited a significant burden compared to the background mutation rate (2.5x, p=7.0E-6). At least eight novel candidate genes carrying de novo variants have plausible roles in lung/heart development. ConclusionsRare variant analysis of a large international consortium identifies two new candidate genes - FBLN2 and PDGFD. The new genes have known functions in vasculogenesis and remodeling but have not been previously implicated in PAH. Trio analysis predicts that ~15% of pediatric IPAH may be explained by de novo variants.

genetics↗