Biology subjects

Sim, K.

Publications and source records attributed to Sim, K..

11 recordsLinked to original sources

bioRxiv2025

A Scalable Toolkit for Modeling 3D Surface-based Brain Geometry

3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N=3,373).

neuroscience↗

bioRxiv2025

Staphylococcus haemolyticus is a reservoir of antibiotic resistance genes in the preterm infant gut

Among coagulase-negative staphylococci, Staphylococcus haemolyticus is a primary cause of bloodstream infections in preterm infants, with gut colonisation being recognised as a risk factor for subsequent infection. Through a re-analysis of a 16S rRNA gene sequencing dataset (n=497 preterm infants), we found that S. haemolyticus was abundant and prevalent in the gut in the first month of life. To better understand the diversity of S. haemolyticus among preterm infants, we generated genome sequences of S. haemolyticus strains (n=140), which were isolated from 44 stool samples of 22 preterm infants from four different hospitals in the United Kingdom. Core genome phylogenetic analyses, incorporating 126 publicly available S. haemolyticus genome sequences, showed that 85/140 (60.1%) of the isolates, from three different hospitals, formed a clonal group with 79/85 (92.9%) strains being assigned to Multi-Locus Sequence Type (ST) 49. Antibiotic resistance genes were highly prevalent in the genome sequences. Using logistic regression, we found a strong association between the presence of the gene mecA and phenotypic resistance to oxacillin (odds ratio [OR]: 158.00, p<0.0001), and the aacA-aphD gene and phenotypic resistance to gentamicin aacA-aphD (OR: 162.00, p<0.001). None of the strains from the preterm infant cohort had a complete Staphylococcal Cassette Chromosome mec (SCCmec) element. The aacA-aphD gene was associated with the transposon Tn4001. Using hybrid genome assemblies, we found it to be present on the chromosome (54.5% of strains) or on diverse plasmids (27.3%). Four strains (18.2%) had Tn4001 copies on both plasmid and chromosome. Our data suggest the existence of a distinct sub-population of S. haemolyticus that has adapted to colonise the gut of preterm infants. Prevalent resistance to antibiotics is of clinical concern and the diversity of genetic contexts of mecA and Tn4001 suggests widespread horizontal gene transfer and recombination in this species.

microbiology↗

bioRxiv2024

Impact of early life antibiotic and probiotic treatment on gut microbiome and resistome of very-low-birth-weight preterm infants

Preterm infants (<37 weeks gestation) are often administered broad-spectrum antibiotics in hospitals due to their vulnerability to severe morbidity, including necrotising enterocolitis and sepsis. However, antibiotics can disrupt the development of early-life microbiota, potentially impairing gut immunity and colonisation resistance. Evidence shows that probiotics (e.g., certain Bifidobacterium strains) may help restore healthy gut microbiota. In this study, we examined the effects of probiotics and antibiotics on the preterm gut microbiome and resistome in two unique cohorts of 34 very-low-birth-weight, human-milk- fed preterm infants (moderate to very preterm), with one cohort receiving probiotics. Within each group, some infants were treated with antibiotics (benzylpenicillin and/or gentamicin) while others served as non-antibiotic treated controls. We performed shotgun metagenomic sequencing on 93 longitudinal faecal samples from 34 infants, generated >300 metagenome- assembled genomes, and obtained [~]90 isolate genomes through targeted culturomics, enabling analysis of the microbiome/resistome at species and strain levels. Additionally, we investigated in vitro horizontal gene transfer (HGT) capacity of preterm infant-derived multidrug-resistant (MDR) pathogen Enterococcus via neonatal gut models. Overall, probiotic supplementation significantly reduced antibiotic resistance gene prevalence, MDR pathogen load, and helped restore a typical early-life microbiota. However, the persistence of MDR pathogens like Enterococcus, with high HGT potential, highlights the need for ongoing surveillance in neonatal care. Our findings underscore the complex interactions between antibiotics, probiotics, and HGT in shaping the neonatal microbiome and support further research into probiotics for antimicrobial stewardship in preterm populations.

microbiology↗

bioRxiv2023

Estimating multimodal brain variability in schizophreniaspectrum disorders: A worldwide ENIGMA study

ObjectiveSchizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. MethodsThis meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. ResultsWe found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. ConclusionsHigher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

neuroscience↗

bioRxiv2023

Connectome architecture shapes large-scale cortical reorganization in schizophrenia: a worldwide ENIGMA study

While schizophrenia is considered a prototypical network disorder characterized by widespread brain-morphological alterations, it still remains unclear whether distributed structural alterations robustly reflect underlying network layout. Here, we tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2,439 adults with schizophrenia and 2,867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n=207), we evaluated structural alterations of schizophrenia against two network susceptibility models: i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; ii) epicenter mapping, which identify regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Schizophrenia-related structural alterations co-localized with interconnected functional and structural hubs and harbored temporo-paralimbic and frontal epicenters. Findings were robust across sites and related to individual symptom profiles. We observed localized unique epicenters for first-episode psychosis and early stages, and transmodal epicenters that were shared across first-episode to chronic stages. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, yielding insights in pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work contributes to recognizing potentially common pathways to better understand macroscale structural alterations, and inter-individual variability in schizophrenia.

neuroscience↗

bioRxiv2022

A Large-Scale ENIGMA Multisite Replication Study of Brain Age in Depression

BackgroundSeveral studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived "brain age gap" has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N=2,126 controls & N=2,675 cases; +1.08 years [SE 0.22], Cohens d=0.14, 95% CI: 0.08-0.20), in independent cohorts that were not part of the original study. MethodsA previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18-75 years) from 13 new cohorts collected from 20 different scanners. ResultsOur ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2=0.47, MAE=7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohens d{square}={square}{square}.15, 95% CI: 0.05-0.25) compared with controls, highly similar to our previous finding. ConclusionsThis study further validates our previously developed ENIGMA brain age algorithm. Importantly, we replicated the brain age gap in depression with a comparable effect size. Thus, two large-scale independent mega-analyses across in total 32 cohorts and >3,400 patients and >2,800 controls worldwide show reliable but subtle effects of brain aging in adult depression.

neuroscience↗

bioRxiv2022

Development of the gut microbiota during early life in premature and term infants

BackgroundThe gastrointestinal (GI) microbiota has been linked to health consequences throughout life, from early life illnesses (e.g. sepsis and necrotising enterocolitis) to lifelong chronic conditions such as obesity and inflammatory bowel disease. It has also been observed that events in early life can lead to shifts in the microbiota, with some of these changes having been documented to persist into adulthood. A particularly extreme example of a divergent early GI microbiota occurs in premature neonates, who display a very different GI community to term infants. Certain characteristic patterns have been associated with negative health outcomes during the neonatal period, and these patterns may prove to have continual damaging effects if not resolved. ResultsIn this study we contrast a set of premature infants with a paired set of term infants (n=37 pairs) at six weeks of life and at two years. In the samples taken at six weeks we find microbial communities differing in both diversity and specific bacterial groups between the two infant cohorts. We identify clinical factors associated with over-abundance of potentially pathogenic organisms (e.g. Enterobacteriaceae) and reduced abundances of some beneficial organisms (e.g. Bifidobacterium). We contrast these findings with samples taken at two years of age, which show that despite a very different initial microbiota, the two infant groups converge to a similar, more adult-like state. We identify clinical factors, including both prematurity and delivery method, that remain associated with components of the microbiota. Both clinical factors and microbial characteristics are compared to the occurrence of childhood wheeze and eczema, revealing associations between components of the GI microbiota and the development of these allergic conditions. ConclusionsThe faecal microbiota differs greatly between infants born at term and those born prematurely during early life, yet it converges over time. Despite this, early clinical factors remain significantly associated with the abundance of some bacterial groups at two years of age. Given the associations made between health conditions and the microbiota, factors that alter the makeup of the gut microbiota, and potentially its trajectory through life, could have important lifelong consequences.

genomics↗

bioRxiv2021

Dissemination and pathogenesis of toxigenic Clostridium perfringens strains linked to neonatal intensive care units and Necrotising Enterocolitis

BackgroundClostridium perfringens is an anaerobic toxin-producing bacterium that has long been associated with intestinal diseases, particularly in neonatal humans and animals. More recently, infant gut microbiome studies have suggested an important link between C. perfringens and the devastating preterm-associated disease Necrotising Enterocolitis (NEC), but in-depth studies on this pathogen (genomics and mechanistic) are lacking. Methods/MaterialsWe isolated and whole-genome sequenced 274 infant-associated C. perfringens isolates from 5 hospitals across the UK between 2011-2016 (including longitudinal samples from 31 individuals). We performed in-depth genomic analyses, phenotypically characterised pathogenic traits of 10 strains (including 4 C. perfringens from NEC patients) and established a novel oral-challenge C57BL/6 mouse infection model for microbe-host studies. ResultsPore-forming toxin encoding genes pfoA and cpb2 were enriched within hypervirulent lineages that exclusively consisted of C. perfringens-associated NEC (CPA-NEC) strains, in addition to overabundance of colonisation factors. Importantly, we identified a circulating C. perfringens variant, eventually linked to a fatal CPA-NEC case. The variant was detected consistently within 6 individuals in two sister hospitals across a 40-day window, demonstrating for the first time the intra- and inter-hospital dissemination of C. perfringens. CPA-NEC isolates were determined phenotypically to be more virulent (linked with overabundance of gene pfoA) than isolates obtained from non-NEC preterm babies. In addition, two pfoA-positive CPA-NEC C. perfringens strains were confirmed to induce clinical inflammatory tissue lesions in vivo. ConclusionsHypervirulent lineages are linked to CPA-NEC, potentially due to the production of pore-forming toxins, coupled with higher metabolic, transmission, and pathogenic capacities. These studies indicate C. perfringens is an important bacterial pathogen in preterm infants and highlights the requirement for further investigation into development of intervention and therapeutic strategies.

microbiology↗

bioRxiv2019

Microbiota supplementation with Bifidobacterium and Lactobacillus modifies the preterm infant gut microbiota and metabolome

Supplementation with members of the early-life microbiota or probiotics is becoming increasingly popular to attempt to beneficially manipulate the preterm gut microbiota. We performed a large longitudinal study comprising two preterm groups; 101 orally supplemented with Bifidobacterium and Lactobacillus (Bif/Lacto) and 133 non-supplemented (Control) matched by age, sex, birth-mode, and diet. 16S rRNA metataxonomic profiling on stool samples (n = 592) indicated a predominance of Bifidobacterium, and a reduction of pathobionts in the Bif/Lacto group. Metabolic phenotyping found a parallel increase in fecal acetate and lactate in the Bif/Lacto group compared to the Control group, which positively correlated with Bifidobacterium abundance consistent with the ability of the supplemented Bifidobacterium strain to metabolize human milk oligosaccharides and reduced gut pH. This study demonstrates that microbiota supplementation can modify the preterm microbiome and the gastrointestinal environment to more closely resemble that of a full-term infant.

microbiology↗

bioRxiv2018

Streaming histogram sketching for rapid microbiome analytics

MotivationThe growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research; allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time.\n\nTo address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching, and classification of microbiome samples in near real-time.\n\nResultsWe apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed histosketch that can be used to efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we show that histosketches can be used to train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a Random Forest Classifier that could accurately predict whether the neonate had received antibiotic treatment (95% accuracy, precision 97%) and could subsequently be used to classify microbiome data streams in less than 12 seconds.\n\nWe provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2GB microbiome in 50 seconds on a standard laptop using 4 cores, with the sketch occupying 3000 bytes of disk space.\n\nAvailabilityOur implementation (HULK) is written in Go and is available at: https://github.com/will-rowe/hulk (MIT License)

genomics↗

bioRxiv2018

Genome Wide Study of Tardive Dyskinesia in Schizophrenia

Tardive dyskinesia (TD) is a severe condition characterized by repetitive involuntary movement of orofacial regions and extremities. Patients treated with antipsychotics typically present with TD symptomatology. Here, we conducted the largest GWAS of TD to date, by meta-analyzing samples of East-Asian, European, and African-American ancestry, followed by analyses of biological pathways and polygenic risk with related phenotypes. We identified a novel locus and three suggestive loci, implicating immune-related pathways. Through integrating trans-ethnic fine-mapping, we identified putative credible causal variants for three of the loci. Multivariate analyses of polygenic risk for TD supports the genetic susceptibility of TD, with relatively lower allele frequencies variants being associated with TD, beyond that of antipsychotic medication. Together, these findings provide new insights into the genetic architecture and biology of TD.

genomics↗