Biology subjects

Harris, M. A.

Publications and source records attributed to Harris, M. A..

14 recordsLinked to original sources

bioRxiv2026

General cognitive function and the brain's structural connectome

General cognitive function ( g) reflects a broad capacity for flexible information processing, yet how brain-wide structural connectivity supports it remains unclear. In 38,824 individuals (26-84 years) across three cohorts, we show that g is supported by a widely distributed white matter network. Across streamline count, fractional anisotropy (FA), and mean diffusivity (MD), meta-analytic associations with g were widespread at global, nodal and edge levels, spanning all cerebral lobes and key subcortical structures and dependent on both inter- and intra-hemispheric connectivity, particularly ipsilateral long-range inter-lobar connections. White matter node-g associations spatially mirrored independent cortical morphometry-g associations, indicating convergence of grey and white matter contributions. Effect sizes increased with age: MD associations became more negative and FA more positive, especially in frontal regions. Edge-level findings replicated across cohorts and predicted g in a hold-out sample. These findings suggest g reflects a distributed structural communication backbone which becomes increasingly important with age.

neuroscience↗

bioRxiv2026

Gene conversion is a key driver of diversity hotspots in M. tuberculosis antigens and virulence-associated loci

Despite the long-held view of Mycobacterium tuberculosis (Mtb) as a genetically conserved pathogen, many genomic regions remain poorly resolved due to high sequence homology and repetitive content. Using complete genome assemblies generated from long-read sequencing of 151 globally representative clinical isolates, we comprehensively analyzed genome-wide patterns of genetic diversity and evolution across the Mtb genome. Our analysis uncovers pronounced diversity hotspots within paralogous regions generated by recurrent gene conversion between homologous genes. In many cases, these hotspots exhibit more than an order of magnitude greater genetic diversity than the rest of the Mtb genome, which is otherwise characterized by remarkably low variation. Mutations within these regions display clustered substitution patterns, excess paralog-matching variants, and distinct mutational spectra consistent with ongoing gene conversion. Our analysis identifies over 300 individual gene conversion events distributed throughout the Mtb phylogeny. These gene conversion events occur predominantly within gene families associated with virulence and host-pathogen interactions, including the PE, PPE, and ESX families. Several of the most pronounced diversity hotspots occur in antigens encoded within paralogous regions. Among these, the vaccine candidate PPE18 harbors mutations in validated epitope sequences and predicted alterations in HLA-II binding. Together, these findings demonstrate that gene conversion actively shapes antigenic and virulence-associated diversity in Mtb.

genomics↗

bioRxiv2024

The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.

bioinformatics↗

bioRxiv2023

General and specific patterns of cortical gene expression as substrates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given genes expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|{beta}| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

neuroscience↗

bioRxiv2021

JaponicusDB: Rapid deployment of a model organism database for an emerging model species

The fission yeast Schizosaccharomyces japonicus has recently emerged as a powerful system for studying the evolution of essential cellular processes, drawing on similarities as well as key differences between S. japonicus and the related, well-established model Schizosaccharomyces pombe. We have deployed the open-source, modular code and tools originally developed for PomBase, the S. pombe model organism database (MOD), to create JaponicusDB (www.japonicusdb.org), a new MOD dedicated to S. japonicus. By providing a central resource with ready access to a growing body of experimental data, ontology-based curation, seamless browsing and querying, and the ability to integrate new data with existing knowledge, JaponicusDB supports fission yeast biologists to a far greater extent than any other source of S. japonicus data. JaponicusDB thus enables S. japonicus researchers to realise the full potential of studying a newly emerging model species, and illustrates the widely applicable power and utility of harnessing reusable PomBase code to build a comprehensive, community-maintainable repository of species-relevant knowledge.

bioinformatics↗

bioRxiv2021

Fission stories: Using PomBase to understand Schizosaccharomyces pombe biology

PomBase (www.pombase.org), the model organism database (MOD) for the fission yeast Schizosaccharomyces pombe, supports research within and beyond the S. pombe community by integrating and presenting genetic, molecular, and cell biological knowledge into intuitive displays and comprehensive data collections. With new content, novel query capabilities, and biologist-friendly data summaries and visualisation, PomBase also drives innovation in the MOD community.

bioinformatics↗

bioRxiv2020

Term Matrix: A novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally, and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes likely reflects errors in literature curation, ontology structure, or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g., amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 2.5 million automatically propagated annotations across all taxa.

bioinformatics↗

bioRxiv2020

Three major dimensions of human brain cortical ageing in relation to cognitive decline across the 8th decade of life.

Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflates information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the 8th decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1,376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions, that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging.

neuroscience↗

bioRxiv2019

Enhanced prediction of cognitive function using aging-sensitive networks within the human structural connectome

Using raw structural and diffusion brain MRI data from the UK Biobank (UKB; N = 3,155, ages 45-75 years) and the Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we examine aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within networks-of-interest in the human brain connectome. In UKB, the magnitude of age-differences in individual node volumes and edge weights corresponds closely with their loadings on their respective principal components of connectome-wide integrity (|rnodes| = 0.459; |redges| = 0.595). In LBC1936, connectome-wide and subnetwork-specific composite indices of node integrity were predictive of processing speed, visuospatial ability, and memory, whereas composite indices of edge integrity were associated specifically with processing speed. Childhood IQ was associated with greater node integrity at age 73. However, node and edge integrity remained associated with age 73 cognitive function after controlling for childhood IQ. Adult connectome integrity is therefore both a marker of early-life cognitive function and a substrate of late-life cognitive aging.

neuroscience↗

bioRxiv2019

Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures

BackgroundSubstantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.\n\nMethodsThe present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2,370 male and 2,574 female UK Biobank participants.\n\nResultsThere was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness ({beta}=.191, q=.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases ({beta}=.098, p=.026), compared to a negative association among controls ({beta}=-.087, p=.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.\n\nConclusionsOur significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.

neuroscience↗

bioRxiv2019

Trajectory of brain maturation in adolescent individuals at familial risk of mood disorder

BackgroundAccelerated biological ageing has been proposed as a mechanism underlying mood disorder, but has been predominantly studied cross-sectionally in adult populations. It remains unclear whether differential ageing/maturation trajectories emerge earlier in life, in particular during the neurodevelopmental period of adolescence, and whether they are associated with onset of mood disorder and/or presence of familial risk. MethodsParticipants were young individuals (16-25 years) from the prospective longitudinal Scottish Bipolar Family Study (SBFS) with and without family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, individual maturational trajectories were captured by the difference between predicted brain age and chronological age (brain-PAD) at baseline and two-year follow-up. Based on clinical assessment at follow-up, individuals were categorised into three groups: (i) controls who remained well (C-well, n=94), (ii) high familial risk who remained well (HR-well, n=73) and (iii) high familial risk who developed a mood disorder (HR-MD, n=38). ResultsResults showed no differences in brain-PAD between groups at baseline or follow-up. However, we found negative trajectories of brain-PAD for HR-MD versus C-well ({beta}= -0.68 years, p<.001) and versus HR-well ({beta}= -0.38 years, p=.01), and for HR-well versus C-well ({beta}= -0.30 years, p=.03). ConclusionsThese findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain maturation trajectory. However, without significantly differential status of brain maturation at follow-up, extended longitudinal research will need to show whether this marks the emergence of maturational lag.

neuroscience↗

bioRxiv2019

Associations between vascular risk factors and brain MRI indices in UK Biobank

AimsSeveral factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular risk factors (VRFs) and detailed aspects of brain macro- and microstructure in large community-dwelling populations across middle- and older age.\n\nMethods and ResultsAssociations between VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholersterolaemia, BMI, and waist-hip ratio) and both global and regional brain structural and diffusion MRI markers were examined in UK Biobank (N = 9722, age range 44-77 years). A larger number of VRFs was associated with greater brain atrophy, lower grey matter volume, and poorer white matter health. Effect sizes were small (brain structural R2 [≤] 1.8%). Higher aggregate vascular risk was related to multiple regional MRI hallmarks associated with dementia risk: lower frontal and temporal cortical volumes, lower subcortical volumes, higher white matter hyperintensity volumes, and poorer white matter microstructure in association and thalamic pathways. Smoking pack years, hypertension and diabetes showed the most consistent associations across all brain measures. Hypercholesterolaemia was not uniquely associated with any MRI marker.\n\nConclusionHigher levels of VRFs were associated with poorer brain health across grey and white matter macro- and microstructure. Effects are mainly additive, converging upon frontal and temporal cortex, subcortical structures, and specific classes of white matter fibres. Though effect sizes were small, these results emphasise the vulnerability of brain health to vascular factors even in relatively healthy middle and older age, and the potential to partly ameliorate cognitive decline by addressing these malleable risk factors.

neuroscience↗

bioRxiv2018

Planar cell polarity pathway and development of the human visual cortex

The radial unit hypothesis provides a framework for global (proliferation) and regional (distribution) expansion of the primate cerebral cortex. Using principal component analysis (PCA), we have identified cortical regions with shared variance in their surface area and cortical thickness, respectively, segmented from magnetic resonance images obtained in 23,800 participants. We then carried out meta-analyses of genome-wide association studies of the first two principal components for each phenotype. For surface area (but not cortical thickness), we have detected strong associations between each of the components and single nucleotide polymorphisms in a number of gene loci. The first (global) component was associated mainly with loci on chromosome 17 (9.5e-32 [≤] p [≤] 2.8e-10), including those detected previously as linked with intracranial volume and/or general cognitive function. The second (regional) component captured shared variation in the surface area of the primary and adjacent secondary visual cortices and showed a robust association with polymorphisms in a locus on chromosome 14 containing Disheveled Associated Activator of Morphogenesis 1 (DAAM1; p=2.4e-34). DAAM1 is a key component in the planar-cell-polarity signaling pathway. In follow-up studies, we have focused on the latter finding and established that: (1) DAAM1 is highly expressed between 12th and 22nd post-conception weeks in the human cerebral cortex; (2) genes co-expressed with DAAM1 in the primary visual cortex are enriched in mitochondria-related pathways; and (3) volume of the lateral geniculate nucleus, which projects to regions of the visual cortex staining for cytochrome oxidase (a mitochondrial enzyme), correlates with the surface area of the visual cortex in major-allele homozygotes but not in carriers of the minor allele. Altogether, we speculate that, in concert with thalamocortical input to cortical subplate, DAAM1 enables migration of neurons to cytochrome-oxidase rich regions of the visual cortex, and, in turn, facilitates regional expansion of this set of cortical regions during development.

neuroscience↗

bioRxiv2017

Sex Differences In The Adult Human Brain: Evidence From 5,216 UK Biobank Participants

Sex differences in the human brain are of interest, for example because of sex differences in the observed prevalence of psychiatric disorders and in some psychological traits. We report the largest single-sample study of structural and functional sex differences in the human brain (2,750 female, 2,466 male participants; 44-77 years). Males had higher volumes, surface areas, and white matter fractional anisotropy; females had thicker cortices and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume or height. There was generally greater male variance across structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

neuroscience↗