Biology subjects

Douaud, G.

Publications and source records attributed to Douaud, G..

11 recordsLinked to original sources

bioRxiv2023

Internally-consistent and fully-unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM

Anatomical MRI templates of the brain are essential to group-level analyses and image processing pipelines, as they provide a reference space for spatial normalisation. While it has become common for studies to acquire multimodal MRI data, many templates are still limited to one type of modality, usually either scalar or tensor-based. Aligning each modality in isolation does not take full advantage of the available complementary information, such as strong contrast between tissue types in structural images, or axonal organisation in the white matter in diffusion tensor images. Most existing strategies for multimodal template construction either do not use all modalities of interest to inform the template construction process, or do not use them in a unified framework. Here, we present multimodal, cross-sectional templates constructed from UK Biobank data: the OMM-1 template, and age-dependent templates for each year of life between 45 to 81. All templates are fully unbiased to represent the average shape of the populations they were constructed from, and internally consistent through jointly informing the template construction process with T1, T2-FLAIR and DTI data. The OMM-1 template was constructed with a multi-resolution, iterative approach using 240 individuals in the 50-55 year age range. The age-dependent templates were estimated using a Gaussian Process, which describes the change in average brain shape with age in 37,330 individuals. All templates show excellent contrast and alignment within and between modalities. The global brain shape and size is not preconditioned on existing templates, although maximal possible compatibility with MNI-152 space was maintained through rigid alignment. We showed benefits in registration accuracy across two datasets (UK Biobank and HCP), when using the OMM-1 as the template compared with FSLs MNI-152 template, and found that the use of age-dependent templates further improved accuracy to a small but detectable extent. All templates are publicly available and can be used as a new reference space for uni- or multimodal spatial alignment.

neuroscience↗

bioRxiv2023

MMORF - FSL's MultiMOdal Registration Framework

We present MMORF--FSLs MultiMOdal Registration Framework--a newly released nonlinear image registration tool designed primarily for application to MRI images of the brain. MMORF is capable of simultaneously optimising both displacement and rotational transformations within a single registration framework by leveraging rich information from multiple scalar and tensor modalities. The regularisation employed in MMORF promotes local rigidity in the deformation, and we have previously demonstrated how this effectively controls both shape and size distortion, and leads to more biologically plausible warps. The performance of MMORF is benchmarked against three established nonlinear registration methods--FNIRT, ANTs and DR-TAMAS--across four domains: FreeSurfer label overlap, DTI similarity, task-fMRI cluster mass, and distortion. Results show that MMORF performs as well as or better than all other methods across every domain--both in terms of accuracy and levels of distortion. MMORF is available as part of FSL, and its inputs and outputs are fully compatible with existing workflows. We believe that MMORF will be a valuable tool for the neuroimaging community, regardless of the domain of any downstream analysis, providing state-of-the-art registration performance that integrates into the rich and widely adopted suite of analysis tools in FSL.

neuroscience↗

bioRxiv2021

Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging

A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging MRI technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We developed a QSM processing pipeline to estimate magnetic susceptibility of multiple brain structures in 35,885 subjects from the UK Biobank prospective epidemiological study. We identified phenotypic associations of magnetic susceptibility that include body iron, disease, diet, and alcohol consumption. Genome-wide associations related magnetic susceptibility to genetic variants with biological functions involving iron, calcium, myelin, and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers world-wide, creating potential to discover novel, non-invasive markers of brain health.

neuroscience↗

bioRxiv2020

Multimodal imaging brain markers in early adolescence are linked with a physically active lifestyle

The World Health Organization (WHO) promotes physical exercise and a healthy lifestyle as means to improve youth development. However, relationships between physical lifestyle and brain development are not fully understood. Here, we asked whether a brain - physical latent mode of covariation underpins the relationship between physical activity, fitness, and physical health measures with multimodal neuroimaging markers. In 50 12-year old school pupils (26 females), we acquired multimodal whole-brain MRI, characterizing brain structure, microstructure, function, myelin content, and blood perfusion. We also acquired physical variables measuring objective fitness levels, 7-days physical activity, body-mass index, heart rate, and blood pressure. Using canonical correlation analysis we unravel a latent mode of brain - physical covariation, independent of demographics, school, or socioeconomic status. We show that MRI metrics with greater involvement in this mode also showed spatially extended patterns across the brain. Specifically, global patterns of greater grey matter perfusion, volume, cortical surface area, greater white matter extra-neurite density, and resting state networks activity, covaried positively with measures reflecting a physically active phenotype (high fit, low sedentary individuals). Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes. These results support the notion of close brain-body relationships and underline the importance of investigating modifiable lifestyle factors not only for physical health but also for brain health early in adolescence. Significance statementAn active lifestyle is key for healthy development. In this work, we answer the following question: How do brain neuroimaging markers relate with young adolescents level of physical activity, fitness, and physical health? Combining advanced whole-brain multimodal MRI metrics with computational approaches, we show a robust relationship between physically active lifestyles and spatially extended, multimodal brain imaging derived phenotypes. Suggesting a wider effect on brain neuroimaging metrics than previously thought, this work underlies the importance of studying physical lifestyle, as well as other brain - body relationships in an effort to foster brain health at this crucial stage in development.

neuroscience↗

bioRxiv2020

Enhanced Brain Imaging Genetics in UK Biobank

UK Biobank is a major prospective epidemiological study that is carrying out detailed multimodal brain imaging on 100,000 participants, and includes genetics and ongoing health outcomes. As a step forwards in understanding genetic influence on brain structure and function, in 2018 we published genome-wide associations of 3,144 brain imaging-derived phenotypes, with a discovery sample of 8,428 UKB subjects. Here we present a new open resource of GWAS summary statistics, resulting from a greatly expanded set of genetic associations with brain phenotypes, using the 2020 UKB imaging data release of approximately 40,000 subjects. The discovery sample has now almost tripled (22,138), the number of phenotypes increased to 3,935 and the number of genetic variants with MAF[≥]1% increased to 10 million. For the first time, we include associations on the X chromosome, and several new classes of image derived phenotypes (primarily, more fine-grained subcortical volumes, and cortical grey-white intensity contrast). Previously we had found 148 replicated clusters of associations between genetic variants and imaging phenotypes; here we find 692 replicating clusters of associations, including 12 on the X chromosome. We describe some of the newly found associations, focussing particularly on the X chromosome and autosomal associations involving the new classes of image derived phenotypes. Our novel associations implicate pathways involved in the rare X-linked syndrome STAR (syndactyly, telecanthus and anogenital and renal malformations), Alzheimers disease and mitochondrial disorders. All summary statistics are openly available for interactive viewing and download on the "BIG40" open web server.

neuroscience↗

bioRxiv2019

XTRACT - Standardised protocols for automated tractography and connectivity blueprints in the human and macaque brain

We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.

neuroscience↗

bioRxiv2019

Brain aging comprises multiple modes of structural and functional change with distinct genetic and biophysical associations

Brain imaging can be used to study how individuals brains are aging, compared against population norms. This can inform on aspects of brain health; for example, smoking and blood pressure can be seen to accelerate brain aging. Typically, a single "brain age" is estimated per subject, whereas here we we identified 62 modes of subject variability, from 21,407 subjects multimodal brain imaging data in UK Biobank. The modes represent different aspects of brain aging, showing distinct patterns of functional and structural brain change, and distinct patterns of association with genetics, lifestyle, cognition, physical measures and disease. While conventional brain-age modelling found no genetic associations, 34 modes had genetic associations. We suggest that it is important not to treat brain aging as a single homogeneous process, and that modelling of distinct patterns of structural and functional change will reveal more biologically meaningful markers of brain aging in health and disease.

neuroscience↗

bioRxiv2019

Population-based neuroimaging reveals traces of childbirth in the maternal brain

Pregnancy and childbirth involve maternal brain adaptations that promote attachment to and protection of the newborn. Using brain imaging and machine learning, we provide evidence for a positive relationship between number of childbirths and a younger-looking brain in 12,021 women, which could not be explained by common genetic variation. The findings demonstrate that parity can be linked to brain health later in life.

neuroscience↗

bioRxiv2018

Human Handedness: Genetics, Microtubules, Neuropsychiatric Diseases and Brain Language Areas

BackgroundThe skew in distribution of handedness is a uniquely human trait, and has fascinated researchers for centuries. The heritability of handedness is estimated at 25%, but defining genetic variants contributing to this trait has so far proved elusive.\n\nMethodsWe performed GWAS of self-reported handedness in UK Biobank, a prospective cohort study of [~]500,000 individuals. Furthermore, we investigated correlations between our associated SNPs and brain imaging-derived phenotypes (IDPs) from >9,000 individuals in UK Biobank, as well as between self-reported handedness and IDPs.\n\nResultsOur association study of 38,322 left-handers vs 356,567 right-handers (excluding ambidextrous participants) revealed three genome-wide significant loci (rs199512, 17q21.31, p=4.1x10-9; rs45608532, 22q11.22, p=1.4x10-8; rs13017199, 2q34, p=3.3x10-8). In the imaging study, we found strong associations between rs199512 and diffusion MRI measures mainly in white matter tracts connecting language-related brain regions (p<2.0x10-6). Direct investigation between handedness and IDPs revealed numerous associations with functional connectivity between the same language-related areas of the brain. A second GWAS of non-right handers (n=44,631) vs right-handers (n=356,567) revealed an additional locus: rs3094128, 6p21.33, p=2.9x10-8. Three of the four associated loci (2q34, 17q21.31, 6p21.33) contain genes that encode microtubule-related proteins that are highly expressed in the brain: MAP2, MAPT and TUBB. These genes are strongly implicated in the pathogenesis of diseases that are known to affect an excess of left-handed people, including schizophrenia.\n\nConclusionsThis is the first GWAS to identify genome-wide significant loci for human handedness in the general population, and the genes at these loci have biological plausibility in contributing to neurodevelopmental lateralization of brain organisation, which appears to predispose both to left-handedness and to certain neurodegenerative and psychiatric diseases.

neuroscience↗

bioRxiv2017

The genetic basis of human brain structure and function: 1,262 genome-wide associations found from 3,144 GWAS of multimodal brain imaging phenotypes from 9,707 UK Biobank participants

The genetic basis of brain structure and function is largely unknown. We carried out genome-wide association studies of 3,144 distinct functional and structural brain imaging derived phenotypes in UK Biobank (discovery dataset 8,428 subjects). We show that many of these phenotypes are heritable. We identify 148 clusters of SNP-imaging associations with lead SNPs that replicate at p<0.05, when we would expect 21 to replicate by chance. Notable significant and interpretable associations include: iron transport and storage genes, related to changes in T2* in subcortical regions; extracellular matrix and the epidermal growth factor genes, associated with white matter micro-structure and lesion volume; genes regulating mid-line axon guidance development associated with pontine crossing tract organisation; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide new insight into the genetic architecture of the brain with relevance to complex neurological and psychiatric disorders, as well as brain development and aging. The full set of results is available on the interactive Oxford Brain Imaging Genetics (BIG) web browser.

genetics↗

bioRxiv2017

Image Processing and Quality Control for the first 10,000 Brain Imaging Datasets from UK Biobank

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.

neuroscience↗