Biology subjects

Traut, N.

Publications and source records attributed to Traut, N..

10 recordsLinked to original sources

bioRxiv2026

Cortical folding patterns are encoded in the geometry of the unfolded neocortex.

Cortical folding patterns are conserved across individuals of gyrencephalic species and are closely related to cytoarchitectural organisation, connectivity, and function. Early morphogen gradients have been proposed as the molecular source of positional information encoding these patterns - a gyral molecular protomap - but the contribution of neocortical geometry to this encoding has not been examined. Here we show that the geometry of the unfolded ferret brain guides the adult folding pattern before any folding has occurred. Using high-resolution MRI surface reconstructions from postnatal day (P) 0 to adults, we demonstrate that newborn neocortical curvature predicts mature curvature maps, sulcal-gyral fate, and fold orientation. Pre-folding curvature correlates with expression of key patterning genes, and a mediation analysis indicates that geometry at P0 is the principal predictor of sulcal-gyral fate at P6. Mechanical simulations show that regions of high curvature act as autonomous anchors that organise the folding pattern. These results suggest that neocortical geometry constitutes a form of positional information that complements molecular patterns in regulating cortical organisation, and that a complete account of cortical development requires the integration of geometric and mechanical processes alongside molecular signalling.

neuroscience↗

bioRxiv2025

Principles of neocortical organisation and behaviour in primates

One sentence summaryThe study of brain MRI from 70 different primate species reveals a fundamental principle of neocortical organisation and behaviour driven by mechanical morphogenesis. The development and evolution of neocortical organisation is typically explained by the interaction of two fundamental factors: genetics and experience-dependent processes. Morphogens and signalling molecules would orchestrate the formation of neocortical areas and connection networks, which are later refined through exposure to environmental stimuli. Evolutionary changes to these genetic programs are thought to account for the diversity of brains and behaviours observed in extant species. However, our phylogenetic comparative study of primate neuroanatomy and behaviour shows this view is incomplete. Using brain MRI from 70 primate species we observed that not only the degree of folding but also the folding pattern changes continuously with brain volume, independently of phylogenetic position. To better understand the consequences of this continuity we focused on New and Old World monkeys which diverged approximately 47 million years ago. Large New World monkeys, such as capuchins, have a significantly larger and more folded neocortex than many of their close phylogenetic relatives, whose brains are barely folded. Notably, in addition to folding, their thickness and connectivity patterns were almost identical to those of phylogenetically distant Old World monkeys. Combined analyses of MRI and endocasts from 105 primate species indicated that the highly folded neocortex of large New World monkeys evolved independently from a common ancestor with a small, unfolded brain. Remarkably, across all 70 species, behavioural similarity correlated substantially more with neuroanatomical similarity than with phylogenetic similarity. Our results challenge the prevailing explanation of the development and evolution of neocortical organisation. We propose that the "capuchin anomaly" can be resolved by incorporating mechanical morphogenesis, alongside genetics and experience, as a third fundamental factor. Growth-driven mechanical instabilities would produce similar neuroanatomical organisation patterns and behaviours, emerging independently of the specific genetic determinants of that growth.

neuroscience↗

bioRxiv2025

Empowering multitrait brain phenotypes GWAS

Brain magnetic resonance imaging (MRI) data are now becoming available in human genetic cohorts including thousands of participants, providing a powerful mean to decipher the genetic architecture of brain phenotypes. Univariates genome-wide association screenings (GWAS) are typically applied as a baseline approach, but there are increasing interest for multitrait approaches to both increase statistical power and uncover shared structure underlying those phenotypes. However, there are limited guidelines on how to select phenotypes to be analyzed jointly and optimize power. Here we investigated factors impacting variant discoverability of state-of-the art multitrait GWAS using 1,010 MRI-derived phenotypes measured in 32,947 participants from the UK Biobank. Our study shows that the expected gain of multitrait approaches over univariate GWAS is highly predictable. We further propose data-driven strategy to define optimize sets and compare its performances with biologically driven approaches.

neuroscience↗

bioRxiv2023

Linking the genetic structure of neuroanatomical phenotypes with psychiatric disorders

There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven challenging, and new approaches are needed to infer potential genetic structure underlying those phenotypes. Here, we demonstrate how multivariate analyses can help reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches. We first conducted univariate and multivariate genome-wide association studies (GWAS) for eight MRI-derived brain volume phenotypes in 20K UK Biobank participants. We performed various enrichment analyses to assess whether and how univariate and multitrait approaches can distinguish disorder-associated and non-disorder-associated variants from six psychiatric disorders: bipolarity, attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, obsessive-compulsive disorder, and major depressive disorder. Univariate MRI GWAS displayed only negligible genetic correlation with psychiatric disorders at all the levels we investigated. Multitrait GWAS identified multiple new associations and showed significant enrichment for variants related to both ADHD and schizophrenia. We further clustered top associated variants based on their MRI multitrait association using an optimized k-medoids approach and detected two clusters displaying not only enrichment for association with ADHD and schizophrenia, but also consistent direction of effects. Functional annotation analyses pointed to multiple potential mechanisms, suggesting in particular a role of neurotrophin pathways on both MRI and schizophrenia. Altogether our results show that multitrait association signature can be used to infer genetically-driven latent MRI variables associated with psychiatric disorders, opening paths for future biomarker development.

genetics↗

bioRxiv2023

BioConvert: a comprehensive format converter for life sciences

AO_SCPLOWBSTRACTC_SCPLOWBioinformatics is a field known for the numerous standards and formats that have been developed over the years. This plethora of formats, sometimes complementary, and often redundant, poses many challenges to bioinformatics data analysts. They constantly need to find the best tool to convert their data into the suitable format, which is often a complex, technical and time consuming task. Moreover, these small yet important tasks are often difficult to make reproducible. To over-come these difficulties, we initiated BioConvert, a collaborative project to facilitate the conversion of life science data from one format to another. BioConvert aggregates existing software within a single framework and complemented them with original code when needed. It provides a common interface to make the user experience more streamlined instead of having to learn tens of them. Currently, BioConvert supports about 50 formats and 100 direct conversions in areas such as alignment, sequencing, phylogeny, and variant calling. In addition to being useful for end-users, BioConvert can also be utilized by developers as a universal benchmarking framework for evaluating and comparing numerous conversion tools. Additionally, we provide a web server implementing an online user-friendly interface to BioConvert, hence allowing direct use for the community.

bioinformatics↗

bioRxiv2022

Diversity and evolution of cerebellar folding in mammals

The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. Ancestral estimations indicate that size and folding of the cerebrum and cerebellum increase and decrease concertedly through evolution. Our analyses confirm the strong correlation between cerebral and cerebellar volumes across species, and show that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial wavelength and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. These findings provide new insights into the diversity and evolution of cerebellar folding and its potential influence on brain organisation across species.

neuroscience↗

bioRxiv2019

Increased contrast of the grey-white matter boundary in the motor, visual and auditory areas in Autism Spectrum Disorders

The contrast of the interface between the cortical grey matter and the white matter is emerging as an important neuroimaging biomarker for several brain disorders. Differences in grey to white matter contrast could be related to abnormalities in neuronal migration or in intra-cortical myelination, and are an appealing biomarker for ASD. Two previous studies have reported differences in contrast between patients with autism spectrum disorder and non-autistic controls. We aimed at replicating this finding using open data from the ABIDE initiative, phases 1 and 2, gathering data from 2,148 subjects from 26 different centres and on 764 individuals from the EU-AIMS project (6 different centres). We used multiple linear regression to study the effect of the diagnosis of ASD on contrast, and 3 different strategies for controlling for multiple comparisons. We did not find statistically significant differences in the EU-AIMS dataset, and those that we found in the ABIDE dataset were due to a single centre. All the code necessary to replicate our analyses has been made available open source: https://github.com/neuroanatomy/GWPC.

neuroscience↗

bioRxiv2019

Polygenic architecture of human neuroanatomical diversity

We analysed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26,000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r[~]0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes ([~]51%) captured [~]1.5 times more genetic variance than the rest; and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF<5% captured <1/4th of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG[~]0.45. Genetic correlations were similar to phenotypic and environmental correlations, however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available at https://github.com/neuroanatomy/genomic-architecture.

neuroscience↗

bioRxiv2017

Cerebellar volume in autism: Meta-analysis and analysis of the ABIDE cohort

Cerebellar volume abnormalities have been often suggested as a possible endophenotype for autism spectrum disorder (ASD). We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature, and an analysis of the Autism Brain Imaging Data Exchange (ABIDE) cohort. Our meta-analysis sought to determine a combined effect size of ASD diagnosis on different measures of the cerebellar anatomy, as well as the effect of possible factors of variability across studies. We then analysed the cerebellar volume of 328 patients and 353 controls from the ABIDE project. The meta-analysis of the literature suggested a weak but significant association between ASD diagnosis and increased cerebellar volume (p=0.049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies in the literature were generally underpowered, however, the number of statistically significant findings was larger than expected. Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex and IQ were important sources of cerebellar volume variability, however, independent of autism diagnosis.

neuroscience↗

bioRxiv2017

Meta-analysis of the variance ratio

IntroductionThe most commonly used effect size when using meta-analysis to compare a measurement of interest in two different populations is the standardised mean difference. This is the mean difference of the measurement divided by the pooled standard deviation in the two groups. The standard deviation is usually supposed to be the same for both groups, although this assumption is often made without any particular evidence. It is possible, however, that the difference of the measurement in the two populations resides precisely in their standard deviations. This could be the case, for example, if a population of patients exhibited more \"abnormal\" values than a control population - both large and small - even if the mean values were the same. Fishers test of equality of variance is designed to compare standard deviations. A variance ratio is a Fishers ratio and Fisher distribution can be used to give confidence intervals to the estimate for one study. However, confidence interval for one study can be very wide if the study does not contain enough subjects. Here we present an approach to combine variance ratios of different studies in a meta-analytic way which produces more robust estimates under these circumstances.

bioinformatics↗