Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach DOI Creative Commons
Jiwon Chung, Sunghun Kim, Ji Hye Won

et al.

IEEE Journal of Translational Engineering in Health and Medicine, Journal Year: 2024, Volume and Issue: 12, P. 659 - 667

Published: Jan. 1, 2024

Neuroimaging genetics represents a multivariate approach aimed at elucidating the intricate relationships between high-dimensional genetic variations and neuroimaging data. Predominantly, existing methodologies revolve around Sparse Canonical Correlation Analysis (SCCA), framework we expand to 1) encompass multiple imaging modalities 2) promote simultaneous identification of structurally linked features across modalities. The brain regions were assessed using diffusion tensor imaging, which quantifies presence neuronal fibers, thereby grounding our in biologically well-founded prior knowledge within SCCA model. In proposed framework, leverage T1-weighted MRI functional (fMRI) time series data delineate both structural characteristics brain. Genetic variations, specifically single nucleotide polymorphisms (SNPs), are also incorporated as modality. Validation methodology was conducted simulated dataset large-scale normative from Human Connectome Project (HCP). Our demonstrated superior performance compared methods on revealed interpretable gene-imaging associations real dataset. Thus, lays groundwork for underpinnings structure function, providing novel insights into field neuroscience. code is available https://github.com/mungegg.

Language: Английский

Genetic architecture of the structural connectome DOI Creative Commons
Michael Wainberg, Natalie J. Forde,

Salim Mansour

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 4, 2024

Abstract Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these remains unclear. We perform genome-wide association studies 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography 26,333 UK Biobank participants, each representing density myelinated within or a pair cortical networks, subcortical structures hemispheres. identify 30 independent significant variants after Bonferroni correction for number studied (126 at nominal significance) implicating genes involved in myelination ( SEMA3A ), neurite elongation guidance NUAK1 , STRN DPYSL2 EPHA3 HGF SHTN1 neural cell proliferation differentiation GMNC CELF4 neuronal migration CCDC88C cytoskeletal CTTNBP2 MAPT DAAM1 MYO16 PLEC metal transport SLC39A8 ). These have four broad patterns spatial with connectivity: some disproportionately strong associations corticothalamic connectivity, interhemispheric both, while others are more spatially diffuse. Structural highly polygenic, median 9.1 percent common estimated to non-zero effects on measure, exhibited signatures negative selection. genetic correlations variety neuropsychiatric cognitive traits, indicating connectivity-altering tend influence health function. Heritability is enriched regions increased chromatin accessibility adult oligodendrocytes (as well as microglia, inhibitory neurons astrocytes) multiple fetal types, suggesting control partially mediated by early development. Our results indicate pervasive, pleiotropic, structured white-matter via diverse neurodevelopmental pathways, support relevance this healthy

Language: Английский

Citations

20
Association and shared biological bases between birth weight and cortical structure DOI Creative Commons
Lu Zhang, Qiaoyue Ge, Zeyuan Sun

et al.

Translational Psychiatry, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 5, 2025

Associations between birth weight and cortical structural phenotypes have been detected; however, the understanding is incomprehensive, potential biological bases are not well defined. Leveraging data from genome-wide association studies, we investigated associations shared transcriptomic, proteomic cellular of 13 phenotypes. Mendelian randomization analyses were performed to examine structure. Downstream transcriptome-wide study (TWAS), proteome-wide (PWAS) summary-based (SMR) utilized identify cis-regulated gene expressions proteins. Finally, cell-type expression-specific integration for complex traits (CELLECT) conducted explore enriched cell types. The found positive global folding index, intrinsic curvature local gyrification surface area volume. transcriptomic-level TWAS SMR identified three both linked at least one phenotype (CNNM2, RABGAP1 CENPW). Parallel PWAS level four proteins RAB7L1, RAB5B PPA2), which CNNM2 was replicated. CELLECT revealed brain types in weight, including pericytes, inhibitory GABAergic neurons cerebrovascular cells. These findings support importance early life growth structure, suggest underlying bases. results provide intriguing targets further research into mechanisms development.

Language: Английский

Citations

2
Polygenic scores for autism are associated with reduced neurite density in adults and children from the general population DOI Creative Commons
Yuanjun Gu, Eva-Maria Stauffer, Saashi A. Bedford

et al.

Molecular Psychiatry, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Abstract Genetic variants linked to autism are thought change cognition and behaviour by altering the structure function of brain. Although a substantial body literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic changes cortical macro- micro-structure. We investigated this using neuroimaging data from adults (UK Biobank, N = 31,748) children (ABCD, 4928). Using polygenic scores correlations we observe robust negative association between for magnetic resonance imaging derived phenotype neurite density (intracellular volume fraction) general population. This result consistent across both adults, cortex white matter tracts, confirmed correlations. There were no sex association. Mendelian randomisation analyses provide evidence causal relationship intracellular fraction, although should be revisited better powered instruments. Overall, study provides shared variant genetics density.

Language: Английский

Citations

1
The genetic relationships between brain structure and schizophrenia DOI Creative Commons
Eva-Maria Stauffer, Richard A. I. Bethlehem, Lena Dorfschmidt

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Nov. 28, 2023

Abstract Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes associated with both and cortical phenotypes. We accessed genome-wide association studies (GWAS) of ( N = 69,369 cases; 236,642 controls), three magnetic resonance imaging (MRI) metrics (surface area, thickness, neurite density index) measured at 180 areas 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 were significantly one or more MRI metrics. Whole genome analysis partial least squares demonstrated significant covariation between area thickness most regions. similarity was strongly coupled to their phenotypic covariance, phenotypes strongest in the hubs structural covariance networks. Pleiotropically enriched neurodevelopmental processes positionally concentrated chromosomes 3p21, 17q21 11p11. Mendelian randomization indicated that genetically determined variation a posterior cingulate could be causal schizophrenia. Parallel analyses GWAS bipolar disorder, Alzheimer’s disease height showed pleiotropic stronger compared other disorders.

Language: Английский

Citations

21
Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology DOI Creative Commons
Saashi A. Bedford, Meng‐Chuan Lai, Michael Lombardo

et al.

Biological Psychiatry, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation sex-biased prevalence, autism ADHD rarely studied together sex differences often overlooked. Population modeling, referred to as normative provides a unified framework for studying age-specific sex-specific divergences in brain development.

Language: Английский

Citations

8
Regional patterns of human cortex development correlate with underlying neurobiology DOI Creative Commons
Leon D. Lotter, Amin Saberi, Justine Y. Hansen

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 12, 2024

Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness and aging trajectories unfold along patterns molecular cellular organization, traceable from population-level to individual developmental trajectories. During childhood adolescence, cortex-wide spatial distributions dopaminergic receptors, inhibitory neurons, glial cell populations, brain-metabolic features explain up 50% variance associated with a lifespan model regional In contrast, modeled change during adulthood are best explained by cholinergic glutamatergic neurotransmitter receptor transporter distributions. These relationships supported gene expression translate longitudinal data 8000 adolescents, explaining 59% at cohort- 18% single-subject level. Integrating neurobiological atlases modeling population neuroimaging provides biologically meaningful path understand living humans.

Language: Английский

Citations

7
Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain DOI Creative Commons
Jacob W. Vogel, Aaron Alexander‐Bloch, Konrad Wagstyl

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(25)

Published: June 11, 2024

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression morphogens and transcription factors. However, whether similar are maintained in adult brain remains unknown. Here, we uncover three axes topographic variation gene human that specifically capture previously identified rostral-caudal, dorsal-ventral, medial-lateral early developmental patterning. The interaction these spatiomolecular i) accurately reconstructs position tissue samples, ii) delineates known functional territories, iii) can model topographical diverse cortical features. distinct canonical differentiating primary sensory cortex association cortex, but radiate parallel with traversed by local field potentials along cortex. We replicate all independent datasets as well two nonhuman primate find each gradient shows a trajectory across lifespan. composed several well-known factors (e.g., PAX6 SIX3 ), small set genes shared strongly enriched for multiple diseases. Together, results provide insight into sculpting functionally regions, governed robust transcriptomic embedded within parenchyma.

Language: Английский

Citations

6
Structural MRI of brain similarity networks DOI
Isaac Sebenius, Lena Dorfschmidt, Jakob Seidlitz

et al.

Nature reviews. Neuroscience, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

Language: Английский

Citations

6
Regional patterns of human cortex development correlate with underlying neurobiology DOI Creative Commons
Leon D. Lotter, Amin Saberi, Justine Y. Hansen

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: May 5, 2023

Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness and aging trajectories unfold along patterns molecular cellular organization, traceable from population-level to individual developmental trajectories. During childhood adolescence, cortex-wide spatial distributions dopaminergic receptors, inhibitory neurons, glial cell populations, brain-metabolic features explain up 50% variance associated with a lifespan model regional In contrast, modeled change during adulthood are best explained by cholinergic glutamatergic neurotransmitter receptor transporter distributions. These relationships supported gene expression translate longitudinal data 8,000 adolescents, explaining 59% at cohort- 18% single-subject level. Integrating neurobiological atlases modeling population neuroimaging provides biologically meaningful path understand living humans.

Language: Английский

Citations

14
Towards interpretable imaging genomics analysis: Methodological developments and applications DOI
Xiaoping Cen, Wei Dong, Wei Lv

et al.

Information Fusion, Journal Year: 2023, Volume and Issue: 102, P. 102032 - 102032

Published: Sept. 19, 2023

Language: Английский

Citations

11