The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area

Tilot, Amanda K.; Khramtsova, Ekaterina A.; Grasby, Katrina; Jahanshad, Neda; Painter, Jodie N.; Colodro‐Conde, Lucía; Bralten, Janita; Hibar, Derrek P.; Lind, Penelope A.; Liu, Siyao; Brotman, Sarah M.; Thompson, Paul M.; Medland, Sarah E.; Macciardi, Fabìo; Stranger, Barbara Elaine; Davis, Lea K.; Fisher, Simon E.; Stein, Jason L.

doi:10.1101/703793

Cited by 4 publications

(3 citation statements)

References 80 publications

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“…In addition, we are aware that variants enter the genome at one stage and are likely selected for at a (much) later stage [29,30]. As such our study differs from the chronological atlas of natural selection in our species presented in [31] (as well as from other studies focusing on more recent periods of our evolutionary history, such as [32]). This may explain some important discrepancies between the overall temporal profile of genes highlighted in [31] and the distribution of HF variants for these genes in our data ( Figure S7).…”

Section: Variant Subset Distributionsmentioning

confidence: 83%

Fine-grained temporal mapping of derived high-frequency variants supports the mosaic nature of the evolution ofHomo sapiens

Andirkó

Moriano

Vitriolo

et al. 2021

Preprint

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As our knowledge about the history of the sapiens lineage becomes increasingly complex, large-scale estimations of the time of emergence of derived variants become essential to be able to offer more precise answers to time-sensitive hypotheses concerning human evolution. Using an open repository of genetic variant age estimations recently made available, we offer here a temporal evaluation of various evolutionarily relevant datasets, such as sapiens-specific variants, high-frequency variants found in genetic windows under positive selection, introgressed variants from extinct human species, as well as putative regulatory variants in various brain regions. We find a recurrent bimodal distribution of high-frequency variants, but also evidence for specific enrichments of gene categories in various time windows, which brings into prominence the 300-500k time slice. We also find evidence for very early mutations impacting the facial phenotype, and much more recent molecular events linked to specific brain regions such as the cerebellum or the precuneus. Additionally, we present a case study of an evolutionarily relevant gene, BAZ1B, and its targets, to emphasize the importance of applying temporal data to specific evolutionary questions. Overall, we present a unique resource that informs and complements our previous knowledge of sapiens evolution using publicly available data, and reinforce the case for the mosaic, temporally very extended nature of the evolutionary trajectory of our species.

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Section: Variant Subset Distributionsmentioning

confidence: 83%

Fine-grained temporal mapping of derived high-frequency variants supports the mosaic nature of the evolution ofHomo sapiens

Andirkó

Moriano

Vitriolo

et al. 2021

Preprint

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“…These discoveries resulted in an annotated atlas of common genetic variants that contribute to shaping the human cerebral cortex. Of particular interest, we found that genetic loci affecting brain morphology show enrichment for developmentally regulated genes 13 and human-specific regulatory elements 26,27 . Ongoing efforts are beginning to map these genetic effects at a finer-grained spatial resolution using shape analysis, surface-and voxel-based analyses [28][29][30][31] .…”

Section: Uncovering the Genetic Basis Of Brain Morphometric Variationmentioning

confidence: 99%

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Thompson¹,

Jahanshad²,

Ching³

et al. 2020

Transl Psychiatry

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467

254

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This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attentiondeficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

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“…Multimodal association cortices including frontal, temporal, and parietal areas are evolutionarily modern areas and present a higher cortical surface expansion in humans with respect to macaque [79]. Interestingly, high expanding regions are less mature at term gestation functionally and structurally allowing shaping by environmental factors [76,80,81] and mature slowly in developmental stages [76]. Regional differences in white matter maturation in later childhood development supports variability in structural connectome [82,83,84].…”

Section: Structural and Functional Interindividual Variability Is Heterogenous Across Cortical Surfacementioning

confidence: 87%

Individual variability in the human connectome maintains selective cross-modal consistency and shares microstructural signatures

Karahan¹,

Tait²,

Si³

et al. 2021

Preprint

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Individuals are different in their behavioural responses and cognitive abilities. Neural underpinnings of individual differences are largely unknown. Here, by using multimodal imaging data including diffusion MRI, functional MRI and MEG, we show the consistency of interindividual variation of connectivity across modalities. We demonstrated that regional differences in individual variability of structural and functional connectomes is characterized by higher variability in association cortices and lower variability in sensory and visual cortices. This pattern is consistent across all modalities at varying degrees as shown by significant alignment between functional and structural connectome variabilities at several clusters of brain regions. Variability in connectivity is associated with cortical myelin content and microstructural properties of connections. Our findings contribute to understanding of individual differences in functional and structural organization of brain and facilitate fingerprinting applications.

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The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area

Cited by 4 publications

References 80 publications

Fine-grained temporal mapping of derived high-frequency variants supports the mosaic nature of the evolution ofHomo sapiens

Fine-grained temporal mapping of derived high-frequency variants supports the mosaic nature of the evolution ofHomo sapiens

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Individual variability in the human connectome maintains selective cross-modal consistency and shares microstructural signatures

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