Genetic influences on human brain morphology

Erp, Theo G.M. van; Cannon, Tyrone D.; Tran, {Helen L.}; Wobbekind, A.D.; Huttunen, Matti; Lönnqvist, Jouko; Kaprio, Jaakko; Salonen, Oili; Valanne, Leena; Poutanen, Veli-Pekka; Standertskjöld‐Nordenstam, C.‐G.; Toga, Arthur W.; Thompson, P.M.

doi:10.1109/isbi.2004.1398605

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Following spatial normalization, we found significant heritability for total brain volume, cerebral volume and total grey matter volume. The estimated heritability for baboon brain volume after spatial normalization (h 2 ¼ 0.82) is quite consistent with published estimates for human brains processed in a similar manner (Baare et al, 2001;Posthuma et al, 2002;Thompson et al, 2001;Toga and Thompson 2005;van Erp et al, 2004).…”

Section: Discussionsupporting

confidence: 87%

Heritability of brain volume, surface area and shape: An MRI study in an extended pedigree of baboons

Rogers

Kochunov

Lancaster³

et al. 2007

Human Brain Mapping

108

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To evaluate baboons (Papio hamadryas) as a primate model for the study of the genetic control of brain size and internal structure, we performed high resolution (<500 microm) magnetic resonance imaging on 109 pedigreed baboons. Quantitative genetic analysis of these MR images using a variance components approach indicates that native (untransformed) brain volume exhibits significant heritability among these baboons (h(2) = 0.52, P = 0.0049), with age and sex also accounting for substantial variation. Using global spatial normalization, we transformed all images to a standard population-specific reference, and recalculated the heritability of brain volume. The transformed images generated heritability estimates of h(2) = 0.82 (P = 0.00022) for total brain volume, h(2) = 0.86 (P = 0.0006) for cerebral volume, h(2) = 0.73 (P = 0.0069) for exposed surface area of the cerebrum and h(2) = 0.67 (P = 0.01) for gray matter volume. Regional differences in the genetic effects on brain structure were calculated using a voxel-based morphometry (VBM) approach. This analysis of regional variation shows that some areas of motor cortex and the superior temporal gyrus show relatively high heritability while other regions (e.g. superior parietal cortex) exhibit lower heritability. The general pattern of regional differences is similar to that observed in previous studies of humans. The present study demonstrates that there is substantial genetic variation underlying individual variation in brain size and structure among Papio baboons, and that broad patterns of genetic influence on variation in brain structure may be similar in baboons and humans.

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Section: Discussionsupporting

confidence: 87%

Heritability of brain volume, surface area and shape: An MRI study in an extended pedigree of baboons

Rogers

Kochunov

Lancaster³

et al. 2007

Human Brain Mapping

108

View full text Add to dashboard Cite

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“…Amongst some of the collaborative neuroimaging genomics efforts in the field are the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) consortium [39], the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [40], and the Human Connectome Project [41]. By conducting GWAS, they are attempting to link SNP biomarkers and genetic variants with structural and functional neuroimaging phenotypes [39,42]. Integrating tools from genetics, “omics”, and imaging, they aim to decipher the human brain and elucidate the intricate molecular underpinnings of neurodegeneration [39,43,44].…”

Section: Genomics and Imaging Meta-analysismentioning

confidence: 99%

“RADIOTRANSCRIPTOMICS”: A synergy of imaging and transcriptomics in clinical assessment

Katrib¹,

Hsu²,

Bui³

et al. 2016

Quant. Biol.

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Recent advances in quantitative imaging and “omics” technology have generated a wealth of mineable biological “big data”. With the push towards a P4 “predictive, preventive, personalized, and participatory” approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose “radiotranscriptomics” as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

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“…Одним из генов-кандидатов является ген подверженности дислексии 1 (DYX1C1). Однако связь между этим геном и нарушениями чтения не была подтвер-ждена в недавнем метаанализе (Tran et al, 2013). Другие гены-кандидаты -KIAA0319, DCDC2 и CMIP -также изучались в исследова-ниях нарушений способностей к чтению.…”

Section: исследования ассоциацийunclassified