Science . . . 50,000 MRI images! The genetic structure of the human cerebral cortex is fully analyzed.

The cerebral cortex is the basis of our complex cognitive abilities.the genetic diversity of human cerebral cortex surface area and thickness is closely related to various phenotypes in neurology, psychology and behavior, and the above two data can be measured in vivo by MRI (Fig. 1).the prominent feature of cerebral cortex fold in animals with multiple gyri is that it can be divided into gyrus and sulcus.the radial unit hypothesis proposes that the expansion of cortical surface area is driven by the proliferation of neural progenitor cells, while the thickness of cerebral cortex is determined by the number of nerve cell divisions [1].through the brain imaging research of twins and family pedigree, it is shown that the total surface area and thickness of cerebral cortex are highly heritable and can be affected by a variety of genetic factors [2-4].however, it is not clear how common genetic variations affect data such as the surface area and thickness of the human cortex.two functional data representations of the cerebral cortex: total surface area and thickness. March 20, 2020, Sarah E. medland research group, Queensland Institute of medicine, Australia; Jason L. Stein, University of North Carolina, Chapel Hill; Paul M. Thompson, University of Southern California; and enigma -The genetic architecture of the human cervical cortex was published in science by several research groups including genetics working group and a number of scientists in different fields. Genome wide association was performed on brain MRI images of more than 50000 individuals Meta analysis revealed the causal relationship between the differences of brain structure, genetic variation and cognitive function.in order to correlate genetic diversity of gene loci with human cerebral cortex, the authors conducted a genome-wide association meta-analysis of 51665 individuals from 60 populations around the world, covering almost all European lineages.these MRI data contain 34 well-defined brain regions.the authors analyzed the total surface area and mean thickness of the whole brain, as well as the surface area and thickness of 34 different brain regions, and divided these data into 70 direct phenotypes (Fig. 2).furthermore, in order to verify the universality of these data, the authors also analyzed eight non European populations and confirmed the high correlation of the results of this meta-analysis.in 34 brain regions of the whole brain, the authors identified 306 loci with genome-wide significant changes in the meta-analysis of 70 cortical phenotypes.it should be mentioned that 118 gene locus has never been found to be related to the intracranial volume, surface area, thickness or volume of cerebral cortex, which provides a novel reference site for subsequent research on cerebral cortex.furthermore, after measuring the total surface area and mean thickness of the cerebral cortex, the authors hope to find out the genetic relationship between the two.through analysis, the authors found that there was a certain degree of genetic negative correlation between the total surface area and the average thickness of the cerebral cortex, which indicated that the genetic influence had an opposite effect on the total surface area and average thickness of the cerebral cortex.moreover, heritability is mainly concentrated in the cerebral cortex or in the neural model derived from neural stem cell differentiation in vitro, such as promoter and enhancer regions.in addition, the authors also found that the heritability of total surface area of cerebral cortex was mainly concentrated in the active regulatory element region in the middle of fetal development, while the heritability of thickness was mainly concentrated in the active regulatory genomic region specific to adult (Fig. 3). the total surface area of cerebral cortex is affected by common genetic variations, which mainly change the gene regulatory activity of neural progenitor cells during fetal development. This conclusion supports the radiation unit hypothesis to a certain extent [1]. in addition, cell cycle related regulatory genes also participate in the genetic regulation of the total surface area of cerebral cortex. Fig. 3 the heritability of total surface area and mean thickness of cerebral cortex is specific in different developmental stages. Subsequently, the authors analyzed the gene loci affecting the total surface area and average thickness of cerebral cortex. in the detection, the authors found that 17 out of 255 repeated detection sites had an impact on the phenotype of total surface area. After multiple rounds of testing, 12 sites were identified, including genes encoding schizophrenia related genes and specific expression in fetal cortical intermediate neural progenitor cells, etc. There are two sites related to mean thickness, which are 40S ribosomal protein involved in laminin receptor and protein that plays an important role in neuronal migration. Br / > we found that there was a weak correlation between the total cortical thickness and the mean surface area of the brain. at the same time, the authors also revealed and analyzed the relationship between genetic variation gene loci and corresponding surface area and thickness in different brain regions. in general, this science presents a grand Atlas of human whole brain nuclear magnetic resonance analysis and genome-wide significance sites. for a long time, people's research on human brain mostly relies on the way of introducing mutations into certain genes in model systems such as mice. however, even though the mouse model is highly similar to the human cerebral cortex in many aspects, such as the types and behavior patterns of nerve cells, the mouse cerebral cortex is also very different from the human cerebral cortex. the work of the authors has determined the corresponding relationship between the total surface area and thickness of human cerebral cortex and the significant sites in the whole genome, which provides an important tool for human beings to understand the genetic structure and development mode of cerebral cortex on a large scale. 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