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Psychiatric disorders are a complex group of disorders of brain dysfunction that cause emotional, cognitive, and behavioral disturbances and disruptions
.
Approximately hundreds of millions of people worldwide suffer from various mental disorders and are classified as a serious public health problem[1].
In recent years, brain imaging data has received extensive attention
in the study of brain diseases and function.
Brain imaging technology, represented by magnetic resonance imaging, can be used to non-invasively and quantitatively evaluate the structure, connectivity and function of the human brain in
vivo.
Although there is a large amount of observational research evidence that there are significant differences in brain imaging phenotypes between patients with mental illness and healthy people, the causal relationship between brain imaging data and the pathogenesis of mental disorders is not clear, and it is of great biological and clinical significance
to explore the causal effect of brain imaging phenotype on mental illness.
On October 10, 2022, Professor Yang Tielin's team of Xi'an Jiaotong University published a paper entitled " Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders.
This study uses genetic evidence to systematically prove the causal relationship between brain imaging phenotype and psychiatric diseases, which is helpful to better predict and intervene in the occurrence of
psychiatric diseases at the brain imaging level.
The study was based on large-scale genomic data on 10 common psychiatric disorders (including ADHD, anorexia nervosa, anxiety, autism, bipolar disorder, depression, obsessive-compulsive disorder, post-traumatic stress disorder, schizophrenia, and tics).
Causal assessment of 587 key brain magnetic resonance imaging (MRI) structural phenotypes was performed
.
The results showed that nine brain image phenotypes, including the FA value of the upper frontal occipital tract and the ICVF value of the upper radial crown, the MD value of the sagittal layer in the callosum, and the volume of the third ventricle, were risk factors
for schizophrenia, anorexia nervosa and bipolar disorder.
At the same time, it was found that the occurrence of schizophrenia leads to an increase
in the surface area and volume of the inferior frontal gyrus.
This study uses genomic information as a link to link brain image phenotype and psychiatric disease, avoiding the shortcomings of sample detection data bias caused by changes in drugs, environment, lifestyle, etc.
in observational studies [2], and ensuring the robustness
of the research results.
The results are shared in the online query database BrainMR ( style="color: rgb(63, 63, 63);font-size: 15px;" _mstmutation="1" _istranslated="1">
1.
Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S.
New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis.
Lancet.
2019; 394(10194):240-8.
2.
Davey Smith G, Hemani G.
Mendelian randomization: genetic anchors for causal inference in epidemiological studies.
Hum Mol Genet.
2014; 23(R1):R89-98.
Psychiatric disorders are a complex group of disorders of brain dysfunction that cause emotional, cognitive, and behavioral disturbances and disruptions
.
Approximately hundreds of millions of people worldwide suffer from various mental disorders and are classified as a serious public health problem[1].
In recent years, brain imaging data has received extensive attention
in the study of brain diseases and function.
Brain imaging technology, represented by magnetic resonance imaging, can be used to non-invasively and quantitatively evaluate the structure, connectivity and function of the human brain in
vivo.
Although there is a large amount of observational research evidence that there are significant differences in brain imaging phenotypes between patients with mental illness and healthy people, the causal relationship between brain imaging data and the pathogenesis of mental disorders is not clear, and it is of great biological and clinical significance
to explore the causal effect of brain imaging phenotype on mental illness.
On October 10, 2022, Professor Yang Tielin's team of Xi'an Jiaotong University published a paper entitled " Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders.
This study uses genetic evidence to systematically prove the causal relationship between brain imaging phenotype and psychiatric diseases, which is helpful to better predict and intervene in the occurrence of
psychiatric diseases at the brain imaging level.
The study was based on large-scale genomic data on 10 common psychiatric disorders (including ADHD, anorexia nervosa, anxiety, autism, bipolar disorder, depression, obsessive-compulsive disorder, post-traumatic stress disorder, schizophrenia, and tics).
Causal assessment of 587 key brain magnetic resonance imaging (MRI) structural phenotypes was performed
.
The results showed that nine brain image phenotypes, including the FA value of the upper frontal occipital tract and the ICVF value of the upper radial crown, the MD value of the sagittal layer in the callosum, and the volume of the third ventricle, were risk factors
for schizophrenia, anorexia nervosa and bipolar disorder.
At the same time, it was found that the occurrence of schizophrenia leads to an increase
in the surface area and volume of the inferior frontal gyrus.
This study uses genomic information as a link to link brain image phenotype and psychiatric disease, avoiding the shortcomings of sample detection data bias caused by changes in drugs, environment, lifestyle, etc.
in observational studies [2], and ensuring the robustness
of the research results.
The results are shared in the online query database BrainMR ( style="color: rgb(63, 63, 63);font-size: 15px;" _mstmutation="1" _istranslated="1">
Original link:
https://doi.
org/10.
1038/s41593-022-01174-7
Pattern maker: Eleven
References
1.
Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S.
New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis.
Lancet.
2019; 394(10194):240-8.
2.
Davey Smith G, Hemani G.
Mendelian randomization: genetic anchors for causal inference in epidemiological studies.
Hum Mol Genet.
2014; 23(R1):R89-98.
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