CACNB2 rs11013860 polymorphism correlates of prefrontal cortex thickness in bipolar patients with first-episode mania

Chen, Jianshan; Tan, Jiuwei; Greenshaw, Andrew J.; Sawalha, Jeffrey; Liu, Yang; Zhang, Xiaofei; Zou, Wenjin; Cheng, Xiaofang; Deng, Wenhao; Zhang, Yizhi; Cui, Liqian; Liu, Chuihong; Sun, Jiaqi; Cheng, Xiongchao; Wu, Qiuxia; Li, Suyi; Mai, Siming; Lan, Xiaofeng; Chen, Yingmei; Cai, Yinglian; Zheng, Chaodun; Cheng, Daomeng; Zhang, Bin; Yang, Chanjuan; Li, Xuan; Li, Xinmin; Ye, Biyu; Yousefnezhad, Muhammad; Zhang, Yamin; Zhao, Liansheng; Soares, Jair C.; Zhang, Xiangyang; Li, Tao; Cao, Bo; Cao, Liping

doi:10.1016/j.jad.2020.02.007

Cited by 10 publications

(5 citation statements)

References 46 publications

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“…We found two studies that found a correlation between rs11013860 A carrier status and brain activity or structure in BD. One found reduced cortical thickness in the frontal region in A carriers BD patients compared to A carriers, HC, or BD C homozygotes (Chen et al, 2020). The other study found an alteration in resting-state FC in BD A carriers, compared to C homozygotes (Liu et al, 2019).…”

Section: Discussionmentioning

confidence: 94%

“…The other study found an alteration in resting-state FC in BD A carriers, compared to C homozygotes (Liu et al, 2019). The CACNB2 rs11013860 polymorphism is a new entry and has been tested for cortical thickness and FC (Liu et al, 2019;Chen et al, 2020); although both studies found it to be a promising marker, the designs of the two studies are disparate.…”

Section: Discussionmentioning

confidence: 98%

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Genetic neuroimaging of bipolar disorder: a systematic 2017–2020 update

Janiri

Kotzalidis

Luzio

et al. 2021

Psychiatric Genetics

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There is evidence of genetic polymorphism influences on brain structure and function, genetic risk in bipolar disorder (BD), and neuroimaging correlates of BD. How genetic influences related to BD could be reflected on brain changes in BD has been efficiently reviewed in a 2017 systematic review. We aimed to confirm and extend these findings through a Preferred Reporting Items for Systematic reviews and Meta-Analyses-based systematic review. Our study allowed us to conclude that there is no replicated finding in the timeframe considered. We were also unable to further confirm prior results of the BDNF gene polymorphisms to affect brain structure and function in BD. The most consistent finding is an influence of the CACNA1C rs1006737 polymorphism in brain connectivity and grey matter structure and function. There was a tendency of undersized studies to obtain positive results and large, genome-wide polygenic risk studies to find negative results in BD. The neuroimaging genetics in BD field is rapidly expanding.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 98%

Genetic neuroimaging of bipolar disorder: a systematic 2017–2020 update

Janiri

Kotzalidis

Luzio

et al. 2021

Psychiatric Genetics

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“…CACNB2 encodes a subunit of a voltage‐dependent calcium channel protein subunit β2, which is predominantly expressed in hippocampal pyramidal neurons [32, 33]. GRIN2B encodes a protein of the N‐methyl‐D‐aspartate (NMDA) receptor family, which plays an important role in the rewarding effects of addictive substances [34–36]. Our results suggest that the interactive pathway for the SUBD common genes was related to processes of synaptic transmission, neurotransmitter and calcium ions (Ca 2+ ) ion release and transport.…”

Section: Discussionmentioning

confidence: 99%

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

et al. 2022

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Background and aims Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome‐wide findings is lacking for substance use. Here, we combined all the genome‐wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs. Methods Systemic literature search for genome‐wide association (GWAS) and RNA‐seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case–control or case/cohort samples. RNA‐seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10−6) in GWAS and reported as significant in RNA‐seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database. Results Total SUBD‐related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA‐seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of ‘modulation of chemical synaptic transmission’, ‘regulation of trans‐synaptic signaling’, two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of ‘dopaminergic synapse’, ‘cocaine addiction’] were identified (significantly higher than random, P < 1 × 10−5). The top shared KEGG pathways (Benjamini–Hochberg‐corrected P‐value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were ‘Epstein–Barr virus infection’, ‘protein processing in endoplasmic reticulum’ and ‘neuroactive ligand‐receptor interaction’, respectively. We also identified substance‐specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD. Conclusions This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome‐wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

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“…Previous studies suggest that white matter may be regulated through a complex set of genes, such as MIR137, CACNA1C, ANK3, and the ITIH3-ITIH4 region (The Schizophrenia Psychiatric Genome-Wide Association Study [GWAS] Consortium, 2011); but efforts to replicate these specific findings have failed (Papiol et al, 2014). Other GWAS have identified additional (to be validated) genetic variants underpinning white matter, including VCAN, implicated in early cell remodeling (Wathlet et al, 2011); NBEAL1, implicated in fetal development (Chen et al, 2004); and CACNB2, which has been associated with cortical thickness in bipolar disorder (Chen et al, 2020). Moreover, in neurotypical children, white matter connectivity between frontal and parietal regions was associated with higher autism polygenic scores (Grove et al, 2019;Khundrakpam et al, 2020).…”

Section: Genetic Influences On Gray-white Matter Tissue Contrastmentioning

confidence: 99%

Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review

Pretzsch

Ecker

2023

Front. Neurosci.

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Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.

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CACNB2 rs11013860 polymorphism correlates of prefrontal cortex thickness in bipolar patients with first-episode mania

Cited by 10 publications

References 46 publications

Genetic neuroimaging of bipolar disorder: a systematic 2017–2020 update

Genetic neuroimaging of bipolar disorder: a systematic 2017–2020 update

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review

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