scholarly journals Deep transcriptome sequencing of subgenual anterior cingulate cortex reveals cross-diagnostic and diagnosis-specific RNA expression changes in major psychiatric disorders

Author(s):  
Nirmala Akula ◽  
Stefano Marenco ◽  
Kory Johnson ◽  
Ningping Feng ◽  
Kevin Zhu ◽  
...  

AbstractDespite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case–control comparisons detected modest expression differences that were correlated across disorders. Case–case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

2019 ◽  
Author(s):  
Nirmala Akula ◽  
Stefano Marenco ◽  
Kory Johnson ◽  
Ningping Feng ◽  
Joanna Cross ◽  
...  

ABSTRACTHow do differences in onset, symptoms, and treatment response arise between various mental illnesses despite substantial overlap of genetic risk factors? To address this question, we carried out deep RNA sequencing of human postmortem subgenual anterior cingulate cortex, a key component of limbic circuits linked to mental illness. Samples were obtained from 200 individuals diagnosed with bipolar disorder, schizophrenia, or major depression, and controls. Differential expression analysis in cases versus controls detected modest differences that were similar across disorders, although transcript-level differences were more pronounced. Case-case comparisons revealed greater expression differences between disorders, including many genes and transcripts that were expressed in opposite directions in each diagnostic group, compared to controls. Relative transcript abundances were associated with common genetic variants that accounted for disproportionate fractions of diagnosis-specific heritability. Inherited genetic risk factors shape the brain transcriptome and contribute to diagnostic differences between broad classes of mental illness.


Author(s):  
Fangyi Gu ◽  
Ting-Huei Chen ◽  
Ruth M Pfeiffer ◽  
Maria Concetta Fargnoli ◽  
Donato Calista ◽  
...  

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F.V Moniz Mendonca ◽  
M.I Mendonca ◽  
A Pereira ◽  
J Monteiro ◽  
J Sousa ◽  
...  

Abstract Background The risk for Coronary Artery Disease (CAD) is determined by both genetic and environmental factors, as well as by the interaction between them. It is estimated that genetic factors could account for 40% to 55% of the existing variability among the population (inheritability). Therefore, some authors have advised that it is time we integrated genetic risk scores into clinical practice. Aim The aim of this study was to evaluate the magnitude of the association between an additive genetic risk score (aGRS) and CAD based on the cumulative number of risk alleles in these variants, and to estimate whether their use is valuable in clinical practice. Methods A case-control study was performed in a Portuguese population. We enrolled 3120 participants, of whom 1687 were CAD patients and 1433 were normal controls. Controls were paired to cases with respect to gender and age. 33 genetic variants known to be associated with CAD were selected, and an aGRS was calculated for each individual. The aGRS was further subdivided into deciles groups, in order to estimate the CAD risk in each decile, defined by the number of risk alleles. The magnitude of the risk (odds ratio) was calculated for each group by multiple logistic regression using the 5th decile as the reference group (median). In order to evaluate the ability of the aGRS to discriminate susceptibility to CAD, two genetic models were performed, the first with traditional risk factors (TRF) and second with TRF plus aGRS. The AUC of the two ROC curves was calculated. Results A higher prevalence of cases over controls became apparent from the 6th decile of the aGRS, reflecting the higher number of risk alleles present (see figure). The difference in CAD risk was only significant from the 6th decile, increasing gradually until the 10th decile. The odds ratio (OR) for the last decile related to 5th decile (median) was 1.87 (95% CI:1.36–2.56; p<0.0001). The first model yielded an AUC=0.738 (95% CI:0.720–0.755) and the second model was slightly more discriminative for CAD risk (AUC=0.748; 95% CI:0.730–0.765). The DeLong test was significant (p=0.0002). Conclusion Adding an aGRS to the non-genetic risk factors resulted in a modest improvement in the ability to discriminate the risk of CAD. Such improvement, even if statistically significant, does not appear to be of real value in clinical practice yet. We anticipate that with the development of further knowledge about different SNPs and their complex interactions, and with the inclusion of rare genetic variants, genetic risk scores will be better suited for use in a clinical setting. Funding Acknowledgement Type of funding source: None


2021 ◽  
Vol 53 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Andrew R. Harper ◽  
◽  
Anuj Goel ◽  
Christopher Grace ◽  
Kate L. Thomson ◽  
...  

2017 ◽  
Vol 8 (4) ◽  
pp. 43-54
Author(s):  
E.A. Varshaver

This article contains a review of research in the realm of neurophysiology of ethnicity. According to this body of research, there are zones of the brain which get active in response to demonstration of ethnic stimuli. Among these zones are amygdala, anterior cingulate cortex, fusiform face area and others. The article describes the research focused on each of these zones, discusses their weaknesses and projects further research on the crossroads of neurophysiology, cognitive science, psychology and sociology.


2019 ◽  
Vol 214 (5) ◽  
pp. 281-287
Author(s):  
Bo Xiang ◽  
Qiang Wang ◽  
Wei Lei ◽  
Mingli Li ◽  
Yinfei Li ◽  
...  

BackgroundPrevious studies have inferred a strong genetic component in schizophrenia. However, the genetic variants involved in the susceptibility to schizophrenia remain unclear.AimsTo detect potential gene pathways and networks associated with schizophrenia, and to explore the relationship between common and rare variants in these pathways and abnormal white matter integrity in schizophrenia.MethodThe analysis included 100 first-episode treatment-naïve patients with schizophrenia and 140 healthy controls. A network-based analysis was carried out on the data collected from the Psychiatric Genomics Consortium Phase I (PGC-I). Based on our genome-wide association study and whole-exome sequencing data-sets, we performed a gene-set analysis to detect associations between the combining effects of common and rare genetic variants and abnormal white matter integrity in schizophrenia.ResultsPatients had significantly reduced functional anisotropy in the left and right anterior cingulate cortex, left and right precuneus and extra-nuclear (t = 4.61–5.10, PFDR < 0.01), compared with controls. Generated from co-expression network analysis of the PGC-1 summary statistics of schizophrenia, a subnetwork of 207 genes associated with schizophrenia was identified (P < 0.01), and 176 genes were co-expressed in four gene modules. Functional enrichment analysis for genes in each module revealed that the yellow module was enriched with highly co-expressed, innate immune response genes. Furthermore, rare variants of enriched genes in the yellow module were associated with reduced functional anisotropy in the left anterior cingulate cortex (P = 0.006; Padjusted = 0.024) in patients only.ConclusionsThe pathogenesis of schizophrenia may be substantially influenced by genes involved in the immune system, via both pathway and network.Declaration of interestsNone.


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Doretta Caramaschi ◽  
Charlie Hatcher ◽  
Rosa H. Mulder ◽  
Janine F. Felix ◽  
Charlotte A. M. Cecil ◽  
...  

AbstractThe occurrence of seizures in childhood is often associated with neurodevelopmental impairments and school underachievement. Common genetic variants associated with epilepsy have been identified and epigenetic mechanisms have also been suggested to play a role. In this study, we analyzed the association of genome-wide blood DNA methylation with the occurrence of seizures in ~ 800 children from the Avon Longitudinal Study of Parents and Children, UK, at birth (cord blood), during childhood, and adolescence (peripheral blood). We also analyzed the association between the lifetime occurrence of any seizures before age 13 with blood DNA methylation levels. We sought replication of the findings in the Generation R Study and explored causality using Mendelian randomization, i.e., using genetic variants as proxies. The results showed five CpG sites which were associated cross-sectionally with seizures either in childhood or adolescence (1–5% absolute methylation difference at pFDR < 0.05), although the evidence of replication in an independent study was weak. One of these sites was located in the BDNF gene, which is highly expressed in the brain, and showed high correspondence with brain methylation levels. The Mendelian randomization analyses suggested that seizures might be causal for changes in methylation rather than vice-versa. In conclusion, we show a suggestive link between seizures and blood DNA methylation while at the same time exploring the limitations of conducting such study.


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