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Differentially methylated regions in bipolar disorder and suicide.

ABSTRACT: The addition of a methyl group to, typically, a cytosine-guanine dinucleotide (CpG) creates distinct DNA methylation patterns across the genome that can regulate gene expression. Aberrant DNA methylation of CpG sites has been associated with many psychiatric disorders including bipolar disorder (BD) and suicide. Using the SureSelect^XT system, Methyl-Seq, we investigated the DNA methylation status of CpG sites throughout the genome in 50 BD individuals (23 subjects who died by suicide and 27 subjects who died from other causes) and 31 nonpsychiatric controls. We identified differentially methylated regions (DMRs) from three analyses: (a) BD subjects compared to nonpsychiatric controls (BD-NC), (b) BD subjects who died by suicide compared to nonpsychiatric controls (BDS-NC), and (c) BDS subjects compared to BD subjects who died from other causes (BDS-BDNS). One DMR from the BDS-NC analysis, located in ARHGEF38, was significantly hypomethylated (23.4%) in BDS subjects. This finding remained significant after multiple testing (P_Bootstrapped = 9.0 × 10^-3 ), was validated using pyrosequencing, and was more significant in males. A secondary analysis utilized Ingenuity Pathway Analysis to identify enrichment in nominally significant DMRs. This identified an association with several pathways including axonal guidance signaling, calcium signaling, β-adrenergic signaling, and opioid signaling. Our comprehensive study provides further support that DNA methylation alterations influence the risk for BD and suicide. However, further investigation is required to confirm these associations and identify their functional consequences.

SUBMITTER: Gaine ME

PROVIDER: S-EPMC8375453 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGrowing evidence shows that epigenetic modifications play a role in Alzheimer's disease (AD). We performed an epigenome-wide association study (EWAS) to evaluate the DNA methylation differences using postmortem superior temporal gyrus (STG) and inferior frontal gyrus (IFG) samples.ResultsSamples from 72 AD patients and 62 age-matched cognitively normal controls were assayed using Illumina© Infinium MethylationEPIC BeadChip. Five and 14 differentially methylated positions (DMPs) associated with pathology (i.e., Braak stage) with p value less than Bonferroni correction threshold of 6.79 × 10-8 in the STG and IFG were identified, respectively. These cytosine-phosphate-guanine (CpG) sites included promoter associated cg26263477 annotated to ABCA7 in the STG (p = 1.21 × 10-11), and cg14058329 annotated to the HOXA5/HOXA3/HOXA-AS3 gene cluster (p = 1.62 × 10-9) and cg09448088 (p = 3.95 × 10-9) annotated to MCF2L in the IFG. These genes were previously reported to harbor DMPs and/or differentially methylated regions (DMRs). Previously reported DMPs annotated to RMGA, GNG7, HOXA3, GPR56, SPG7, PCNT, RP11-961A15.1, MCF2L, RHBDF2, ANK1, PCNT, TPRG1, and RASGEF1C were replicated (p < 0.0001). One hundred twenty-one and 173 DMRs associated with pathology in the STG and IFG, respectively, were additionally identified. Of these, DMRs annotated to 30 unique genes were also identified as significant DMRs in the same brain region in a recent meta-analysis, while additional DMRs annotated to 12 genes were reported as DMRs in a different brain region or in a cross-cortex meta-analysis. The significant DMRs were enriched in promoters, CpG islands, and exons in the genome. Gene set enrichment analysis of DMPs and DMRs showed that gene sets involved in neuroinflammation (e.g., microglia differentiation), neurogenesis, and cognition were enriched (false discovery rate (FDR) < 0.05).ConclusionsTwenty-two DMPs and 30 DMRs associated with pathology were replicated, and novel DMPs and DMRs were discovered.

Project description:BACKGROUND:DNA methylation is an epigenetic modification that is studied at a single-base resolution with bisulfite treatment followed by high-throughput sequencing. After alignment of the sequence reads to a reference genome, methylation counts are analyzed to determine genomic regions that are differentially methylated between two or more biological conditions. Even though a variety of software packages is available for different aspects of the bioinformatics analysis, they often produce results that are biased or require excessive computational requirements. RESULTS:DMRfinder is a novel computational pipeline that identifies differentially methylated regions efficiently. Following alignment, DMRfinder extracts methylation counts and performs a modified single-linkage clustering of methylation sites into genomic regions. It then compares methylation levels using beta-binomial hierarchical modeling and Wald tests. Among its innovative attributes are the analyses of novel methylation sites and methylation linkage, as well as the simultaneous statistical analysis of multiple sample groups. To demonstrate its efficiency, DMRfinder is benchmarked against other computational approaches using a large published dataset. Contrasting two replicates of the same sample yielded minimal genomic regions with DMRfinder, whereas two alternative software packages reported a substantial number of false positives. Further analyses of biological samples revealed fundamental differences between DMRfinder and another software package, despite the fact that they utilize the same underlying statistical basis. For each step, DMRfinder completed the analysis in a fraction of the time required by other software. CONCLUSIONS:Among the computational approaches for identifying differentially methylated regions from high-throughput bisulfite sequencing datasets, DMRfinder is the first that integrates all the post-alignment steps in a single package. Compared to other software, DMRfinder is extremely efficient and unbiased in this process. DMRfinder is free and open-source software, available on GitHub ( github.com/jsh58/DMRfinder ); it is written in Python and R, and is supported on Linux.

Project description:We conducted a retrospective investigation of potential clinical, demographic, and neuropsychological risk factors for suicide attempts in patients diagnosed with bipolar disorder.Participants included 67 adult inpatients and outpatients aged 18-60 years meeting DSM-IV criteria for bipolar disorder (bipolar I and II disorders, bipolar disorder not otherwise specified). We assessed demographic factors, mood symptoms, psychosis, trauma history, trait impulsivity, trait aggression, and reasons for living. The primary outcome measures were the Barratt Impulsiveness Scale-version II, Aggression Questionnaire, and 10 cognitive outcome variables. The cognitive outcome variables assessed cognitive performance across several domains, including processing speed, attention, verbal learning, and executive function. Another aspect of cognitive function, decision making, was assessed using the Iowa Gambling Task. The study was conducted from July 2007-July 2009.We found that nonattempters reported significantly higher trait impulsivity scores on the Barratt Impulsiveness Scale compared to attempters (t(57) = 2.2, P = .03) and that, among attempters, lower trait impulsivity score was associated with higher scores of lethality of prior attempts (r(25) = -0.53, P = .01). Analyses revealed no other group differences on demographic, clinical, or neurocognitive variables when comparing attempters versus nonattempters. Regression models failed to identify any significant predictors of past suicide attempt.The largely negative results of our study are particularly important in highlighting the clinical dilemma faced by many clinicians when trying to predict which patients will make serious suicide attempts and which patients are at a lower risk for acting on suicidal thoughts. A limitation of our work is that we examined stable trait measures of impulsivity among a euthymic sample rather than mood state or the impact of mood state on traits. Overall, we conclude that suicidal behavior is extremely difficult to predict, even when comprehensive clinical and neurocognitive information is available.

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Differentially methylated regions in bipolar disorder and suicide.

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