Catechol-O-Methyltransferase Val158Met Polymorphism on Striatum Structural Covariance Networks in Alzheimer's Disease

Difference in Methylation and Expression of Brain-Derived Neurotrophic Factor in Alzheimer's Disease and Mild Cognitive Impairment

Due to the increasing number of progressive dementias in the population, numerous studies are being conducted that seek to determine risk factors, biomarkers and pathological mechanisms that could help to differentiate between normal symptoms of aging, mild cognitive impairment (MCI) and dementia. The aim of this study was to investigate the possible association of levels of BDNF and COMT gene expression and methylation in peripheral blood cells with the development of Alzheimer's disease (AD). Our results revealed higher expression levels of BDNF (p < 0.001) in MCI subjects compared to individuals diagnosed with AD. However, no difference in COMT gene expression (p = 0.366) was detected. DNA methylation of the CpG islands and other sequences with potential effects on gene expression regulation revealed just one region (BDNF_9) in the BDNF gene (p = 0.078) with marginally lower levels of methylation in the AD compared to MCI subjects. Here, we show that the level of BDNF expression in the periphery is decreased in subjects with AD compared to individuals with MCI. The combined results from the gene expression analysis and DNA methylation analysis point to the potential of BDNF as a marker that could help distinguish between MCI and AD patients.

Structural Covariance Network as an Endophenotype in Alzheimer's Disease-Susceptible Single-Nucleotide Polymorphisms and the Correlations With Cognitive Outcomes

The cognitive manifestations of Alzheimer’s disease (AD) are related to brain network degeneration, and genetic differences may mediate network degeneration. Several AD-susceptible loci have been reported to involve amyloid or tau cascades; however, their relationships with gray matter (GM) volume and cognitive outcomes have yet to be established. We hypothesized that single-nucleotide polymorphism genotype groups may interact with apolipoprotein E4 (ApoE4) status or independently exert an effect on cognitive outcomes. We also hypothesized that GM structural covariance networks (SCNs) may serve as an endophenotype of the genetic effect, which, in turn, may be related to neurobehavior test scores. Gray matter SCNs were constructed in 324 patients with AD using T1 magnetic resonance imaging with independent component analysis (ICA). We assessed the effects of 15 genetic loci (rs9349407, rs3865444, rs670139, rs744373, rs3851179, rs11136000, rs3764650, rs610932, rs6887649, rs7849530, rs4866650, rs3765728, rs34011, rs6656401, and rs597668) using additive, recessive, and dominant models on cognitive outcomes. Statistical analysis was performed to explore the independent role of each locus, interactions with ApoE4 status, and relationships to GM ICA network intensity score. For outcome measures, we used the Mini-Mental State Examination (MMSE), Cognitive Abilities Screening Instrument (CASI) total score, and short-term memory (STM) subscores, adjusted for the covariates of education, disease duration, and age. Clinically, the CD2AP G allele showed a protective role in MMSE, CASI total, and CASI-STM scores independently or via interactions with non-ApoE4 status, while the CR1 A genotype group was associated with lower STM subscores independent of ApoE4 status. Three loci showed synergic interactions with ApoE4: BIN 1, MS4A6A, and FTMT. Of the 15 meaningful ICA components, 5 SCNs (anterior and posterior hippocampus, right temporal, left thalamus, default mode network) showed relationships with general cognitive performance, in which only the ApoE4 and MS4A6A genotype groups were independently related to the hippocampus network. The genetic loci MS4A6A, BIN1, CLU, CR1, BIN1, PICALM, and FGF1 influenced the networks independently or in synergy. This study suggests that AD-susceptible loci may each exert clinical significance independently through interactions with ApoE4 status or through SCNs as an endophenotype and that this effect is associated with the cognitive outcomes.

Methylation quantitative trait locus rs5326 is associated with susceptibility and effective dosage of methadone maintenance treatment for heroin use disorder

RATIONALE

Opioid use disorder is a complicated brain disease with high heritability. The underlying mechanisms of the genetic underpinnings in the susceptibility and treatment response of opioid use disorder remain elusive.

OBJECTIVES

To reveal the potential associations of genotypes and gene methylations of dopaminergic system genes, as well as roles of them in opioid use disorder. In the present study, we detected the DNA methylation in the promoter regions of five representative dopaminergic system genes (DRD1, DRD2, SLC6A3, TH, and COMT) between 120 patients with heroin use disorder in methadone maintenance treatment (MMT) program and 111 healthy controls. The associations of 25 SNPs in the above genes and methylation of 237 CpG sites, known as methylation quantitative trait loci (mQTLs), were determined. Then, the correlations of the above mQTLs and traits of heroin use disorder were analyzed in a sample set of 801 patients with heroin use disorder and 930 healthy controls.

RESULTS

Our results demonstrated that several mQTLs in the DRD1 and DRD2 genes were identified both in the heroin use disorder and healthy control groups. Interestingly, rs4867798-CpG_174872884 and rs5326-CpG_174872884 in the DRD1 gene were the unique SNP-CpG pairs in the patients with heroin use disorder. Furthermore, mQTL rs5326 was associated with the susceptibility and effective dosage of MMT for heroin use disorder, and demonstrated allele-specific correlation with the expression of the DRD1 gene in the human caudate.

CONCLUSIONS

Our findings suggest that some mQTLs may be associated with traits of opioid use disorder by implicating the DNA methylation and gene expression.

Relationships of Cerebrospinal Fluid Alzheimer's Disease Biomarkers and COMT, DBH, and MAOB Single Nucleotide Polymorphisms

The noradrenergic and dopaminergic systems are affected in Alzheimer’s disease (AD). Polymorphisms in genes encoding enzymes and proteins that are components of these systems can affect products of transcription and translation and lead to altered enzymatic activity and alterations in overall dopamine and noradrenaline levels. Catechol-O-methyltransferase (COMT) and monoamine oxidase B (MAOB) are the enzymes that regulate degradation of dopamine, while dopamine β-hydroxylase (DBH) is involved in synthesis of noradrenaline. COMT Val158Met (rs4680), DBH rs1611115 (also called –1021C/T or –970C/T), and MAOB rs1799836 (also called A644G) polymorphisms have been previously associated with AD. We assessed whether these polymorphisms are associated with cerebrospinal fluid (CSF) AD biomarkers including total tau (t-tau), phosphorylated tau proteins (p-tau₁₈₁, p-tau₁₉₉, and p-tau₂₃₁), amyloid-β₄₂ (Aβ₄₂), and visinin-like protein 1 (VILIP-1) to test possible relationships of specific genotypes and pathological levels of CSF AD biomarkers. The study included 233 subjects: 115 AD, 53 mild cognitive impairment, 54 subjects with other primary causes of dementia, and 11 healthy controls. Significant decrease in Aβ₄₂ levels was found in patients with GG compared to AG COMT Val158Met genotype, while t-tau and p-tau₁₈₁ levels were increased in patients with AA compared to AG COMT Val158Met genotype. Aβ₄₂ levels were also decreased in carriers of A allele in MAO-B rs1799836 polymorphism, while p-tau₁₈₁ levels were increased in carriers of T allele in DBH rs1611115 polymorphism. These results indicate that COMT Val158Met, DBH rs1611115, and MAOB rs1799836 polymorphisms deserve further investigation as genetic markers of AD.