Epigenetic differences in monozygotic twins discordant for major depressive disorder

Molecular mechanisms underlying major depressive disorder and post-stroke affective disorders

Two of the most common and incapacitating mental health disorders around the world are major depressive disorder (MDD) and post-stroke depression (PSD). MDD is thought to result from abnormal connectivity between the monoaminergic, glutamatergic, GABAergic, and/or cholinergic pathways. Additional factors include the roles of hormonal, immune, ageing, as well as the influence of cellular, molecular, and epigenetics in the development of mood disorders. This complexity of factors has been anticipated by the Swiss psychiatrists Paul Kielholz and Jules Angst who introduced a multimodal treatment of MDD. Depression is the predominant mood disorder, impacting around one-third of individuals who have experienced a stroke. MDD and PSD share common underlying biological mechanisms related to the disruption of monoaminergic pathways. The major contributor to PSD is the stroke lesion location, which can involve the disruption of the serotoninergic, dopaminergic, glutamatergic, GABAergic, or cholinergic pathways. Additionally, various other disorders such as mania, bipolar disorder, anxiety disorder, and apathy might occur post-stroke, although their prevalence is considerably lower. However, there are differences in the onset of MDD among mood disorders. Some mood disorders develop gradually and can persist for a lifetime, potentially culminating in suicide. In contrast, PSD has a rapid onset because of the severe disruption of neural pathways essential for mood behavior caused by the lesion. However, PSD might also spontaneously resolve several months after a stroke, though it is associated with higher mortality. This review also provides a brief overview of the treatments currently available in medical practice.

Hif-1α regulates Tet1-c-Myc binding involved in depression-like behavior in prenatal hypoxia offspring

Prenatal hypoxia (PH) is one of the most common adverse stimulation during pregnancy. The brain is fragile in the fetal period and sensitive to hypoxia. The offspring who have experienced PH may be at increased risk of developing neurodevelopmental disorders after birth and various neuropsychiatric diseases after adulthood. In this study, pregnant mice used to generate PH offspring were treated with hypoxia (10.5% oxygen) from gestational day 12.5 to 17.5. Compared with control mice, the birth weight of offspring in the PH group was significantly lower and the male adult offspring exhibited significant depression-like behavior. The expression of the oxygen-sensitive subunit of hypoxia-inducible factor (Hif-1α) was significantly elevated, whereas Ten-eleven translocated methylcytosine dioxygenase 1 (Tet1) and c-Myc, which is closely related to cell proliferation, was significantly decreased in the hippocampus of the male offspring in the PH group. In addition, the PH group showed increased binding of Hif-1α to Tet1, and decreased binding of Tet1 to c-Myc, resulting in increased ubiquitinated degradation of c-Myc and decreased neurogenesis in the hippocampus of the male offspring. These findings suggest that Hif-1α regulates Tet1-c-Myc binding involved in depression-like behavior in PH offspring and Hif-1α can be used as a detection index of stress-related diseases.

Rapid Eye Movement Sleep Deprivation Enhances Adenosine Receptor Activation and the CREB1/YAP1/c-Myc Axis to Alleviate Depressive-like Behaviors in Rats

As neuromodulators, adenosine and its receptors are mediators of sleep-wake regulation. A putative correlation between CREB1 and depression has been predicted in our bioinformatics analyses, and its expression was also predicted to be upregulated in response to sleep deprivation. Therefore, this study aims to elaborate the A1 and A2A adenosine receptors and CREB1-associated mechanism underlying the antidepressant effect of rapid eye movement sleep deprivation (REMSD) in rats with chronic unpredictable mild stress (CUMS)-induced depressive-like behaviors. The modeled rats were injected with adenosine A1 receptor antagonist DPCPX or adenosine A2A receptor antagonist ZM241385 to assess the role of adenosine receptors in depression. In addition, ectopic expression and depletion experiments of CREB1 and YAP1 were also conducted in vivo and in vitro. It was found that REMSD alleviated depressive-like behaviors in CUMS rats, as shown by increased spontaneous activity, sucrose consumption and percentage, and shortened escape latency and immobility duration. Meanwhile, A1 or A2A adenosine receptor antagonists negated the antidepressant effect of REMSD. REMSD enhanced adenosine receptor activation and promoted the phosphorylation of CREB1, thus increasing the expression of CREB1. In addition, the overexpression of CREB1 activated the YAP1/c-Myc axis and consequently alleviated depressive-like behaviors. Collectively, our results provide new mechanistic insights for an understanding of the antidepressant effect of REMSD, which is associated with the activation of adenosine receptors and the CREB1/YAP1/c-Myc axis.

Association of Epigenetic Differences Screened in a Few Cases of Monozygotic Twins Discordant for Attention-Deficit Hyperactivity Disorder With Brain Structures

The present study examined the relationship between DNA methylation differences and variations in brain structures involved in the development of attention-deficit hyperactivity disorder (ADHD). First, we used monozygotic (MZ) twins discordant (2 pairs of 4 individuals, 2 boys, mean age 12.5 years) for ADHD to identify candidate DNA methylation sites involved in the development of ADHD. Next, we tried to replicate these candidates in a case-control study (ADHD: N = 18, 15 boys, mean age 10.0 years; Controls: N = 62, 40 boys, mean age 13.9 years). Finally, we examined how methylation rates at those sites relate to the degree of local structural alterations where significant differences were observed between cases and controls. As a result, we identified 61 candidate DNA methylation sites involved in ADHD development in two pairs of discordant MZ twins, among which elevated methylation at a site in the sortilin-related Vps10p domain containing receptor 2 (SorCS2) gene was replicated in the case-control study. We also observed that the ADHD group had significantly reduced gray matter volume (GMV) in the precentral and posterior orbital gyri compared to the control group and that this volume reduction was positively associated with SorCS2 methylation. Furthermore, the reduced GMV regions in children with ADHD are involved in language processing and emotional control, while SorCS2 methylation is also negatively associated with emotional behavioral problems in children. These results indicate that SorCS2 methylation might mediate a reduced GMV in the precentral and posterior orbital gyri and therefore influence the pathology of children with ADHD.

Machine Learning Methods for Predicting Postpartum Depression: Scoping Review

BACKGROUND

Machine learning (ML) offers vigorous statistical and probabilistic techniques that can successfully predict certain clinical conditions using large volumes of data. A review of ML and big data research analytics in maternal depression is pertinent and timely, given the rapid technological developments in recent years.

OBJECTIVE

This study aims to synthesize the literature on ML and big data analytics for maternal mental health, particularly the prediction of postpartum depression (PPD).

METHODS

We used a scoping review methodology using the Arksey and O'Malley framework to rapidly map research activity in ML for predicting PPD. Two independent researchers searched PsycINFO, PubMed, IEEE Xplore, and the ACM Digital Library in September 2020 to identify relevant publications in the past 12 years. Data were extracted from the articles' ML model, data type, and study results.

RESULTS

A total of 14 studies were identified. All studies reported the use of supervised learning techniques to predict PPD. Support vector machine and random forest were the most commonly used algorithms in addition to Naive Bayes, regression, artificial neural network, decision trees, and XGBoost (Extreme Gradient Boosting). There was considerable heterogeneity in the best-performing ML algorithm across the selected studies. The area under the receiver operating characteristic curve values reported for different algorithms were support vector machine (range 0.78-0.86), random forest method (0.88), XGBoost (0.80), and logistic regression (0.93).

CONCLUSIONS

ML algorithms can analyze larger data sets and perform more advanced computations, which can significantly improve the detection of PPD at an early stage. Further clinical research collaborations are required to fine-tune ML algorithms for prediction and treatment. ML might become part of evidence-based practice in addition to clinical knowledge and existing research evidence.

An information-based framework for development national twin registry: Scoping review and focus group discussion

BACKGROUND

Registries in various clinical domains have been established in the last decades. The specific genetic structure of twins has enabled researchers to find answers to the role of genetics and the environment in medical sciences. Thus, twin registries were developed across the world to support twin studies. Our main objective was to devise a conceptual model for developing the national twin registry to ensure the success of this registry.

METHODS

In this descriptive and qualitative study, the combination of literature review and focus group discussions was applied to achieve suitable models for developing a national twin registry based on lessons learned from founded registries. The qualitative synthesis and reporting results were conducted based on the COREQ checklist.

RESULTS

According to a systematic literature review, the characteristics and employed strategies employed by established twin registries were recognized. Moreover, based on our objectives, suitable models for registry development were defined. The source of information, the different levels of data, and the information flow were determined based on this model.

CONCLUSION

Suggesting a conceptual framework for twin registry development at the national level based on the experiences of other countries could contribute to a greater understanding of twin registry implementation efficiently.

Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder

Up to 60% of patients with major depressive disorder (MDD) do not respond to the first treatment with antidepressants. Response to antidepressants is a polygenic trait, although its underpinning genetics has not been fully clarified. This study aimed to investigate if polygenic risk scores (PRSs) for major psychiatric disorders and trait neuroticism (NEU) were associated with non-response or resistance to antidepressants in MDD. PRSs for bipolar disorder, MDD, NEU, and schizophrenia (SCZ) were computed in 1,148 patients with MDD. Summary statistics from the largest meta-analyses of genome-wide association studies were used as base data. Patients were classified as responders, non-responders to one treatment, non-responders to two or more treatments (treatment-resistant depression or TRD). Regression analyses were adjusted for population stratification and recruitment sites. PRSs did not predict either non-response vs response or TRD vs response after Bonferroni correction. However, SCZ-PRS was nominally associated with non-response (p = 0.003). Patients in the highest SCZ-PRS quintile were more likely to be non-responders than those in the lowest quintile (OR = 2.23, 95% CI = 1.21-4.10, p = 0.02). Patients in the lowest SCZ-PRS quintile showed higher response rates when they did not receive augmentation with second-generation antipsychotics (SGAs), while those in the highest SCZ-PRS quintile had a poor response independently from the treatment strategy (p = 0.009). A higher genetic liability to SCZ may reduce treatment response in MDD, and patients with low SCZ-PRSs may show higher response rates without SGA augmentation. Multivariate approaches and methodological refinements will be necessary before clinical implementations of PRSs.

Unraveling the Genetics of Congenital Diaphragmatic Hernia: An Ongoing Challenge

Congenital diaphragmatic hernia (CDH) is a congenital structural anomaly in which the diaphragm has not developed properly. It may occur either as an isolated anomaly or with additional anomalies. It is thought to be a multifactorial disease in which genetic factors could either substantially contribute to or directly result in the developmental defect. Patients with aneuploidies, pathogenic variants or de novo Copy Number Variations (CNVs) impacting specific genes and loci develop CDH typically in the form of a monogenetic syndrome. These patients often have other associated anatomical malformations. In patients without a known monogenetic syndrome, an increased genetic burden of de novo coding variants contributes to disease development. In early years, genetic evaluation was based on karyotyping and SNP-array. Today, genomes are commonly analyzed with next generation sequencing (NGS) based approaches. While more potential pathogenic variants are being detected, analysis of the data presents a bottleneck-largely due to the lack of full appreciation of the functional consequence and/or relevance of the detected variant. The exact heritability of CDH is still unknown. Damaging de novo alterations are associated with the more severe and complex phenotypes and worse clinical outcome. Phenotypic, genetic-and likely mechanistic-variability hampers individual patient diagnosis, short and long-term morbidity prediction and subsequent care strategies. Detailed phenotyping, clinical follow-up at regular intervals and detailed registries are needed to find associations between long-term morbidity, genetic alterations, and clinical parameters. Since CDH is a relatively rare disorder with only a few recurrent changes large cohorts of patients are needed to identify genetic associations. Retrospective whole genome sequencing of historical patient cohorts using will yield valuable data from which today's patients and parents will profit Trio whole genome sequencing has an excellent potential for future re-analysis and data-sharing increasing the chance to provide a genetic diagnosis and predict clinical prognosis. In this review, we explore the pitfalls and challenges in the analysis and interpretation of genetic information, present what is currently known and what still needs further study, and propose strategies to reap the benefits of genetic screening.

Influence of heritability on occlusal traits: a systematic review of studies in twins

BACKGROUND

The aim of this systematic review was to identify, evaluate, and provide a current literature about the influence of heritability on the determination of occlusal traits.

MATERIALS AND METHODS

MEDLINE, SCOPUS, Web of Science, LILACS, and Google Scholar were searched without restrictions up to March 2020. Studies with twin method were considered and the risk of bias assessment was performed using quality of genetic association studies checklist (Q-Genie). The coefficient of heritability (h²), model-fitting approaches, and coefficient correlation were used to estimate the genetic/environmental influence on occlusal traits. The GRADE tool was used to assess the quality of the evidence.

RESULTS

Ten studies met the eligibility criteria. Three studies presented good quality, five moderate quality, and two poor quality. Most studies have found that the intra-arch traits, mainly the maxillary arch morphology, such as width (h² 16-100%), length (h² 42-100%), and shape (h² 42-90%), and the crowding, mainly for mandibular arch (h² 35-81%), are under potential heritability influence. The traits concerning the inter-arch relationship, as overjet, overbite, posterior crossbite, and sagittal molar relation, seem not to be genetically determined. The certainty of the evidence was graded as low for all outcomes.

CONCLUSIONS

Although weak, the available evidence show that the heritability factors are determinant for the intra-arch traits, namely, arch morphology and crowding. Possibly due they are functionally related, the occlusal traits concerning the maxillary and mandibular relationship seem to have environmental factors as determinants. In this scenario, early preventive approaches can offer a more effective and efficient orthodontic treatment.

Machine Learning Models for the Prediction of Postpartum Depression: Application and Comparison Based on a Cohort Study

Background

Postpartum depression (PPD) is a serious public health problem. Building a predictive model for PPD using data during pregnancy can facilitate earlier identification and intervention.

Objective

The aims of this study are to compare the effects of four different machine learning models using data during pregnancy to predict PPD and explore which factors in the model are the most important for PPD prediction.

Methods

Information on the pregnancy period from a cohort of 508 women, including demographics, social environmental factors, and mental health, was used as predictors in the models. The Edinburgh Postnatal Depression Scale score within 42 days after delivery was used as the outcome indicator. Using two feature selection methods (expert consultation and random forest-based filter feature selection [FFS-RF]) and two algorithms (support vector machine [SVM] and random forest [RF]), we developed four different machine learning PPD prediction models and compared their prediction effects.

Results

There was no significant difference in the effectiveness of the two feature selection methods in terms of model prediction performance, but 10 fewer factors were selected with the FFS-RF than with the expert consultation method. The model based on SVM and FFS-RF had the best prediction effects (sensitivity=0.69, area under the curve=0.78). In the feature importance ranking output by the RF algorithm, psychological elasticity, depression during the third trimester, and income level were the most important predictors.

Conclusions

In contrast to the expert consultation method, FFS-RF was important in dimension reduction. When the sample size is small, the SVM algorithm is suitable for predicting PPD. In the prevention of PPD, more attention should be paid to the psychological resilience of mothers.

Twin study designs as a tool to identify new candidate genes for depression: A systematic review of DNA methylation studies

Monozygotic (MZ) twin studies constitute a key resource for the dissection of environmental and biological risk factors for human complex disorders. Given that epigenetic differences accumulate throughout the lifespan, the assessment of MZ twin pairs discordant for depression offers a genetically informative design to explore DNA methylation while accounting for the typical confounders of the field, shared by co-twins of a pair. In this review, we systematically evaluate all twin studies published to date assessing DNA methylation in association with depressive phenotypes. However, difficulty to recruit large numbers of MZ twin pairs fails to provide enough sample size to develop genome-wide approaches. Alternatively, region and pathway analysis revealed an enrichment for nervous system related functions; likewise, evidence supports an accumulation of methylation variability in affected subjects when compared to their co-twins. Nevertheless, longitudinal studies incorporating known risk factors for depression such as childhood trauma are required for understanding the role that DNA methylation plays in the etiology of depression.

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

BACKGROUND

Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.

RESULTS

Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression.

CONCLUSIONS

Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

Genetic and epigenetic study of an Alzheimer's disease family with monozygotic triplets

Age at onset of Alzheimer's disease is highly variable, and its modifiers (genetic or environmental) could act through epigenetic changes, such as DNA methylation at CpG sites. DNA methylation is also linked to ageing-the strongest Alzheimer's disease risk factor. DNA methylation age can be calculated using age-related CpGs and might reflect biological ageing. We conducted a clinical, genetic and epigenetic investigation of a unique Ashkenazi Jewish family with monozygotic triplets, two of whom developed Alzheimer's disease at ages 73 and 76, while the third at age 85 has no cognitive complaints or deficits in daily activities. One of their offspring developed Alzheimer's disease at age 50. Targeted sequencing of 80 genes associated with neurodegeneration revealed that the triplets and the affected offspring are heterozygous carriers of the risk APOE ε4 allele, as well as rare substitutions in APP (p.S198P), NOTCH3 (p.H1235L) and SORL1 (p.W1563C). In addition, we catalogued 52 possibly damaging rare variants detected by NeuroX array in affected individuals. Analysis of family members on a genome-wide DNA methylation chip revealed that the DNA methylation age of the triplets was 6-10 years younger than chronological age, while it was 9 years older in the offspring with early-onset Alzheimer's disease, suggesting accelerated ageing.

Twin Registries Moving Forward and Meeting the Future: A Review

Twin registries have developed as a valuable resource for the study of many aspects of disease and society over the years in many different countries. A number of these registries include large numbers of twins with data collected at varying information levels for twin cohorts over the past several decades. More recent expansion of twin datasets has allowed for the collection of genetic data, together with many other levels of 'omic' information along with multiple demographic, physiological, health outcomes and other measures typically used in epidemiologic research. Other twin data sources outside these registries reflect research interests in particular aspects of disease or specific phenotypic assessment. Twin registries have the potential to play a key role in many aspects of the artificial intelligence/machine learning-driven projects of the future and will continue to keep adapting to the changing research landscape.

Genome-wide profiling of DNA methylome and transcriptome in peripheral blood monocytes for major depression: A Monozygotic Discordant Twin Study

DNA methylation plays an important role in major depressive disorder (MDD), but the specific genes and genomic regions associated with MDD remain largely unknown. Here we conducted genome-wide profiling of DNA methylation (Infinium MethylationEPIC BeadChip) and gene expression (RNA-seq) in peripheral blood monocytes from 79 monozygotic twin pairs (mean age 38.2 ± 15.6 years) discordant on lifetime history of MDD to identify differentially methylated regions (DMRs) and differentially expressed genes (DEGs) associated with MDD, followed by replication in brain tissue samples. Integrative DNA methylome and transcriptome analysis and network analysis was performed to identify potential functional epigenetic determinants for MDD. We identified 39 DMRs and 30 DEGs associated with lifetime history of MDD. Some genes were replicated in postmortem brain tissue. Integrative DNA methylome and transcriptome analysis revealed both negative and positive correlations between DNA methylation and gene expression, but the correlation pattern varies greatly by genomic locations. Network analysis revealed distinct gene modules enriched in signaling pathways related to stress responses, neuron apoptosis, insulin receptor signaling, mTOR signaling, and nerve growth factor receptor signaling, suggesting potential functional relevance to MDD. These results demonstrated that altered DNA methylation and gene expression in peripheral blood monocytes are associated with MDD. Our results highlight the utility of using peripheral blood epigenetic markers and demonstrate that a monozygotic discordant co-twin control design can aid in the discovery of novel genes associated with MDD. If validated, the newly identified genes may serve as novel biomarkers or druggable targets for MDD and related disorders.

Epigenome-wide association study of depression symptomatology in elderly monozygotic twins

Depression is a severe and debilitating mental disorder diagnosed by evaluation of affective, cognitive and physical depression symptoms. Severity of these symptoms strongly impacts individual's quality of life and is influenced by a combination of genetic and environmental factors. One of the molecular mechanisms allowing for an interplay between these factors is DNA methylation, an epigenetic modification playing a pivotal role in regulation of brain functioning across lifespan. The aim of this study was to investigate if there are DNA methylation signatures associated with depression symptomatology in order to identify molecular mechanisms contributing to pathophysiology of depression. We performed an epigenome-wide association study (EWAS) of continuous depression symptomatology score measured in a cohort of 724 monozygotic Danish twins (346 males, 378 females). Through EWAS analyses adjusted for sex, age, flow-cytometry based blood cell composition, and twin relatedness structure in the data we identified depression symptomatology score to be associated with blood DNA methylation levels in promoter regions of neuropsin (KLK8, p-value = 4.7 × 10^-7) and DAZ associated protein 2 (DAZAP2, p-value = 3.13 × 10^-8) genes. Other top associated probes were located in gene bodies of MAD1L1 (p-value = 5.16 × 10^-6), SLC29A2 (p-value = 6.15 × 10^-6) and AKT1 (p-value = 4.47 × 10^-6), all genes associated before with development of depression. Additionally, the following three measures (a) DNAmAge (calculated with Horvath and Hannum epigenetic clock estimators) adjusted for chronological age, (b) difference between DNAmAge and chronological age, and (c) DNAmAge acceleration were not associated with depression symptomatology score in our cohort. In conclusion, our data suggests that depression symptomatology score is associated with DNA methylation levels of genes implicated in response to stress, depressive-like behaviors, and recurrent depression in patients, but not with global DNA methylation changes across the genome.

Epistasis of HTR1A and BDNF risk genes alters cortical 5-HT1A receptor binding: PET results link genotype to molecular phenotype in depression

Alterations of the 5-HT_1A receptor and BDNF have consistently been associated with affective disorders. Two functional single nucleotide polymorphisms (SNPs), rs6295 of the serotonin 1A receptor gene (HTR1A) and rs6265 of brain-derived neurotrophic factor gene (BDNF), may impact transcriptional regulation and expression of the 5-HT_1A receptor. Here we investigated interaction effects of rs6295 and rs6265 on 5-HT_1A receptor binding. Forty-six healthy subjects were scanned with PET using the radioligand [carbonyl-¹¹C]WAY-100635. Genotyping was performed for rs6265 and rs6295. Subjects showing a genotype with at least three risk alleles (G of rs6295 or A of rs6265) were compared to control genotypes. Cortical surface binding potential (BP_ND) was computed for 32 cortical regions of interest (ROI). Mixed model was applied to study main and interaction effects of ROI and genotype. ANOVA was used for post hoc analyses. Individuals with the risk genotypes exhibited an increase in 5-HT_1A receptor binding by an average of 17% (mean BP_ND 3.56 ± 0.74 vs. 2.96 ± 0.88). Mixed model produced an interaction effect of ROI and genotype on BP_ND and differences could be demonstrated in 10 ROI post hoc. The combination of disadvantageous allelic expression of rs6295 and rs6265 may result in a 5-HT_1A receptor profile comparable to affective disorders as increased 5-HT_1A receptor binding is a well published phenotype of depression. Thus, epistasis between BDNF and HTR1A may contribute to the multifactorial risk for affective disorders and our results strongly advocate further research on this genetic signature in affective disorders.

A cross comparison between Ayurvedic etiology of Major Depressive Disorder and bidirectional effect of gut dysregulation

Ayurveda, an Indian medical science has been practiced for thousands of years. What makes Ayurveda relevant today is its subtle understanding of the environment and its focus on the generation of good health through one's own lifestyle choices. The digestive system has long been an area of critical importance within the Ayurvedic system and is only now being acknowledged by modern science as a key component in the regulation of physical and mental well-being. The gut microbiome and enteric nervous system are two particular areas in which the onset of psychiatric disorders, such as depression, have been associated. There are some striking similarities between this biomedical understanding of the gastrointestinal system and the Ayurvedic perspective of disease development. Major Depressive Disorder (MDD) is becoming increasingly linked with gut dysregulation in contemporary literature and is a pathology explored within both the Ayurvedic and Western systems of medicine. This literature review seeks to draw parallels between these two areas of study and highlight the importance of the digestive system when diagnosing and treating MDD.

Childhood Trauma, DNA Methylation of Stress-Related Genes, and Depression: Findings From Two Monozygotic Twin Studies

OBJECTIVE

DNA methylation has been associated with both early life stress and depression. This study examined the combined association of DNA methylation at multiple CpG probes in five stress-related genes with depressive symptoms and tested whether these genes methylation mediated the association between childhood trauma and depression in two monozygotic (MZ) twin studies.

METHODS

The current analysis comprised 119 MZ twin pairs (84 male pairs [mean = 55 years] and 35 female pairs [mean = 36 years]). Peripheral blood DNA methylation of five stress-related genes (BDNF, NR3C1, SLC6A4, MAOA, and MAOB) was quantified by bisulfite pyrosequencing or 450K BeadChip. We applied generalized Poisson linear-mixed models to examine the association between each single CpG methylation and depressive symptoms. The joint associations of multiple CpGs in a single gene or all five stress-related genes as a pathway were tested by weighted truncated product method. Mediation analysis was conducted to test the potential mediating effect of stress gene methylation on the relationship between childhood trauma and depressive symptoms.

RESULTS

Multiple CpG probes showed nominal individual associations, but very few survived multiple testing. Gene-based or gene-set approach, however, revealed significant joint associations of DNA methylation in all five stress-related genes with depressive symptoms in both studies. Moreover, two CpG probes in the BDNF and NR3C1 mediated approximately 20% of the association between childhood trauma and depressive symptoms.

CONCLUSIONS

DNA methylation at multiple CpG sites are jointly associated with depressive symptoms and partly mediates the association between childhood trauma and depression. Our results highlight the importance of testing the combined effects of multiple CpG loci on complex traits and may unravel a molecular mechanism through which adverse early life experiences are biologically embedded.

Investigating the Epigenetic Discrimination of Identical Twins Using Buccal Swabs, Saliva, and Cigarette Butts in the Forensic Setting

Monozygotic (MZ) twins are typically indistinguishable via forensic DNA profiling. Recently, we demonstrated that epigenetic differentiation of MZ twins is feasible; however, proportions of twin differentially methylated CpG sites (tDMSs) identified in reference-type blood DNA were not replicated in trace-type blood DNA. Here we investigated buccal swabs as typical forensic reference material, and saliva and cigarette butts as commonly encountered forensic trace materials. As an analog to a forensic case, we analyzed one MZ twin pair. Epigenome-wide microarray analysis in reference-type buccal DNA revealed 25 candidate tDMSs with >0.5 twin-to-twin differences. MethyLight quantitative PCR (qPCR) of 22 selected tDMSs in trace-type DNA revealed in saliva DNA that six tDMSs (27.3%) had >0.1 twin-to-twin differences, seven (31.8%) had smaller (<0.1) but robustly detected differences, whereas for nine (40.9%) the differences were in the opposite direction relative to the microarray data; for cigarette butt DNA, results were 50%, 22.7%, and 27.3%, respectively. The discrepancies between reference-type and trace-type DNA outcomes can be explained by cell composition differences, method-to-method variation, and other technical reasons including bisulfite conversion inefficiency. Our study highlights the importance of the DNA source and that careful characterization of biological and technical effects is needed before epigenetic MZ twin differentiation is applicable in forensic casework.

Association of Novel ALX4 Gene Polymorphisms with Antidepressant Treatment Response: Findings from the CO-MED Trial

Genome-wide association studies (GWAS) were conducted in participants of the CO-MED (Combining Medications to Enhance Depression Outcomes) trial, a randomized, 3-treatment arm clinical trial of major depressive disorder (MDD) designed to identify markers of differential treatment outcome (response and remission). The QIDS-SR (Quick Inventory of Depressive Symptomatology, Self-Reported version) was used to measure response at week 6 (QIDS-SR ≤5) and remission at week 12 (QIDS-SR ≤6 and ≤8 at the last two study visits). Three treatment groups (escitalopram monotherapy, escitalopram + bupropion, and venlafaxine + mirtazapine) were evaluated. GWAS identified a potentially regulatory SNP rs10769025 in the ALX4 gene on chromosome 11 with a strong association (p value = 9.85925E-08) with response to escitalopram monotherapy in Caucasians. Further, haplotype analysis on 7 ALX4 variants showed that a regulatory haplotype CAAACTG was significantly associated (odds ratio = 3.4, p = 2.00E-04) with response to escitalopram monotherapy at week 6. Ingenuity pathway analyses in the present study suggest that ALX4 has an indirect connection with antidepressant gene pathways in MDD, which may account for the genetic association with treatment outcome. Functional genomics studies to investigate the role of ALX4 in antidepressant treatment outcome will be an interesting future direction.

Epigenetic Drugs for Mood Disorders

There is increasing evidence that changes in epigenetic mechanisms of gene expression are involved in the pathogenesis of mood disorders. Such evidence stems from studies conducted on postmortem brain tissues and peripheral cells or tissues of patients with mood disorders. This article describes and discusses the epigenetic changes in the mood disorders (major depressive disorder and bipolar disorder) found to date. The article also describes and discusses preclinical drug trials of epigenetic drugs for treating mood disorders. In addition, nonrandomized and randomized controlled trials of nutritional drugs with effects on epigenetic mechanisms of gene expression in patients with major depressive disorder and bipolar disorder are discussed. Trials of epigenetic drugs and nutritional drugs with epigenetic effects are showing promising results for the treatment of mood disorders. Thus, epigenetic drugs and nutritional drugs with epigenetic effects could be useful in the treatment of patients with these disorders.

Epigenetic profiles associated with major depression in the human brain

We conducted an epigenome-wide association study of Major Depressive Disorder (MDD) in brain-derived DNA using two analytic approaches. DNA methylation data (GSE41826) was used in differential methylation (DM) analyses controlling for age, sex, suicide status, and post-mortem interval; and in weighted gene co-methylation network analyses (WGCNA) in probes mapping to transcription start sites. No probes in the DM analysis survived FDR correction. Nominally significant DM probes were enriched in synaptic function-related genes. WGCNA revealed one module correlated with MDD, enriched in genes associated with mitochondrial function. DM and WGCNA both showed enrichment of genes involved in transcription and DNA binding.

Heritability of saccadic eye movements in spinocerebellar ataxia type 2: insights into an endophenotype marker

Background

Saccade slowing has been proposed as endophenotype marker in Spinocerebellar Ataxia type 2 (SCA2), nevertheless the heritability of this trait has not been properly demonstrated. Thus the present paper was aimed to assess the heritability of different saccadic parameters in SCA2.

Methods

Forty-eight SCA2 patients, 25 preclinical carriers and 24 non-SCA2 mutation carriers underwent electronystagmographical assessments of saccadic eye movements as well as neurological examination and ataxia scoring. Estimates of heritability based on the intraclass correlation coefficients were calculated for saccade velocity, accuracy and latency as well as for age at disease onset from 36, 17 and 15 sibling pairs of SCA2 patients, preclinical carriers and controls, respectively.

Results

Saccade velocity was significantly reduced in SCA2 patients and preclinical carriers, whereas decreased saccade accuracy and increased saccade latency were only observed in the patients cohort. Intraclass correlation coefficient for saccade velocity was highly significant in SCA2 patients, estimating a heritability around 94%, whereas for the age at ataxia onset this estimate was around 68%.

Conclusions

Electronystagmographical measure of saccade velocity showed higher familial aggregation between SCA2 patients leading the suitability of this disease feature as endophenotype marker, with potential usefulness for the search of modifier genes and neurobiological underpinnings of the disease and as outcome measure in future neuroprotective clinical trials.

The influence of the rs6295 gene polymorphism on serotonin-1A receptor distribution investigated with PET in patients with major depression applying machine learning

Major depressive disorder (MDD) is the most common neuropsychiatric disease and despite extensive research, its genetic substrate is still not sufficiently understood. The common polymorphism rs6295 of the serotonin-1A receptor gene (HTR1A) is affecting the transcriptional regulation of the 5-HT_1A receptor and has been closely linked to MDD. Here, we used positron emission tomography (PET) exploiting advances in data mining and statistics by using machine learning in 62 healthy subjects and 19 patients with MDD, which were scanned with PET using the radioligand [carbonyl-¹¹C]WAY-100635. All the subjects were genotyped for rs6295 and genotype was grouped in GG vs C allele carriers. Mixed model was applied in a ROI-based (region of interest) approach. ROI binding potential (BP_ND) was divided by dorsal raphe BP_ND as a specific measure to highlight rs6295 effects (BP_Div). Mixed model produced an interaction effect of ROI and genotype in the patients' group but no effects in healthy controls. Differences of BP_Div was demonstrated in seven ROIs; parahippocampus, hippocampus, fusiform gyrus, gyrus rectus, supplementary motor area, inferior frontal occipital gyrus and lingual gyrus. For classification of genotype, 'RandomForest' and Support Vector Machines were used, however, no model with sufficient predictive capability could be computed. Our results are in line with preclinical data, mouse model knockout studies as well as previous clinical analyses, demonstrating the two-pronged effect of the G allele on 5-HT_1A BP_ND for, we believe, the first time. Future endeavors should address epigenetic effects and allosteric heteroreceptor complexes. Replication in larger samples of MDD patients is necessary to substantiate our findings.

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.