Somatic MED12 Mutations in Myometrial Cells.

Over 70% of leiomyoma (LM) harbor MED12 mutations, primarily in exon 2 at c.130-131 (GG). Myometrial cells are the cell origin of leiomyoma, but the MED12 mutation status in non-neoplastic myometrial cells is unknown. In this study, we investigated the mutation burden of MED12 in myometrium. As traditional Sanger or even NGS sequencing may not be able to detect MED12 mutations that are lower than 0.1% in the testing sample, we used duplex deep sequencing analysis (DDS) to overcome this limitation. Tumor-free myometria (confirmed by pathology evaluation) were dissected, and genomic DNA from MED12 exon 2 (test) and TP53 exon 5 (control) were captured by customer-designed probe sets, followed by DDS. Notably, DDS demonstrated that myometrial cells harbored a high frequency of mutations in MED12 exon 2 and predominantly in code c.130-131. In contrast, the baseline mutations in other coding sequences of MED12 exon 2 as well as in the TP53 mutation hotspot, c.477-488 were comparably low in myometrial cells. This is the first report demonstrating a non-random accumulation of MED12 mutations at c.130-131 sites in non-neoplastic myometrial cells which provide molecular evidence of early somatic mutation events in myometrial cells. This early mutation may contribute to the cell origin for uterine LM development in women of reproductive age.

The Impact of High Adiposity on Endometrial Progesterone Response and Metallothionein Regulation.

CONTEXT: Obesity is a disease with deleterious effects on the female reproductive tract, including the endometrium. OBJECTIVE: We sought to understand the effects of excess adipose on the benign endometrium. DESIGN: A physiologic in vitro coculture system was developed, consisting of multicellular human endometrial organoids, adipose spheroids, and menstrual cycle hormones. Native human endometrial tissue samples women with and without obesity were also analyzed. SETTING: Academic institution. PATIENTS: Benign endometrial tissues from premenopausal women were obtained following written consent. MAIN OUTCOME MEASURES: Gene expression, protein expression, chromatin binding, and expression of DNA damage and oxidative damage markers were measured. RESULTS: Under high-adiposity conditions, endometrial organoids downregulated endometrial secretory phase genes, suggestive of an altered progesterone response. Progesterone specifically upregulated the metallothionein (MT) gene family in the epithelial cells of endometrial organoids, while high adiposity significantly downregulated the MT genes. Silencing MT genes in endometrial epithelial cells resulted in increased DNA damage, illustrating the protective role of MTs. Native endometrium from women with obesity displayed increased MT expression and oxidative damage in the stroma and not in the epithelium, indicating the cell-specific impact of obesity on MT genes. CONCLUSIONS: Taken together, the in vitro and in vivo systems used here revealed that high adiposity or obesity can alter MT expression by decreasing progesterone response in the epithelial cells and increasing oxidative stress in the stroma.

Single-neuron whole genome sequencing identifies increased somatic mutation burden in Alzheimer's disease related genes.

Accumulation of somatic mutations in human neurons is associated with aging and neurodegeneration. To shed light on the somatic mutational burden in Alzheimer's disease (AD) neurons and get more insight into the role of somatic mutations in AD pathogenesis, we performed single-neuron whole genome sequencing to detect genome-wide somatic mutations (single nucleotide variants (SNVs) and Indels) in 96 single prefrontal cortex neurons from 8 AD patients and 8 elderly controls. We found that the mutational burden is ∼3000 somatic mutations per neuron genome in elderly subjects. AD patients have increased somatic mutation burden in AD-related annotation categories, including AD risk genes and differentially expressed genes in AD neurons. Mutational signature analysis showed somatic SNVs (sSNVs) primarily caused by aging and oxidative DNA damage processes but no significant difference was detected between AD and controls. Additionally, functional somatic mutations identified in AD patients showed significant enrichment in several AD-related pathways, including AD pathway, Notch-signaling pathway and Calcium-signaling pathway. These findings provide genetic insights into how somatic mutations may alter the function of single neurons and exert their potential roles in the pathogenesis of AD.

Analysis of endometrial carcinoma TCGA reveals differences in DNA methylation in tumors from Black and White women.

OBJECTIVE: Racial disparities exist in cancer patients both in incidence and death rates. In endometrial cancer, Black patients are reported to have higher incidence of aggressive endometrial cancer subtypes and higher death rates than White women. To date, diagnostic and prognostic biomarkers associated with race-specific methylation driven genes have yet to be identified. The objective of this study was to explore DNA methylation patterns in endometrial tumor samples from White and Black women. METHODS: Differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) were identified in White tumor samples compared to Black tumor samples using Endometrial Carcinoma (EC) methylation and clinical data from The Cancer Genome Atlas (TCGA). Survival analysis was performed using survival R package and results were visualized using Kaplan-Meier plots. To access the correlation between changes in methylation and gene expression, we downloaded raw RNA-sequencing by Expectation-Maximization (RSEM) counts data from The Cancer Genome Atlas (TCGA) using TCGABiolinks package (v2.18.0). RESULTS: Our analysis revealed 704 differentially methylated CpGs in tumors from Black and White women. These differentially methylated genes showed strong negative correlation with gene expression and statistically significant enrichment in regulatory regions such as DNase I hypersensitivity sites (DHSs) and transcription factor binding sites (TFBSs). Increased variability in methylation occurred in genes such as the insulin signaling pathway in Black tumor samples. CONCLUSION: By using two independent statistical method based on means (DMR, DMCs) and variances (DVCs) on the endometrial carcinoma TCGA data, we showed that endometrial tumors from Black women are hypomethylated and more hypervariable than tumors from White women. In-depth investigation of these methylation driven markers can aid in successful management of endometrial cancer disparities and improved overall survival in Black and White populations.

Myometrial oxidative stress drives MED12 mutations in leiomyoma.

BACKGROUND: More than 70% of leiomyomas (LM) harbor MED12 mutations, primarily in exon 2 at c.130-131(GG). The cause of MED12 mutations in myometrial cells remains largely unknown. We hypothesized that increased ROS promotes MED12 mutations in myometrial cells through the oxidation of guanine nucleotides followed by misrepair. METHODS: Genomic oxidative burden (8-OHdG) was evaluated in vitro and in vivo by immunohistochemistry. MED12 mutations were examined by Sanger sequencing and deep sequencing. Transcriptome examined by RNA-seq was performed in myometrium with and without LM, in primary myometrial cells treated with ROS. 8-OHdG mediated misrepair was analyzed by CRISPR/Cas9. RESULTS: Uteri with high LM burden had a significantly higher rate of MED12 mutations than uteri with low LM burden. Compelling data suggest that the uterus normally produces reactive oxidative species (ROS) in response to stress, and ROS levels in LM are elevated due to metabolic defects. We demonstrated that genomic oxidized guanine (8-OHdG) was found at a significantly higher level in the myometrium of uteri that had multiple LM compared to myometrium without LM. Transcriptome and pathway analyses detected ROS stress in myometrium with LM. Targeted replacement of guanine with 8-OHdG at MED12 c.130 by CRISPR/Cas9 significantly increased the misrepair of G>T. Exposure of primary myometrial cells to oxidative stress in vitro increased misrepair/mutations as detected by duplex sequencing. CONCLUSIONS: Together, our data identified a clear connection between increased myometrial oxidative stress and a high rate of MED12 mutations that may underlie the risk of LM development and severity in women of reproductive age.

An opportunity for primary prevention research in psychotic disorders.

An opportunity has opened for research into primary prevention of psychotic disorders, based on progress in endophenotypes, genetics, and genomics. Primary prevention requires reliable prediction of susceptibility before any symptoms are present. We studied a battery of measures where published data supports abnormalities of these measurements prior to appearance of initial psychosis symptoms. These neurobiological and behavioral measurements included cognition, eye movement tracking, Event Related Potentials, and polygenic risk scores. They generated an acceptably precise separation of healthy controls from outpatients with a psychotic disorder. METHODS: The Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) measured this battery in an ancestry-diverse series of consecutively recruited adult outpatients with a psychotic disorder and healthy controls. Participants include all genders, 16 to 50 years of age, 261 with psychotic disorders (Schizophrenia (SZ) 109, Bipolar with psychosis (BPP) 92, Schizoaffective disorder (SAD) 60), 110 healthy controls. Logistic Regression, and an extension of the Linear Mixed Model to include analysis of pairwise interactions between measures (Environmental kernel Relationship Matrices (ERM)) with multiple iterations, were performed to predict case-control status. Each regression analysis was validated with four-fold cross-validation. RESULTS AND CONCLUSIONS: Sensitivity, specificity, and Area Under the Curve of Receiver Operating Characteristic of 85%, 62%, and 86%, respectively, were obtained for both analytic methods. These prediction metrics demonstrate a promising diagnostic distinction based on premorbid risk variables. There were also statistically significant pairwise interactions between measures in the ERM model. The strong prediction metrics of both types of analytic model provide proof-of-principle for biologically-based laboratory tests as a first step toward primary prevention studies. Prospective studies of adolescents at elevated risk, vs. healthy adolescent controls, would be a next step toward development of primary prevention strategies.

Absence of coding somatic single nucleotide variants within well-known candidate genes in late-onset sporadic Alzheimer's Disease based on the analysis of multi-omics data.

Somatic mutations arise randomly or are induced by environmental factors, which may increase the risk of Alzheimer's disease (AD). Identifying somatic mutations in sporadic AD (SAD) may provide new insight of the disease. To evaluate the potential contribution of somatic single nucleotide variations (SNVs), particularly that of well-known AD-candidate genes, we investigated sequencing data sets from four platforms: whole-genome sequencing (WGS), deep whole-exome sequencing (WES) on paired brain and liver samples, RNA sequencing (RNA-seq), and single-cell whole-genome sequencing (scWGS) of brain samples from 16 AD patients and 16 non-AD individuals. We found that the average number, mean variant allele fractions (VAFs) and mutational signatures of somatic SNVs have similar distributions between AD brains and non-AD brains. We did not identify any somatic SNVs within coding regions of the APP, PSEN1, PSEN2, nor in APOE. This study shows that somatic SNVs within the coding region of AD-candidate genes are unlikely to be a common causal factor for SAD.

Biotyping in psychosis: using multiple computational approaches with one data set.

Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.

GWAS significance thresholds for deep phenotyping studies can depend upon minor allele frequencies and sample size.

An important issue affecting genome-wide association studies with deep phenotyping (multiple correlated phenotypes) is determining the suitable family-wise significance threshold. Straightforward family-wise correction (Bonferroni) of p < 0.05 for 4.3 million genotypes and 335 phenotypes would give a threshold of p < 3.46E-11. This would be too conservative because it assumes all tests are independent. The effective number of tests, both phenotypic and genotypic, must be adjusted for the correlations between them. Spectral decomposition of the phenotype matrix and LD-based correction of the number of tested SNPs are currently used to determine an effective number of tests. In this paper, we compare these calculated estimates with permutation-determined family-wise significance thresholds. Permutations are performed by shuffling individual IDs of the genotype vector for this dataset, to preserve correlation of phenotypes. Our results demonstrate that the permutation threshold is influenced by minor allele frequency (MAF) of the SNPs, and by the number of individuals tested. For the more common SNPs (MAF > 0.1), the permutation family-wise threshold was in close agreement with spectral decomposition methods. However, for less common SNPs (0.05 < MAF ≤ 0.1), the permutation threshold calculated over all SNPs was off by orders of magnitude. This applies to the number of individuals studied (here 777) but not to very much larger numbers. Based on these findings, we propose that the threshold to find a particular level of family-wise significance may need to be established using separate permutations of the actual data for several MAF bins.

Alteration of the gut microbiome in first-episode drug-naïve and chronic medicated schizophrenia correlate with regional brain volumes.

The human gut microbiome plays an important role in the basic neurodevelopmental processes of the central nervous system and has been implicated in several neuropsychiatric disorders. However, the connection between the gut microbiome and the underlying pathogenesis of schizophrenia (SCZ) is poorly defined. Here we analyzed the faecal samples from 40 first-episode drug-naïve SCZ (FSCZ) patients, 85 chronically antipsychotic-treated SCZ (TSCZ) patients and 69 healthy controls (HCs) using 16S rRNA gene sequence to determine whether the alterations of the gut microbiome were associated with SCZ or antipsychotic treatment. In addition, we acquired the T1-weighted brain imaging data by using structural magnetic resonance imaging to test whether microbial composition correlated with structural brain signatures. Our analyses revealed low microbiome alpha-diversity indexes in TSCZ patients but not in FSCZ patients as compared to HCs. Importantly, both FSCZ and TSCZ patients had distinct changes in gut microbial composition at certain taxa including Christensenellaceae, Enterobacteriaceae, Pasteurellaceae, Turicibacteraceae at the family level and Escherichia at genus level as compared to HCs. We also found significant disturbances of gut microbial composition in TSCZ versus FSCZ patients (eg. Enterococcaceae and Lactobacillaceae). Most interestingly, our exploratory analyses found specific SCZ-associated microbiota to be correlated with the right middle frontal gyrus (rMFG) volume which was aberrant in SCZ patients. Our findings extend prior work and suggest a possible link between the gut microbiome and brain structure which may be implicated in the pathology of SCZ.