A rare duplication on chromosome 16p11.2 is identified in patients with psychosis in Alzheimer's disease

A brain DNA co-methylation network analysis of psychosis in Alzheimer's disease

INTRODUCTION

The presence of psychosis in Alzheimer's disease (AD) is suggested to be associated with distinct molecular and neuropathological profiles in the brain.

METHODS

We assessed brain DNA methylation in AD donors with psychosis (AD+P) and without psychosis (AD-P) using the EPIC array. Weighted gene correlation network analysis identified modules of co-methylated genes in a discovery cohort (PITT-ADRC: N = 113 AD+P, N = 40 AD-P), with validation in an independent cohort (BDR: N = 79 AD+P, N = 117 AD-P), with Gene Ontology and cell-type enrichment analysis. Genetic data were integrated to identify methylation quantitative trait loci (mQTLs), which were co-localized with GWAS for related traits.

RESULTS

We replicated one AD+P associated module, which was enriched for synaptic pathways and in excitatory and inhibitory neurons. mQTLs in this module co-localized with variants associated with schizophrenia and educational attainment.

DISCUSSION

This represents the largest epigenetic study of AD+P to date, identifying pleiotropic relationships between AD+P and related traits.

HIGHLIGHTS

DNA methylation was assessed in the prefrontal cortex in subjects with AD+P and AD-P. WGCNA identified six modules of co-methylated loci associated with AD+P in a discovery cohort. One of the modules was replicated in an independent cohort. This module was enriched for synaptic genes and in excitatory and inhibitory neurons. mQTLs mapping to genes in the module co-localized with GWAS loci for schizophrenia and educational attainment.

The pleiotropic spectrum of proximal 16p11.2 CNVs

Recurrent genomic rearrangements at 16p11.2 BP4-5 represent one of the most common causes of genomic disorders. Originally associated with increased risk for autism spectrum disorder, schizophrenia, and intellectual disability, as well as adiposity and head circumference, these CNVs have since been associated with a plethora of phenotypic alterations, albeit with high variability in expressivity and incomplete penetrance. Here, we comprehensively review the pleiotropy associated with 16p11.2 BP4-5 rearrangements to shine light on its full phenotypic spectrum. Illustrating this phenotypic heterogeneity, we expose many parallels between findings gathered from clinical versus population-based cohorts, which often point to the same physiological systems, and emphasize the role of the CNV beyond neuropsychiatric and anthropometric traits. Revealing the complex and variable clinical manifestations of this CNV is crucial for accurate diagnosis and personalized treatment strategies for carrier individuals. Furthermore, we discuss areas of research that will be key to identifying factors contributing to phenotypic heterogeneity and gaining mechanistic insights into the molecular pathways underlying observed associations, while demonstrating how diversity in affected individuals, cohorts, experimental models, and analytical approaches can catalyze discoveries.

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

The neural signatures of psychoses in Alzheimer's disease: a neuroimaging genetics approach

Psychoses in Alzheimer's disease (AD) are associated with worse prognosis. Genetic vulnerability for schizophrenia (SCZ) may drive AD-related psychoses, yet its impact on brain constituents is still unknown. This study aimed to investigate the association between polygenic risk scores (PRSs) for SCZ and psychotic experiences (PE) and grey matter (GM) volume in patients with AD with (AD-PS) and without (AD-NP) psychosis. Clinical, genetic and T1-weighted MRI data for 800 participants were extracted from the ADNI database: 203 healthy controls, 121 AD-PS and 476 AD-NP. PRSs were calculated using a Bayesian approach and analysed at ten p-value thresholds. Standard voxel-based morphometry was used to process MRI data. Logistic regression models including both PRSs for SCZ and PE, and an AD-PRS were used to predict psychosis in AD. Associations between PRSs and GM volume were investigated in the whole sample and the three groups independently. Only the AD-PRS predicted psychosis in AD. Inconsistent associations between the SCZ-PRS and PE-PRS and GM volumes were found across groups. The SCZ-PRS was negatively associated with medio-temporal/subcortical volumes and positively with medial/orbitofrontal volumes in the AD-PS group. Only medio-temporal areas were more atrophic in the AD-PS group, while there was no significant correlation between psychosis severity and GM volume. Although not associated with psychoses, the SCZ-PRS was correlated with smaller medio-temporal and larger orbitofrontal volumes in AD-PS. Similar alterations have also been observed in SCZ patients. This finding suggest a possible disconnection between these regions associated with psychoses in more advanced AD.

Prediction of Synaptically Localized RNAs in Human Neurons Using Developmental Brain Gene Expression Data

In the nervous system, synapses are special and pervasive structures between axonal and dendritic terminals, which facilitate electrical and chemical communications among neurons. Extensive studies have been conducted in mice and rats to explore the RNA pool at synapses and investigate RNA transport, local protein synthesis, and synaptic plasticity. However, owing to the experimental difficulties of studying human synaptic transcriptomes, the full pool of human synaptic RNAs remains largely unclear. We developed a new machine learning method, called PredSynRNA, to predict the synaptic localization of human RNAs. Training instances of dendritically localized RNAs were compiled from previous rodent studies, overcoming the shortage of empirical instances of human synaptic RNAs. Using RNA sequence and gene expression data as features, various models with different learning algorithms were constructed and evaluated. Strikingly, the models using the developmental brain gene expression features achieved superior performance for predicting synaptically localized RNAs. We examined the relevant expression features learned by PredSynRNA and used an independent test dataset to further validate the model performance. PredSynRNA models were then applied to the prediction and prioritization of candidate RNAs localized to human synapses, providing valuable targets for experimental investigations into neuronal mechanisms and brain disorders.

Alzheimer's Disease-Related Psychosis: An Overview of Clinical Manifestations, Pathogenesis, and Current Treatment

Behavioral and psychotic manifestations, including aggression, delusions, and hallucinations, are frequent comorbidities in patients with debilitating nervous illnesses such as Alzheimer's disease (AD), Amyotrophic Lateral Sclerosis, Multiple Sclerosis, and Parkinson's disease. AD-related psychosis may be linked to a poor disease prognosis, highlighting that early detection and management are mandatory. The manifestations are variable and may be very heterogeneous, imposing a real diagnostic issue. Some assessment tools such as BEHAVE-AD, CERAD-BRSD, and the Psycho-Sensory Hallucinations Scale have been designed to facilitate the diagnosis. The mechanisms behind neurodegeneration-related psychosis are complex and are not fully understood, imposing a burden on researchers to find appropriate management modalities. Familial history and some genetic disturbances may have a determinant role in these delusions and hallucinations in cases with AD. The loss of neuronal cells, atrophy in some regions of the central nervous, and synaptic dysfunction may also contribute to these comorbidities. Furthermore, inflammatory disturbances triggered by pro-inflammatory agents such as interleukins and tumor necrosis factors are stratified among the potential risk factors of the onset of numerous psychotic symptoms in Alzheimer's patients. Little is known about the possible management tools; therefore, it is urgent to conduct well-designed trials to investigate pharmacological and non-pharmacological interventions that can improve the care process of these patients. This review summarizes the current findings regarding the AD-related psychosis symptoms, pathological features, assessment, and management.

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through  GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.

Computational prediction of CRISPR-impaired non-coding regulatory regions

Genome-wide CRISPR screens are becoming more widespread and allow the simultaneous interrogation of thousands of genomic regions. Although recent progress has been made in the analysis of CRISPR screens, it is still an open problem how to interpret CRISPR mutations in non-coding regions of the genome. Most of the tools concentrate on the interpretation of mutations introduced in gene coding regions. We introduce a computational pipeline that uses epigenomic information about regulatory elements for the interpretation of CRISPR mutations in non-coding regions. We illustrate our analysis protocol on the analysis of a genome-wide CRISPR screen in hTERT-RPE1 cells and reveal novel regulatory elements that mediate chemoresistance against doxorubicin in these cells. We infer links to established and to novel chemoresistance genes. Our analysis protocol is general and can be applied on any cell type and with different CRISPR enzymes.

Whole Blood Transcriptome Characterization of 3xTg-AD Mouse and Its Modulation by Transcranial Direct Current Stimulation (tDCS)

The 3xTg-AD mouse is a widely used model in the study of Alzheimer’s Disease (AD). It has been extensively characterized from both the anatomical and behavioral point of view, but poorly studied at the transcriptomic level. For the first time, we characterize the whole blood transcriptome of the 3xTg-AD mouse at three and six months of age and evaluate how its gene expression is modulated by transcranial direct current stimulation (tDCS). RNA-seq analysis revealed 183 differentially expressed genes (DEGs) that represent a direct signature of the genetic background of the mouse. Moreover, in the 6-month-old 3xTg-AD mice, we observed a high number of DEGs that could represent good peripheral biomarkers of AD symptomatology onset. Finally, tDCS was associated with gene expression changes in the 3xTg-AD, but not in the control mice. In conclusion, this study provides an in-depth molecular characterization of the 3xTg-AD mouse and suggests that blood gene expression can be used to identify new biomarkers of AD progression and treatment effects.

Examining the association between genetic liability for schizophrenia and psychotic symptoms in Alzheimer's disease

Psychosis (delusions or hallucinations) in Alzheimer's disease (AD + P) occurs in up to 50% of individuals and is associated with significantly worse clinical outcomes. Atypical antipsychotics, first developed for schizophrenia, are commonly used in AD + P, suggesting shared mechanisms. Despite this implication, little empirical research has been conducted to examine whether there are mechanistic similarities between AD + P and schizophrenia. In this study, we tested whether polygenic risk score (PRS) for schizophrenia was associated with AD + P. Schizophrenia PRS was calculated using Psychiatric Genomics Consortium data at ten GWAS p value thresholds (PT) in 3111 AD cases from 11 cohort studies characterized for psychosis using validated, standardized tools. Association between PRS and AD + P status was tested by logistic regression in each cohort individually and the results meta-analyzed. The schizophrenia PRS was associated with AD + P at an optimum PT of 0.01. The strongest association was for delusions where a one standard deviation increase in PRS was associated with a 1.18-fold increased risk (95% CI: 1.06-1.3; p = 0.001). These new findings point towards psychosis in AD-and particularly delusions-sharing some genetic liability with schizophrenia and support a transdiagnostic view of psychotic symptoms across the lifespan.

A comprehensive screening of copy number variability in dementia with Lewy bodies

The role of genetic variability in dementia with Lewy bodies (DLB) is now indisputable; however, data regarding copy number variation (CNV) in this disease has been lacking. Here, we used whole-genome genotyping of 1454 DLB cases and 1525 controls to assess copy number variability. We used 2 algorithms to confidently detect CNVs, performed a case-control association analysis, screened for candidate CNVs previously associated with DLB-related diseases, and performed a candidate gene approach to fully explore the data. We identified 5 CNV regions with a significant genome-wide association to DLB; 2 of these were only present in cases and absent from publicly available databases: one of the regions overlapped LAPTM4B, a known lysosomal protein, whereas the other overlapped the NME1 locus and SPAG9. We also identified DLB cases presenting rare CNVs in genes previously associated with DLB or related neurodegenerative diseases, such as SNCA, APP, and MAPT. To our knowledge, this is the first study reporting genome-wide CNVs in a large DLB cohort. These results provide preliminary evidence for the contribution of CNVs in DLB risk.

Modulating Neuroinflammation to Treat Neuropsychiatric Disorders

Neuroinflammation is recognised as one of the potential mechanisms mediating the onset of a broad range of psychiatric disorders and may contribute to nonresponsiveness to current therapies. Both preclinical and clinical studies have indicated that aberrant inflammatory responses can result in altered behavioral responses and cognitive deficits. In this review, we discuss the role of inflammation in the pathogenesis of neuropsychiatric disorders and ask the question if certain genetic copy-number variants (CNVs) associated with psychiatric disorders might play a role in modulating inflammation. Furthermore, we detail some of the potential treatment strategies for psychiatric disorders that may operate by altering inflammatory responses.

Genetics of psychosis of Alzheimer disease

Psychotic symptoms, comprised of delusions and hallucinations, occur in about half of individuals with Alzheimer disease (AD with psychosis, AD+P). These individuals have greater agitation, aggression, depression, functional impairment, and mortality than individuals without psychosis (AD-P). Although the exact etiopathogenesis of AD+P is unclear, the rapidly developing field of genomics continues to expand our understanding of this disease. Several independent studies have demonstrated familial aggregation and heritability of AD+P. Linkage studies have been suggestive of loci on several chromosomes associated with AD+P. Association studies examining apolipoprotein E gene, the best established genetic risk factor for late-onset AD, did not find any significant association of this gene with AD+P. Other candidate gene studies focusing on monoamine neurotransmitter systems have yielded equivocal results. A genome-wide association study and studies examining copy number variations recently have detected suggestive associations, but have been underpowered. Approaches to increase sizes of AD+P samples for genome wide association studies are discussed. © 2016 Wiley Periodicals, Inc.

Reversal of dendritic phenotypes in 16p11.2 microduplication mouse model neurons by pharmacological targeting of a network hub

The architecture of dendritic arbors contributes to neuronal connectivity in the brain. Conversely, abnormalities in dendrites have been reported in multiple mental disorders and are thought to contribute to pathogenesis. Rare copy number variations (CNVs) are genetic alterations that are associated with a wide range of mental disorders and are highly penetrant. The 16p11.2 microduplication is one of the CNVs most strongly associated with schizophrenia and autism, spanning multiple genes possibly involved in synaptic neurotransmission. However, disease-relevant cellular phenotypes of 16p11.2 microduplication and the driver gene(s) remain to be identified. We found increased dendritic arborization in isolated cortical pyramidal neurons from a mouse model of 16p11.2 duplication (dp/+). Network analysis identified MAPK3, which encodes ERK1 MAP kinase, as the most topologically important hub in protein-protein interaction networks within the 16p11.2 region and broader gene networks of schizophrenia-associated CNVs. Pharmacological targeting of ERK reversed dendritic alterations associated with dp/+ neurons, outlining a strategy for the analysis and reversal of cellular phenotypes in CNV-related psychiatric disorders.

MOLECULAR GENETIC STUDIES OF COMORBIDITY

This review focuses at the problem of the genetic basis of comorbidity. We discuss the concepts and terms relating to combinations of diseases. The guidelines of the study of comorbidity using modern high throughput methods and approaches of genetics, molecular biology and bioinformatics are designated. In this review we present results of studies showing genetic specificity for the combined phenotypes dif-ferent from the isolated disease, we considergene-gene and gene-environment interactions in comorbidity. We also discuss the role of single nucleotide polymorphisms and structural genome variations in the development of comorbidity. Own results of researching shared genes of inversely comorbid diseases like as bronchial asthma and tuberculosis are presented.