Genome-wide copy-number variation study of 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.

Epigenome-Wide DNA Methylation in Unipolar Depression: Predictive Biomarker of Antidepressant Treatment Response?

BACKGROUND

Despite the well-documented efficacy of antidepressant agents for the treatment of major depressive disorder (MDD), initial treatment nonresponse rates are high. Recent years have seen an increase in research into predictive biomarkers toward improving diagnosis and individualized treatment. Among those, epigenetic mechanisms such as DNA methylation constitute promising candidate markers in predicting antidepressant treatment response in MDD. The present study sought to address epigenome-wide DNA methylation as a predictor of antidepressant treatment response in the largest sample to date of patients with MDD.

METHODS

Epigenome-wide DNA methylation was analyzed using the Infinium MethylationEPIC BeadChip in peripheral blood of n = 230 Caucasian patients with MDD receiving 6-week antidepressant treatment in a naturalistic in-patient setting as well as in a subsample of n = 107 patients primarily receiving continuous treatment with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors. Treatment response was assessed by means of the Hamilton Depression Scale.

RESULTS

No genome-wide significant hits were observed. Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment. In patients treated with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors, differential DNA methylation at 11 CpGs, for example, mapping to the TIMP2, VDAC1, or SORL1 genes, was suggestively associated with treatment response.

CONCLUSIONS

The present results provide preliminary evidence for altered DNA methylation patterns to be associated with antidepressant treatment response in MDD. Provided significant replication in independent and larger samples, the present findings might in the future aid in clinical decision-making toward more individualized and thus more efficacious treatments of MDD.

Single Cell Sequencing Technology and Its Application in Alzheimer's Disease

Alzheimer's disease (AD) involves degeneration of cells in the brain. Due to insidious onset and slow progression, AD is often not diagnosed until it gets progressed to a more severe stage. The diagnosis and treatment of AD has been a challenge. In recent years, high-throughput sequencing technologies have exhibited advantages in exploring the pathogenesis of diseases. However, the types of cells of the central nervous system are complex and traditional bulk sequencing cannot reflect their heterogeneity. Single-cell sequencing technology enables study at the individual cell level and has an irreplaceable advantage in the study of complex diseases. In recent years, this field has expanded rapidly and several types of single-cell sequencing technologies have emerged, including transcriptomics, epigenomics, genomics and proteomics. This review article provides an overview of these single-cell sequencing technologies and their application in AD.

The role of structural variations in Alzheimer's disease and other neurodegenerative diseases

Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.

Neuropsychiatric Symptoms of Alzheimer's Disease: An Anatomic-Genetic Framework for Treatment Development

BACKGROUND

Despite the burden on patients and caregivers, there are no approved therapies for the neuropsychiatric symptoms of Alzheimer's disease (NPS-AD). This is likely due to an incomplete understanding of the underlying mechanisms.

OBJECTIVE

To review the neurobiological mechanisms of NPS-AD, including depression, psychosis, and agitation.

METHODS

Understanding that genetic encoding gives rise to the function of neural circuits specific to behavior, we review the genetics and neuroimaging literature to better understand the biological underpinnings of depression, psychosis, and agitation.

RESULTS

We found that mechanisms involving monoaminergic biosynthesis and function are likely key elements of NPS-AD and while current treatment approaches are in line with this, the lack of effectiveness may be due to contributions from additional mechanisms including neurodegenerative, vascular, inflammatory, and immunologic pathways.

CONCLUSION

Within an anatomic-genetic framework, development of novel effective biological targets may engage targets within these pathways but will require a better understanding of the heterogeneity in NPS-AD.

DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN-/SOX10- (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in 'bulk' cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.

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.

Copy Number Variation Identification on 3,800 Alzheimer's Disease Whole Genome Sequencing Data from the Alzheimer's Disease Sequencing Project

Alzheimer's Disease (AD) is a progressive neurologic disease and the most common form of dementia. While the causes of AD are not completely understood, genetics plays a key role in the etiology of AD, and thus finding genetic factors holds the potential to uncover novel AD mechanisms. For this study, we focus on copy number variation (CNV) detection and burden analysis. Leveraging whole-genome sequence (WGS) data released by Alzheimer's Disease Sequencing Project (ADSP), we developed a scalable bioinformatics pipeline to identify CNVs. This pipeline was applied to 1,737 AD cases and 2,063 cognitively normal controls. As a result, we observed 237,306 and 42,767 deletions and duplications, respectively, with an average of 2,255 deletions and 1,820 duplications per subject. The burden tests show that Non-Hispanic-White cases on average have 16 more duplications than controls do (p-value 2e-6), and Hispanic cases have larger deletions than controls do (p-value 6.8e-5).

A Case of Early-Onset Alzheimer's Disease Mimicking Schizophrenia in a Patient with Presenilin 1 Mutation (S170P)

Atypical psychological symptoms frequently occur in early-onset Alzheimer's disease (EOAD), which makes it difficult to differentiate it from other psychiatric disorders. We report the case of a 28-year-old woman with EOAD, carrying a presenilin-1 mutation (S170P), who was initially misdiagnosed with schizophrenia because of prominent psychiatric symptoms in the first 1-2 years of the disease. Amyloid-β positron emission tomography (PET) showed remarkably high tracer uptake in the striatum and thalamus. Tau PET showed widespread cortical uptake and relatively low uptake in the subcortical and medial temporal regions. Our case advocates for considering EOAD diagnosis for young patients with psychiatric and atypical cognitive symptoms.

A Comprehensive Analysis of Unique and Recurrent Copy Number Variations in Alzheimer's Disease and its Related Disorders

BACKGROUND

Copy number variations (CNVs) play an important role in the genetic etiology of various neurological disorders, including Alzheimer's disease (AD). Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) were shown to have share mechanisms and signaling pathways with AD.

OBJECTIVE

We aimed to assess CNVs regions that may harbor genes contributing to AD, T2DM, and MDD in 67 Saudi familial and sporadic AD patients, with no alterations in the known genes of AD and genotyped previously for APOE.

METHODS

DNA was analyzed using the CytoScan-HD array. Two layers of filtering criteria were applied. All the identified CNVs were checked in the Database of Genomic Variants (DGV).

RESULTS

A total of 1086 CNVs (565 gains and 521 losses) were identified in our study. We found 73 CNVs harboring genes that may be associated with AD, T2DM or MDD. Nineteen CNVs were novel. Most importantly, 42 CNVs were unique in our studied cohort existing only in one patient. Two large gains on chromosomes 1 and 13 harbored genes implicated in the studied disorders. We identified CNVs in genes that encode proteins involved in the metabolism of amyloid-β peptide (AGRN, APBA2, CR1, CR2, IGF2R, KIAA0125, MBP, RER1, RTN4R, VDR and WISPI) or Tau proteins (CACNAIC, CELF2, DUSP22, HTRA1 and SLC2A14).

CONCLUSION

The present work provided information on the presence of CNVs related to AD, T2DM, and MDD in Saudi Alzheimer's patients.

Psychosis in Alzheimer's Disease

PURPOSE OF REVIEW

To review the incidence, treatment and genetics of psychosis in people with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

RECENT FINDINGS

Psychosis in Alzheimer's disease (AD) has an incidence of ~ 10% per year. There is limited evidence regarding psychological interventions. Pharmacological management has focused on atypical antipsychotics, balancing modest benefits with evidence of long-term harms. The 5HT2A inverse agonist pimavanserin appears to confer benefit in PD psychosis with initial evidence of benefit in AD. Cholinesterase inhibitors give modest benefits in DLB psychosis. The utility of muscarinic agonists, lithium, glutamatergic and noradrenergic modulators needs further study. Recent work has confirmed the importance of psychosis in MCI as well as AD. The lack of evidence regarding psychological therapies is an urgent knowledge gap, but there is encouraging evidence for emerging pharmacological treatments. Genetics will provide an opportunity for precision medicine and new treatment targets.

Genetic architecture of common non-Alzheimer's disease dementias

Frontotemporal dementia (FTD), dementia with Lewy bodies (DLB) and vascular dementia (VaD) are the most common forms of dementia after Alzheimer's disease (AD). The heterogeneity of these disorders and/or the clinical overlap with other diseases hinder the study of their genetic components. Even though Mendelian dementias are rare, the study of these forms of disease can have a significant impact in the lives of patients and families and have successfully brought to the fore many of the genes currently known to be involved in FTD and VaD, starting to give us a glimpse of the molecular mechanisms underlying these phenotypes. More recently, genome-wide association studies have also pointed to disease risk-associated loci. This has been particularly important for DLB where familial forms of disease are very rarely described. In this review we systematically describe the Mendelian and risk genes involved in these non-AD dementias in an effort to contribute to a better understanding of their genetic architecture, find differences and commonalities between different dementia phenotypes, and uncover areas that would benefit from more intense research endeavors.

Psychosis-associated DNA methylomic variation in Alzheimer's disease cortex

Psychotic symptoms are a common and debilitating feature of Alzheimer's disease (AD) and are associated with a more rapid course of decline. Current evidence from postmortem and neuroimaging studies implicates frontal, temporal, and parietal lobes, with reported disruptions in monoaminergic pathways. However, the molecular mechanisms underlying this remain unclear. In the present study, we investigated methylomic variation associated with AD psychosis in 3 key brain regions implicated in the etiology of psychosis (prefrontal cortex, entorhinal cortex, and superior temporal gyrus) in postmortem brain samples from 29 AD donors with psychosis and 18 matched AD donors without psychosis. We identified psychosis-associated methylomic changes in a number of loci, with these genes being enriched in known schizophrenia-associated genetic and epigenetic variants. One of these known loci resided in the AS3MT gene-previously implicated in schizophrenia in a large GWAS meta-analysis. We used bisulfite-pyrosequencing to confirm hypomethylation across 4 neighboring CpG sites in the ASM3T gene. Finally, our regional analysis nominated multiple CpG sites in TBX15 and WT1, which are genes that have been previously implicated in AD. Thus one potential implication from our study is whether psychosis-associated variation drives reported associations in AD case-control studies.

A Genetic Study of Psychosis in Huntington's Disease: Evidence for the Involvement of Glutamate Signaling Pathways

BACKGROUND

Psychotic symptoms of delusions and hallucinations occur in about 5% of persons with Huntington's disease (HD). The mechanisms underlying these occurrences are unknown, but the same symptoms also occur in schizophrenia, and thus genetic risk factors for schizophrenia may be relevant to the development of psychosis in HD.

OBJECTIVE

To investigate the possible role of genes associated with schizophrenia in the occurrence of psychotic symptoms in HD.

METHODS

DNA from subjects with HD and psychosis (HD+P; n = 47), subjects with HD and no psychosis (HD-P; n = 126), and controls (CTLs; n = 207) was genotyped using the Infinium PsychArray-24 v1.1 BeadChip. The allele frequencies of single-nucleotide polymorphisms (SNPs) that were previously associated with schizophrenia and related psychiatric disorders were compared between these groups.

RESULTS

Of the 30 candidate genes tested, 10 showed an association with psychosis in HD. The majority of these genes, including CTNNA2, DRD2, ERBB4, GRID2, GRIK4, GRM1, NRG1, PCNT, RELN, and SLC1A2, demonstrate network interactions related to glutamate signaling.

CONCLUSIONS

This study suggests genetic associations between several previously identified candidate genes for schizophrenia and the occurrence of psychotic symptoms in HD. These data support the potential role of genes related to glutamate signaling in HD psychosis.

GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10-8). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10-6. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders.

Genetic Variations and Precision Medicine

The time and costs associated with the sequencing of a human genome have decreased significantly in recent years. Many people have chosen to have their genomes sequenced to receive genomics-based personalized healthcare services. To reach the goal of genomics-based precision medicine, health information management (HIM) professionals need to manage and analyze patients' genomic data. Two important pieces of information from the genome sequence are the risk of genetic diseases and the specific medication or pharmacogenomic results for the individual patient, both of which are linked to a patient's genetic variations. In this review article, we introduce genetic variations, including their data types, relevant databases, and some currently available analysis methods and systems. HIM professionals can choose to use these databases, methods, and systems in the management and analysis of patients' genomic data.

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.

Copy Number Variations in Adult-onset Neuropsychiatric Diseases

Adult-onset neuropsychiatric diseases are one of the most challenging areas of medicine. While symptomatic treatments are available, for most of these diseases the exact pathomechanism is not known, thus, disease-modifying therapies are difficult to conceptualize and find. The two most common and best studied neuropsychiatric diseases affecting higher cortical functions in humans are schizophrenia and Alzheimer's disease; both diseases have high heritability, however, the genetic architecture is not fully elucidated. Robust Single Nucleotide Variant (SNV) studies have identified several loci with modest effect sizes. While Copy Number Variants (CNV) make an important contribution to genetic variation, CNV GWAS suffer from dependence on mainly SNP arrays with underperforming genotyping accuracy. We evaluated dynamic range of the assays for three types of CNV loci, including biallelic deletion, high copy gain, and fusion gene, to assess the depth of exploration of the contribution of CNVs to disease susceptibility. Despite the suboptimal genotyping, novel mechanisms are emerging and further large-scale studies with genotyping assays optimized for CNV detection are needed. Furthermore, the CHRFAM7A human-specific fusion gene association warrants large scale locus specific association studies in AD, schizophrenia, bipolar disorder and ADHD.

Revealing Alzheimer's disease genes spectrum in the whole-genome by machine learning

Background

Alzheimer’s disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes in the development of disease. For this purpose, expanding the AD-associated gene set is necessary. In past research, the prediction methods for AD related genes has been limited in their exploration of the target genome regions. We here present a genome-wide method for AD candidate genes predictions.

Methods

We present a machine learning approach (SVM), based upon integrating gene expression data with human brain-specific gene network data, to discover the full spectrum of AD genes across the whole genome.

Results

We classified AD candidate genes with an accuracy and the area under the receiver operating characteristic (ROC) curve of 84.56% and 94%. Our approach provides a supplement for the spectrum of AD-associated genes extracted from more than 20,000 genes in a genome wide scale.

Conclusions

In this study, we have elucidated the whole-genome spectrum of AD, using a machine learning approach. Through this method, we expect for the candidate gene catalogue to provide a more comprehensive annotation of AD for researchers.

Electronic supplementary material

The online version of this article (10.1186/s12883-017-1010-3) contains supplementary material, which is available to authorized users.

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.

Network biology concepts in complex disease comorbidities

The co-occurrence of diseases can inform the underlying network biology of shared and multifunctional genes and pathways. In addition, comorbidities help to elucidate the effects of external exposures, such as diet, lifestyle and patient care. With worldwide health transaction data now often being collected electronically, disease co-occurrences are starting to be quantitatively characterized. Linking network dynamics to the real-life, non-ideal patient in whom diseases co-occur and interact provides a valuable basis for generating hypotheses on molecular disease mechanisms, and provides knowledge that can facilitate drug repurposing and the development of targeted therapeutic strategies.

Genetic variants associated with susceptibility to psychosis in late-onset Alzheimer's disease families

Psychotic symptoms are frequent in late-onset Alzheimer's disease (LOAD) patients. Although the risk for psychosis in LOAD is genetically mediated, no genes have been identified. To identify loci potentially containing genetic variants associated with risk of psychosis in LOAD, a total of 263 families from the National Institute of Aging-LOAD cohort were classified into psychotic (LOAD+P, n = 215) and nonpsychotic (LOAD-P, n = 48) families based on the presence/absence of psychosis during the course of LOAD. The LOAD+P families yielded strong evidence of linkage on chromosome 19q13 (two-point [2-pt] ​logarithm of odds [LOD] = 3.8, rs2285513 and multipoint LOD = 2.7, rs541169). Joint linkage and association in 19q13 region detected strong association with rs2945988 (p = 8.7 × 10(-7)). Linkage results for the LOAD-P families yielded nonsignificant 19q13 LOD scores. Several 19q13 single-nucleotide polymorphisms generalized the association of LOAD+P in a Caribbean Hispanic (CH) cohort, and the strongest signal was rs10410711 (pmeta = 5.1 × 10(-5)). A variant located 24 kb upstream of rs10410711 and rs10421862 was strongly associated with LOAD+P (pmeta = 1.0 × 10(-5)) in a meta-analysis of the CH cohort and an additional non-Hispanic Caucasian dataset. Identified variants rs2945988 and rs10421862 affect brain gene expression levels. Our results suggest that genetic variants in genes on 19q13, some of which are involved in brain development and neurodegeneration, may influence the susceptibility to psychosis in LOAD patients.