Alterations in gut microbiota and host transcriptome of patients with coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is a widespread heart condition caused by atherosclerosis and influences millions of people worldwide. Early detection of CAD is challenging due to the lack of specific biomarkers. The gut microbiota and host-microbiota interactions have been well documented to affect human health. However, investigation that reveals the role of gut microbes in CAD is still limited. This study aims to uncover the synergistic effects of host genes and gut microbes associated with CAD through integrative genomic analyses.

RESULTS

Herein, we collected 52 fecal and 50 blood samples from CAD patients and matched controls, and performed amplicon and transcriptomic sequencing on these samples, respectively. By comparing CAD patients with health controls, we found that dysregulated gut microbes were significantly associated with CAD. By leveraging the Random Forest method, we found that combining 20 bacteria and 30 gene biomarkers could distinguish CAD patients from health controls with a high performance (AUC = 0.92). We observed that there existed prominent associations of gut microbes with several clinical indices relevant to heart functions. Integration analysis revealed that CAD-relevant gut microbe genus Fusicatenibacter was associated with expression of CAD-risk genes, such as GBP2, MLKL, and CPR65, which is in line with previous evidence (Tang et al., Nat Rev Cardiol 16:137-154, 2019; Kummen et al., J Am Coll Cardiol 71:1184-1186, 2018). In addition, the upregulation of immune-related pathways in CAD patients were identified to be primarily associated with higher abundance of genus Blautia, Eubacterium, Fusicatenibacter, and Monoglobus.

CONCLUSIONS

Our results highlight that dysregulated gut microbes contribute risk to CAD by interacting with host genes. These identified microbes and interacted risk genes may have high potentials as biomarkers for CAD.

Novel functional atrial fibrillation risk genes and pathways identified from coexpression analyses in human left atria

BACKGROUND

Genomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging.

OBJECTIVE

The purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes.

METHODS

Cis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module.

RESULTS

One hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.

CONCLUSION

Candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes.

Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

Identification of MKNK1 and TOP3A as ovarian endometriosis risk-associated genes using integrative genomic analyses and functional experiments

The risk of endometriosis (EM), which is a common complex gynaecological disease, is related to genetic predisposition. However, it is unclear how genetic variants confer the risk of EM. Here, via Sherlock integrative analysis, we combined large-scale genome-wide association studies (GWAS) summary statistics on EM (N = 245,494) with a blood-based eQTL dataset (N = 1490) to identify EM risk-related genes. For validation, we leveraged two independent eQTL datasets (N = 769) for integration with the GWAS data. Thus, we prioritised 14 genes, including GIMAP4, TOP3A, and NMNAT3, which showed significant association with susceptibility to EM. We also utilised two independent methods, Multi-marker Analysis of GenoMic Annotation and S-PrediXcan, to further validate the EM risk-associated genes. Moreover, protein-protein interaction network analysis showed the 14 genes were functionally connected. Functional enrichment analyses further demonstrated that these genes were significantly enriched in metabolic and immune-related pathways. Differential gene expression analysis showed that in peripheral blood samples from patients with ovarian EM, TOP3A, MKNK1, SIPA1L2, and NUCB1 were significantly upregulated, while HOXB2, GIMAP5, and MGMT were significantly downregulated compared with their expression levels in samples from the controls. Immunohistochemistry further confirmed the increased expression levels of MKNK1 and TOP3A in the ectopic and eutopic endometrium compared to normal endometrium, while HOBX2 was downregulated in the endometrium of women with ovarian EM. Finally, in ex vivo functional experiments, MKNK1 knockdown inhibited ectopic endometrial stromal cells (EESCs) migration and invasion. TOP3A knockdown inhibited EESCs proliferation, migration, and invasion, while promoting their apoptosis. Convergent lines of evidence suggested that MKNK1 and TOP3A are novel EM risk-related genes.

Neurodevelopmental disturbances in schizophrenia: evidence from genetic and environmental factors

Since more than 3 decades, schizophrenia (SZ) has been regarded as a neurodevelopmental disorder. The neurodevelopmental hypothesis proposes that SZ is associated with genetic and environmental risk factors, which influence connectivity in neuronal circuits during vulnerable developmental periods. We carried out a non-systematic review of genetic/environmental factors that increase SZ risk in light of its neurodevelopmental hypothesis. We also reviewed the potential impact of SZ-related environmental and genetic risk factors on grey and white matter pathology and brain function based on magnetic resonance imaging and post-mortem studies. Finally, we reviewed studies that have used patient-derived neuronal models to gain knowledge of the role of genetic and environmental factors in early developmental stages. Taken together, these studies indicate that a variety of environmental factors may interact with genetic risk factors during the pre- or postnatal period and/or during adolescence to induce symptoms of SZ in early adulthood. These risk factors induce disturbances of macro- and microconnectivity in brain regions involving the prefrontal, temporal and parietal cortices and the hippocampus. On the molecular and cellular level, a disturbed synaptic plasticity, loss of oligodendrocytes and impaired myelination have been shown in brain regions of SZ patients. These cellular/histological phenotypes are related to environmental risk factors such as obstetric complications, maternal infections and childhood trauma and genetic risk factors identified in recent genome-wide association studies. SZ-related genetic risk may contribute to active processes interfering with synaptic plasticity in the adult brain. Advances in stem cell technologies are providing promising mechanistic insights into how SZ risk factors impact the developing brain. Further research is needed to understand the timing of the different complex biological processes taking place as a result of the interplay between genetic and environmental factors.

PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study

Copy Number Variation (CNV) refers to a type of structural genomic alteration in which a segment of chromosome is duplicated or deleted. To date, many CNVs have been identified as causative genetic elements for several diseases and phenotypes. However, performing a CNV-based genome-wide association study is challenging due to inconsistency in length and occurrence of CNVs across different individuals under investigation. One of the most efficient strategies to address this issue is building CNV regions (genomic regions in which CNVs are overlapping - CNVRs). However, this approach is susceptible to a high false positive rate due to overlapping and co-occurring of confounding CNVRs with true positive CNVRs. Here, we develop PeakCNV that differentiates false-positive CNVRs from true positives by calculating a new metric, independence ranking score, (IR-score) via a feature ranking approach. We compared the performance of PeakCNV with other current existing tools by carrying out two case studies one using the CNV genotype data for individuals with prostate cancer (194 cases and 2,392 healthy individuals) and the second one for individuals with neurodevelopmental disorders (19,642 cases and 6,451 healthy individuals). Crucially, our benchmarking analyses on prostate cancer cohort indicated that PeakCNV identifies a fewer risk candidate CNVRs with shorter lengths compared to other tools. Importantly, these CNVRs cover a greater proportion of case over healthy individuals compared to other tools. The accuracy of PeakCNV in identifying relevant candidate CNVRs was reproducible in the case study on neurodevelopmental disorders. Using data from the FANTOM5 expression atlas and the Clinical Genomic Database, we show that the candidate CNVRs identified by PeakCNV for neurodevelopmental disorders overlap with a greater number of genes with the brain-enriched expression, and a greater number of genes that are associated with neurological conditions compared to candidate CNVRs identified by other tools. Taken together, PeakCNV outperformed current existing CNV association study tools by identifying more biologically meaningful CNVRs relevant to the phenotype of interest. PeakCNV is publicly available for the analysis of CNV-associated diseases and is accessible from https://rdrr.io/github/mahdieh1/PeakCNV.

Adult neural stem cells and schizophrenia

Schizophrenia (SCZ) is a devastating and complicated mental disorder accompanied by variable positive and negative symptoms and cognitive deficits. Although many genetic risk factors have been identified, SCZ is also considered as a neurodevelopmental disorder. Elucidation of the pathogenesis and the development of treatment is challenging because complex interactions occur between these genetic risk factors and environment in essential neurodevelopmental processes. Adult neural stem cells share a lot of similarities with embryonic neural stem cells and provide a promising model for studying neuronal development in adulthood. These adult neural stem cells also play an important role in cognitive functions including temporal and spatial memory encoding and context discrimination, which have been shown to be closely linked with many psychiatric disorders, such as SCZ. Here in this review, we focus on the SCZ risk genes and the key components in related signaling pathways in adult hippocampal neural stem cells and summarize their roles in adult neurogenesis and animal behaviors. We hope that this would be helpful for the understanding of the contribution of dysregulated adult neural stem cells in the pathogenesis of SCZ and for the identification of potential therapeutic targets, which could facilitate the development of novel medication and treatment.

Single cell sequencing analysis identifies genetics-modulated ORMDL3+ cholangiocytes having higher metabolic effects on primary biliary cholangitis

BACKGROUND

Primary biliary cholangitis (PBC) is a classical autoimmune disease, which is highly influenced by genetic determinants. Many genome-wide association studies (GWAS) have reported that numerous genetic loci were significantly associated with PBC susceptibility. However, the effects of genetic determinants on liver cells and its immune microenvironment for PBC remain unclear.

RESULTS

We constructed a powerful computational framework to integrate GWAS summary statistics with scRNA-seq data to uncover genetics-modulated liver cell subpopulations for PBC. Based on our multi-omics integrative analysis, 29 risk genes including ORMDL3, GSNK2B, and DDAH2 were significantly associated with PBC susceptibility. By combining GWAS summary statistics with scRNA-seq data, we found that cholangiocytes exhibited a notable enrichment by PBC-related genetic association signals (Permuted P < 0.05). The risk gene of ORMDL3 showed the highest expression proportion in cholangiocytes than other liver cells (22.38%). The ORMDL3⁺ cholangiocytes have prominently higher metabolism activity score than ORMDL3^- cholangiocytes (P = 1.38 × 10^-15). Compared with ORMDL3^- cholangiocytes, there were 77 significantly differentially expressed genes among ORMDL3⁺ cholangiocytes (FDR < 0.05), and these significant genes were associated with autoimmune diseases-related functional terms or pathways. The ORMDL3⁺ cholangiocytes exhibited relatively high communications with macrophage and monocyte. Compared with ORMDL3^- cholangiocytes, the VEGF signaling pathway is specific for ORMDL3⁺ cholangiocytes to interact with other cell populations.

CONCLUSIONS

To the best of our knowledge, this is the first study to integrate genetic information with single cell sequencing data for parsing genetics-influenced liver cells for PBC risk. We identified that ORMDL3⁺ cholangiocytes with higher metabolism activity play important immune-modulatory roles in the etiology of PBC.

Joint-Tissue Integrative Analysis Identified Hundreds of Schizophrenia Risk Genes

Genome-wide association studies (GWAS) have identified a large number of schizophrenia risk variants, and most of them are mapped to noncoding regions. By leveraging multiple joint-tissue gene expression data and GWAS data, we herein performed a transcriptome-wide association study (TWAS) and Mendelian randomization (MR) analysis and identified 144 genes whose mRNA levels were related to genetic risk of schizophrenia. Most of these genes exhibited diametrically opposite trends of expression in prenatal and postnatal brain tissues, despite that their expression levels in dorsolateral prefrontal cortex (DLPFC) tissues did not significantly differ between schizophrenics and healthy controls. We then found significant enrichment of these genes in dopamine-related pathways that were repeatedly implicated in schizophrenia pathogenesis and in the action of antipsychotic drugs. Gene expression analysis using single cell RNA-sequencing (scRNA-seq) data of mid-gestation fetal brains further revealed enrichment of these genes in glutamatergic excitatory neurons and cycling progenitors. These lines of evidence, in consistency with previous findings, confirmed the polygenic nature of schizophrenia and highlighted involvement of early neurodevelopment aberrations in this disorder. Further investigations using advanced algorithms in both bulk brain tissues and in single cells and at different developmental stages are necessary to characterize transcriptomic features of schizophrenia pathogenesis along brain development.

Identification of risk genes related to myocardial infarction and the construction of early SVM diagnostic model

BACKGROUND

Myocardial Infarction (MI) is a fatal cardiovascular system disease. At present, the diagnosis of MI patients is mainly based on the patient's clinical manifestations, dynamic changes in electrocardiogram (ECG), and changes in myocardial enzymes. ECG is insufficient to diagnose an acute coronary syndrome or acute myocardial infarction, since ST-segment deviation might be also present in other conditions, such as acute pericarditis and early repolarization patterns. Given the low specificity and effectiveness of the current diagnostic strategies, an accurate diagnostic approach based on the level of gene expression is urgently needed in the clinic.

METHODS AND RESULTS

We compared the gene's expression between MI patients and normal samples. The RNAseq data were downloaded from the GEO database. Differentially expressed genes underwent a feature selection process, and the signatures were selected to train a machine-learning model. In this study, we identified the risk genes associated with MI as signatures and uses the SVM to establish a diagnostic model. The accuracy of the model on discovery data is 0.87, which significantly improves the diagnostic efficiency of early detection of MI patients (MIPs). Two independent datasets were applied to verify the diagnostic model. Our model can effectively distinguish the control group from the disease group.

CONCLUSIONS

We used risk genes to construct a diagnostic model for MI diagnosis, which can effectively distinguish MIPs from normal samples in the both of the discovery data and validation data. In the validation data, we found that percutaneous coronary intervention could indeed reverse MI to a certain extent, and the gene expression level of patients treated with percutaneous coronary intervention (PCI) was closer to the normal state.

Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma

BACKGROUND

Childhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown.

METHODS

In the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma.

RESULTS

Based on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group.

CONCLUSIONS

We provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.

Identification and functional analysis of specific MS risk miRNAs and their target genes

BACKGROUND

It has been widely acknowledged that abnormal expression of microRNAs (miRNAs) may lead to the occurrence and development of MS through regulating target genes. Currently, only few studies have comprehensively evaluated the function and relationship between MS-related miRNAs and their target genes.

METHODS

Differentially expressed miRNAs in MS patients' serum and plasma were selected by reviewing numerous literatures manually. Then, thousands of target genes were screened by several online databases, of which 899 MS-related genes were further identified. Gene ontology, protein-protein interaction and KEGG pathway analysis were used to determine high-risk pathways and MS risk genes. Transcriptomic datasets from GEO was analyzed to evaluate these risk genes.

RESULTS

28 MS-related miRNAs were extracted. MiR-30e, miR-93, miR-155 were identified as the most crucial miRNAs through targeting hub genes: PIK3CA, PIK3R1, PIK3R2 and MAPK8. Seven immune pathways were screened out according to KEGG pathway analysis. Six transcriptomic datasets were used to evaluate results, and PIK3CA was differentially expressed in MS patients compared with healthy donors.

CONCLUSIONS

According to our research, MS-related miRNAs and their target genes of MS were identified and comprehensively evaluated. This work may provide a new insight for discovering pathogenesis and possible biomarkers of MS in future studies.

Methyl-CpG Binding Protein 2 in Alzheimer Dementia

Despite decades of research on Alzheimer disease, understanding the complexity of the genetic and molecular interactions involved in its pathogenesis remains far from our grasp. Methyl-CpG Binding Protein 2 (MeCP2) is an important epigenetic regulator enriched in the brain, and recent findings have implicated MeCP2 as a crucial player in Alzheimer disease. Here, we provide comprehensive insights into the pathophysiological roles of MeCP2 in Alzheimer disease. In particular, we focus on how the alteration of MeCP2 expression can impact Alzheimer disease through risk genes, amyloid-β and tau pathology, cell death and neurodegeneration, and cellular senescence. We suggest that Alzheimer disease can be adversely affected by upregulated MeCP2-dependent repression of risk genes (MEF2C, ADAM10, and PM20D1), increased tau accumulation, and neurodegeneration through neuronal cell death (excitotoxicity and apoptosis). In addition, we propose that the progression of Alzheimer disease could be caused by reduced MeCP2-mediated enhancement of astrocytic and microglial senescence and consequent glial SASP (senescence-associated secretory phenotype)-dependent neuroinflammation. We surmise that any imbalance in MeCP2 function would accelerate or cause Alzheimer disease pathogenesis, implying that MeCP2 may be a potential drug target for the treatment and prevention of Alzheimer disease.

A critical review of zebrafish schizophrenia models: Time for validation?

Schizophrenia is a mental disorder that affects 1% of the population worldwide and is manifested as a broad spectrum of symptoms, from hallucinations to memory impairment. It is believed that genetic and/or environmental factors may contribute to the occurrence of this disease. Recently, the zebrafish has emerged as a valuable and attractive model for various neurological disorders including schizophrenia. In this review, we describe current pharmacological models of schizophrenia with special emphasis on providing insights into the pros and cons of using zebrafish as a behavioural model of this disease. Moreover, we highlight the advantages and utility of using zebrafish for elucidating the genetic mechanisms underlying this psychiatric disorder. We believe that the zebrafish has high potential also in the area of precision medicine and may complement the development of therapeutics, especially for pharmacoresistant patients.

Evidence from genome wide association studies implicates reduced control of Epstein-Barr virus infection in multiple sclerosis susceptibility

BACKGROUND

Genome wide association studies have identified > 200 susceptibility loci accounting for much of the heritability of multiple sclerosis (MS). Epstein-Barr virus (EBV), a memory B cell tropic virus, has been identified as necessary but not sufficient for development of MS. The molecular and immunological basis for this has not been established. Infected B cell proliferation is driven by signalling through the EBV produced cell surface protein LMP1, a homologue of the MS risk gene CD40.

METHODS

We have investigated transcriptomes of B cells and EBV-infected B cells at Latency III (LCLs) and identified MS risk genes with altered expression on infection and with expression levels associated with the MS risk genotype (LCLeQTLs). The association of LCLeQTL genomic burden with EBV phenotypes in vitro and in vivo was examined. The risk genotype effect on LCL proliferation with CD40 stimulation was assessed.

RESULTS

These LCLeQTL MS risk SNP:gene pairs (47 identified) were over-represented in genes dysregulated between B and LCLs (p < 1.53 × 10^-4), and as target loci of the EBV transcription factor EBNA2 (p < 3.17 × 10^-16). Overall genetic burden of LCLeQTLs was associated with some EBV phenotypes but not others. Stimulation of the CD40 pathway by CD40L reduced LCL proliferation (p < 0.001), dependent on CD40 and TRAF3 MS risk genotypes. Both CD40 and TRAF3 risk SNPs are in binding sites for the EBV transcription factor EBNA2, with expression of each correlated with EBNA2 expression dependent on genotype.

CONCLUSIONS

These data indicate targeting EBV may be of therapeutic benefit in MS.

A review on neuroimaging studies of genetic and environmental influences on early brain development

The past decades witnessed a surge of interest in neuroimaging study of normal and abnormal early brain development. Structural and functional studies of normal early brain development revealed massive structural maturation as well as sequential, coordinated, and hierarchical emergence of functional networks during the infancy period, providing a great foundation for the investigation of abnormal early brain development mechanisms. Indeed, studies of altered brain development associated with either genetic or environmental risks emerged and thrived. In this paper, we will review selected studies of genetic and environmental risks that have been relatively more extensively investigated-familial risks, candidate risk genes, and genome-wide association studies (GWAS) on the genetic side; maternal mood disorders and prenatal drug exposures on the environmental side. Emerging studies on environment-gene interactions will also be reviewed. Our goal was not to perform an exhaustive review of all studies in the field but to leverage some representative ones to summarize the current state, point out potential limitations, and elicit discussions on important future directions.

Computational drug repurposing for inflammatory bowel disease using genetic information

As knowledge of the genetics behind inflammatory bowel disease (IBD) has continually improved, there has been a demand for methods that can use this data in a clinically significant way. Genome-wide association analyses for IBD have identified 232 risk genetic loci for the disorder. While identification of these risk loci enriches our understanding of the underlying biology of the disorder, their identification does not serve a clinical purpose. A potential use of this genetic information is to look for potential IBD drugs that target these loci in a procedure known as drug repurposing. The demand for new drug treatments for IBD is high due to the side effects and high costs of current treatments. We hypothesize that IBD genetic variants obtained from GWAS and the candidate genes prioritized from the variants have a causal relationship with IBD drug targets. A computational drug repositioning study was done due to its efficiency and inexpensiveness compared to traditional in vitro or biochemical approaches. Our approach for drug repurposing was multi-layered; it not only focused on the interactions between drugs and risk IBD genes, but also the interactions between drugs and all of the biological pathways the risk genes are involved in. We prioritized IBD candidate genes using identified genetic variants and identified potential drug targets and drugs that can be potentially repositioned or developed for IBD using the identified candidate genes. Our analysis strategy can be applied to repurpose drugs for other complex diseases using their risk genes identified from genetic analysis.

Surprising conservation of schizophrenia risk genes in lower organisms reflects their essential function and the evolution of genetic liability

Schizophrenia is a devastating psychiatric illness that affects approximately 1% of the population. Genetic variation in multiple genes causes elevated risk for the disorder, but the molecular basis is inadequately understood and it is not clear how risk genes have evolved and persisted in the genome. To address these issues, we have identified orthologs/homologs of 344 schizophrenia risk genes (from the Psychiatric Genomics Consortium dataset) in lower organisms, including C. elegans, Drosophila and zebrafish, along with phenotypes produced by genetic disruption in C. elegans. Schizophrenia risk genes were evolutionarily conserved at significantly higher rates in C. elegans (81%) and zebrafish (88%) than genes in general for these two species (40-70%). The risk-gene equivalents were highly (~3-fold) enriched for essential genes consistent with polygenic mutation threshold models, which propose that genetic susceptibility results from the inevitable expression of harmful combinations of risk variants in the population. Most notably, numerous examples of cross-species synteny revealed how blocks of risk genes geared toward a shared biological purpose coalesced into proximity during evolution. We obtained initial evidence that schizophrenia risk genes affected different stages of development, potentially allowing differential modulation by the environment. Taken together, studies of the conservation of schizophrenia risk genes in simple model organisms provided novel insights into the molecular basis for genetic susceptibility to a complex human psychiatric disorder.

[Genetic risk variants in Parkinson's disease and other movement disorders]

Movement disorders are often genetically complex with genetic risk factors playing a major role. For example, monogenic causes of Parkinson's disease (PD) can be found in only 2-5% of patients who often have an early onset (<40 years). In the majority of patients, common genetic variants seem to contribute to the disease risk. To date, 24 genetic risk factors have been identified. For restless legs syndrome (RLS), six different risk variants have been reported but no monogenic cause is known yet. For the genetic risk factors of essential tremor and dystonia, which are less well studied, only five and two candidate variants, respectively, have been described but their roles still require independent confirmation. In this review, we provide an overview on the involved genes, their function, and discuss possible, disease mechanism-driven therapies.

The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism

INTRODUCTION

We analyzed the effects of the top 20 Alzheimer disease (AD) risk genes on gray-matter density (GMD) and metabolism.

METHODS

We ran stepwise linear regression analysis using posterior cingulate hypometabolism and medial temporal GMD as outcomes and all risk variants as predictors while controlling for age, gender, and APOE ε4 genotype. We explored the results in 3D using Statistical Parametric Mapping 8.

RESULTS

Significant predictors of brain GMD were SLC24A4/RIN3 in the pooled and mild cognitive impairment (MCI); ZCWPW1 in the MCI; and ABCA7, EPHA1, and INPP5D in the AD groups. Significant predictors of hypometabolism were EPHA1 in the pooled, and SLC24A4/RIN3, NME8, and CD2AP in the normal control group.

DISCUSSION

Multiple variants showed associations with GMD and brain metabolism. For most genes, the effects were limited to specific stages of the cognitive continuum, indicating that the genetic influences on brain metabolism and GMD in AD are complex and stage dependent.

Unraveling the mechanistic complexity of Alzheimer's disease through systems biology

Alzheimer's disease (AD) is a complex, multifactorial disease that has reached global epidemic proportions. The challenge remains to fully identify its underlying molecular mechanisms that will enable development of accurate diagnostic tools and therapeutics. Conventional experimental approaches that target individual or small sets of genes or proteins may overlook important parts of the regulatory network, which limits the opportunity of identifying multitarget interventions. Our perspective is that a more complete insight into potential treatment options for AD will only be made possible through studying the disease as a system. We propose an integrative systems biology approach that we argue has been largely untapped in AD research. We present key publications to demonstrate the value of this approach and discuss the potential to intensify research efforts in AD through transdisciplinary collaboration. We highlight challenges and opportunities for significant breakthroughs that could be made if a systems biology approach is fully exploited.

Transcriptomics and mechanistic elucidation of Alzheimer's disease risk genes in the brain and in vitro models

In this study, we have assessed the expression and splicing status of genes involved in the pathogenesis or affecting the risk of Alzheimer's disease (AD) in the postmortem inferior temporal cortex samples obtained from 60 subjects with varying degree of AD-related neurofibrillary pathology. These subjects were grouped based on neurofibrillary pathology into 3 groups: Braak stages 0-II, Braak stages III-IV, and Braak stages V-VI. We also examined the right frontal cortical biopsies obtained during life from 22 patients with idiopathic shunt-responding normal pressure hydrocephalus, a disease that displays similar pathologic alterations as seen in AD. These 22 patients were categorized according to dichotomized amyloid-β positive or negative pathology in the biopsies. We observed that the expression of FRMD4A significantly decreased, and the expression of MS4A6A significantly increased in relation to increasing AD-related neurofibrillary pathology. Moreover, the expression of 2 exons in both CLU and TREM2 significantly increased with increase in AD-related neurofibrillary pathology. However, a similar trend toward increased expression in CLU and TREM2 was observed with most of the studied exons, suggesting a global change in the expression rather than altered splicing. Correlation of gene expression with well-established AD-related factors, such as α-, β-, and γ-secretase activities, brain amyloid-β42 levels, and cerebrospinal fluid biomarkers, revealed a positive correlation between β-secretase activity and the expression of TREM2 and BIN1. In expression quantitative trait loci analysis, we did not detect significant effects of the risk alleles on gene expression or splicing. Analysis of the normal pressure hydrocephalus biopsies revealed no differences in the expression or splicing profiles of the studied genes between amyloid-β positive and negative patients. Using the protein-protein interaction-based in vitro pathway analysis tools, we found that downregulation of FRMD4A associated with increased APP-β-secretase interaction, increased amyloid-β40 secretion, and altered phosphorylation of tau. Taken together, our results suggest that the expression of FRMD4A, MS4A6A, CLU, and TREM2 is altered in relation to increasing AD-related neurofibrillary pathology, and that FRMD4A may play a role in amyloidogenic and tau-related pathways in AD. Therefore, investigation of gene expression changes in the brain and effects of the identified genes on disease-associated pathways in vitro may provide mechanistic insights on how alterations in these genes may contribute to AD pathogenesis.

Genetics of Parkinson's disease: the yield

The discovery of genes implicated in familial forms of Parkinson's disease (PD) has provided new insights into the molecular events leading to neurodegeneration. Clinically, patients with genetically determined PD can be difficult to distinguish from those with sporadic PD. Monogenic causes include autosomal dominantly (SNCA, LRRK2, VPS35, EIF4G1) as well as recessively (PARK2, PINK1, DJ-1) inherited mutations. Additional recessive forms of parkinsonism present with atypical signs, including very early disease onset, dystonia, dementia and pyramidal signs. New techniques in the search for phenotype-associated genes (next-generation sequencing, genome-wide association studies) have expanded the spectrum of both monogenic PD and variants that alter risk to develop PD. Examples of risk genes include the two lysosomal enzyme coding genes GBA and SMPD1, which are associated with a 5-fold and 9-fold increased risk of PD, respectively. It is hoped that further knowledge of the genetic makeup of PD will allow designing treatments that alter the course of the disease.

Genetics of Parkinson's disease: the yield

The discovery of genes implicated in familial forms of Parkinson's disease (PD) has provided new insights into the molecular events leading to neurodegeneration. Clinically, patients with genetically determined PD can be difficult to distinguish from those with sporadic PD. Monogenic causes include autosomal dominantly (SNCA, LRRK2, VPS35, EIF4G1) as well as recessively (PARK2, PINK1, DJ-1) inherited mutations. Additional recessive forms of parkinsonism present with atypical signs, including very early disease onset, dystonia, dementia and pyramidal signs. New techniques in the search for phenotype-associated genes (next-generation sequencing, genome-wide association studies) have expanded the spectrum of both monogenic PD and variants that alter risk to develop PD. Examples of risk genes include the two lysosomal enzyme coding genes GBA and SMPD1, which are associated with a 5-fold and 9-fold increased risk of PD, respectively. It is hoped that further knowledge of the genetic makeup of PD will allow designing treatments that alter the course of the disease.