Model-based gene selection shows engrailed 1 is associated with antipsychotic response

Osteoporosis and low bone mass among schizophrenia and bipolar disorder: A cross-sectional study with newly diagnosed, drug-naïve subjects

BACKGROUND

A growing body of data shows that schizophrenia (SCZ) and bipolar disorder (BD) have substantial metabolic risks; however, few studies have focused on bone metabolism. This study aimed to assess the prevalence and associated influencing factors of low bone mass and osteoporosis in SCZ and BD before pharmacological effects occur.

METHODS

108 healthy controls (HCs) and drug-naïve individuals with SCZ (n = 56) and BD (n = 130) had their lumbar spine (L1-L4) and left femur (Neck/Trochanter/Ward's triangle) bone mineral density (BMD) determined using dual-energy X-ray absorptiometry. Besides, we measured bone turnover markers (BTMs) levels, including procollagen I N-terminal propeptide, osteocalcin, and C-terminal cross-linking telopeptide of type I collagen in different groups.

RESULTS

Individuals with SCZ and BD had significantly lower BMD and significantly higher prevalence of low bone mass and osteoporosis compared with HCs. In the main observation regions of the total lumbar (F = 18.368, p < 0.001) and left femur (F = 14.790, p < 0.001), BMD was lower in individuals with SCZ and BD than HCs, with SCZ showing lower BMD than BD. The osteocalcin (H = 11.421, p = 0.003) levels were significantly higher in SCZ and BD than HCs. Binary regression analysis showed that SCZ or BD was an independent risk factor for low bone mass and osteoporosis. In addition, sex, age, and BTMs also influenced the occurrence of low bone mass and osteoporosis.

LIMITATIONS

Cross-sectional study.

CONCLUSION

The results findings of the study might contribute to our understanding of the increased risk of bone metabolism in SCZ and BD.

CLINICAL TRIAL REGISTRATION

www.chictr.org.cn, identifier ChiCTR1900021379.

Engrailed: Pathological and physiological effects of a multifunctional developmental gene

Engrailed-1 (EN1) is a developmental gene that encodes En1, a highly conserved transcription factor involved in regionalization during early embryogenesis and in the later maintenance of normal neurons. After birth, EN1 still plays a role in the development and physiology of the body; for example, it exerts a protective effect on midbrain dopaminergic (mDA) neurons, and loss of EN1 causes mDA neurons in the ventral midbrain to gradually die approximately 6 weeks after birth, resulting in motor and nonmotor symptoms similar to those observed in Parkinson's disease. Notably, EN1 has been identified as a possible susceptibility gene for idiopathic Parkinson's disease in humans. EN1 is involved in the processes of wound-healing scar production and tissue and organ fibrosis. Additionally, EN1 can lead to tumorigenesis and thus provides a target for the treatment of some tumors. In this review, we summarize the effects of EN1 on embryonic organ development, describe the consequences of the deletion or overexpression of the EN1 gene, and discuss the pathways in which EN1 is involved. We hope to clarify the role of EN1 as a developmental gene and present potential therapeutic targets for diseases involving the EN1 gene.

Evidence that the frontal pole has a significant role in the pathophysiology of schizophrenia

Different regions of the cortex have been implicated in the pathophysiology of schizophrenia. Recently published data suggested there are many more changes in gene expression in the frontal pole (Brodmann's Area (BA) 10) compared to the dorsolateral prefrontal cortex (BA 9) and the anterior cingulate cortex (BA 33) from patients with schizophrenia. These data argued that the frontal pole is significantly affected by the pathophysiology of schizophrenia. The frontal pole is a region necessary for higher cognitive functions and is highly interconnected with many other brain regions. In this review we summarise the growing body of evidence to support the hypothesis that a dysfunctional frontal pole, due at least in part to its widespread effects on brain function, is making an important contribution to the pathophysiology of schizophrenia. We detail the many structural, cellular and molecular abnormalities in the frontal pole from people with schizophrenia and present findings that argue the symptoms of schizophrenia are closely linked to dysfunction in this critical brain region.

The Methylation Pattern for Knee and Hip Osteoarthritis

Osteoarthritis is one of the most prevalent chronic joint diseases for middle-aged and elderly people. But in recent years, the number of young people suffering from the disease increases quickly. It is known that osteoarthritis is a common degenerative disease caused by the combination and interaction of many factors such as natural and environmental factors. DNA methylations reflect the effects of environmental factors. Several researches on DNA methylation at specific genes in OA cartilage indicated the great potential roles of DNA methylation in OA. To systematically investigate the methylation pattern in knee and hip osteoarthritis, we analyzed the methylation profiles in cartilage of 16 OA hip samples, 19 control hip samples and 62 OA knee samples. 12 discriminative methylation sites were identified using advanced minimal Redundancy Maximal Relevance (mRMR) and Incremental Feature Selection (IFS) methods. The SVM classifier of these 12 methylation sites from genes like MEIS1, GABRG3, RXRA, and EN1, can perfectly classify the OA hip samples, control hip samples and OA knee samples evaluated with LOOCV (Leave-One Out-Cross Validation). These 12 methylation sites can not only serve as biomarker, but also provide underlying mechanism of OA.

Engrailed 1 overexpression as a potential prognostic marker in Lower Grade Glioma

Background

Engrailed 1 (EN1), as a member of homeobox-containing transcription factors, participates in the development of the brain. High expressions of EN1 exist in various tumors. However, the role of EN1 in lower grade glioma (LGG) is still unknown.

Methods

Coefficients of Cox regression were examined by data mining among 13 cancer types using OncoLnc to validate EN1 expressions in LGG patients from The Cancer Genome Atlas database (TCGA). Bioinformatic analysis was performed by using R2 and the UCSC Xena browser based on the data from 273 glioma cases in GSE16011 from GEO datasets and 530 cases of LGG patients in TCGA. Cases in GSE16011 were divided into two groups according to IDH1 mutation status. Cases in TCGA-LGG were classified to subtypes according to histopathological results, IDH1 mutation status and 1p19q status. The Kaplan–Meier survival curves were performed to analyze the relationship between EN1 expressions and clinicopathological characteristics and survival time respectively.

Results

Cox regression results showed that LGG was ranked statistically first among 13 different cancer types according to the false discovery rate (FDR) correction. Results from GSE16011 showed that: glioma, LGG and LGG with IDH1 mutation patients with high EN1 expressions had significantly shorter 5, 10, and 15-year overall survival time (OS) (p < 0.001). Similar results from TCGA-LGG showed that LGG patients with high EN1 expressions had significantly shorter 15-year OS, irrespective of IDH1 mutation and 1p19q co-deletion (p < 0.001). The astrocytoma subgroup showed highest levels of EN1 expression and shortest 5, 10 and 15-year OS compared with oligoastrocytoma and oligodendroglioma (p < 0.05).

Conclusion

EN1 can be used as a prognostic marker in LGG patients, combined with IDH1 mutation and 1p19q co-deletion.

Analysis of methylation datasets identified significantly changed genes and functional pathways in osteoarthritis

BACKGROUND

Researches indicate that epigenetics was involved in osteoarthritis (OA). The purpose of this study was to describe the alterations of DNA methylation in hip and knee OA by comparing DNA methylome of OA cartilage and non-OA samples and to identify novel genes and pathways associated with OA.

METHODS

We gained two expression profiling datasets (GSE73626 and GSE63695) from the GEO dataset. The RnBeads in R package was used to identify differentially methylated CpG sites. Genes that showed significant differences in DNA methylation between OA and normal control groups underwent functional annotation analysis using the online tool of GeneCodis. Furthermore, we used the Sequenom MassARRAY platform (CapitalBio, Beijing, China) to perform the quantitative methylation analysis.

RESULTS

A total of 249 hypermethylated sites and 96 hypomethylated sites were obtained from OA samples compared with normal control samples. Functional analysis of differentially methylated genes obtained that embryonic skeletal system morphogenesis, cartilage development, and skeletal system development may be involved in the pathogenesis of OA. Eight genes including HOXB3, HOXB4, HOXB6, HOXC4, HOXC10, HOXD3, TBX3, and TBX5 were identified as potential novel biomarkers for OA.

CONCLUSION

Taken together, our study found different molecular characteristics between OA patients and normal controls. This may provide new clues to elucidate the pathogenesis of OA.Key Points• Embryonic skeletal system morphogenesis, cartilage development, skeletal system development may be involved in the pathogenesis of OA.• Eight genes are identified as potential novel markers for OA.• Our future in vivo molecular intervention experiments will extend our current findings.

Association between EN1 rs4144782 and susceptibility of knee osteoarthritis: A case-control study

Osteoarthritis (OA) is a complex disease that affects the whole joint, resulting from the combined influence of biomechanical factors and genetic factors. The heritable component for primary OA accounts for about 60% of variation in population liability to the disease. So far, genome-wide association studies (GWAS) and candidate gene studies have established many OA-related loci. However, these findings account for only a rather small fraction of the genetic component. To further reveal the genetic architecture of OA, we conducted this case-control study to explore the association of locus EN1 rs4144782 and knee OA susceptibility in a Chinese population. EN1 rs4144782 was significantly associated with increased risk of knee OA (OR=1.26; 95% CI: 1.05-1.50, P value=0.012). In dominant model, compared with carriers of GG genotype, those with AG or AA genotype have an 1.44-fold increased risk of OA (OR: 1.44; 95% CI: 1.10-1.88; P value=0.008). Subgroup analyses didn't change the results materially. This should be the first association study of EN1 locus on risk of OA, and our finding suggested that the EN1 rs4144782 might contribute to the susceptibility of knee OA.

Association study of 167 candidate genes for schizophrenia selected by a multi-domain evidence-based prioritization algorithm and neurodevelopmental hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

The pharmacogenetics of symptom response to antipsychotic drugs

Antipsychotic drugs are limited in their efficacy by the relatively poor response of negative and cognitive symptoms of schizophrenia as well as by the substantial variability in response between patients. Pharmacogenetic studies have sought to identify the genetic factors that underlie the individual variability in response to treatment, with a past emphasis on dopamine and serotonin receptors as candidate genes. Few studies have separated effects on positive and negative symptoms, despite the established differences in response to drug treatment between these syndromes. Where this has been done most findings are consistent with the conclusion that dopamine receptor polymorphisms relate to positive symptom response, while negative symptom improvement is influenced by polymorphisms of genes involved in 5-HT neurotransmission. A wide range of polymorphisms in other candidate genes have been investigated, with some positive findings in those genes associated with glutamatergic transmission and/or risk factors for schizophrenia. However, there remains a lack of good replicated findings; furthermore there is little evidence to support drug-specific genetic associations with treatment response. While most past studies focused on single candidate genes, technology now permits genome-wide association studies with response to antipsychotics. Although not without major limitations, these "hypothesis-free" approaches are beginning to identify further important risk factors for treatment response. Again there is little consistency between various studies, although some of the polymorphisms identified are in genes involved in neurodevelopment, which is increasingly being recognized as important in the pathophysiology of schizophrenia.

The pharmacogenetics of antipsychotic treatment

There is substantial interindividual variability in the effects of treatment with antipsychotic drugs not only in the emergence of adverse effects but also in symptom response. It is becoming increasingly clear that much of this variability is due to genetic factors; pharmacogenetics is the study of those factors, with the eventual goal of identifying genetic predictors of treatment effects. There have been many reported associations of single nucleotide polymorphisms (SNPs) in candidate genes with the consequences of antipsychotic drug treatment. Thus variations in dopaminergic and serotoninergic genes may influence positive and negative symptom outcome, respectively. Among the adverse effects, tardive dyskinesia and weight gain have been the most studied, with some consistent associations of functional SNPs in genes relating to pharmacological mechanisms. Technological advance has permitted large-scale genome-wide association studies (GWAS), but as yet there are few reports that replicate prior findings with candidate genes. Nevertheless, GWAS may identify associations which provide new clues relating to underlying mechanisms.

An integrative functional genomics approach for discovering biomarkers in schizophrenia

Schizophrenia (SZ) is a complex disorder resulting from both genetic and environmental causes with a lifetime prevalence world-wide of 1%; however, there are no specific, sensitive and validated biomarkers for SZ. A general unifying hypothesis has been put forward that disease-associated single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) are more likely to be associated with gene expression quantitative trait loci (eQTL). We will describe this hypothesis and review primary methodology with refinements for testing this paradigmatic approach in SZ. We will describe biomarker studies of SZ and testing enrichment of SNPs that are associated both with eQTLs and existing GWAS of SZ. SZ-associated SNPs that overlap with eQTLs can be placed into gene-gene expression, protein-protein and protein-DNA interaction networks. Further, those networks can be tested by reducing/silencing the gene expression levels of critical nodes. We present pilot data to support these methods of investigation such as the use of eQTLs to annotate GWASs of SZ, which could be applied to the field of biomarker discovery. Those networks that have association with SNP markers, especially cis-regulated expression, might lead to a more clear understanding of important candidate genes that predispose to disease and alter expression. This method has general application to many complex disorders.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

In silico whole genome association scan for murine prepulse inhibition

BACKGROUND

The complex trait of prepulse inhibition (PPI) is a sensory gating measure related to schizophrenia and can be measured in mice. Large-scale public repositories of inbred mouse strain genotypes and phenotypes such as PPI can be used to detect Quantitative Trait Loci (QTLs) in silico. However, the method has been criticized for issues including insufficient number of strains, not controlling for false discoveries, the complex haplotype structure of inbred mice, and failing to account for genotypic and phenotypic subgroups.

METHODOLOGY/PRINCIPAL FINDINGS

We have implemented a method that addresses these issues by incorporating phylogenetic analyses, multilevel regression with mixed effects, and false discovery rate (FDR) control. A genome-wide scan for PPI was conducted using over 17,000 single nucleotide polymorphisms (SNPs) in 37 strains phenotyped. Eighty-nine SNPs were significant at a false discovery rate (FDR) of 5%. After accounting for long-range linkage disequilibrium, we found 3 independent QTLs located on murine chromosomes 1 and 13. One of the PPI positives corresponds to a region of human chromosome 6p which includes DTNBP1, a gene implicated in schizophrenia. Another region includes the gene Tsn which alters PPI when knocked out. These genes also appear to have correlated expression with PPI.

CONCLUSIONS/SIGNIFICANCE

These results support the usefulness of using an improved in silico mapping method to identify QTLs for complex traits such as PPI which can be then be used for to help identify loci influencing schizophrenia in humans.